commit 260d86d3f1d9956f81e446a8d37195b37dd44455 Author: chaopower Date: Mon Jul 31 13:49:34 2023 +0800 初始化 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..70e7711 --- /dev/null +++ b/.gitignore @@ -0,0 +1,215 @@ +# ---> Python +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +# ---> Perl +!Build/ +.last_cover_stats +/META.yml +/META.json +/MYMETA.* +*.o +*.pm.tdy +*.bs + +# Devel::Cover +cover_db/ + +# Devel::NYTProf +nytprof.out + +# Dist::Zilla +/.build/ + +# Module::Build +_build/ +Build +Build.bat + +# Module::Install +inc/ + +# ExtUtils::MakeMaker +/blib/ +/_eumm/ +/*.gz +/Makefile +/Makefile.old +/MANIFEST.bak +/pm_to_blib +/*.zip + +# ---> Perl6 +# Gitignore for Perl 6 (http://www.perl6.org) +# As part of https://github.com/github/gitignore + +# precompiled files +.precomp +lib/.precomp + +nohup.out + +log/* +!log/readme.md +example/* +!example/readme.md + +/.report/ \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..e69de29 diff --git a/database/chemo_drug_combine.csv b/database/chemo_drug_combine.csv new file mode 100644 index 0000000..0554675 --- /dev/null +++ b/database/chemo_drug_combine.csv @@ -0,0 +1,28 @@ +癌种 用药方案 方案缩写 source +非小细胞肺癌 顺铂+紫杉醇 TP lung85gene +非小细胞肺癌 卡铂+紫杉醇 TP lung85gene +非小细胞肺癌 顺铂+紫杉醇脂质体 LP lung85gene +非小细胞肺癌 卡铂+紫杉醇脂质体 LP lung85gene +非小细胞肺癌 顺铂+白蛋白紫杉醇 nab-TP lung85gene +非小细胞肺癌 卡铂+白蛋白紫杉醇 nab-TP lung85gene +非小细胞肺癌 顺铂+多西他赛 DP lung85gene +非小细胞肺癌 卡铂+多西他赛 DP lung85gene +非小细胞肺癌 奈达铂+多西他赛 DP lung85gene +非小细胞肺癌 顺铂+吉西他滨 GP lung85gene +非小细胞肺癌 卡铂+吉西他滨 GP lung85gene +非小细胞肺癌 顺铂+培美曲塞 PP lung85gene +非小细胞肺癌 卡铂+培美曲塞 PP lung85gene +非小细胞肺癌 顺铂+长春瑞滨 NP lung85gene +非小细胞肺癌 顺铂+依托泊苷 EP lung85gene +小细胞肺癌 顺铂+依托泊苷 EP lung85gene +小细胞肺癌 卡铂+依托泊苷 EC lung85gene +小细胞肺癌 洛铂+依托泊苷 EL lung85gene +小细胞肺癌 顺铂+伊立替康 IP lung85gene +小细胞肺癌 卡铂+伊立替康 IC lung85gene +结直肠癌 奥沙利铂+亚叶酸钙+氟尿嘧啶 FOLFOX crc88gene +结直肠癌 伊立替康+亚叶酸钙+氟尿嘧啶 FOLFIRI crc88gene +结直肠癌 奥沙利铂+卡培他滨 CAPEOX（又称Xelox） crc88gene +结直肠癌 伊立替康+奥沙利铂+亚叶酸钙+氟尿嘧啶 FOLFOXIRI crc88gene +结直肠癌 伊立替康+卡培他滨 CapIRI或XELIRI crc88gene +结直肠癌 奥沙利铂+雷替曲塞 / crc88gene +结直肠癌 伊立替康+雷替曲塞 / crc88gene diff --git a/main.py b/main.py new file mode 100644 index 0000000..5c4d4df --- /dev/null +++ b/main.py @@ -0,0 +1,24 @@ +import json +import os +import socket +import sys + +from docxtpl import DocxTemplate + +from tools.parsexlsx import run + + +def main(path): + resjson = run(path) + res = json.loads(resjson) + barcode = res['c']['barcode'] + tplpath = os.path.join(os.path.dirname(__file__), 'template', 'nreport.docx') + tpl = DocxTemplate(tplpath) + tpl.render(res) + path = os.path.join(os.path.dirname(__file__), 'result', f'{barcode}.docx') + tpl.save(path) + return path + + +if __name__ == '__main__': + main(sys.argv[1]) \ No newline at end of file diff --git a/result/2023WSSW000709-T.docx b/result/2023WSSW000709-T.docx new file mode 100644 index 0000000..2c6a567 Binary files /dev/null and b/result/2023WSSW000709-T.docx differ diff --git a/result/BC-20220705.docx b/result/BC-20220705.docx new file mode 100644 index 0000000..bdbc34c Binary files /dev/null and b/result/BC-20220705.docx differ diff --git a/result/readme.md b/result/readme.md new file mode 100644 index 0000000..e69de29 diff --git a/scripts/BC-20220314_report.docx b/scripts/BC-20220314_report.docx new file mode 100644 index 0000000..9a6871c Binary files /dev/null and b/scripts/BC-20220314_report.docx differ diff --git a/scripts/BC-20220705_report.docx b/scripts/BC-20220705_report.docx new file mode 100644 index 0000000..8260ca4 Binary files /dev/null and b/scripts/BC-20220705_report.docx differ diff --git a/scripts/check_report_merge_20230713.py b/scripts/check_report_merge_20230713.py new file mode 100644 index 0000000..7e7358c --- /dev/null +++ b/scripts/check_report_merge_20230713.py @@ -0,0 +1,486 @@ +#!/usr/bin/python3 +# -*- coding: UTF-8 -*- + +import pandas as pd +from pandas import DataFrame +import numpy as np +import logging +import re +import sys +import os +import json +import glob +import openpyxl +from openpyxl import Workbook, load_workbook +from openpyxl.drawing.image import Image + +if len(sys.argv) != 3: + print(" ".join(['usage:python', sys.argv[0], 'output_dir', 'name'])) + sys.exit() + + +def snv_fusion_cnv(output_dir, name): + out_xlsx = "".join([output_dir, '/report/', name, '.check_new.xlsx']) + + # genefunction + genefunction = {} + gf = open("/dataseq/jmdna/codes/reportbase/gene_function.txt", 'r', encoding='utf-8').readlines() + for line in gf[1:]: + gene = line.strip().split("\t")[0] + func = line.strip().split("\t")[1] + genefunction[gene.upper()] = func + genefunction['.'] = '.' + + ##drug_mechanism + drug_mechanism = {} + drug_fh = open("/dataseq/jmdna/codes/reportbase/target_drug.txt", 'r', encoding='utf-8').readlines() + for line in drug_fh[1:]: + disease = line.split("\t")[8] + mechanism = line.split("\t")[11] + drugs = line.split("\t")[0].split('|') + line.split("\t")[1].split('|') + if disease or mechanism: + for drug in drugs: + drug_mechanism[drug.upper()] = "\\\\".join([disease, mechanism]).strip() + + ''' + snvindel_sheet + ''' + + ##input + filter_file = "".join([output_dir, '/report/', name, '.snp.indel.Somatic.annoall.hg19_multianno_filtered.txt']) + pos_file = "".join([output_dir, '/mutation/', name, '.snvindel.pos.dedup.txt']) + vus_file = "".join([output_dir, '/mutation/', name, '.snvindel.vus.txt']) + neg_file = "".join([output_dir, '/mutation/', name, '.snvindel.neg.txt']) + ##filter_file + if os.path.getsize(filter_file) > 0: + snv = pd.read_table(filter_file, sep="\t") + cols = [index for index, row in snv[snv['可信'] == 0].iterrows()] + snv.drop(cols, inplace=True) + snv.insert(loc=24, column='ACMG_level', value=0) + snv.insert(loc=25, column='Deleterious', value=0) + snv.insert(loc=26, column='freq_high', value=0) + for index, row in snv.iterrows(): + if re.search("Likely_pathogenic|drug", (row['CLNSIG']), re.I): + snv.loc[index, 'ACMG_level'] = '2' + elif re.search("pathogenic", (row['CLNSIG']), re.I) and not re.search("Conflicting", (row['CLNSIG']), re.I): + snv.loc[index, 'ACMG_level'] = '1' + else: + snv.loc[index, 'ACMG_level'] = '3' + snv.loc[index, "Deleterious"] = ( + snv.loc[index, ['MutationTaster_pred', 'FATHMM_pred', 'MetaLR_pred']].tolist().count("D")) + snv.loc[index, "freq_high"] = ((snv.loc[ + index, ['1000g2015aug_all', '1000g2015aug_eas', 'esp6500siv2_all', 'ExAC_nontcga_ALL', + 'ExAC_nontcga_EAS', 'gnomAD_genome_ALL', 'gnomAD_genome_EAS']]).replace('.', '0')).max() + snv_1 = snv.iloc[:, list(range(14)) + [15, 17, 18, 20, 23, 24, 25, 26, 111, 112, 113]] + else: + snv_1 = pd.DataFrame(columns=[]) + + ##pos_file + if os.path.getsize(pos_file) > 0: + pos = pd.read_table(pos_file, sep="\t") + pos = pos.iloc[:, [7, 10, 18, 23, 24, 25, 29, 30, 31, 32]] + pos_1 = pd.DataFrame( + columns=['AAChange.refGene', 'OKBSIG', 'AMP_evidence_level', 'AMP_mut_level', 'Indication', 'Drug', + 'Response_Type', 'Evidence_Source', 'EfficacyEvidence', 'Drug_Detail', 'Gene_function', + 'Drug_Category']) + pos = list(pos.groupby(['Gene.refGene', 'AAChange.refGene', 'fun_change'])) + for i in pos: + for index, row in i[1].iterrows(): + drugs = row['药物中文名'].replace(" + ", ",") + drugs = list(set(drugs.split(","))) + drug_mm = '' + for drug in drugs: + if drug.upper() in drug_mechanism.keys(): + drug_mm += '[[' + drug + ']]' + drug_mechanism[drug.upper()] + i[1].loc[index, ['Drug_Detail']] = drug_mm + if row['标签'] == '非适应症': + row['证据等级'] = 'C' + if (re.search("敏感", row['Response_Type_C']) and row['证据等级'] == 'A'): + i[1].loc[index, ['Drug_Category']] = 'a' + elif re.search("敏感", row['Response_Type_C']) and row['证据等级'] == 'C': + i[1].loc[index, ['Drug_Category']] = 'b' + elif re.search("耐药", row['Response_Type_C']): + i[1].loc[index, ['Drug_Category']] = 'd' + else: + i[1].loc[index, ['Drug_Category']] = 'c' + i[1]['AMP_mut_level'] = i[1]['证据等级'].replace(['A', 'B', 'C', 'D'], ['I', 'I', 'II', 'II']) + pos_1.loc[len(pos_1)] = [i[0][1], i[0][2], '|'.join(list(i[1]['证据等级'])), + '|'.join(list(i[1]['AMP_mut_level'])), '|'.join(list(i[1]['疾病中文名'])), + '|'.join(list(i[1]['药物中文名'])), \ + '|'.join(list(i[1]['Response_Type_C'])), '|'.join(list(i[1]['Evidence_Source_C'])), + '|'.join(list(i[1]['EfficacyEvidence'])), '|'.join(list(i[1]['Drug_Detail'])), + genefunction[i[0][0].upper()], '|'.join(list(i[1]['Drug_Category']))] + else: + pos_1 = pd.DataFrame(columns=[]) + + ##vus_file + if os.path.getsize(vus_file) > 0: + vus = pd.read_table(vus_file, sep="\t") + vus_1 = vus.iloc[:, [9, 17]] + vus_1.insert(loc=2, column='AMP_mut_level', value='III') + vus_1 = vus_1.rename(columns={'fun_change': 'OKBSIG'}) + else: + vus_1 = pd.DataFrame(columns=[]) + + ##neg_file + if os.path.getsize(neg_file) > 0: + neg = pd.read_table(neg_file, sep="\t") + neg_1 = neg.iloc[:, [9, 17]] + neg_1.insert(loc=2, column='AMP_mut_level', value='IIII') + neg_1 = neg_1.rename(columns={'fun_change': 'OKBSIG'}) + else: + neg_1 = pd.DataFrame(columns=[]) + + snvindel_sheet = pd.DataFrame( + columns=['可信', 'Chr', 'Start', 'End', 'Ref', 'Alt', 'AAChange.refGene', 'mutant_frequency', 'total_reads', + 'mutant_reads', 'strand_bias', 'Otherinfo10', 'Func.refGene', 'Gene.refGene', 'ExonicFunc.refGene', + 'avsnp150', 'cosmic91', 'CLNDN', 'CLNSIG', 'ACMG_level', 'Deleterious', 'freq_high', 'OKBSIG', + 'AMP_evidence_level', 'AMP_mut_level', 'Indication', 'Drug', 'Response_Type', 'Evidence_Source', + 'EfficacyEvidence', 'Drug_Detail', 'Gene_function', 'Drug_Category', 'Otherinfo11', 'Otherinfo12', + 'Otherinfo13']) + pos_vus_neg = pd.concat([pos_1, vus_1, neg_1]) + snv_pos_vus_neg = snv_1.merge(pos_vus_neg, how='left', on='AAChange.refGene') + snvindel_sheet = pd.concat([snvindel_sheet, snv_pos_vus_neg]) + snvindel_sheet.rename(columns={"可信": "Validated"}) + snvindel_sheet = snvindel_sheet.replace(np.nan, '.') + snvindel_sheet.rename(columns={"可信": "Validated"}, inplace=True) + + ''' + fusion_sheet + ''' + + fusion_pos_file = "".join([output_dir, '/fusion/', name, '.fusion.pos.dedup.txt']) + fusion_vus_file = "".join([output_dir, '/fusion/', name, '.fusion.vus.txt']) + if os.path.getsize(fusion_pos_file) > 0: + fusion_pos = pd.read_table(fusion_pos_file, sep="\t") + else: + fusion_pos = pd.DataFrame(columns=[]) + + if os.path.getsize(fusion_vus_file) > 0: + fusion_vus = pd.read_table(fusion_vus_file, sep="\t") + fusion_vus.insert(loc=0, column='可信', value=1) + else: + fusion_vus = pd.DataFrame(columns=[]) + fusion_pos_vus = pd.concat([fusion_pos, fusion_vus]) + fusion_sheet = pd.DataFrame( + columns=['Validated', 'CHROM1', 'POS1', 'CHROM2', 'POS2', 'GENE1', 'GENE2', 'FUSION', 'Support_reads(PE:SR)', + 'Depth', 'FREQ1', 'FREQ2', 'OKBSIG', 'AMP_evidence_level', \ + 'AMP_mut_level', 'Indication', 'Drug', 'Response_Type', 'Evidence_Source', 'Efficacy_Evidence', + 'Drug_Detail', 'Gene_function', 'Drug_Category', 'INFO', 'FORMAT', 'Sample']) + + if not fusion_pos_vus.empty: + fusion_pos_vus = fusion_pos_vus.replace(np.nan, '.') + fusion = list(fusion_pos_vus.groupby( + ['可信', '#CHROM', 'POS', 'CHROM2', 'POS2', 'GENE1', 'GENE2', 'FUSION', 'FREQ1', 'FREQ2', 'fun_change', + 'INFO', 'FORMAT', name, 'Gene_Symbol'])) + for i in fusion: + for index, row in i[1].iterrows(): + drugs = row['药物中文名'].replace(" + ", ",") + drugs = list(set(drugs.split(","))) + drug_mm = '' + for drug in drugs: + if drug.upper() in drug_mechanism.keys(): + drug_mm += '[[' + drug + ']]' + drug_mechanism[drug.upper()] + i[1].loc[index, ['Drug_Detail']] = drug_mm + if row['标签'] == '非适应症': + row['证据等级'] = 'C' + if (re.search("敏感", row['Response_Type_C']) and row['证据等级'] == 'A'): + i[1].loc[index, ['Drug_Category']] = 'a' + elif re.search("敏感", row['Response_Type_C']) and row['证据等级'] == 'C': + i[1].loc[index, ['Drug_Category']] = 'b' + elif re.search("耐药", row['Response_Type_C']): + i[1].loc[index, ['Drug_Category']] = 'd' + elif row['Response_Type_C'] == '.': + i[1].loc[index, ['Drug_Category']] = '.' + else: + i[1].loc[index, ['Drug_Category']] = 'c' + i[1]['AMP_mut_level'] = i[1]['证据等级'].replace(['A', 'B', 'C', 'D'], ['I', 'I', 'II', 'II']) + fusion_sheet.loc[len(fusion_sheet)] = list(i[0][0:8]) + [i[0][13].split(":")[1], + i[0][13].split(":")[7]] + list(i[0][8:11]) + [ + '|'.join(list(i[1]['证据等级'])), + '|'.join(list(i[1]['AMP_mut_level'])), \ + '|'.join(list(i[1]['疾病中文名'])), '|'.join(list(i[1]['药物中文名'])), + '|'.join(list(i[1]['Response_Type_C'])), + '|'.join(list(i[1]['Evidence_Source_C'])), + '|'.join(list(i[1]['EfficacyEvidence'])), \ + '|'.join(list(i[1]['Drug_Detail'])), + genefunction[i[0][14].upper()], + '|'.join(list(i[1]['Drug_Category']))] + list(i[0][11:14]) + fusion_sheet = fusion_sheet.replace(np.nan, '.') + + ''' + cnv_sheet + ''' + + cnv_pos_file = "/home/jm001/test/reference_standard/lung85gene/Tissue/BKDL202603539-1a/cnvkit/BKDL202603539-1a.cnv.pos.dedup.txt" + cnv_sheet = pd.DataFrame( + columns=['Validated', 'Chromosome', 'Start', 'End', 'Gene', 'Depth', 'Probes', 'Copy_number', 'OKBSIG', + 'Gene_Symbol', 'AMP_evidence_level', 'AMP_mut_level', \ + 'Indication', 'Drug', 'Response_Type', 'Evidence_Source', 'Efficacy_Evidence', 'Drug_Detail', + 'Gene_Function', 'Drug_Category']) + if os.path.getsize(cnv_pos_file) > 0: + cnv_pos = pd.read_table(cnv_pos_file, sep="\t") + cnv = list(cnv_pos.groupby( + ['可信', 'chromosome', 'start', 'end', 'gene', 'depth', 'probes', 'cn', 'fun_change', 'Gene_Symbol'])) + for i in cnv: + for index, row in i[1].iterrows(): + drugs = row['药物中文名'].replace(" + ", ",") + drugs = list(set(drugs.split(","))) + drug_mm = '' + for drug in drugs: + if drug.upper() in drug_mechanism.keys(): + drug_mm += '[[' + drug + ']]' + drug_mechanism[drug.upper()] + i[1].loc[index, ['Drug_Detail']] = drug_mm + if row['标签'] == '非适应症': + row['证据等级'] = 'C' + if (re.search("敏感", row['Response_Type_C']) and row['证据等级'] == 'A'): + i[1].loc[index, ['Drug_Category']] = 'a' + elif re.search("敏感", row['Response_Type_C']) and row['证据等级'] == 'C': + i[1].loc[index, ['Drug_Category']] = 'b' + elif re.search("耐药", row['Response_Type_C']): + i[1].loc[index, ['Drug_Category']] = 'd' + elif row['Response_Type_C'] == '.': + i[1].loc[index, ['Drug_Category']] = '.' + else: + i[1].loc[index, ['Drug_Category']] = 'c' + i[1]['AMP_mut_level'] = i[1]['证据等级'].replace(['A', 'B', 'C', 'D'], ['I', 'I', 'II', 'II']) + cnv_sheet.loc[len(cnv_sheet)] = list(i[0][0:10]) + ['|'.join(list(i[1]['证据等级'])), + '|'.join(list(i[1]['AMP_mut_level'])), \ + '|'.join(list(i[1]['疾病中文名'])), + '|'.join(list(i[1]['药物中文名'])), + '|'.join(list(i[1]['Response_Type_C'])), + '|'.join(list(i[1]['Evidence_Source_C'])), + '|'.join(list(i[1]['EfficacyEvidence'])), \ + '|'.join(list(i[1]['Drug_Detail'])), + genefunction[i[0][9].upper()], + '|'.join(list(i[1]['Drug_Category']))] + else: + cnv_pos = pd.DataFrame(columns=[]) + + with pd.ExcelWriter(out_xlsx) as writer: + snvindel_sheet.to_excel(writer, sheet_name="snvindel", index=False) + fusion_sheet.to_excel(writer, sheet_name="fusion", index=False) + cnv_sheet.to_excel(writer, sheet_name="cnv", index=False) + + ##加入cnvkit/*.cnv.png + wb = openpyxl.load_workbook(filename=out_xlsx) + ws = wb['cnv'] + mr = ws.max_row + cell = 'C' + str(mr + 4) + cnv_pic = "".join([output_dir, '/cnvkit/', name, '.cnv.png']) + image = Image(cnv_pic) + ws.add_image(image, cell) + wb.save(out_xlsx) + + +class PostProcess: + """ + excel处理 + """ + + def __init__(self, path, outpath): + self.path = path + self.outpath = outpath + self.neeecol = self.need_col() + + def need_col(self): + """ + 读取所需列 + """ + path = os.path.join(os.path.dirname(__file__), 'columns.csv') + cols = pd.read_csv(path) + cols = cols.fillna('') + cols_record = cols.to_dict('list') + for sheet in cols_record: + cols_record[sheet] = [x for x in cols_record[sheet] if x] + return cols_record + + def msi(self): + """ + Process msi result files + """ + msi_files = glob.glob(os.path.join(self.path, 'MSI', '*.msi')) + msi_res = dict() + if msi_files: + df = pd.read_csv(msi_files[0], sep='\t') + res = df.to_dict('records')[0] + msi_res['msi_count'] = res['Total_Number_of_Sites'] + msi_res['msi_value'] = res['%'] + if msi_res['msi_value'] >= 0.3: + msi_res['msi_result'] = 'MSI-H' + msi_res['msi_predict'] = '对免疫检查点抑制剂可能敏感' + else: + msi_res['msi_result'] = 'MSS' + msi_res['msi_predict'] = '对免疫检查点抑制剂可能不敏感' + return [msi_res] + + def chemo(self): + """ + 化疗 + """ + chemo_files = glob.glob(os.path.join(self.path, 'chemo', '*chemo.res.txt')) + chemo_res = [] + if chemo_files: + df = pd.read_csv(chemo_files[0], sep='\t') + df = df.fillna('.') + chemo_res = df.to_dict('records') + return chemo_res + + def heredity(self): + """ + 遗传 + """ + heredi_files = glob.glob(os.path.join(self.path, 'mutation', '*Germline*filtered.txt')) + heredires = [] + if heredi_files: + df = pd.read_csv(heredi_files[0], sep='\t') + df = df.fillna('.') + tmdf1 = df[ + ['1000g2015aug_all', '1000g2015aug_eas', 'esp6500siv2_all', 'ExAC_nontcga_ALL', 'ExAC_nontcga_EAS', + 'gnomAD_genome_ALL', 'gnomAD_genome_EAS']].replace('.', 0).applymap(lambda x: eval(str(x))) + df['freq_high'] = tmdf1.max(axis=1) + tmdf2 = df[['MutationTaster_pred', 'FATHMM_pred', 'MetaLR_pred']] + df['Deleterious'] = tmdf2.apply(lambda x: x.tolist().count('D'), axis=1) + df_need = df[self.neeecol.get('HCS', [])] + try: + heredires = df_need.to_dict('records') + except KeyError as e: + raise UserWarning('表头设置和配置文件不对应', e) + return heredires + + def MMR(self): + """ + MMR + """ + mmr_files = glob.glob(os.path.join(self.path, 'MMR', '*mmr.pre.txt')) + mmr = [] + if mmr_files: + df = pd.read_csv(mmr_files[0], sep='\t') + df = df.fillna('.') + tmdf1 = df[ + ['1000g2015aug_all', '1000g2015aug_eas', 'esp6500siv2_all', 'ExAC_nontcga_ALL', 'ExAC_nontcga_EAS', + 'gnomAD_genome_ALL', 'gnomAD_genome_EAS']].replace('.', 0).applymap(lambda x: eval(str(x))) + df['freq_high'] = tmdf1.max(axis=1) + tmdf2 = df[['MutationTaster_pred', 'FATHMM_pred', 'MetaLR_pred']] + df['Deleterious'] = tmdf2.apply(lambda x: x.tolist().count('D'), axis=1) + df_need = df[self.neeecol.get('HCS', [])] + try: + mmr = df_need.to_dict('records') + except KeyError as e: + raise UserWarning('表头设置和配置文件不对应', e) + return mmr + + def hotspot(self): + hotspot_files = glob.glob( + os.path.join(self.path, 'mutation', 'hotspot', '*hotspot.snp.indel.filter.anno.hg19_multianno.txt')) + if hotspot_files: + return self.txt_2_excel(hotspot_files[0]) + + def splicing(self): + splicing_files = glob.glob( + os.path.join(self.path, 'mutation', '*.target.splicing.txt')) + if splicing_files: + return self.txt_2_excel(splicing_files[0]) + + def indication(self): + indication_files = glob.glob( + os.path.join(self.path, 'mutation', '*indication.txt')) + if indication_files: + return self.txt_2_excel(indication_files[0]) + + def longindel(self): + longindel_files = glob.glob( + os.path.join(self.path, 'fusion', '*.longindel.pos.txt')) + if longindel_files: + return self.txt_2_excel(longindel_files[0]) + + def cms(self): + """ + 样本信息 + """ + cms_files = glob.glob(os.path.join(self.path, 'qc', '*_post.json')) + cms_info_need = [] + if cms_files: + file_read = open(cms_files[0], 'r') + cms_info = json.load(file_read)['data'] + file_read.close() + df = pd.DataFrame(cms_info) + df_need = df[self.neeecol.get('sample_info', [])] + try: + cms_info_need = df_need.to_dict('records') + except KeyError as e: + raise UserWarning('表头设置和配置文件不对应', e) + return cms_info_need + + def qc(self): + qc_files = glob.glob(os.path.join(self.path, 'qc', '*_post.json')) + qc_res = [] + if qc_files: + df = pd.read_csv(qc_files[0], sep='\t', header=None) + df = df.set_index(0).T + qc_res = df.to_dict('records') + return qc_res + + # + # def snv(self): + # # filter file + # filter_files = glob.glob(os.path.join(self.path, 'report', '*snp.indel.Somatic.annoall.hg19_multianno_filtered.txt')) + # if filter_files: + # snv = pd.read_csv(filter_files[0], sep="\t") + # def sign_drug_Category(x): + # if '敏感' in x['Response_Type_C'] and x['证据等级'] == 'A': + # return 'a' + # elif '敏感' in x['Response_Type_C'] and x['证据等级'] == 'C': + # return 'b' + # elif '耐药' in x['Response_Type_C']: + # return 'd' + # else: + # return 'c' + # # pos_file 处理 + # pos_files = glob.glob(os.path.join(self.path, 'mutation', '*snvindel.pos.txt')) + # if pos_files: + # pos = pd.read_csv(pos_files[0], sep='\t') + # pos['证据等级'] = pos.apply(lambda x: 'C' if x['标签'] == '非适应症' else x['证据等级'], axis=1) + # pos['Drug_Category'] = pos.apply(sign_drug_Category, axis=1) + # pos['AMP_mut_level'] = pos['证据等级'].replace(['A', 'B', 'C', 'D'], ['I', 'I', 'II', 'II']) + # agg_list = ['证据等级', 'AMP_mut_level', '疾病中文名', '药物中文名', '证据等级', 'Response_Type_C', 'Evidence_Source_C', + # 'EfficacyEvidence', 'Drug_Category'] + # agg_dict = {column: ','.join for column in agg_list} + # pos_group =pos.groupby(['Gene.refGene','AAChange.refGene','fun_change']).agg(agg_dict, axis=1) + + def txt_2_excel(self, path): + try: + df = pd.read_csv(path, sep='\t') + except pd.errors.EmptyDataError: + return [] + return df.to_dict('records') + + def collect(self): + writer = pd.ExcelWriter(self.outpath, mode='a', engine='openpyxl') + sheet = { + 'MSI': self.msi(), + 'chemo': self.chemo(), + 'HCS': self.heredity(), + 'sample_info': self.cms(), + 'MMR': self.MMR(), + 'hotspot': self.hotspot(), + 'MET': self.splicing(), + 'indication': self.indication(), + 'longindel': self.longindel(), + 'qc': self.qc() + } + # 遍历CSV文件列表 + for sheet_name in sheet: + # 读取CSV文件为DataFrame + df = pd.DataFrame(sheet[sheet_name]) + df.to_excel(writer, sheet_name=sheet_name, index=False) + # 保存并关闭Excel写入器 + writer.close() + + +if __name__ == '__main__': + snv_fusion_cnv(sys.argv[1], sys.argv[2]) + # 未加日志，未添加路径 + out_xlsx = "".join([sys.argv[1], '/report/', sys.argv[2], '.check_new.xlsx']) + postprocess = PostProcess(sys.argv[1], out_xlsx) + postprocess.collect() diff --git a/scripts/comcancergene_report.py b/scripts/comcancergene_report.py new file mode 100644 index 0000000..e14835b --- /dev/null +++ b/scripts/comcancergene_report.py @@ -0,0 +1,864 @@ +#!/usr/bin/python3 +# -*- coding: UTF-8 -*- + +##https://www.pianshen.com/article/5314917437/ +##https://zhuanlan.zhihu.com/p/366902690 +##https://itpcb.com/a/277599 +import docxtpl +from docx.shared import Mm +from docxtpl import DocxTemplate,RichText +import pandas as pd +from pandas import DataFrame +import re +import sys +import os +import json +import time + +if len(sys.argv) != 5: + print(" ".join(['usage:python',sys.argv[0],'output_dir','tumor','sample_type(t for tissue,c for cfdna)']),'projcet') + sys.exit() + + +output_dir=sys.argv[1] +name=sys.argv[2] +Sample_type=sys.argv[3] +projcet=sys.argv[4] +snv_base="".join([name,'.snvindel.pos.dedup.txt']) +snv_file='/'.join([output_dir,'mutation',snv_base]) +snv_base_vus="".join([name,'.snvindel.vus.txt']) +snv_file_vus='/'.join([output_dir,'mutation',snv_base_vus]) +fusion_base="".join([name,'.fusion.pos.dedup.txt']) +fusion_file='/'.join([output_dir,'fusion',fusion_base]) +cnv_base="".join([name,'.cnv.pos.dedup.txt']) +cnv_file='/'.join([output_dir,'cnvkit',cnv_base]) +qc_base=''.join([name,'_qc.txt']) +qc_file='/'.join([output_dir,'qc',qc_base]) +report_base="".join([name,'_report.docx']) +report_file='/'.join([output_dir,'report',report_base]) +indication_file="".join([output_dir,'/mutation/','indication.txt']) + +context = {'list1':[],'list2':{},'list3':{},'clingene1':[],'clingene2':[],'nonclingenes':[],'genefunc':{}, +'indication':[],'mmr':[],'chemo':[]} + + +#genefunction +genefunction={} +gf=open("/dataseq/jmdna/codes/reportbase/gene_function.txt",'r',encoding='utf-8').readlines() +for line in gf[1:]: + gene=line.strip().split("\t")[0] + func=line.strip().split("\t")[1] + genefunction[gene.upper()]=func + +##sensitive_resistant_drug +drug_disease={} +drug_mechanism={} +drug_fh=open("/dataseq/jmdna/codes/reportbase/target_drug.txt",'r',encoding='utf-8').readlines() +for line in drug_fh[1:]: + disease=line.split("\t")[8] + mechanism=line.split("\t")[11] + drugs=line.split("\t")[0].split('|') + if disease or mechanism: + for drug in drugs: + drug_disease[drug.upper()]=disease + drug_mechanism[drug.upper()]=mechanism + + +sensitive_resistant_drug=[{'type':'可能敏感药物','drug':[]},{'type':'可能耐药药物','drug':[]}] + +##somatic snvindel处理 +snv_size = os.path.getsize(snv_file) +if snv_size>0: + snv=pd.read_table(snv_file,sep="\t") + cols=[index for index,row in snv[snv['可信']==0].iterrows()] + snv.drop(cols,inplace=True) + genes=snv['Gene.refGene'].drop_duplicates() + if len(genes): + for gene in genes: + rt={} + rt[gene]=[] + muts=snv['AAChange.refGene'][snv['Gene.refGene']==gene].drop_duplicates() + for mut in muts: + info2={mut:[]} + for index,row in snv[snv['AAChange.refGene']==mut].iterrows(): + info3={} + info3['drug']=row['药物中文名'] + info3['effect']=row['Response_Type_C'] + info3['tumor']=row['疾病中文名'] + info3['evidence']=row['Evidence_Source_C'] + info3['sig']=row['EfficacyEvidence'] + info2[mut].append(info3) +##sensitive_resistant_drug + drugs=row['Drug'].replace(" + ",",") + drugs=drugs.split(",") + drugs_chinese=row['药物中文名'].replace(" + ",",") + drugs_chinese=drugs_chinese.split(",") + bool=0 + for drug in drugs: + if drug.upper() in drug_disease.keys(): + if re.search(r'敏感',row['Response_Type_C']): + sensitive_drug={} + sensitive_drug['name']=drugs_chinese[bool] + sensitive_drug['mechanism']=("\n".join([drug_disease[drug.upper()],drug_mechanism[drug.upper()]])).strip() + if sensitive_drug not in sensitive_resistant_drug[0]['drug']: + sensitive_resistant_drug[0]['drug'].append(sensitive_drug) + elif re.search(r'耐药',row['Response_Type_C']): + resistant_drug={} + resistant_drug['name']=drugs_chinese[bool] + resistant_drug['mechanism']=("\n".join([drug_disease[drug.upper()],drug_mechanism[drug.upper()]])).strip() + if resistant_drug not in sensitive_resistant_drug[1]['drug']: + sensitive_resistant_drug[1]['drug'].append(resistant_drug) + bool+=1 + context['list2'][mut]=info2[mut] + info={} + info['gene']=snv['Gene.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0] + m=re.search(r'(p\..*)$',mut) + if m: + info['p']=m.group(1) + else: + m=re.search(r'(c\..*)$',mut) + info['p']=m.group(1) + info['freq']=snv['Freq'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0] + A=[] + B=[] + C=[] + D=[] + for index,row in snv[(snv['AAChange.refGene']==mut) & (snv['标签']=='适应症') & snv['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence='A' + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + A.extend(ds_new) + for index,row in snv[(snv['AAChange.refGene']==mut) & (snv['标签']=='非适应症') & snv['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence='C' + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + B.extend(ds_new) + for index,row in snv[(snv['AAChange.refGene']==mut) & (snv['标签']=='.') & snv['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence=row['证据等级'] + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + C.extend(ds_new) + for index,row in snv[(snv['AAChange.refGene']==mut) & snv['Response_Type_C'].str.contains("耐药")].iterrows(): + evidence='' + if row['标签']=='非适应症': + evidence='C' + else: + evidence=row['证据等级'] + ds=row['药物中文名'].split(",") + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + D.extend(ds_new) + A=sorted(set(A),key=A.index) + B=sorted(set(B),key=B.index) + C=sorted(set(C),key=C.index) + D=sorted(set(D),key=D.index) + info['drug_A']="\n".join(A) + info['drug_B']="\n".join(B) + info['drug_C']="\n".join(C) + info['drug_D']="\n".join(D) + if not info['drug_A']: + info['drug_A']='/' + if not info['drug_B']: + info['drug_B']='/' + if not info['drug_C']: + info['drug_C']='/' + if not info['drug_D']: + info['drug_D']='/' + context['list1'].append(info) + rt[gene].append("".join([info['p'],'(',info['freq'],')'])) +##genefunc + context['genefunc'][mut]=genefunction[gene.upper()] +##clingenes + clingene1={} + clingene2={} + for index,row in snv[(snv['AAChange.refGene']==mut)].iterrows(): + if row['标签']=='适应症' or row['证据等级']=='B': + clingene1['freq']=snv['Freq'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0] + if len((snv['AAChange.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0]).split(":")) == 5: + (clingene1['gene'],clingene1['transcript'],clingene1['exon'],clingene1['nacid'],clingene1['aacid'])=(snv['AAChange.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0]).split(":") + else: + (clingene1['gene'],clingene1['transcript'],clingene1['exon'],clingene1['nacid'])=(snv['AAChange.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0]).split(":") + clingene1['aacid'] = '/' + clingene1['muttype']=snv['ExonicFunc.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0] + if re.match("nonsynonymous SNV",clingene1['muttype']): + clingene1['muttype']='错义突变' + elif re.search("^frameshift",clingene1['muttype']): + clingene1['muttype']='移码突变' + elif re.search("^nonframeshift",clingene1['muttype']): + clingene1['muttype']='非移码突变' + elif re.match("stopgain",clingene1['muttype']): + clingene1['muttype']='提前终止' + else: + clingene1['muttype']='/' + context['clingene1'].append(clingene1) + else: + clingene2['freq']=snv['Freq'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0] + if len((snv['AAChange.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0]).split(":")) == 5: + (clingene2['gene'],clingene2['transcript'],clingene2['exon'],clingene2['nacid'],clingene2['aacid'])=(snv['AAChange.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0]).split(":") + else: + (clingene2['gene'],clingene2['transcript'],clingene2['exon'],clingene2['nacid'])=(snv['AAChange.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0]).split(":") + clingene2['aacid'] = '/' + clingene2['muttype']=snv['ExonicFunc.refGene'][snv['AAChange.refGene']==mut].reset_index(drop=True)[0] + if re.match("nonsynonymous SNV",clingene2['muttype']): + clingene2['muttype']='错义突变' + elif re.search("^frameshift",clingene2['muttype']): + clingene2['muttype']='移码突变' + elif re.search("^nonframeshift",clingene2['muttype']): + clingene2['muttype']='非移码突变' + elif re.match("stopgain",clingene2['muttype']): + clingene2['muttype']='提前终止' + else: + clingene2['muttype']='/' + context['clingene2'].append(clingene2) + break + context['list3'][gene]="\n".join(rt[gene]) + else: + snv_size=0 + + +##target vus and nontarget vus + +snv_size_vus = os.path.getsize(snv_file_vus) +if snv_size_vus>0: + snv_vus=pd.read_table(snv_file_vus,sep="\t") + for index,row in snv_vus.iterrows(): + if float(row['Freq'].replace('%',''))>=2: + nonclingene={} + if len(row['AAChange.refGene'].split(":")) == 5: + (nonclingene['gene'],nonclingene['transcript'],nonclingene['exon'],nonclingene['nacid'],nonclingene['aacid'])=row['AAChange.refGene'].split(":") + else: + (nonclingene['gene'],nonclingene['transcript'],nonclingene['exon'],nonclingene['nacid'])=row['AAChange.refGene'].split(":") + nonclingene['aacid'] = '/' + nonclingene['freq']=row['Freq'] + nonclingene['muttype']=row['ExonicFunc.refGene'] + if re.match("nonsynonymous SNV",nonclingene['muttype']): + nonclingene['muttype']='错义突变' + elif re.search("^frameshift",nonclingene['muttype']): + nonclingene['muttype']='移码突变' + elif re.search("^nonframeshift",nonclingene['muttype']): + nonclingene['muttype']='非移码突变' + elif re.match("stopgain",nonclingene['muttype']): + nonclingene['muttype']='提前终止' + else: + nonclingene['muttype']='/' + context['nonclingenes'].append(nonclingene) + + +##fusion处理 +fusion_size = os.path.getsize(fusion_file) +if fusion_size>0: + fusion=pd.read_table(fusion_file,sep="\t") + cols=[index for index,row in fusion[fusion['可信']==0].iterrows()] + fusion.drop(cols,inplace=True) + genes=fusion['Gene_Symbol'].drop_duplicates() + if len(genes): + for gene in genes: + rt={} + rt[gene]=[] + fusions=fusion['FUSION'][fusion['Gene_Symbol']==gene].drop_duplicates() + for mut in fusions: + info2={mut:[]} + for index,row in fusion[fusion['FUSION']==mut].iterrows(): + info3={} + info3['drug']=row['药物中文名'] + info3['effect']=row['Response_Type_C'] + info3['tumor']=row['疾病中文名'] + info3['evidence']=row['Evidence_Source_C'] + info3['sig']=row['EfficacyEvidence'] + info2[mut].append(info3) +##sensitive_resistant_drug + drugs=row['Drug'].replace(" + ",",") + drugs=drugs.split(",") + drugs_chinese=row['药物中文名'].replace(" + ",",") + drugs_chinese=drugs_chinese.split(",") + bool=0 + for drug in drugs: + if drug.upper() in drug_disease.keys(): + if re.search(r'敏感',row['Response_Type_C']): + sensitive_drug={} + sensitive_drug['name']=drugs_chinese[bool] + sensitive_drug['mechanism']=("\n".join([drug_disease[drug.upper()],drug_mechanism[drug.upper()]])).strip() + if sensitive_drug not in sensitive_resistant_drug[0]['drug']: + sensitive_resistant_drug[0]['drug'].append(sensitive_drug) + elif re.search(r'耐药',row['Response_Type_C']): + resistant_drug={} + resistant_drug['name']=drugs_chinese[bool] + resistant_drug['mechanism']=("\n".join([drug_disease[drug.upper()],drug_mechanism[drug.upper()]])).strip() + if resistant_drug not in sensitive_resistant_drug[1]['drug']: + sensitive_resistant_drug[1]['drug'].append(resistant_drug) + bool+=1 + context['list2'][mut]=info2[mut] + info={} + info['gene']=mut + info['p']='融合' + info['freq']="".join([str(fusion['FREQ1'][fusion['FUSION']==mut].reset_index(drop=True)[0]),'%']) + A=[] + B=[] + C=[] + D=[] + for index,row in fusion[(fusion['FUSION']==mut) & (fusion['标签']=='适应症') & fusion['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence='A' + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + A.extend(ds_new) + for index,row in fusion[(fusion['FUSION']==mut) & (fusion['标签']=='非适应症') & fusion['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence='C' + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + B.extend(ds_new) + for index,row in fusion[(fusion['FUSION']==mut) & (fusion['标签']=='.') & fusion['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence=row['证据等级'] + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + C.extend(ds_new) + for index,row in fusion[(fusion['FUSION']==mut) & fusion['Response_Type_C'].str.contains("耐药")].iterrows(): + evidence='' + if row['标签']=='非适应症': + evidence='C' + else: + evidence=row['证据等级'] + ds=row['药物中文名'].split(",") + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + D.extend(ds_new) + A=sorted(set(A),key=A.index) + B=sorted(set(B),key=B.index) + C=sorted(set(C),key=C.index) + D=sorted(set(D),key=D.index) + info['drug_A']="\n".join(A) + info['drug_B']="\n".join(B) + info['drug_C']="\n".join(C) + info['drug_D']="\n".join(D) +# info['drug_A']="\n".join(list(set(fusion['药物中文名'][(fusion['FUSION']==mut) & (fusion['标签']=='适应症') & fusion['Response_Type_C'].str.contains("敏感")].str.cat(sep=",").split(",")))) +# info['drug_B']="\n".join(list(set(fusion['药物中文名'][(fusion['FUSION']==mut) & (fusion['标签']=='非适应症') & fusion['Response_Type_C'].str.contains("敏感")].str.cat(sep=",").split(",")))) +# info['drug_C']="\n".join(list(set(fusion['药物中文名'][(fusion['FUSION']==mut) & (fusion['标签']=='.') & fusion['Response_Type_C'].str.contains("敏感")].str.cat(sep=",").split(",")))) +# info['drug_D']="\n".join(list(set(fusion['药物中文名'][(fusion['FUSION']==mut) & fusion['Response_Type_C'].str.contains("耐药")].str.cat(sep=",").split(",")))) + if not info['drug_A']: + info['drug_A']='/' + if not info['drug_B']: + info['drug_B']='/' + if not info['drug_C']: + info['drug_C']='/' + if not info['drug_D']: + info['drug_D']='/' + context['list1'].append(info) + rt[gene].append("".join([info['gene'],'(',info['freq'],')'])) +##genefunc + context['genefunc'][mut]=genefunction[gene.upper()] +##clingenes + clingene1={} + clingene2={} + for index,row in fusion[(fusion['FUSION']==mut)].iterrows(): + if row['标签']=='适应症' or row['证据等级']=='B': + clingene1['gene']= info['gene'] + clingene1['freq']= info['freq'] + (clingene1['transcript'],clingene1['exon'],clingene1['nacid'],clingene1['aacid'])=("/","/","/","/") + clingene1['muttype']= '融合' + context['clingene1'].append(clingene1) + else: + clingene2['gene']= info['gene'] + clingene2['freq']= info['freq'] + (clingene2['transcript'],clingene2['exon'],clingene2['nacid'],clingene2['aacid'])=("/","/","/","/") + clingene2['muttype']= '融合' + context['clingene2'].append(clingene2) + context['list3'][gene]="\n".join(rt[gene]) + else: + fusion_size=0 + + +##cnv处理 +cnv_size = os.path.getsize(cnv_file) +if cnv_size>0: + cnv=pd.read_table(cnv_file,sep="\t") + cols=[index for index,row in cnv[cnv['可信']==0].iterrows()] + cnv.drop(cols,inplace=True) + genes=cnv['gene'].drop_duplicates() + if len(genes): + for gene in genes: + rt={} + rt[gene]=[] + cnvs=cnv['Gene_Symbol'][cnv['gene']==gene].drop_duplicates() + for mut in cnvs: + info={} + info['gene']=mut + copy=cnv['cn'][cnv['Gene_Symbol']==mut].reset_index(drop=True)[0] + if copy > 2: + info['p']='扩增' + else: + info['p']='缺失' + A=[] + B=[] + C=[] + D=[] + for index,row in cnv[(cnv['Gene_Symbol']==mut) & (cnv['标签']=='适应症') & cnv['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence='A' + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + A.extend(ds_new) + for index,row in cnv[(cnv['Gene_Symbol']==mut) & (cnv['标签']=='非适应症') & cnv['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence='C' + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + B.extend(ds_new) + for index,row in cnv[(cnv['Gene_Symbol']==mut) & (cnv['标签']=='.') & cnv['Response_Type_C'].str.contains("敏感")].iterrows(): + ds=row['药物中文名'].split(",") + evidence=row['证据等级'] + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + C.extend(ds_new) + for index,row in cnv[(cnv['Gene_Symbol']==mut) & cnv['Response_Type_C'].str.contains("耐药")].iterrows(): + evidence='' + if row['标签']=='非适应症': + evidence='C' + else: + evidence=row['证据等级'] + ds=row['药物中文名'].split(",") + ds_new=[str(x) + '【' + evidence + ' 级】'for x in ds] + D.extend(ds_new) + A=sorted(set(A),key=A.index) + B=sorted(set(B),key=B.index) + C=sorted(set(C),key=C.index) + D=sorted(set(D),key=D.index) + info['drug_A']="\n".join(A) + info['drug_B']="\n".join(B) + info['drug_C']="\n".join(C) + info['drug_D']="\n".join(D) + info['freq']=" ".join([str(copy),'拷贝']) +# info['drug_A']="\n".join(list(set(cnv['药物中文名'][(cnv['Gene_Symbol']==mut) & (cnv['标签']=='适应症') & cnv['Response_Type_C'].str.contains("敏感")].str.cat(sep=",").split(",")))) +# info['drug_B']="\n".join(list(set(cnv['药物中文名'][(cnv['Gene_Symbol']==mut) & (cnv['标签']=='非适应症') & cnv['Response_Type_C'].str.contains("敏感")].str.cat(sep=",").split(",")))) +# info['drug_C']="\n".join(list(set(cnv['药物中文名'][(cnv['Gene_Symbol']==mut) & (cnv['标签']=='.') & cnv['Response_Type_C'].str.contains("敏感")].str.cat(sep=",").split(",")))) +# info['drug_D']="\n".join(list(set(cnv['药物中文名'][(cnv['Gene_Symbol']==mut) & cnv['Response_Type_C'].str.contains("耐药")].str.cat(sep=",").split(",")))) + if not info['drug_A']: + info['drug_A']='/' + if not info['drug_B']: + info['drug_B']='/' + if not info['drug_C']: + info['drug_C']='/' + if not info['drug_D']: + info['drug_D']='/' + context['list1'].append(info) + info2={mut:[]} + for index,row in cnv[cnv['Gene_Symbol']==mut].iterrows(): + info3={} + info3['drug']=row['药物中文名'] + info3['effect']=row['Response_Type_C'] + info3['tumor']=row['疾病中文名'] + info3['evidence']=row['Evidence_Source_C'] + info3['sig']=row['EfficacyEvidence'] + info2[mut].append(info3) +##sensitive_resistant_drug + drugs=row['Drug'].replace(" + ",",") + drugs=drugs.split(",") + drugs_chinese=row['药物中文名'].replace(" + ",",") + drugs_chinese=drugs_chinese.split(",") + bool=0 + for drug in drugs: + if drug.upper() in drug_disease.keys(): + if re.search(r'敏感',row['Response_Type_C']): + sensitive_drug={} + sensitive_drug['name']=drugs_chinese[bool] + sensitive_drug['mechanism']=("\n".join([drug_disease[drug.upper()],drug_mechanism[drug.upper()]])).strip() + if sensitive_drug not in sensitive_resistant_drug[0]['drug']: + sensitive_resistant_drug[0]['drug'].append(sensitive_drug) + elif re.search(r'耐药',row['Response_Type_C']): + resistant_drug={} + resistant_drug['name']=drugs_chinese[bool] + resistant_drug['mechanism']=("\n".join([drug_disease[drug.upper()],drug_mechanism[drug.upper()]])).strip() + if resistant_drug not in sensitive_resistant_drug[1]['drug']: + sensitive_resistant_drug[1]['drug'].append(resistant_drug) + bool+=1 + rt[gene].append("".join([info['p'],'(',info['freq'],')'])) + context['list2'][" ".join([mut,info['p']])]=info2[mut] +##genefunc + context['genefunc'][" ".join([mut,info['p']])]=genefunction[mut.upper()] +##clingenes + clingene1={} + clingene2={} + for index,row in cnv[(cnv['Gene_Symbol']==mut)].iterrows(): + if row['标签']=='适应症' or row['证据等级']=='B': + clingene1['gene']=info['gene'] + clingene1['freq']= info['freq'] + (clingene1['transcript'],clingene1['exon'],clingene1['nacid'],clingene1['aacid'])=("/","/","/","/") + clingene1['muttype']= info['p'] + context['clingene1'].append(clingene1) + else: + clingene2['gene']=info['gene'] + clingene2['freq']= info['freq'] + (clingene2['transcript'],clingene2['exon'],clingene2['nacid'],clingene2['aacid'])=("/","/","/","/") + clingene2['muttype']= info['p'] + context['clingene2'].append(clingene2) + context['list3'][gene]="\n".join(rt[gene]) + else: + cnv_size=0 + + +##msi +if Sample_type == 't': + msi_file=''.join([output_dir,'/MSI/',name,'.msi']) + msi=(open(msi_file,'r').readlines()[1]).split("\t") + context['msi_count']=msi[0] + context['msi_value']=round(float(msi[2].strip())/100,2) + if context['msi_value']>=0.3: + context['msi_result']='MSI-H' + context['msi_predict']='对免疫检查点抑制剂可能敏感' + else: + context['msi_result']='MSS' + context['msi_predict']='对免疫检查点抑制剂可能不敏感' + + +##MMR处理 +mmr_file=''.join([output_dir,'/MMR/',name,"_mmr.txt"]) +mmr_size = os.path.getsize(mmr_file) +mmr_result=0 +mmr_result_summary=[] +if mmr_size>0: + mmr_fh=open(mmr_file,'r',encoding='utf-8').readlines() + for line in mmr_fh[1:]: + mmr={} + mmr['gene']= line.strip().split("\t")[0] + mmr['transcript'] = line.strip().split("\t")[1] + mmr['nacid'] = line.strip().split("\t")[2] + mmr['aacid'] = line.strip().split("\t")[3] + mmr['muttype'] = line.strip().split("\t")[5] + mmr['freq'] = line.strip().split("\t")[4] + mmr['sig'] = line.strip().split("\t")[6] + if mmr['sig'] != '意义未明突变': + mmr_result+=1 + mmr_result_summary.append(mmr['gene'] + ' ' + mmr['aacid']) + context['mmr'].append(mmr) + +context['mmr_result']=mmr_result +mmr_result_summary=' | '.join(mmr_result_summary) +if mmr_result_summary: + context['mmr_result_summary']=mrr_result_summary + context['mmr_predict']="对免疫检查点抑制剂可能敏感" +else: + context['mmr_result_summary']="未检测到相关基因突变" + context['mmr_predict']="对免疫检查点抑制剂可能不敏感" + + + +##chemo +chemo_file=''.join([output_dir,'/chemo/',name,".drug.res.txt"]) +chemo_fh=open(chemo_file,'r') +bool=0 +chemos=chemo_fh.readlines()[1:] +chemo_result=0 +recommend_drug=[] +normal_drug=[] +restrict_drug=[] +while bool0: + hereditary_file1_fh=open(hereditary_file1,'r') + for line in hereditary_file1_fh.readlines()[1:]: + hereditary_cancer_1={} + lines=line.strip().split("\t") + hereditary_cancer_1['gene']=lines[0] + hereditary_cancer_1['syndrome']=lines[1] + hereditary_cancer_1['hereditary_type']=lines[2] + hereditary_cancer_1['type']=lines[3] + hereditary_cancer_1['result']=lines[4] + hereditary_result+=len(lines[4].split(";")) + hereditary_result_summary.append(hereditary_cancer_1['gene'] + ' ' + hereditary_cancer_1['result']) + hereditary_disease.append(hereditary_cancer_1['syndrome']) + context['hereditary_cancer_1'].append(hereditary_cancer_1) + + context['hereditary_result']=hereditary_result + if hereditary_result_summary: + context['hereditary_disease']=';'.join(hereditary_disease) + context['hereditary_result_summary']=' | '.join(hereditary_result_summary) + else: + context['hereditary_disease']='/' + context['hereditary_result_summary']='未检测到相关基因突变' + + hereditary_risk=[] + bool=0 + heres=hereditary_file2_fh.readlines()[1:] + while bool=85: + Q30_result='合格' +else: + Q30_result='警戒' + +depth=qc.loc['mean_depth(dedup)','B'] +if Sample_type == 'c': + if depth>=1000: + depth_result='合格' + else: + depth_result='警戒' +elif Sample_type == 't': + if depth>=500: + depth_result='合格' + else: + depth_result='警戒' + +uniformity=qc.loc['coverage(>=0.2*meanx)','B'] +if uniformity>=90: + uniformity_result='合格' +else: + uniformity_result='警戒' + +if Q30_result=='合格' and depth_result=='合格' and uniformity_result=='合格': + context['qc_result']='合格' +else: + context['qc_result']='警戒' + +context['Q30']=Q30 +context['Q30_result']=Q30_result +context['depth']=depth +context['uniformity']=uniformity +context['depth_result']=depth_result +context['uniformity_result']=uniformity_result + + + +##阴性模块处理 +##list1 +if len(context['list1'])==0: + context['list1']=[{'gene':'/','freq':'/','drug_A':'/','drug_B':'/','drug_C':'/','drug_D':'/'}] + +##list2 +if len(context['list2'])==0: + context['list2']= {'/':[{'drug':'/','effect':'/','tumor':'/','evidence':'/','sig':'/'}]} + context['genefunc']['/']='/' + + +##clingenes,nonclingenes +if len(context['clingenes1'])==0: + context['clingenes1']=[{'gene':'/','transcript':'/','nacid':'/','aacid':'/','exon':'/','muttype':'/','freq':'/'}] +if len(context['clingenes2'])==0: + context['clingenes2']=[{'gene':'/','transcript':'/','nacid':'/','aacid':'/','exon':'/','muttype':'/','freq':'/'}] +if len(context['nonclingenes'])==0: + context['nonclingenes']=[{'gene':'/','transcript':'/','nacid':'/','aacid':'/','exon':'/','muttype':'/','freq':'/'}] + +##sensitive_resistant_drug +if len(context['sensitive_resistant_drug'][0]['drug'])==0: + context['sensitive_resistant_drug'][0]['drug']=[{'name':'/','mechanism':'/'}] +if len(context['sensitive_resistant_drug'][1]['drug'])==0: + context['sensitive_resistant_drug'][1]['drug']=[{'name':'/','mechanism':'/'}] + +##mmr +if len(context['mmr'])==0: + context['mmr']=[{'gene':'/','transcript':'/','nacid':'/','aacid':'/','muttype':'/','freq':'/','sig':'/'}] + +##info +post_file=''.join([output_dir,'/qc/',name,'_post.json']) +sex='/' +age='/' +phone='/' +medical_history='/' +family_history='/' +sample_id=name +sample_type='/' +report_date=time.strftime("%Y-%m-%d", time.localtime()) +arrival_date=report_date +cancer_type='/' +pathologic_diagnosis='/' + +if os.path.isfile(post_file): +# if post_file.exists(): + post_fh=open(post_file,'r') + post=json.load(post_fh) + name=post["data"][0]["name"] + sex=post["data"][0]["gender"] + age=post["data"][0]["age"] + medical_history=post["data"][0]["treatHistory"] + family_history=post["data"][0]["sickFamilyHistory"] + sample_id=post["data"][0]["barcode"] + # sample_id_control=post["data"][0]["barcode_N"] + sample_type=post["data"][0]["source"] + # sample_type_control=post["data"][0]["source_N"] +# sample_type_control = post["data"][0].get('source_N', '/') + arrival_date=post["data"][0]["receiveTime"].split(' ')[0] + cancer_type=post["data"][0]["zlType"] + pathologic_diagnosis=post["data"][0]["treatResult"] + +context['info']={ +'name':name, +'sex':sex, +'age':age, +'phone':phone, +'medical_history':medical_history, +'family_history':family_history, +'sample_id':sample_id, +'sample_type':sample_type, +'report_date':report_date, +'arrival_date':arrival_date, +'cancer_type':cancer_type, +'pathologic_diagnosis':pathologic_diagnosis} +context['report_time']=report_date + +##模板替换 +file_real = os.path.realpath(sys.argv[0]) +Exe_Path = os.path.dirname(file_real) + +report_template={'lung85gene':{'t':'lung85-tissue-oem.docx','c':'lung85-blood-oem.docx'}, +'crc88gene':{'t':'CRC88-tissue-oem.docx','c':'CRC88-blood-oem.docx'}} +doc_full = os.path.join(Exe_Path, report_template[projcet][Sample_type]) + +doc = DocxTemplate(doc_full) + +doc.render(context) +doc.save(report_file) diff --git a/server.py b/server.py new file mode 100644 index 0000000..b27563d --- /dev/null +++ b/server.py @@ -0,0 +1,85 @@ +import json +import os +import socket +import struct +import sys +from datetime import datetime + +from main import main +from tools.common import basedir + + +def recvdata(conn, path): + """ + 接受文件 + :param conn: + :param path: + :return: + """ + header_size = struct.unpack('i', conn.recv(4))[0] + header_bytes = conn.recv(header_size) + header_json = header_bytes.decode('utf-8') + header_dic = json.loads(header_json) + content_len = header_dic['contentlen'] + content_name = header_dic['contentname'] + recv_len = 0 + fielpath = os.path.join(path, '%s_%s' % (datetime.now().strftime("%m%d%H%M"), content_name)) + file = open(fielpath, 'wb') + while recv_len < content_len: + correntrecv = conn.recv(1024 * 1000) + file.write(correntrecv) + recv_len += len(correntrecv) + file.close() + return fielpath + + +def senddata(conn, path, message=None): + name = os.path.basename(os.path.realpath(path)) + if not message: + with open(path, 'rb') as file: + content = file.read() + headerdic = dict( + contentlen=len(content), + contentname=name + ) + headerjson = json.dumps(headerdic) + headerbytes = headerjson.encode('utf-8') + headersize = len(headerbytes) + conn.send(struct.pack('i', headersize)) + conn.send(headerbytes) + conn.sendall(content) + else: + headerdic = dict( + contentlen=len(path), + contentname='message' + ) + headerjson = json.dumps(headerdic) + headerbytes = headerjson.encode('utf-8') + headersize = len(headerbytes) + conn.send(struct.pack('i', headersize)) + conn.send(headerbytes) + conn.sendall(path.encode('utf-8')) + + +def server(): + myserver = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + adrss = ("", 8190) + myserver.bind(adrss) + myserver.listen(5) + while True: + try: + myclient, adddr = myserver.accept() + recv_content = recvdata(myclient, os.path.join(basedir, 'xlsx')) + outputpath = main(recv_content) + senddata(myclient, outputpath) + print('生成成功') + except Exception as e: + print(e, '有错误') + # continue + + +if __name__ == '__main__': + if len(sys.argv) > 1: + outputpath = main(sys.argv[1]) + else: + server() diff --git a/t.json b/t.json new file mode 100644 index 0000000..a1a8146 --- /dev/null +++ b/t.json @@ -0,0 +1,1746 @@ +{ + "c": { + "sampleId": 60406928, + "sampleSn": "/", + "barcode": "2023WSSW000709-T", + "name": "刘杰", + "agentName": "上海清港泉生物科技有限公司", + "hospitalName": "/", + "testDoctor": "/", + "itemName": "LZ118.新80基因组织版", + "itemNum": 1, + "sampleStatus": "YWC", + "contact": "", + "source": "蜡块", + "makeTime": "2023-03-21 00:00:00", + "receiveTime": "2023-03-25", + "reportTime": "2023-07-31", + "remark": "留样本，实验后转寄", + "idCard": "", + "lockStatus": 0, + "waringTime": "0000-00-00 00:00:00", + "division": "/", + "zlType": "——", + "familySn": "/", + "estimateEndTime": "0000-00-00 00:00:00", + "doctorUserId": 0, + "areaAgentId": 1253, + "agentId": 2008, + "unitAgentId": 2007, + "labId": 0, + "orderType": "/", + "receiveStatus": 1, + "sampleInfoId": 94338196, + "gender": "女", + "age": 57, + "contactAddr": "/", + "familyRel": "/", + "birthday": "/", + "treatmentNo": "/", + "treatHistory": "——", + "sickFamilyHistory": "——", + "treatResult": "结肠癌" + }, + "snvindel": [ + { + "gene": "APC", + "transcript": "NM_000038", + "exon": "exon16", + "nacid": "c.4156A>T", + "aacid": "p.R1386X", + "mutant_frequency": "26.4%", + "AMP_mut_level": "III", + "muttype": "提前终止", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "APC:NM_000038:exon16:c.4156A>T:p.R1386X" + }, + { + "gene": "EGFR", + "transcript": "NM_005228", + "exon": "exon12", + "nacid": "c.1352G>A", + "aacid": "p.R451H", + "mutant_frequency": "1.33%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "EGFR:NM_005228:exon12:c.1352G>A:p.R451H" + }, + { + "gene": "EGFR", + "transcript": "NM_005228", + "exon": "exon17", + "nacid": "c.1994G>A", + "aacid": "p.G665D", + "mutant_frequency": "1.01%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "EGFR:NM_005228:exon17:c.1994G>A:p.G665D" + }, + { + "gene": "EGFR", + "transcript": "NM_005228", + "exon": "exon28", + "nacid": "c.3508C>T", + "aacid": "p.P1170S", + "mutant_frequency": "1.37%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "EGFR:NM_005228:exon28:c.3508C>T:p.P1170S" + }, + { + "gene": "EGFR", + "transcript": "NM_201283", + "exon": "exon10", + "nacid": "c.1213A>G", + "aacid": "p.S405G", + "mutant_frequency": "1.09%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "EGFR:NM_201283:exon10:c.1213A>G:p.S405G" + }, + { + "gene": "FGFR3", + "transcript": "NM_000142", + "exon": "exon6", + "nacid": "c.670G>A", + "aacid": "p.G224S", + "mutant_frequency": "1.82%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "FGFR3:NM_000142:exon6:c.670G>A:p.G224S" + }, + { + "gene": "KRAS", + "transcript": "NM_004985", + "exon": "exon2", + "nacid": "c.35G>T", + "aacid": "p.G12V", + "mutant_frequency": "22.18%", + "AMP_mut_level": "II", + "muttype": "错义突变", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "drug_category": { + "c": "考比替尼 + Ipatasertib 【C 级】\n贝美替尼 【C 级】\n曲美替尼 【D 级】\nRMC-6236 【D 级】", + "d": "西妥昔单抗 【C 级】\n曲妥珠单抗 + 妥卡替尼 【C 级】\n帕尼单抗 【C 级】\n曲妥珠单抗 + 帕妥珠单抗,曲妥珠单抗 + 拉帕替尼,trastuzumab deruxtecan 【C 级】\nEGFR-TKI 【C 级】" + }, + "drug_content": [ + { + "index": 0, + "DrugCn": "西妥昔单抗", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Cetuximab是一种表皮生长因子受体(EGFR)拮抗剂，FDA指出Cetuximab不适用于RAS突变型或RAS突变情况未知的结直肠癌患者(FDA-approval: 11/2020)。" + }, + { + "index": 1, + "DrugCn": "曲妥珠单抗 + 妥卡替尼", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "FDA推荐Trastuzumab + Tucatinib应用于携带HER2重复，RAS野生型的结直肠癌患者(NCCN: Rectal Cancer-Version 4.2022)" + }, + { + "index": 2, + "DrugCn": "帕尼单抗", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Panitumumab是一种表皮生长因子受体(EGFR)拮抗剂，FDA指出Panitumumab不适用于RAS突变型或RAS突变状态未知的转移性结直肠癌患者(FDA-approval: 06/2017)。" + }, + { + "index": 3, + "DrugCn": "曲妥珠单抗 + 帕妥珠单抗,曲妥珠单抗 + 拉帕替尼,trastuzumab deruxtecan", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出携带KRAS突变的结直肠癌患者对trastuzumab + pertuzumab,trastuzumab + lapatinib,trastuzumab deruxtecan治疗不敏感(NCCN: Colon Cancer-Version 2.2021)。" + }, + { + "index": 4, + "DrugCn": "EGFR-TKI", + "Response_Type": "耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出携带KRAS、BRAF基因突变和ALK、ROS1融合的非小细胞肺癌患者可能对EGFR信号通路抑制剂类靶向药物耐药(NCCN: Non-Small Cell Lung Cancer-Version 6.2021)。" + }, + { + "index": 5, + "DrugCn": "考比替尼 + Ipatasertib", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项Ib期临床试验中，13例携带KRAS突变的晚期实体瘤肿瘤患者接受Cobimetinib+ipatasertib联合治疗后，2例部分缓解，3例病情稳定，6例疾病进展为最佳反应(PMID: 32737717)。" + }, + { + "index": 6, + "DrugCn": "贝美替尼", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项I期临床试验中，纳入21位晚期实体瘤患者接受Binimetinib治疗，其中8例患者携带KRAS突变。在纳入分析的18例患者中，14例患者病情稳定，包含4例携带KRAS突变患者(PMID: 27071922)。" + }, + { + "index": 7, + "DrugCn": "曲美替尼", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床前研究", + "Efficacy_Evidence": "在一项临床前研究中，曲美替尼可抑制BRAF V600E和KRAS突变肿瘤细胞系的增殖，其IC50值低于PD0325901或selumetinib，虽然曲美替尼和PD0325901在体外对MEK1具有相似的效力。与PD0325901相比，在这些浓度下用曲美替尼或CH5126766处理48小时，可在KRAS突变细胞(H2030)和表达活性CRAF数量增加的A375细胞中更持久地抑制pERK活性(PMID: 24746704)。" + }, + { + "index": 8, + "DrugCn": "RMC-6236", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床前研究", + "Efficacy_Evidence": "在体外实验中，RMC-6236抑制了细胞生长，并诱导多种RAS癌细胞株凋亡，在临床前体内异种移植模型中，RMC-6236可抑制RAS通路的激活长达48小时。与健康组织相比RMC-6236对肿瘤组织的亲和力更高，在多种细胞系来源的异种移植模型（NSCLC、CRC和PDAC等）中RMC-6236对KRAS突变（特别是KRAS G12D, KRAS G12V和 KRAS G12R）均有明显也持久的肿瘤消退效果（Abstract: Koltun et al. Abstract# 3597, AACR 2022）。" + } + ], + "alter": "KRAS:NM_004985:exon2:c.35G>T:p.G12V" + }, + { + "gene": "NF1", + "transcript": "NM_000267", + "exon": "exon38", + "nacid": "c.5694G>C", + "aacid": "p.E1898D", + "mutant_frequency": "1.07%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "NF1:NM_000267:exon38:c.5694G>C:p.E1898D" + }, + { + "gene": "PIK3CA", + "transcript": "NM_006218", + "exon": "exon10", + "nacid": "c.1636C>A", + "aacid": "p.Q546K", + "mutant_frequency": "2.4%", + "AMP_mut_level": "II", + "muttype": "错义突变", + "Gene_function": "PIK3CA基因编码磷脂酰肌醇3-激酶(PI3K)的p110α催化亚基，PI3K是由受体酪氨酸激酶 [例如表皮生长因子受体(EGFR)和人表皮生长受体2 (HER2/ERBB2)] 驱动的信号转导通路中的整合信号分子。PI3K的活性形式由调节性p85亚单位和催化性p110亚单位组成。激活的PI3K将PIP2转化为PIP3，引发AKT(蛋白激酶B)的磷酸化和雷帕霉素(mTOR)激酶的激活。PI3K/AKT/mTOR信号通路通过调节各种细胞功能(包括细胞增殖、存活、代谢和细胞骨架重组)来促进肿瘤发生(PMID: 16453012)。", + "drug_category": { + "c": "阿培利司 【C 级】\nRLY-2608 【D 级】" + }, + "drug_content": [ + { + "index": 9, + "DrugCn": "阿培利司", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "在一项I期临床试验中，携带PIK3CA基因突变的晚期实体瘤患者当使用Alpelisib (BYL719)治疗后，58.2% (78/134)的患者病情得到控制，1个患者获得完全缓解，7个部分缓解，70个患者疾病稳定，临床受益率 (CR+PR+SD>24 weeks)为15.7% (21/134)(PMID: 29401002; NCT01219699)。" + }, + { + "index": 10, + "DrugCn": "RLY-2608", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "RLY-2608是一种新型PI3Kα抑制剂，一项I期临床研究旨在评估RLY-2608作为单药在PI3KCA突变的晚期实体瘤患者以及与氟维司群联合用于PIK3CA突变，HR+，HER2-转移性乳腺癌（MBC）的中的临床活性。实验正在进行中（Abstract: Perez et al. Abstract# TPS1124, ASCO 2022）。" + } + ], + "alter": "PIK3CA:NM_006218:exon10:c.1636C>A:p.Q546K" + }, + { + "gene": "RET", + "transcript": "NM_020975", + "exon": "exon2", + "nacid": "c.220G>A", + "aacid": "p.G74S", + "mutant_frequency": "1.24%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "RET:NM_020975:exon2:c.220G>A:p.G74S" + }, + { + "gene": "TP53", + "transcript": "NM_000546", + "exon": "exon4", + "nacid": "c.216dupC", + "aacid": "p.V73Rfs*76", + "mutant_frequency": "27.53%", + "AMP_mut_level": "II", + "muttype": "移码突变", + "Gene_function": "TP53编码p53肿瘤抑制蛋白，这是一种转录因子，通过诱导下游抗肿瘤反应，如DNA损伤修复和凋亡，对细胞应激(包括DNA损伤和致癌性激活)产生应答(PMID: 11099028)。p53蛋白由一个N末端反式激活结构域，一个中心DNA结合结构域、一个寡聚结构域，以及一个C末端调节结构域组成(PMID: 22713868)。", + "drug_category": { + "c": "培唑帕尼 + 伏立诺他 【C 级】\n贝伐珠单抗 【C 级】" + }, + "drug_content": [ + { + "index": 11, + "DrugCn": "培唑帕尼 + 伏立诺他", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "在一项I期试验中，Votrient（培唑帕尼）和Zolinza（伏立诺他）的联合疗法改善了携带TP53热点突变的晚期实体瘤患者的无进展生存期和总生存率，疾病稳定率为45％（5/11），而未检测到TP53突变患者的疾病稳定率为16％（4/25）（PMID：25669829）。" + }, + { + "index": 12, + "DrugCn": "贝伐珠单抗", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项临床试验中，106位携带TP53突变的晚期实体瘤患者使用VEGF/VEGFR抑制剂如Bevacizumab治疗，其疾病稳定、部分缓解、完全缓解、总生存期、从开始治疗到治疗失败的时间这些指标均好于TP53基因野生型的82位患者(PMID: 27466356)。在一项回顾性研究中，携带TP53基因突变的癌症患者采用bevacizumab治疗，其疾病无进展生存期长于TP53基因野生型患者(PMID: 23670029)。" + } + ], + "alter": "TP53:NM_000546:exon4:c.216dupC:p.V73Rfs*76" + } + ], + "fusion": [], + "cnv": [], + "hotspot": [ + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "A", + "AMP_mut_level": "I", + "Indication": "结直肠癌", + "DrugCn": "西妥昔单抗", + "Response_Type": "耐药", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Cetuximab是一种表皮生长因子受体(EGFR)拮抗剂，FDA指出Cetuximab不适用于RAS突变型或RAS突变情况未知的结直肠癌患者(FDA-approval: 11/2020)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "d", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "A", + "AMP_mut_level": "I", + "Indication": "结直肠癌", + "DrugCn": "曲妥珠单抗 + 妥卡替尼", + "Response_Type": "耐药", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "FDA推荐Trastuzumab + Tucatinib应用于携带HER2重复，RAS野生型的结直肠癌患者(NCCN: Rectal Cancer-Version 4.2022)", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "d", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "A", + "AMP_mut_level": "I", + "Indication": "结直肠癌", + "DrugCn": "帕尼单抗", + "Response_Type": "耐药", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Panitumumab是一种表皮生长因子受体(EGFR)拮抗剂，FDA指出Panitumumab不适用于RAS突变型或RAS突变状态未知的转移性结直肠癌患者(FDA-approval: 06/2017)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "d", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "A", + "AMP_mut_level": "I", + "Indication": "结直肠癌", + "DrugCn": "曲妥珠单抗 + 帕妥珠单抗,曲妥珠单抗 + 拉帕替尼,trastuzumab deruxtecan", + "Response_Type": "耐药", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出携带KRAS突变的结直肠癌患者对trastuzumab + pertuzumab,trastuzumab + lapatinib,trastuzumab deruxtecan治疗不敏感(NCCN: Colon Cancer-Version 2.2021)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "d", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "C", + "AMP_mut_level": "II", + "Indication": "非小细胞肺癌", + "DrugCn": "EGFR-TKI", + "Response_Type": "耐药", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出携带KRAS、BRAF基因突变和ALK、ROS1融合的非小细胞肺癌患者可能对EGFR信号通路抑制剂类靶向药物耐药(NCCN: Non-Small Cell Lung Cancer-Version 6.2021)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "d", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "B", + "AMP_mut_level": "I", + "Indication": "结直肠癌", + "DrugCn": "Irinotecan + 司美替尼", + "Response_Type": "可能敏感", + "Evidence_Source": "临床II期", + "Efficacy_Evidence": "在一项II期临床研究中，Selumetinib (AZD6244)联合Camptosar (伊立替康)导致9.7% (3/31)携带KRAS外显子2突变的结直肠癌患者部分反应，51.6% (16/31)患者病情稳定(PMID: 25322874)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "c", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "C", + "AMP_mut_level": "II", + "Indication": "结直肠癌", + "DrugCn": "曲美替尼", + "Response_Type": "可能敏感", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "在一项I期临床试验中，8名患有结肠直肠癌的患者中包含3名携带KRAS突变的患者，在使用Mekinist（曲美替尼）治疗疾病稳定（PMID:22805291）。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "c", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "C", + "AMP_mut_level": "II", + "Indication": "实体瘤", + "DrugCn": "考比替尼 + Ipatasertib", + "Response_Type": "可能敏感", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项Ib期临床试验中，13例携带KRAS突变的晚期实体瘤肿瘤患者接受Cobimetinib+ipatasertib联合治疗后，2例部分缓解，3例病情稳定，6例疾病进展为最佳反应(PMID: 32737717)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "c", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "C", + "AMP_mut_level": "II", + "Indication": "实体瘤", + "DrugCn": "贝美替尼", + "Response_Type": "可能敏感", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项I期临床试验中，纳入21位晚期实体瘤患者接受Binimetinib治疗，其中8例患者携带KRAS突变。在纳入分析的18例患者中，14例患者病情稳定，包含4例携带KRAS突变患者(PMID: 27071922)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "c", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "D", + "AMP_mut_level": "II", + "Indication": "实体瘤", + "DrugCn": "曲美替尼", + "Response_Type": "可能敏感", + "Evidence_Source": "临床前研究", + "Efficacy_Evidence": "在一项临床前研究中，曲美替尼可抑制BRAF V600E和KRAS突变肿瘤细胞系的增殖，其IC50值低于PD0325901或selumetinib，虽然曲美替尼和PD0325901在体外对MEK1具有相似的效力。与PD0325901相比，在这些浓度下用曲美替尼或CH5126766处理48小时，可在KRAS突变细胞(H2030)和表达活性CRAF数量增加的A375细胞中更持久地抑制pERK活性(PMID: 24746704)。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "c", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "mutant_frequency": 0.2234, + "total_reads": 1817, + "mutant_reads": 406, + "strand_bias": "222:184", + "Otherinfo10": "PASS", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "ExonicFunc.refGene": "nonsynonymous SNV", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNSIG": "Pathogenic", + "ACMG_level": 1, + "Deleterious": 2, + "freq_high": 0, + "OKBSIG": "Oncogenic", + "AMP_evidence_level": "D", + "AMP_mut_level": "II", + "Indication": "实体瘤", + "DrugCn": "RMC-6236", + "Response_Type": "可能敏感", + "Evidence_Source": "临床前研究", + "Efficacy_Evidence": "在体外实验中，RMC-6236抑制了细胞生长，并诱导多种RAS癌细胞株凋亡，在临床前体内异种移植模型中，RMC-6236可抑制RAS通路的激活长达48小时。与健康组织相比RMC-6236对肿瘤组织的亲和力更高，在多种细胞系来源的异种移植模型（NSCLC、CRC和PDAC等）中RMC-6236对KRAS突变（特别是KRAS G12D, KRAS G12V和 KRAS G12R）均有明显也持久的肿瘤消退效果（Abstract: Koltun et al. Abstract# 3597, AACR 2022）。", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "Drug_Category": "c", + "Otherinfo11": "SAMPLE=2023WSSW000709-T;TYPE=SNV;DP=1817;VD=406;AF=0.2234;BIAS=2:2;REFBIAS=742:665;VARBIAS=222:184;PMEAN=39.5;PSTD=1;QUAL=34;QSTD=1;SBF=0.4986;ODDRATIO=1.08124472893195;MQ=60;SN=44.111;HIAF=0.2215;ADJAF=0.0083;SHIFT3=0;MSI=2;MSILEN=1;NM=1.2;HICNT=397;HICOV=1792;LSEQ=AGGCACTCTTGCCTACGCCA;RSEQ=CAGCTCCAACTACCACAAGT;DUPRATE=0;SPLITREAD=0;SPANPAIR=0", + "Otherinfo12": "GT:DP:VD:AD:AF:RD:ALD", + "Otherinfo13": "0/1:1817:406:1407,406:0.2234:742,665:222,184" + } + ], + "MET": [], + "longindel": [], + "MMR": [ + { + "gene": "MSH2", + "transcript": "NM_000251", + "c_change": "c.2425G>A", + "p_change": "p.E809K", + "freq": "51.85%", + "muttype": "错义突变", + "sig": "意义未明突变" + } + ], + "sum": { + "mmr": { + "result_summary": "MSH2 p.E809K", + "predict": "对免疫检查点抑制剂可能敏感", + "mmr_num": 1 + }, + "chemo": { + "drug_num": 22, + "drug_category": { + "常规": "卡铂,奥沙利铂,甲氨蝶呤,多西他赛,多柔比星", + "推荐": "环磷酰胺,顺铂,卡培他滨,替加氟,替吉奥,吉西他滨,伊立替康,依托泊苷,紫杉醇,丝裂霉素,表柔比星,昂丹司琼,格拉司琼", + "谨慎": "氟尿嘧啶,培美曲塞,长春新碱,长春瑞滨" + } + }, + "hcs": { + "num": 3 + }, + "hereditary": { + "result": "TP53 p.V73Rfs*76", + "disease": "Li-Fraumeni综合征", + "risk": "结直肠癌,胰腺癌,甲状腺癌,胃癌,肾上腺皮质癌,乳腺癌,胶质母细胞瘤,星形细胞瘤,骨肉瘤,软组织肉瘤,急性淋巴细胞白血病,急性髓性白血病,骨髓增生异常综合征,淋巴瘤,头颈鳞癌,肾细胞癌,喉癌,肺癌,皮肤癌,卵巢癌,前列腺癌,睾丸癌,妊娠期绒毛膜癌" + }, + "signtb_num": 3, + "signdrug_num": 8 + }, + "MSI": { + "msi_count": 13, + "msi_value": 0, + "msi_result": "MSS", + "msi_predict": "对免疫检查点抑制剂可能不敏感" + }, + "chemo": { + "chemo_res": [ + { + "index": 1, + "药物名称": "环磷酰胺", + "疗效": 1, + "毒副": 0, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好" + }, + { + "index": 2, + "药物名称": "卡铂", + "疗效": 2, + "毒副": -1, + "推荐程度": "常规", + "疗效和毒副总结": "疗效较好,毒副较高" + }, + { + "index": 3, + "药物名称": "奥沙利铂", + "疗效": 3, + "毒副": -2, + "推荐程度": "常规", + "疗效和毒副总结": "疗效较好,毒副较高" + }, + { + "index": 4, + "药物名称": "顺铂", + "疗效": 2, + "毒副": 1, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好,毒副较低" + }, + { + "index": 5, + "药物名称": "卡培他滨", + "疗效": 0, + "毒副": 9, + "推荐程度": "推荐", + "疗效和毒副总结": "毒副较低" + }, + { + "index": 6, + "药物名称": "替加氟", + "疗效": 0, + "毒副": 4, + "推荐程度": "推荐", + "疗效和毒副总结": "毒副较低" + }, + { + "index": 7, + "药物名称": "替吉奥", + "疗效": 0, + "毒副": 4, + "推荐程度": "推荐", + "疗效和毒副总结": "毒副较低" + }, + { + "index": 8, + "药物名称": "氟尿嘧啶", + "疗效": 1, + "毒副": -2, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效较好,毒副较高" + }, + { + "index": 9, + "药物名称": "吉西他滨", + "疗效": 0, + "毒副": 1, + "推荐程度": "推荐", + "疗效和毒副总结": "毒副较低" + }, + { + "index": 10, + "药物名称": "培美曲塞", + "疗效": -2, + "毒副": 0, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效较差" + }, + { + "index": 11, + "药物名称": "甲氨蝶呤", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "index": 12, + "药物名称": "伊立替康", + "疗效": 0, + "毒副": 2, + "推荐程度": "推荐", + "疗效和毒副总结": "毒副较低" + }, + { + "index": 13, + "药物名称": "依托泊苷", + "疗效": 0, + "毒副": 1, + "推荐程度": "推荐", + "疗效和毒副总结": "毒副较低" + }, + { + "index": 14, + "药物名称": "多西他赛", + "疗效": -1, + "毒副": 1, + "推荐程度": "常规", + "疗效和毒副总结": "疗效较差,毒副较低" + }, + { + "index": 15, + "药物名称": "紫杉醇", + "疗效": 1, + "毒副": 1, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好,毒副较低" + }, + { + "index": 16, + "药物名称": "长春新碱", + "疗效": -1, + "毒副": 0, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效较差" + }, + { + "index": 17, + "药物名称": "长春瑞滨", + "疗效": -1, + "毒副": 0, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效较差" + }, + { + "index": 18, + "药物名称": "丝裂霉素", + "疗效": 1, + "毒副": 0, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好" + }, + { + "index": 19, + "药物名称": "多柔比星", + "疗效": 1, + "毒副": -1, + "推荐程度": "常规", + "疗效和毒副总结": "疗效较好,毒副较高" + }, + { + "index": 20, + "药物名称": "表柔比星", + "疗效": 2, + "毒副": 0, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好,毒副一般" + }, + { + "index": 21, + "药物名称": "昂丹司琼", + "疗效": 2, + "毒副": 0, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好" + }, + { + "index": 22, + "药物名称": "格拉司琼", + "疗效": 1, + "毒副": 0, + "推荐程度": "推荐", + "疗效和毒副总结": "疗效较好" + } + ], + "chemo_comb": { + "结直肠癌": [ + { + "用药方案": "奥沙利铂+亚叶酸钙+氟尿嘧啶", + "方案缩写": "FOLFOX", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "用药方案": "伊立替康+亚叶酸钙+氟尿嘧啶", + "方案缩写": "FOLFIRI", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "用药方案": "奥沙利铂+卡培他滨", + "方案缩写": "CAPEOX（又称Xelox）", + "source": "crc88gene", + "临床提示": "推荐" + }, + { + "用药方案": "伊立替康+奥沙利铂+亚叶酸钙+氟尿嘧啶", + "方案缩写": "FOLFOXIRI", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "用药方案": "伊立替康+卡培他滨", + "方案缩写": "CapIRI或XELIRI", + "source": "crc88gene", + "临床提示": "推荐" + }, + { + "用药方案": "奥沙利铂+雷替曲塞", + "方案缩写": "/", + "source": "crc88gene", + "临床提示": "可选" + }, + { + "用药方案": "伊立替康+雷替曲塞", + "方案缩写": "/", + "source": "crc88gene", + "临床提示": "推荐" + } + ] + }, + "chemo_info": { + "丝裂霉素": [ + { + "检测基因": "NQO1", + "检测位点": "rs1800566", + "基因型": "GG", + "证据等级": "3", + "drugsort": 6, + "用药提示": "疗效较好" + } + ], + "伊立替康": [ + { + "检测基因": "UGT1A1", + "检测位点": "rs3064744", + "基因型": "TA[6]/TA[6]", + "证据等级": "1A/1B", + "drugsort": 5, + "用药提示": "毒副较低" + }, + { + "检测基因": "UGT1A1", + "检测位点": "rs4148323", + "基因型": "GG", + "证据等级": "1A/1B", + "drugsort": 5, + "用药提示": "毒副较低" + } + ], + "依托泊苷": [ + { + "检测基因": "DYNC2H1", + "检测位点": "rs716274", + "基因型": "AA", + "证据等级": "3", + "drugsort": 5, + "用药提示": "毒副较低" + } + ], + "卡培他滨": [ + { + "检测基因": "DPYD", + "检测位点": "rs115232898", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs1801266", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs1801268", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs55886062", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs67376798", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs72549303", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs72549309", + "基因型": "ATGA/ATGA", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs75017182", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs3918290", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + } + ], + "卡铂": [ + { + "检测基因": "ERCC1", + "检测位点": "rs11615", + "基因型": "AG", + "证据等级": "3", + "drugsort": 2, + "用药提示": "毒副较高" + }, + { + "检测基因": "XRCC1", + "检测位点": "rs25487", + "基因型": "CC", + "证据等级": "2B", + "drugsort": 2, + "用药提示": "疗效较好" + } + ], + "吉西他滨": [ + { + "检测基因": "CDA", + "检测位点": "rs2072671", + "基因型": "AA", + "证据等级": "3", + "drugsort": 4, + "用药提示": "毒副较低" + } + ], + "培美曲塞": [ + { + "检测基因": "MTHFR", + "检测位点": "rs1801133", + "基因型": "AG", + "证据等级": "3", + "drugsort": 4, + "用药提示": "疗效较差" + }, + { + "检测基因": "TYMS", + "检测位点": "rs11280056", + "基因型": "TTAAAG/del", + "证据等级": "3", + "drugsort": 4, + "用药提示": "疗效较差" + } + ], + "多柔比星": [ + { + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "疗效较好" + }, + { + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + } + ], + "多西他赛": [ + { + "检测基因": "CASP7", + "检测位点": "rs2227310", + "基因型": "CC", + "证据等级": "3", + "drugsort": 5, + "用药提示": "疗效较差" + }, + { + "检测基因": "CYP3A4", + "检测位点": "rs2740574", + "基因型": "TT", + "证据等级": "3", + "drugsort": 5, + "用药提示": "毒副较低" + } + ], + "奥沙利铂": [ + { + "检测基因": "XRCC1", + "检测位点": "rs25487", + "基因型": "CC", + "证据等级": "2B", + "drugsort": 2, + "用药提示": "疗效较好" + }, + { + "检测基因": "GSTP1", + "检测位点": "rs1695", + "基因型": "AA", + "证据等级": "3", + "drugsort": 2, + "用药提示": "毒副较高" + }, + { + "检测基因": "ERCC2", + "检测位点": "rs13181", + "基因型": "TT", + "证据等级": "3", + "drugsort": 2, + "用药提示": "疗效较好" + }, + { + "检测基因": "ERCC1", + "检测位点": "rs11615", + "基因型": "AG", + "证据等级": "3", + "drugsort": 2, + "用药提示": "毒副较高" + } + ], + "昂丹司琼": [ + { + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "AA", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较好" + }, + { + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "AA", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较好" + } + ], + "替加氟": [ + { + "检测基因": "DPYD", + "检测位点": "rs67376798", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs75017182", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs3918290", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs55886062", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + } + ], + "替吉奥": [ + { + "检测基因": "DPYD", + "检测位点": "rs3918290", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs55886062", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs67376798", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs75017182", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + } + ], + "格拉司琼": [ + { + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "AA", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较好" + } + ], + "氟尿嘧啶": [ + { + "检测基因": "DPYD", + "检测位点": "rs72549303", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "TYMS", + "检测位点": "rs11280056", + "基因型": "TTAAAG/del", + "证据等级": "3", + "drugsort": 3, + "用药提示": "毒副较高" + }, + { + "检测基因": "NQO1", + "检测位点": "rs1800566", + "基因型": "GG", + "证据等级": "3", + "drugsort": 3, + "用药提示": "疗效较好" + }, + { + "检测基因": "DPYD", + "检测位点": "rs72549309", + "基因型": "ATGA/ATGA", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs1801266", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs1801268", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs3918290", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "GSTP1", + "检测位点": "rs1695", + "基因型": "AA", + "证据等级": "3", + "drugsort": 3, + "用药提示": "毒副较高" + }, + { + "检测基因": "DPYD", + "检测位点": "rs75017182", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs55886062", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs67376798", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + }, + { + "检测基因": "DPYD", + "检测位点": "rs115232898", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 3, + "用药提示": "毒副较低" + } + ], + "环磷酰胺": [ + { + "检测基因": "SOD2", + "检测位点": "rs4880", + "基因型": "AG", + "证据等级": "3", + "drugsort": 1, + "用药提示": "疗效居中" + }, + { + "检测基因": "GSTP1", + "检测位点": "rs1695", + "基因型": "AA", + "证据等级": "3", + "drugsort": 1, + "用药提示": "疗效较好" + } + ], + "甲氨蝶呤": [ + { + "检测基因": "MTHFR", + "检测位点": "rs1801133", + "基因型": "AG", + "证据等级": "2A", + "drugsort": 4, + "用药提示": "毒副居中" + } + ], + "紫杉醇": [ + { + "检测基因": "CYP2C8", + "检测位点": "rs11572080", + "基因型": "CC", + "证据等级": "3", + "drugsort": 5, + "用药提示": "毒副较低" + }, + { + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "AA", + "证据等级": "3", + "drugsort": 5, + "用药提示": "疗效较好" + } + ], + "表柔比星": [ + { + "检测基因": "NQO1", + "检测位点": "rs1800566", + "基因型": "GG", + "证据等级": "3", + "drugsort": 6, + "用药提示": "疗效较好" + }, + { + "检测基因": "GSTP1", + "检测位点": "rs1695", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较低,疗效较好" + }, + { + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + } + ], + "长春新碱": [ + { + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "AA", + "证据等级": "3", + "drugsort": 5, + "用药提示": "疗效较差" + } + ], + "长春瑞滨": [ + { + "检测基因": "CASP7", + "检测位点": "rs2227310", + "基因型": "CC", + "证据等级": "3", + "drugsort": 5, + "用药提示": "疗效较差" + } + ], + "顺铂": [ + { + "检测基因": "XRCC1", + "检测位点": "rs25487", + "基因型": "CC", + "证据等级": "2B", + "drugsort": 2, + "用药提示": "疗效较好" + }, + { + "检测基因": "XPC", + "检测位点": "rs2228001", + "基因型": "TT", + "证据等级": "3", + "drugsort": 2, + "用药提示": "毒副较低" + }, + { + "检测基因": "TPMT", + "检测位点": "rs1142345", + "基因型": "TT", + "证据等级": "3", + "drugsort": 2, + "用药提示": "毒副较低" + }, + { + "检测基因": "ERCC1", + "检测位点": "rs11615", + "基因型": "AG", + "证据等级": "3", + "drugsort": 2, + "用药提示": "毒副较高" + } + ] + } + }, + "HCS": [ + { + "Validated": 1, + "Chr": "chr5", + "Start": 112175447, + "End": 112175447, + "Ref": "A", + "Alt": "T", + "Func.refGene": "exonic", + "Gene.refGene": "APC", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "stopgain", + "AAChange.refGene": "APC:NM_000038:exon16:c.4156A>T:p.R1386X", + "avsnp150": ".", + "cosmic91": "ID=COSV57330977;OCCURENCE=6(large_intestine)", + "CLNALLELEID": ".", + "CLNDN": ".", + "CLNDISDB": ".", + "CLNREVSTAT": ".", + "CLNSIG": ".", + "1000g2015aug_all": ".", + "1000g2015aug_eas": ".", + "esp6500siv2_all": ".", + "ExAC_nontcga_ALL": ".", + "ACMG_level": 3 + }, + { + "Validated": 1, + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "A", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "nonsynonymous SNV", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>T:p.G12V", + "avsnp150": "rs121913529", + "cosmic91": "ID=COSV55497419;OCCURENCE=20(breast),1(female_genital_tract_(site_indeterminate)),7(liver),36(peritoneum),9(genital_tract),7(oesophagus),24(cervix),5668(large_intestine),1(central_nervous_system),189(biliary_tract),2(pleura),1(vulva),341(ovary),20(NS),45(stomach),90(haematopoietic_and_lymphoid_tissue),8(kidney),9(soft_tissue),32(urinary_tract),2142(pancreas),1(autonomic_ganglia),11(gastrointestinal_tract_(site_indeterminate)),30(skin),42(prostate),1579(lung),25(thyroid),5(upper_aerodigestive_tract),24(testis),4(thymus),1(eye),42(small_intestine),165(endometrium)", + "CLNALLELEID": "27622", + "CLNDN": "Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Nevus_sebaceous|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Carcinoma_of_pancreas|not_provided", + "CLNDISDB": "Human_Phenotype_Ontology:HP:0001914,Human_Phenotype_Ontology:HP:0004808,Human_Phenotype_Ontology:HP:0004843,Human_Phenotype_Ontology:HP:0005516,Human_Phenotype_Ontology:HP:0006724,Human_Phenotype_Ontology:HP:0006728,MONDO:MONDO:0018874,MeSH:D015470,MedGen:C0023467,OMIM:601626,Orphanet:ORPHA519,SNOMED_CT:17788007|Human_Phenotype_Ontology:HP:0002408,MONDO:MONDO:0007154,MedGen:C0917804,OMIM:108010,Orphanet:ORPHA46724,SNOMED_CT:234142008|Human_Phenotype_Ontology:HP:0010815,MedGen:C3854181|Human_Phenotype_Ontology:HP:0012209,MONDO:MONDO:0011908,MedGen:C0349639,OMIM:607785,Orphanet:ORPHA86834|Human_Phenotype_Ontology:HP:0030358,MONDO:MONDO:0005233,MeSH:D002289,MedGen:C0007131,SNOMED_CT:254637007|Human_Phenotype_Ontology:HP:0100031,MONDO:MONDO:0015074,MeSH:D013964,MedGen:C0040136,Orphanet:ORPHA100087|Human_Phenotype_Ontology:HP:0100615,MONDO:MONDO:0021068,MeSH:D010051,MedGen:C0919267,OMIM:167000,SNOMED_CT:123843001|Human_Phenotype_Ontology:HP:0100834,MeSH:D015179,MedGen:C0009404,SNOMED_CT:126837005|MONDO:MONDO:0005192,MeSH:C562463,MedGen:C0235974,OMIM:260350,Orphanet:ORPHA217074,SNOMED_CT:372142002|MedGen:CN517202", + "CLNREVSTAT": "criteria_provided,_multiple_submitters,_no_conflicts", + "CLNSIG": "Pathogenic", + "1000g2015aug_all": ".", + "1000g2015aug_eas": ".", + "esp6500siv2_all": ".", + "ExAC_nontcga_ALL": ".", + "ACMG_level": 1 + }, + { + "Validated": 1, + "Chr": "chr17", + "Start": 7579470, + "End": 7579470, + "Ref": "-", + "Alt": "G", + "Func.refGene": "exonic", + "Gene.refGene": "TP53", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "frameshift insertion", + "AAChange.refGene": "TP53:NM_000546:exon4:c.216dupC:p.V73Rfs*76", + "avsnp150": "rs730882018", + "cosmic91": "ID=COSV52710145;OCCURENCE=2(salivary_gland),3(breast),1(oesophagus),8(large_intestine),1(biliary_tract),2(stomach),1(haematopoietic_and_lymphoid_tissue),1(soft_tissue),3(pancreas),5(skin),4(prostate),3(lung),4(upper_aerodigestive_tract)", + "CLNALLELEID": "181025", + "CLNDN": "Multiple_myeloma|Hereditary_cancer-predisposing_syndrome|Li-Fraumeni_syndrome|Li-Fraumeni-like_syndrome|Breast_and/or_ovarian_cancer", + "CLNDISDB": "Human_Phenotype_Ontology:HP:0006775,MONDO:MONDO:0009693,MeSH:D009101,MedGen:C0026764,OMIM:254500,Orphanet:ORPHA29073,SNOMED_CT:109989006,SNOMED_CT:55921005|MONDO:MONDO:0015356,MedGen:C0027672,Orphanet:ORPHA140162,SNOMED_CT:699346009|MONDO:MONDO:0018875,MedGen:C0085390,OMIM:PS151623,Orphanet:ORPHA524,SNOMED_CT:428850001|MedGen:C2675080|MedGen:CN221562", + "CLNREVSTAT": "criteria_provided,_multiple_submitters,_no_conflicts", + "CLNSIG": "Pathogenic", + "1000g2015aug_all": ".", + "1000g2015aug_eas": ".", + "esp6500siv2_all": ".", + "ExAC_nontcga_ALL": ".", + "ACMG_level": 1 + } + ], + "hereditary": [ + { + "基因": "TP53", + "遗传性肿瘤综合征": "Li-Fraumeni综合征", + "遗传方式": "AD", + "杂合/纯合": "杂合", + "检测结果": "p.V73Rfs*76" + } + ], + "qc": { + "raw_reads": 9598256, + "raw_bases": 1439738400, + "clean_reads": 9488546, + "clean_bases": 1406177980, + "clean_reads_rate(%)": 98.86, + "Q20(%)": 97.89, + "q30": 94.32, + "mapped_reads": 9471537, + "mapped_rate(%)": 99.82, + "dup_reads": 2485892, + "dup_rate(%)": 26.25, + "probe_bed_size": 493464, + "target_reads": 5448673, + "capture_rate(reads)": 57.53, + "mean_depth_raw": 1298.63, + "depth": 937.62, + "coverage(>0x)": 47.05, + "coverage(>10x)": 41.56, + "coverage": 35.53, + "coverage(>=80%)": 0 + }, + "indication": [ + { + "基因": "BRAF", + "检测内容": "突变", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌/实体瘤" + }, + { + "基因": "ERBB2", + "检测内容": "扩增", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌" + }, + { + "基因": "KRAS", + "检测内容": "突变", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌" + }, + { + "基因": "NRAS", + "检测内容": "突变", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌" + }, + { + "基因": "NTRK1", + "检测内容": "突变/融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + }, + { + "基因": "NTRK2", + "检测内容": "融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + }, + { + "基因": "NTRK3", + "检测内容": "突变/融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + }, + { + "基因": "RET", + "检测内容": "融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + } + ], + "drugs": { + "drugs_detail": { + "西妥昔单抗": "ERBITUX是一种表皮生长因子受体(EGFR)拮抗剂，其适应症包括：1.联合放疗用于治疗局部或区域晚期头颈鳞癌。2.联合铂类和氟尿嘧啶用于治疗头颈部复发性局部疾病或转移性头颈鳞癌。3.铂类治疗后进展的复发性或转移性头颈鳞癌。4.联合FOLFIRI用于K-Ras野生型、EGFR表达阳性的转移性结直肠癌的一线治疗。5.联合伊立替康用于治疗对基于伊立替康化疗耐药的K-Ras野生型、EGFR表达阳性的转移性结直肠癌患者。6.单药用于治疗对奥沙利铂和伊立替康为基础的化疗失败或对伊立替康不耐受的K-Ras野生型、EGFR表达阳性的转移性结直肠癌患者。7.联合康奈非尼用于先前治疗后携带BRAF V600E突变的转移性结直肠癌(CRC)成人患者。\\\\表皮生长因子受体（EGFR，HER1，c-ErbB-1）是一种跨膜糖蛋白，是I型受体酪氨酸激酶亚家族（包括EGFR，HER2，HER3和HER4）的成员。EGFR在包括皮肤和毛囊在内的许多正常上皮组织中组成性表达。EGFR的表达在许多人类肿瘤（包括头颈部、结肠和直肠癌）中也能检测到。西妥昔单抗(Cetuximab)可以特异性地与正常细胞和肿瘤细胞表面的EGFR结合,竞争性抑制EGFR与表皮生长因子（EGF）或其他配体（如转化生长因子-α）的结合。体外试验和体内动物研究表明，西妥昔单抗(Cetuximab)与EGFR的结合可阻断受体相关激酶的磷酸化和激活，从而抑制细胞生长，诱导细胞凋亡，降低基质金属蛋白酶和血管内皮生长因子的生成。EGFR信号转导可导致野生型Ras蛋白的激活，但在有Ras体细胞激活突变的细胞中，Ras突变蛋白处于持续激活状态，且独立于EGFR的调控。在体外，西妥昔单抗(Cetuximab)可介导针对某些类型的人类肿瘤的抗体依赖性细胞介导的细胞毒作用（ADCC）。体外试验和体内动物研究表明，西妥昔单抗(Cetuximab)可抑制表达EGFR肿瘤细胞的生长和存活。在缺乏EGFR表达的人肿瘤异种移植模型中未观察到西妥昔单抗(Cetuximab)的抗肿瘤作用。在小鼠人源肿瘤异种移植模型中，放疗或伊立替康(Irinotecan)加用西妥昔单抗(Cetuximab)后，抗肿瘤效果比单纯放疗或化疗更好。", + "曲妥珠单抗": "Herceptin是一种HER2/neu受体拮抗剂，其适应症为：1.HER2过表达的乳腺癌。2.HER2过表达的转移性胃或胃食管交界处腺癌。\\\\HER2（或c-erbB2）原癌基因编码一个185 kDa的跨膜受体蛋白，该蛋白在结构上与表皮生长因子受体有关。曲妥珠单抗/赫赛汀（Trastuzumab/Herceptin）在体外及动物实验中均显示出可抑制HER2过表达肿瘤细胞的增殖。曲妥珠单抗/赫赛汀（Trastuzumab/Herceptin）是抗体依赖性细胞毒性（ADCC）的介体。在体外研究中，与未过表达HER2的癌细胞相比，曲妥珠单抗/赫赛汀（Trastuzumab/Herceptin）介导的ADCC优先作用于过表达HER2的癌细胞。", + "妥卡替尼": "TUKYSA是一种激酶抑制剂，其适应证为：1.联合曲妥珠单抗和卡培他滨治疗既往转移治疗中接受过一种或多种抗HER2治疗的晚期不可切除性或转移性HER2阳性乳腺癌成人患者，包括发生脑转移的患者。2.联合曲妥珠单抗治疗患者之前在氟嘧啶、奥沙利铂和伊立替康化疗治疗后进展的RAS野生型，HER2阳性不可切除或转移性结直肠癌患者，。\\\\Tucatinib是HER2的酪氨酸激酶抑制剂。 在体外试验中，Tucatinib能够抑制HER2和HER3磷酸化，从而抑制下游MAPK和AKT信号通路和细胞增殖，并且在表达HER2的肿瘤细胞中显示出抗肿瘤活性。在体内研究中，Tucatinib可以抑制表达HER2肿瘤的生长。与单独使用这两种药物相比，Tucatinib和曲妥珠单抗（Trastuzumab)联合在体外试验和体内研究中均表现出增强的抗肿瘤活性。", + "帕尼单抗": "Vectibix是一种表皮生长因子受体(EGFR)拮抗剂，其适应症为：1.联合FOLFOX用于RAS野生型(KRAS和NRAS均为野生型)转移性结直肠癌(mCRC)的一线治疗。2.单药用于治疗既往接受含氟嘧啶类、奥沙利铂和伊立替康化疗后疾病进展的RAS野生型mCRC。\\\\跨膜糖蛋白EGFR是I型受体酪氨酸激酶（包括EGFR，HER2，HER3和HER4）亚家族的成员。EGFR在包括皮肤和毛囊在内的正常上皮组织中组成性表达。某些人类癌症（包括结肠癌和直肠癌）中EGFR过表达。EGFR与其正常配体（例如EGF、转化生长因子-α）的相互作用导致一系列胞内蛋白的磷酸化和激活，继而调节与细胞生长、存活、运动性以及增殖相关基因的转录。KRAS（Kirsten大鼠肉瘤病毒癌基因同源物）和NRAS（神经母细胞瘤RAS病毒癌基因同源物）是RAS癌基因家族中高度相关的成员。通过EGFR的信号转导可导致野生型KRAS和NRAS蛋白激活。然而，在具有RAS体细胞激活突变的细胞中，RAS突变蛋白处于持续激活状态，不依赖EGFR的调控。帕尼单抗（Panitumumab）可以与正常细胞和肿瘤细胞上的EGFR特异性结合，并竞争性抑制EGFR配体的结合。非临床研究表明，帕尼单抗（Panitumumab）与EGFR结合可阻止配体诱导的受体自磷酸化和受体相关激酶的激活，从而抑制细胞生长、诱导细胞凋亡、减少促炎细胞因子和血管生长因子的产生以及EGFR的内在化。体外试验和体内动物研究表明，帕尼单抗（Panitumumab）可以抑制某些表达EGFR人类肿瘤细胞系的生长和存活。", + "帕妥珠单抗": "PERJETA是一种HER2/neu受体拮抗剂，其适应症为：1.联合曲妥珠单抗和多西紫杉醇用于治疗既往未接受过抗HER2治疗或转移性疾病化疗的HER2阳性转移性乳腺癌(MBC)。2.联合曲妥珠单抗和化疗用于：(1)HER2阳性的局部晚期、炎性或早期乳腺癌(直径大于2cm或淋巴结阳性)的新辅助治疗，作为早期乳腺癌整体治疗方案的一部分。(2)具有复发高风险的HER2阳性早期乳腺癌的辅助治疗。\\\\帕妥珠单抗（Pertuzumab）靶向细胞外人表皮生长因子受体2蛋白（HER2）的二聚化结构域（子结构域Ⅱ），从而阻断HER2与其它HER家族成员（包括EGFR、HER3和HER4）的配体依赖性异源二聚化作用。结果，帕妥珠单抗（Pertuzumab）通过两条主要信号途径（有丝分裂原激活蛋白[MAP]激酶和磷酸肌醇3激酶[PI3K]）抑制配体启动的细胞内信号传导。这些信号通路的抑制分别导致细胞生长停滞和凋亡。此外，帕妥珠单抗（Pertuzumab）介导抗体依赖性细胞介导的细胞毒性作用（ADCC）。尽管单独使用帕妥珠单抗（Pertuzumab）能抑制人肿瘤细胞的增殖，但在过表达HER2的异种移植模型中，帕妥珠单抗（Pertuzumab）和曲妥珠单抗（Trastuzumab）联合可以增强抗肿瘤活性。", + "拉帕替尼": "TYKERB是一种激酶抑制剂，其适应症为：1.联合卡培他滨用于治疗过表达人表皮生长因子受体2(HER2)并且既往接受过蒽环类、紫杉类和曲妥珠单抗等治疗的晚期或转移性乳腺癌。2.联合来曲唑用于治疗过表达HER2受体适用激素治疗的绝经后妇女激素受体阳性转移性乳腺癌。\\\\拉帕替尼（Lapatinib）是一种4-苯胺喹唑啉类抑制剂，可抑制人表皮生长因子受体（EGFR [ErbB1]）和人表皮生长因子受体2（HER2 [ErbB2]）的胞内酪氨酸激酶结构域活性（预估Kiapp值分别为3 nM和13 nM），消除半衰期大于或等于300分钟。拉帕替尼（Lapatinib）可在体外和各种动物模型中抑制ErbB驱动的肿瘤细胞生长。在一项体外研究的4种受试肿瘤细胞系中，拉帕替尼（Lapatinib）和 5-FU（卡培他滨的活性代谢物）联合用药显示出相加作用。在对曲妥珠单抗（Trastuzumab）耐受的细胞系中拉帕替尼（Lapatinib）的生长抑制作用已得到评估。拉帕替尼（Lapatinib）对于可在含曲妥珠单抗（Trastuzumab）培养基中长期生长的乳腺癌细胞系也保持显著活性。这些体外研究表明，这两种药物之间没有交叉耐药性。共表达HER2的激素受体阳性乳腺癌细胞（如雌激素受体[ER]和/或孕激素受体[PgR]）易对内分泌治疗产生耐受。同样，激素受体阳性乳腺癌细胞缺乏EGFR或HER2时会上调这些受体蛋白表达，使肿瘤对内分泌治疗耐受。", + "考比替尼": "COTELLIC是一种激酶抑制剂，其适应症为联合维莫非尼用于治疗携带BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。\\\\考比替尼(Cobimetinib)是一种靶向有丝分裂原活化蛋白激酶（MAPK）/细胞外信号调节激酶1（MEK1）和MEK2的可逆抑制剂。MEK蛋白是细胞外信号调节激酶(ERK)通路的上游调控蛋白，该通路可促进细胞增殖。BRAF V600E和K突变导致包括MEK1和MEK2在内的BRAF途径的组成性激活。在移植表达BRAF V600E肿瘤细胞系的小鼠中，考比替尼(Cobimetinib)抑制了肿瘤细胞的生长。考比替尼(Cobimetinib)和维罗非尼(Vemurafenib)靶向RAS/RAF/MEK/ERK通路的两种不同激酶。与单独使用这两种药物相比，考比替尼(Cobimetinib)和维罗非尼(Vemurafenib)联合用药在体外可增加细胞凋亡，在植入表达BRAF V600E突变的肿瘤细胞系的小鼠中可抑制肿瘤生长。此外,在小鼠肿瘤细胞移植模型中,考比替尼(Cobimetinib)还可以阻止维罗非尼(Vemurafenib)介导的野生型BRAF肿瘤细胞系的生长。", + "贝美替尼": "MEKTOVI是一种激酶抑制剂，联合康奈非尼用于治疗BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。\\\\贝美替尼(Binimetinib)是一种有丝分裂原激活的细胞外信号调节激酶1（MEK1）和MEK2活性的可逆抑制剂。MEK蛋白是细胞外信号相关激酶（ERK）途径的上游调控蛋白。在体外，贝美替尼(Binimetinib)在非细胞试验中能抑制细胞外信号相关激酶(ERK)的磷酸化，并抑制了BRAF突变型人黑素瘤细胞系的活力和MEK依赖性磷酸化。在BRAF突变的小鼠异种移植瘤模型中，贝美替尼(Binimetinib)也能抑制体内ERK磷酸化和肿瘤生长。贝美替尼(Binimetinib)和康奈非尼(Encorafenib)靶向RAS/RAF/MEK/ERK通路的两种不同激酶。与单独使用任何一种药物相比，康奈非尼(Encorafenib)和贝美替尼(Binimetinib)联合用药在体外对BRAF突变阳性细胞系产生更强的抗增殖活性，且在BRAF V600E突变型人类黑色素瘤小鼠异种移植研究中，对肿瘤生长抑制显示出更强的抗肿瘤活性。此外，与单独使用两种药物相比，联合使用贝美替尼(Binimetinib)和康奈非尼(Encorafenib)延缓了BRAF V600E突变型人黑色素瘤小鼠异种移植瘤模型耐药性的出现。", + "曲美替尼": "MEKINIST是一种激酶抑制剂，其适应症为：1.单药用于治疗携带BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。2.联合达拉菲尼用于：(1)携带BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。(2)携带BRAF V600E或V600K突变且完全切除后累及淋巴结的黑色素瘤患者的辅助治疗。(3)携带BRAF V600E突变的转移性非小细胞肺癌(NSCLC)。(4)没有令人满意的局部区域治疗选择的BRAF V600E突变的局部晚期或转移性间变性甲状腺癌(ATC)。(5)携带BRAF V600E突变的不可切除或转移性实体瘤成人和6岁及以上的儿童患者的治疗，且这些患者在之前的治疗后进展，没有满意的替代治疗方案。（6）需要接受系统治疗并携带BRAF V600E突变的低级别胶质瘤( LGG )患者（1岁及以上）。\\\\曲美替尼（Trametinib）是有丝分裂原激活的细胞外信号调节激酶1（MEK1）和MEK2激活以及MEK1和MEK2激酶活性的可逆抑制剂。MEK蛋白是细胞外信号相关激酶（ERK）途径的上游调控因子，可促进细胞增殖。BRAF V600E突变导致包括MEK1和MEK2在内的BRAF途径的组成性激活。曲美替尼（Trametinib）在体外和体内抑制各种BRAF V600突变阳性肿瘤细胞的生长。曲美替尼（Trametinib）和达拉非尼（Dabrafenib）靶向RAS/RAF/MEK/ERK通路中的两种不同激酶。与单独使用这两种药物相比，曲美替尼（Trametinib）和达拉非尼（Dabrafenib）联合用药可加强对BRAF V600突变阳性肿瘤细胞系生长的抑制作用，并延长对BRAF V600突变阳性肿瘤异种移植物肿瘤生长的抑制作用。", + "阿培利司": "PIQRAY是一种激酶抑制剂，适用于联合氟维司群用于治疗既往接受内分泌治疗后疾病进展、携带PIK3CA突变、激素受体(HR)阳性、人表皮生长因子受体2 (HER2)阴性的绝经后妇女和男性晚期或转移性乳腺癌。\\\\阿培利司（Alpelisib）是PI3Kα的抑制剂，主要具有针对PI3Kα的抑制活性。在体外和体内模型中，PIK3CA基因的获得性突变将导致PI3Kα和Akt信号通路的激活，从而使细胞性状发生转化以及促使肿瘤的产生。在乳腺癌细胞系中，阿培利司（Alpelisib）抑制PI3K下游靶标（包括Akt）的磷酸化，并在具有PIK3CA突变的细胞系中显示出活性。在体内，阿培利司（Alpelisib）在移植瘤模型（包括乳腺癌模型）中抑制PI3K/Akt信号通路并降低肿瘤生长。通过阿培利司（Alpelisib）治疗抑制PI3K已显示出可诱导乳腺癌细胞中雌激素受体（ER）转录的增加。在ER阳性、PIK3CA突变的乳腺癌细胞系的移植瘤模型中，阿培利司（Alpelisib）和氟维司琼（Fulvestrant）联合治疗显示出较单一治疗更强的抗肿瘤活性。", + "RLY-2608": "RLY-2608是一种新型变构、泛突变、选择性PI3Kα抑制剂,一项临床I期研究正在评估RLY-2608作为单药在PI3KCA突变的晚期实体瘤患者( pts )中的临床活性，以及联合氟维司群在PIK3CA突变、HR +、HER2 -转移性乳腺癌( MBC )患者中的临床活性。", + "培唑帕尼": "VOTRIENT是一种激酶抑制剂，适用于晚期肾细胞癌(RCC)和既往接受过化疗的晚期软组织肉瘤(STS)成人患者。\\\\培唑帕尼（Pazopanib）是血管内皮生长因子受体（VEGFR）-1/2/3，血小板衍生生长因子受体（PDGFR）-α/β，成纤维细胞生长因子受体（FGFR）-1/3，细胞因子受体（Kit），白介素2受体诱导的T细胞激酶（Itk），淋巴细胞特异性蛋白酪氨酸激酶（Lck）和跨膜糖蛋白受体酪氨酸激酶（c-Fms）的多靶点酪氨酸激酶抑制剂。 在体外，培唑帕尼（Pazopanib）抑制配体诱导的VEGFR-2、Kit和PDGFR-β受体自身磷酸化。 在体内，培唑帕尼（Pazopanib）抑制小鼠肺中VEGF诱导的VEGFR-2磷酸化、小鼠模型的血管生成以及小鼠中某些人源肿瘤异种移植物的生长。", + "伏立诺他": "ZOLINZA是一种组蛋白去乙酰化酶(HDAC)抑制剂，用于治疗在两种全身治疗期间或之后出现进展，持续或复发疾病的的皮肤T细胞淋巴瘤(CTCL)患者的皮肤表现。\\\\伏立诺他(Vorinostat)可在纳摩尔级浓度下抑制组蛋白脱乙酰基酶HDAC1、HDAC2和HDAC3（I类）和HDAC6（II类）的酶活性（IC50 < 86 nM）。这些酶催化去除组蛋白赖氨酸残基上的乙酰基基团。在某些肿瘤细胞中，HDACs过表达，或异常募集到致癌的转录因子上，导致核小体核心组蛋白乙酰化不足。伏立诺他(Vorinostat)通过抑制组蛋白脱乙酰基酶来导致乙酰化组蛋白的累积，并诱导某些转化细胞的细胞周期停滞和/或凋亡。伏立诺他(Vorinostat)抗肿瘤作用的机制尚未完全阐明。", + "贝伐珠单抗": "Avastin是一种血管内皮生长因子抑制剂，其适应症为：1.与基于氟尿嘧啶的静脉化疗联合用于转移性结直肠癌的一线或二线治疗。2.与基于氟嘧啶-伊立替康或氟嘧啶-奥沙利铂的化疗联合用于含Avastin一线方案治疗后疾病进展的转移性结直肠癌的二线治疗。3.与卡铂、紫杉醇联合用于不可切除的、局部晚期、复发性或转移性非鳞状非小细胞肺癌的一线治疗。4.成人复发性胶质母细胞瘤。5.联合干扰素α用于治疗转移性肾细胞癌。6.与紫杉醇、顺铂或紫杉醇、拓扑替康联合，用于治疗持续性、复发性或转移性宫颈癌。7.上皮性卵巢癌、输卵管癌或原发性腹膜癌：(1)与卡铂和紫杉醇联合，然后使用Avastin单药，用于治疗首次手术切除后的III期或IV期疾病。(2)与紫杉醇、聚乙二醇脂质体多柔比星或拓扑替康联合，用于治疗既往接受不超过2个化疗方案的铂耐复发性疾病。(3)与卡铂、紫杉醇或卡铂、吉西他滨联合，然后使用Avastin单药，用于治疗铂敏感复发性疾病。8.与Atezolizumab联合用于治疗既往未接受过全身治疗的不可切除或转移性肝细胞癌(HCC)患者。\\\\Bevacizumab结合VEGF并阻止VEGF与其内皮细胞表面的受体(Flt-1和KDR)相互作用。在体外血管生成模型中，VEGF与其受体的相互作用导致内皮细胞增殖和新血管形成。在裸鼠结肠癌异种移植模型中给予贝伐单抗，导致微血管生长减少和转移疾病进展的抑制。", + "司美替尼": "KOSELUGO是一种激酶抑制剂，适用于2岁及以上患有1型神经纤维瘤(NF1)、有症状的、不能手术的丛状神经纤维瘤(PN)的儿童患者。\\\\Selumetinib是丝裂原活化蛋白激酶激酶1和2（MEK1/2）的抑制剂。MEK1/2蛋白是细胞外信号相关激酶（ERK）途径的上游调节因子。MEK和ERK都是RAS调节的RAF-MEK-ERK通路的关键组成部分，该通路通常在不同类型的癌症中被激活。在产生与人类NF1基因型和表型相似的神经纤维瘤的转基因NF1小鼠模型中，口服塞洛替尼抑制ERK磷酸化，并减少神经纤维瘤的数量、体积和增殖。" + }, + "drugs_type": { + "可能敏感": [ + "Ipatasertib", + "RMC-6236", + "考比替尼", + "贝美替尼", + "曲美替尼", + "阿培利司", + "RLY-2608", + "伏立诺他", + "培唑帕尼", + "贝伐珠单抗" + ], + "耐药": [ + "trastuzumab deruxtecan", + "西妥昔单抗", + "帕妥珠单抗", + "妥卡替尼", + "曲妥珠单抗", + "帕尼单抗", + "拉帕替尼", + "EGFR-TKI" + ] + } + } +} \ No newline at end of file diff --git a/template/nreport.docx b/template/nreport.docx new file mode 100644 index 0000000..14c6a08 Binary files /dev/null and b/template/nreport.docx differ diff --git a/template/~$report.docx b/template/~$report.docx new file mode 100644 index 0000000..7847fac Binary files /dev/null and b/template/~$report.docx differ diff --git a/tools/__init__.py b/tools/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tools/common.py b/tools/common.py new file mode 100644 index 0000000..9588ccd --- /dev/null +++ b/tools/common.py @@ -0,0 +1,3 @@ +import os + +basedir = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) diff --git a/tools/parsexlsx.py b/tools/parsexlsx.py new file mode 100644 index 0000000..af4805f --- /dev/null +++ b/tools/parsexlsx.py @@ -0,0 +1,457 @@ +import json +import re +import sys +import time +from collections import defaultdict + +import pandas as pd + +from tools.readxlsx import read + + +def tree(): + return defaultdict(tree) + + +class BaseAssignment: + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.result = tree() # 报告结果 + self.signtb = set() # 具有明确或潜在临床意义的基因变异 + self.signdurg = set() # 潜在临床获益的治疗药物 + + self.drugs_type = dict() + + +class Parse(BaseAssignment): + + def __init__(self, sampledata, *args, **kwargs): + super().__init__(*args, **kwargs) + self.sampledata = sampledata + + def cms(self): + """ + 样本信息处理 + """ + data = pd.DataFrame(self.sampledata['sample_info']) + if data.empty: + raise UserWarning('sample_info表为空，生成报告失败！') + data = data.applymap( + lambda x: str(x).replace('.', '/').replace('-', '/').replace('——', '/') if str(x) in ['.', '-', '——'] else x) + data_dict = data.to_dict('index')[0] + data_dict['receiveTime'] = re.split(' ', data_dict['receiveTime'])[0] + data_dict['reportTime'] = time.strftime("%Y-%m-%d", time.localtime()) + self.result['c'] = data_dict + + def target(self): + data = pd.DataFrame(self.sampledata['snvindel']) + res = [] + if data.empty: + self.result['snvindel'] = res + return + + data = data[data['Validated'] == 1].reset_index() + data['muttype'] = '/' + data.loc[data['ExonicFunc.refGene'].str.match('nonsynonymous SNV'), 'muttype'] = '错义突变' + data.loc[data['ExonicFunc.refGene'].str.match('^frameshift'), 'muttype'] = '移码突变' + data.loc[data['ExonicFunc.refGene'].str.match('^nonframeshift'), 'muttype'] = '非移码突变' + data.loc[data['ExonicFunc.refGene'].str.match('stopgain'), 'muttype'] = '提前终止' + + # 拆分hgvs + data[['gene', 'transcript', 'exon', 'nacid', 'aacid']] = data['AAChange.refGene'].str.split(':', expand=True) + # 没有氨基酸改变用核苷酸改变代替 + data['aacid'] = data['aacid'].fillna(data['nacid']) + + for alter, alter_data in data.groupby('AAChange.refGene'): + alter_data_need = alter_data[['gene', 'transcript', 'exon', 'nacid', 'aacid', 'mutant_frequency', + 'AMP_mut_level', 'muttype', 'Gene_function']] + alter_res = alter_data_need.iloc[0].to_dict() + alter_res['drug_category'] = self._drug_category(alter_data) + drug_content = alter_data[ + ['DrugCn', 'Response_Type', 'Indication', 'Evidence_Source', 'Efficacy_Evidence']] + drug_content = drug_content[drug_content['DrugCn'] != '.'] + alter_res['drug_content'] = drug_content.reset_index().to_dict('records') + alter_res['alter'] = alter + res.append(alter_res) + + # 汇总 + if alter_res['AMP_mut_level'] in ['I', 'II']: + self.signtb.add(alter) + + self.result['snvindel'] = res + + def fusion(self): + data = pd.DataFrame(self.sampledata['fusion']) + res = [] + if data.empty: + self.result['fusion'] = res + return + data = data[data['Validated'] == 1].reset_index() + for alter, alter_data in data.groupby('FUSION'): + alter_data_need = alter_data[['FUSION', 'FREQ1', 'AMP_mut_level', 'Gene_function']] + alter_res = alter_data_need.iloc[0].to_dict() + alter_res['drug_category'] = self._drug_category(alter_data) + drug_content = alter_data[ + ['DrugCn', 'Response_Type', 'Indication', 'Evidence_Source', 'Efficacy_Evidence']] + drug_content = drug_content[drug_content['DrugCn'] != '.'] + alter_res['drug_content'] = drug_content.reset_index().to_dict('records') + alter_res['alter'] = '%s 融合' % (alter_res['FUSION'].replace('-', ':')) + res.append(alter_res) + + # 汇总 + if alter_res['AMP_mut_level'] in ['I', 'II']: + self.signtb.add(alter) + + self.result['fusion'] = res + + def cnv(self): + data = pd.DataFrame(self.sampledata['cnv']) + res = [] + if data.empty: + self.result['cnv'] = res + return + data = data[data['Validated'] == 1].reset_index() + for alter, alter_data in data.groupby('Gene_Symbol'): + alter_data_need = alter_data[['Gene_Symbol', 'Copy_number', 'AMP_mut_level', 'Gene_function']].reset_index() + alter_data_need['muttype'] = '缺失' + alter_data_need.loc[alter_data_need['Copy_number'] > 2, 'muttype'] = '扩增' + alter_res = alter_data_need.iloc[0].to_dict() + alter_res['drug_category'] = self._drug_category(alter_data) + drug_content = alter_data[ + ['DrugCn', 'Response_Type', 'Indication', 'Evidence_Source', 'Efficacy_Evidence']] + drug_content = drug_content[drug_content['DrugCn'] != '.'] + alter_res['drug_content'] = drug_content.reset_index().to_dict('records') + alter_res['alter'] = '%s %s' % (alter, alter_res['muttype']) + res.append(alter_res) + + # 汇总 + if alter_res['AMP_mut_level'] in ['I', 'II']: + self.signtb.add(alter) + self.result['cnv'] = res + + def hotspot(self): + self._to_records('hotspot') + + def met(self): + self._to_records('MET') + + def longindel(self): + self._to_records('longindel') + + def mmr(self): + data = pd.DataFrame(self.sampledata['MMR']) + result_summary = '未检测到相关基因突变' + predict = '对免疫检查点抑制剂可能不敏感' + mmr_num = 0 + res = [] + + if not data.empty: + tmdf = data[['gene', 'p_change']].reset_index() + tmdf['result_summary'] = tmdf.apply(lambda x: '%s %s' % (x['gene'], x['p_change']), axis=1) + result_summary = ' | '.join(tmdf['result_summary'].to_list()) + predict = '对免疫检查点抑制剂可能敏感' + mmr_num = len(data.index) + res = data.to_dict('records') + + self.result['MMR'] = res + self.result['sum']['mmr'] = dict( + result_summary=result_summary, + predict=predict, + mmr_num=mmr_num + ) + + def msi(self): + self._to_dicts('MSI') + + # def chemo(self): + # data = pd.DataFrame(self.sampledata['chemo']) + # + # project = data['project'].to_list()[0] + # + # # 分类汇总 同位点，药物合并 drug.infos.txt + # drugrsid = data[['drugname', 'genename', 'rsid', 'result', 'level', 'tips', 'drugsort']] + # drugrsid = drugrsid.drop_duplicates() + # resdrugrsid = drugrsid.groupby(['drugname', 'genename', 'rsid', 'result', 'level', 'drugsort'])['tips'].agg( + # ','.join).reset_index() + # resdrugrsid.rename(columns= + # {'drugname': '药物', 'genename': '检测基因', 'rsid': '检测位点', 'result': '基因型', + # 'level': '证据等级', 'tips': '用药提示'}, + # inplace=True) + # resdrugrsid = resdrugrsid.sort_values(by=['drugsort', '药物', '检测基因']) + # self.result['chemo']['druginfo'] = resdrugrsid.to_dict('records') + # + # # 药物 药物疗效 推荐程度合并 drug.res.txt + # drugtypesum = data[['drugname', 'drugtype', 'rsid', 'weights']] + # drugtypesum = drugtypesum.drop_duplicates() + # drugtyperes = list() + # drugsum = dict() + # for drug, drugdata in drugtypesum.groupby('drugname'): + # tipsnum = drugdata.groupby(['drugtype']).agg({'weights': 'sum'}).to_dict('index') + # sumlist = list() + # if 'LX' in tipsnum: + # LX = tipsnum['LX']['weights'] + # if LX > 0: + # lxdes = '疗效较好' + # lxnum = 1 + # elif LX == 0: + # lxdes = '疗效一般' + # lxnum = 0 + # else: + # lxdes = '疗效较差' + # lxnum = -1 + # sumlist.append(lxdes) + # else: + # LX = 0 + # lxnum = 0 + # if 'DF' in tipsnum: + # DF = tipsnum['DF']['weights'] + # if DF > 0: + # dfdes = '毒副较低' + # dfnum = 1 + # elif DF == 0: + # dfdes = '毒副一般' + # dfnum = 0 + # else: + # dfdes = '毒副较高' + # dfnum = -1 + # sumlist.append(dfdes) + # else: + # DF = 0 + # dfnum = 0 + # + # # 评价方式 疗效 1 0 -1, 毒副 1 0 -1 ，可形成9宫格 + # sumnum = lxnum + dfnum + # if sumnum > 0: + # sumdes = '推荐' + # elif sumnum == 0: + # sumdes = '常规' + # else: + # sumdes = '谨慎' + # + # # 特别药物处理 + # if (drug == "氟尿嘧啶" or drug == "卡培他滨") and DF < 0: + # sumdes = '谨慎' + # + # drugtyperes.append(dict( + # 药物名称=drug, + # 疗效=LX, + # 毒副=DF, + # 推荐程度=sumdes, + # 疗效和毒副总结=','.join(sumlist) + # )) + # drugsum[drug] = sumdes + # + # # 报告中展示药物有顺序 + # drugsort = data[['drugname', 'drugsort']].drop_duplicates() + # drugsort_dict = drugsort.set_index('drugname')['drugsort'].to_dict() + # drugtyperes_sort = sorted(drugtyperes, key=lambda x: ( + # drugsort_dict[x['药物名称']] if x['药物名称'] in drugsort_dict else 100, x['药物名称'])) + # + # drugtyperes_sort_df = pd.DataFrame(drugtyperes_sort) + # self.result['chemo']['sum'] = drugtyperes_sort_df.groupby('推荐程度')['药物名称'].apply(','.join).to_dict() + # self.result['chemo']['drugres'] = drugtyperes_sort_df.to_dict('records') + # + # # 联合用药 + # drug_combine_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'database', + # 'chemo_drug_combine.csv') + # drug_combine = pd.read_csv(drug_combine_path, sep='\t') + # drug_combine.fillna('.', inplace=True) + # drug_combine_data = drug_combine[drug_combine['source'].str.contains(project)] + # drug_combine_data = drug_combine_data.reset_index() + # if not drug_combine_data.empty: + # drug_combine_data['临床提示'] = drug_combine_data['用药方案'].apply(self._get_drug_plan, args=(drugsum,)) + # self.result['chemo']['combine'] = drug_combine_data.groupby('癌种').apply( + # lambda group: group.set_index('癌种').to_dict('records')).to_dict() + # else: + # self.result['chemo']['combine'] = dict() + # self.result['sum']['chemo_drug_num'] = len(drugsum.keys()) + + def chemo(self): + chemo_res = self._to_records('chemo_res', need=True) + chemo_res_df = pd.DataFrame(chemo_res) + chemo_res_df.index = chemo_res_df.index + 1 + chemo_res_df = chemo_res_df.reset_index() + self.result['chemo']['chemo_res'] = chemo_res_df.to_dict('records') + self.result['sum']['chemo']['drug_num'] = len(chemo_res) + self.result['sum']['chemo']['drug_category'] = pd.DataFrame(chemo_res).groupby('推荐程度')['药物名称'].apply( + ','.join).to_dict() + + chemo_comb = self._to_records('chemo_comb', need=True) + chemo_comb_res = dict() + if chemo_comb: + chemo_comb_res = pd.DataFrame(chemo_comb).groupby('癌种').apply( + lambda group: group.set_index('癌种').to_dict('records')).to_dict() + self.result['chemo']['chemo_comb'] = chemo_comb_res + + chemo_info = self._to_records('chemo_info', need=True) + chemo_info_res = dict() + if chemo_info: + chemo_info_res = pd.DataFrame(chemo_info).groupby('药物').apply( + lambda group: group.set_index('药物').to_dict('records')).to_dict() + self.result['chemo']['chemo_info'] = chemo_info_res + + def hcs(self): + self._to_records('HCS') + self.result['sum']['hcs']['num'] = len(self.result['HCS']) + + def heredity(self): + """ + 遗传的结果文件 + :return: + """ + hereditary = pd.DataFrame(self.sampledata['hereditary']) + result = '/' + disease = '/' + risk = '/' + if not hereditary.empty: + result = '|'.join(hereditary.apply(lambda x: '%s %s' % (x['基因'], x['检测结果']), axis=1).to_list()) + disease = '|'.join(hereditary['遗传性肿瘤综合征'].to_list()) + + hereditary_risk = pd.DataFrame(self.sampledata['hereditary_risk']) + if not hereditary_risk.empty: + risk = ','.join(hereditary_risk[hereditary_risk['风险值'] == '偏高']['肿瘤类型'].to_list()) + + self.result['hereditary'] = hereditary.to_dict('records') + self.result['sum']['hereditary']['result'] = result + self.result['sum']['hereditary']['disease'] = disease + self.result['sum']['hereditary']['risk'] = risk + + def qc(self): + # self._to_dicts('qc') + data = pd.DataFrame(self.sampledata['qc']) + res = {} + if not data.empty: + data.rename(columns={ + 'Q30(%)': 'q30', + 'mean_depth(dedup)': 'depth', + 'coverage(>=0.2*meanx)': 'coverage' + }, inplace=True) + res = data.to_dict('index')[0] + self.result['qc'] = res + + def drugs(self): + data = pd.DataFrame(self.sampledata['drugs']) + res = {} + if not data.empty: + data = data.dropna() + data = data[data['drug_detail'] != '.'] + res = data.set_index('drug_name')['drug_detail'].to_dict() + self.result['drugs']['drugs_detail'] = res + + def indication(self): + self._to_records('indication') + + def _to_records(self, sheetname, need=False): + """ + for many lines + :param sheetname: + :return: + """ + data = pd.DataFrame(self.sampledata[sheetname]) + res = [] + if data.empty: + self.result[sheetname] = res + return + res = data.to_dict('records') + if need: + return res + self.result[sheetname] = res + + def _to_dicts(self, sheetname): + """ + for single line + :param sheetname: + :return: + """ + data = pd.DataFrame(self.sampledata[sheetname]) + res = {} + if data.empty: + self.result[sheetname] = res + return + res = data.to_dict('index')[0] + self.result[sheetname] = res + + def _drug_category(self, groupdata): + drug_category_res = dict() + for drug_category, drug_category_alter_data in groupdata.groupby('Drug_Category'): + if drug_category == '.': + continue + # 敏感，可能敏感药物统计 + if drug_category in ['a', 'b', 'c']: + self.signdurg.update(set(drug_category_alter_data['DrugCn'].str.split(',').explode().tolist())) + drug_category_alter_data['drugdes'] = drug_category_alter_data.apply( + lambda x: '%s 【%s 级】' % (x['DrugCn'], x['AMP_evidence_level']), axis=1) + drug_category_res[drug_category] = '\n'.join(drug_category_alter_data['drugdes'].to_list()) + + # 所有药物信息 + groupdata['list_col'] = groupdata['DrugCn'].str.replace(' + ', '+').str.split(r'[+,]') + exploded_df = groupdata.explode('list_col').reset_index() + exploded_df = exploded_df[(exploded_df['list_col'] != '.') & (exploded_df['list_col'] != '')] + exploded_dict = exploded_df.groupby('Response_Type')['list_col'].agg(lambda x: list(set(x))).to_dict() + + for drug_type in exploded_dict: + if drug_type in self.drugs_type: + self.drugs_type[drug_type].extend(exploded_dict[drug_type]) + else: + self.drugs_type[drug_type] = exploded_dict[drug_type] + + # for drugall in exploded_df['Drug_Detail'].to_list(): + # for drug in drugall.split('|'): + # match = re.search(r'\[\[(.*?)]](.*?)$', drug) + # if match: + # self.drugs_record['drugs'].update({match.group(1).strip(): match.group(2).strip()}) + return drug_category_res + + @staticmethod + def _get_drug_plan(x, drugsum): + tlist = x.split('+') + tdeslist = list() + for tdes in tlist: + if tdes.strip() in drugsum: + t1_des = drugsum[tdes.strip()] + tdeslist.append(t1_des) + + if '慎用' in tdeslist or '谨慎' in tdeslist: + return '慎用' + elif '推荐' in tdeslist: + return '推荐' + elif '常规' in tdeslist: + return '可选' + else: + return '可选' + + def collect(self): + self.cms() + self.target() + self.fusion() + self.cnv() + self.hotspot() + self.met() + self.longindel() + self.mmr() + self.msi() + self.chemo() + self.hcs() + self.heredity() + self.qc() + self.indication() + self.drugs() + + # 汇总 + self.result['sum']['signtb_num'] = len(self.signtb) + self.result['sum']['signdrug_num'] = len(self.signdurg) + self.result['drugs']['drugs_type'] = {key: self.drugs_type[key] for key in sorted(self.drugs_type.keys())} + return self.result + + +def run(path): + parse = Parse(read(path)) + res = parse.collect() + resjson = json.dumps(res, indent=4, ensure_ascii=False) + with open('t.json', 'w') as f: + f.write(resjson) + return resjson + + +if __name__ == '__main__': + run(sys.argv[1]) diff --git a/tools/readxlsx.py b/tools/readxlsx.py new file mode 100644 index 0000000..3a55640 --- /dev/null +++ b/tools/readxlsx.py @@ -0,0 +1,27 @@ +import pandas as pd +import logging +import json +import sys + +logger = logging.getLogger('main.sub') + + +def read(merge): + df = pd.read_excel(merge, None) + samplelist = df['sample_info']['sampleSn'].to_list() + if not samplelist: + logger.error('sample_info表为空！读取excel信息失败！') + raise UserWarning('sample_info表为空！读取excel信息失败！') + samdict = dict() + for name, contents in df.items(): + if contents.empty: + samdict[name] = [] + continue + contents.fillna('.', inplace=True) + samdict[name] = contents.to_dict('list') + return samdict + + +if __name__ == '__main__': + res = read(sys.argv[1]) + print(res) \ No newline at end of file diff --git a/tools/t.json b/tools/t.json new file mode 100644 index 0000000..7ab8f83 --- /dev/null +++ b/tools/t.json @@ -0,0 +1,4617 @@ +{ + "c": { + "sampleId": "21777459", + "sampleSn": "/", + "barcode": "BC-20220705", + "name": "江杰", + "agentName": "上海佰驰", + "hospitalName": "/", + "testDoctor": "-", + "itemName": "LZ103/肿瘤160基因检测（组织版）", + "itemNum": "1", + "sampleStatus": "YWC", + "contact": "-", + "source": "白片", + "makeTime": "2022-07-05 15:57:00", + "receiveTime": "2022-07-06 08:39:44", + "reportTime": "2022-07-13 08:27:05", + "remark": "/", + "idCard": "", + "lockStatus": "0", + "waringTime": "2022-07-13 08:39:44", + "division": "/", + "zlType": "/", + "familySn": "/", + "estimateEndTime": "2022-07-13 08:39:44", + "doctorUserId": "0", + "areaAgentId": "1253", + "agentId": "3285", + "unitAgentId": "3284", + "labId": "0", + "orderType": "/", + "receiveStatus": "1", + "sampleInfoId": "55660486", + "gender": "男", + "age": "69", + "contactAddr": "/", + "familyRel": "/", + "birthday": "/", + "treatmentNo": "/" + }, + "snvindel": [ + { + "gene": "ALK", + "transcript": "NM_004304", + "exon": "exon1", + "nacid": "c.386G>T", + "aacid": "p.G129V", + "mutant_frequency": "35.67%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "ALK:NM_004304:exon1:c.386G>T:p.G129V" + }, + { + "gene": "APC", + "transcript": "NM_000038", + "exon": "exon16", + "nacid": "c.2626C>T", + "aacid": "p.R876X", + "mutant_frequency": "25.35%", + "AMP_mut_level": "III", + "muttype": "提前终止", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "APC:NM_000038:exon16:c.2626C>T:p.R876X" + }, + { + "gene": "APC", + "transcript": "NM_000038", + "exon": "exon16", + "nacid": "c.4057G>T", + "aacid": "p.E1353X", + "mutant_frequency": "34.46%", + "AMP_mut_level": "III", + "muttype": "提前终止", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "APC:NM_000038:exon16:c.4057G>T:p.E1353X" + }, + { + "gene": "ARID1A", + "transcript": "NM_006015", + "exon": "exon1", + "nacid": "c.736G>A", + "aacid": "p.A246T", + "mutant_frequency": "1.06%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "ARID1A:NM_006015:exon1:c.736G>A:p.A246T" + }, + { + "gene": "BRIP1", + "transcript": "NM_032043", + "exon": "exon7", + "nacid": "c.752G>A", + "aacid": "p.R251H", + "mutant_frequency": "1.24%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "BRIP1:NM_032043:exon7:c.752G>A:p.R251H" + }, + { + "gene": "KRAS", + "transcript": "NM_004985", + "exon": "exon2", + "nacid": "c.35G>A", + "aacid": "p.G12D", + "mutant_frequency": "43.31%", + "AMP_mut_level": "I", + "muttype": "错义突变", + "Gene_function": "KRAS是小分子GTP酶RAS家族的成员，该家族催化GTP水解为GDP。在生理条件下，这些RAS蛋白在活性(GTP结合)和非活性(GDP结合)状态间循环，以激活受体酪氨酸激酶(RTK)下游的MAPK和PI3K致癌途径信号传导(PMID: 22189424)。RAS酶的功能受到鸟嘌呤核苷酸交换因子(GEF)如SOS的调节，这些因子可以使GDP与GTP交换，也可以通过GTP酶活化蛋白如NF1调节，提高RAS水解GTP的能力。一旦被激活，RAS可通过激活不同的细胞内信号传导途径(包括RAF/MEK/ERK和PI3K/AKT/mTOR途径)介导细胞增殖和其他细胞功能的调节。", + "drug_category": { + "c": "曲美替尼 【C 级】\n考比替尼 + Ipatasertib 【C 级】\n贝美替尼 【C 级】\n曲美替尼 【D 级】\nRMC-6236 【D 级】\nIrinotecan + 司美替尼 【B 级】", + "d": "西妥昔单抗 【A 级】\n曲妥珠单抗 + 妥卡替尼 【A 级】\n曲妥珠单抗 + 帕妥珠单抗,曲妥珠单抗 + 拉帕替尼,trastuzumab deruxtecan 【A 级】\nEGFR-TKI 【C 级】\n帕尼单抗 【A 级】" + }, + "drug_content": [ + { + "index": 0, + "DrugCn": "西妥昔单抗", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Cetuximab是一种表皮生长因子受体(EGFR)拮抗剂，FDA指出Cetuximab不适用于RAS突变型或RAS突变情况未知的结直肠癌患者(FDA-approval: 11/2020)。" + }, + { + "index": 1, + "DrugCn": "曲妥珠单抗 + 妥卡替尼", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "FDA推荐Trastuzumab + Tucatinib应用于携带HER2重复，RAS野生型的结直肠癌患者(NCCN: Rectal Cancer-Version 4.2022)" + }, + { + "index": 2, + "DrugCn": "曲妥珠单抗 + 帕妥珠单抗,曲妥珠单抗 + 拉帕替尼,trastuzumab deruxtecan", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出携带KRAS突变的结直肠癌患者对trastuzumab + pertuzumab,trastuzumab + lapatinib,trastuzumab deruxtecan治疗不敏感(NCCN: Colon Cancer-Version 2.2021)。" + }, + { + "index": 3, + "DrugCn": "EGFR-TKI", + "Response_Type": "耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出携带KRAS、BRAF基因突变和ALK、ROS1融合的非小细胞肺癌患者可能对EGFR信号通路抑制剂类靶向药物耐药(NCCN: Non-Small Cell Lung Cancer-Version 6.2021)。" + }, + { + "index": 4, + "DrugCn": "曲美替尼", + "Response_Type": "可能敏感", + "Indication": "结直肠癌", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "在一项I期临床试验中，8名患有结肠直肠癌的患者中包含3名携带KRAS突变的患者，在使用Mekinist（曲美替尼）治疗疾病稳定（PMID:22805291）。" + }, + { + "index": 5, + "DrugCn": "考比替尼 + Ipatasertib", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项Ib期临床试验中，13例携带KRAS突变的晚期实体瘤肿瘤患者接受Cobimetinib+ipatasertib联合治疗后，2例部分缓解，3例病情稳定，6例疾病进展为最佳反应(PMID: 32737717)。" + }, + { + "index": 6, + "DrugCn": "贝美替尼", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "在一项I期临床试验中，纳入21位晚期实体瘤患者接受Binimetinib治疗，其中8例患者携带KRAS突变。在纳入分析的18例患者中，14例患者病情稳定，包含4例携带KRAS突变患者(PMID: 27071922)。" + }, + { + "index": 7, + "DrugCn": "曲美替尼", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床前研究", + "Efficacy_Evidence": "在一项临床前研究中，曲美替尼可抑制BRAF V600E和KRAS突变肿瘤细胞系的增殖，其IC50值低于PD0325901或selumetinib，虽然曲美替尼和PD0325901在体外对MEK1具有相似的效力。与PD0325901相比，在这些浓度下用曲美替尼或CH5126766处理48小时，可在KRAS突变细胞(H2030)和表达活性CRAF数量增加的A375细胞中更持久地抑制pERK活性(PMID: 24746704)。" + }, + { + "index": 8, + "DrugCn": "帕尼单抗", + "Response_Type": "耐药", + "Indication": "结直肠癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Panitumumab是一种表皮生长因子受体(EGFR)拮抗剂，FDA指出Panitumumab不适用于RAS突变型或RAS突变状态未知的转移性结直肠癌患者(FDA-approval: 06/2017)。" + }, + { + "index": 9, + "DrugCn": "RMC-6236", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床前研究", + "Efficacy_Evidence": "在体外实验中，RMC-6236抑制了细胞生长，并诱导多种RAS癌细胞株凋亡，在临床前体内异种移植模型中，RMC-6236可抑制RAS通路的激活长达48小时。与健康组织相比RMC-6236对肿瘤组织的亲和力更高，在多种细胞系来源的异种移植模型（NSCLC、CRC和PDAC等）中RMC-6236对KRAS突变（特别是KRAS G12D, KRAS G12V和 KRAS G12R）均有明显也持久的肿瘤消退效果（Abstract: Koltun et al. Abstract# 3597, AACR 2022）。" + }, + { + "index": 10, + "DrugCn": "Irinotecan + 司美替尼", + "Response_Type": "可能敏感", + "Indication": "结直肠癌", + "Evidence_Source": "临床II期", + "Efficacy_Evidence": "在一项II期临床研究中，Selumetinib (AZD6244)联合Camptosar (伊立替康)导致9.7% (3/31)携带KRAS外显子2突变的结直肠癌患者部分反应，51.6% (16/31)患者病情稳定(PMID: 25322874)。" + } + ], + "alter": "KRAS:NM_004985:exon2:c.35G>A:p.G12D" + }, + { + "gene": "NF1", + "transcript": "NM_000267", + "exon": "exon2", + "nacid": "c.204+1G>A", + "aacid": "c.204+1G>A", + "mutant_frequency": "1.27%", + "AMP_mut_level": "II", + "muttype": "/", + "Gene_function": "NF1基因编码一种GTP酶激活蛋白(GAP)，用于小GTP酶HRAS、KRAS和NRAS的激活(PMID: 1946382)。NF1蛋白与RAS结合时可稳定RAS蛋白的GTP酶活性，将RAS从与GTP结合的激活状态转换成与GDP结合的失活状态(PMID: 9302992)。GAP相关结构域(GRD)是NF1的催化结构域，它仅占NF1蛋白约10％，但直接负责其GAP活性。", + "drug_category": { + "c": "司美替尼 【C 级】\n曲美替尼 【D 级】" + }, + "drug_content": [ + { + "index": 11, + "DrugCn": "司美替尼", + "Response_Type": "敏感", + "Indication": "神经纤维瘤", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Selumetinib是一种激酶抑制剂，FDA批准用于治疗2岁及以上患有1型神经纤维瘤(NF1)、有症状的、不能手术的丛状神经纤维瘤(PN)的儿童患者(FDA-approval: 04/2020)。" + }, + { + "index": 12, + "DrugCn": "曲美替尼", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床试验", + "Efficacy_Evidence": "Nf1是一种肿瘤抑制因子，因此在肿瘤进展过程中神经纤维蛋白表达可能会降低.有研究发现，厄洛替尼耐药与神经纤维蛋白（由NF1基因编码的RAS GTP酶激活蛋白）表达减少有关.用MEK抑制剂治疗神经纤维蛋白缺陷肺癌恢复了对厄洛替尼的敏感性（PMID: 24535670）。一名24岁男性患者，有NF1相关视神经胶质瘤病史(4岁)，对替莫唑胺治疗后复发的肿瘤进行基因组分析发现以下异常：KDR扩增、KIT扩增、NF1剪接位点3870+1G>T(预测产生截短蛋白)、PDGFRA扩增、CDKN2A/B丢失和ATRX剪接位点4809+1G>a。接受MEK抑制剂(曲美替尼)治疗3周内，强化程度和肿块效应明显降低。治疗2个月后，MRI显示进一步改善，皮质类固醇完全停用。鉴于治疗难治性疾病，4 个月的持续临床获益优于其他标准治疗方案(PMID: 26936308)。一项临床实验在携带NF1功能缺失的黑色素瘤细胞系中，MEK抑制剂曲美替尼具有显著的抗肿瘤作用(PMID: 24576830)。一项Ⅱ期临床实验中评估了MAP/ERK激酶I/II抑制剂selumetinib（AZD6244，ARRY-142886）pLGG患者中的疗效，1型神经纤维瘤病（NF1）相关pLGG（WHO一级和二级）的儿童。25 名符合条件的可评估儿童被计入第 3 层。10/25 （40%） 患者实现了 PR，中位随访时间为 48.6 个月（8.6-59.1;IQR=12.2），对于没有进展的 17 名受试者（PMID: 31151904）。" + } + ], + "alter": "NF1:NM_000267:exon2:c.204+1G>A" + }, + { + "gene": "NTRK1", + "transcript": "NM_002529", + "exon": "exon5", + "nacid": "c.551C>T", + "aacid": "p.A184V", + "mutant_frequency": "4.08%", + "AMP_mut_level": "III", + "muttype": "错义突变", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "NTRK1:NM_002529:exon5:c.551C>T:p.A184V" + }, + { + "gene": "SDHD", + "transcript": "NM_003002", + "exon": "exon4", + "nacid": "c.439_440insTGGGCATCTGCAAAGCTGTTGCCATGCTGTGGAAGCTCTGACCTTTTTGACTTCATACTTTGAAGAATTGATGAGATCGGAAGAGCACACGTCTGAACTCCAGTCACAGACTGTCGGATCTCGTATGCCGTCTTCTGCTTGAATGATACGGCGACCACCGAGATCTACACTCTCTAACAGACACTCTTTCCCTACACGACGCTCTTCCGATC", + "aacid": "p.V147_G148delinsVGICKAVAMLWKLX", + "mutant_frequency": "1.15%", + "AMP_mut_level": "III", + "muttype": "提前终止", + "Gene_function": ".", + "drug_category": {}, + "drug_content": [], + "alter": "SDHD:NM_003002:exon4:c.439_440insTGGGCATCTGCAAAGCTGTTGCCATGCTGTGGAAGCTCTGACCTTTTTGACTTCATACTTTGAAGAATTGATGAGATCGGAAGAGCACACGTCTGAACTCCAGTCACAGACTGTCGGATCTCGTATGCCGTCTTCTGCTTGAATGATACGGCGACCACCGAGATCTACACTCTCTAACAGACACTCTTTCCCTACACGACGCTCTTCCGATC:p.V147_G148delinsVGICKAVAMLWKLX" + } + ], + "fusion": [ + { + "FUSION": "CD74-ROS1", + "FREQ1": 1.11, + "AMP_mut_level": "I", + "drug_category": { + "a": "克唑替尼 【A 级】\n恩曲替尼 【A 级】\n赛瑞替尼 【A 级】\n布格替尼 【A 级】\n洛拉替尼 【A 级】", + "c": "克唑替尼,恩曲替尼 【C 级】\n洛普替尼 【B 级】" + }, + "drug_content": [ + { + "index": 0, + "DrugCn": "克唑替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Crizotinib(XALKORI)是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)或ROS1阳性的转移性非小细胞肺癌(NSCLC)(FDA-approval: 01/2021)。" + }, + { + "index": 1, + "DrugCn": "恩曲替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "ROZLYTREK（Entrectinib）是一种激酶抑制剂，FDA批准Entrectinib用于治疗ROS1阳性的转移性非小细胞肺癌(NSCLC)成人患者(FDA-approval: 08/2019)。" + }, + { + "index": 2, + "DrugCn": "赛瑞替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南建议使用Ceritinib治疗携带ROS1融合的非小细胞肺癌（NSCLC）(NCCN: Non-Small Cell Lung Cancer-Version 4.2021)。" + }, + { + "index": 3, + "DrugCn": "布格替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南建议使用Brigatinib治疗携带ROS1融合的非小细胞肺癌（NSCLC）(NCCN: Non-Small Cell Lung Cancer-Version 4.2021)。" + }, + { + "index": 4, + "DrugCn": "洛拉替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南建议使用Lorlatinib治疗携带ROS1融合的非小细胞肺癌（NSCLC）(NCCN: Non-Small Cell Lung Cancer-Version 4.2021)。" + }, + { + "index": 5, + "DrugCn": "克唑替尼,恩曲替尼", + "Response_Type": "敏感", + "Indication": "皮肤黑色素瘤", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南推荐Crizotinib,Entrectinib用于治疗携带融合的皮肤黑色素瘤患者(NCCN: Hepatobiliary Cancers-Version 3.2022)。" + }, + { + "index": 6, + "DrugCn": "洛普替尼", + "Response_Type": "可能敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "临床I/II期", + "Efficacy_Evidence": "FDA已经授予 repotrectinib 用于携带ROS1阳性，已接受过一种ROS1 TKI治疗但没有接受过以铂类为基础的化疗的转移性非小细胞肺癌治疗的突破性治疗认定。Repotrectinib对与ROS1融合的患者具有良好的临床效应，且I/II期研究结果表明，repotrectinib在ROS1融合晚期非小细胞肺癌患者中耐受性良好。（FDA breakthrough therapy designation;Abstract: Cho et al. Abstract# MA11.07, IASLC 2021）" + } + ] + }, + { + "FUSION": "EML4-ALK", + "FREQ1": 4.86, + "AMP_mut_level": "I", + "drug_category": { + "a": "克唑替尼 【A 级】\n阿来替尼 【A 级】\n赛瑞替尼 【A 级】\n布格替尼 【A 级】\n洛拉替尼 【A 级】\n恩沙替尼 【A 级】", + "c": "克唑替尼,赛瑞替尼,布格替尼,洛拉替尼,阿来替尼 【C 级】\nASP3026 【C 级】\n恩曲替尼 【C 级】", + "d": "阿法替尼,厄洛替尼,吉非替尼 【A 级】" + }, + "drug_content": [ + { + "index": 7, + "DrugCn": "克唑替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Crizotinib(XALKORI)是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)或ROS1阳性的转移性非小细胞肺癌(NSCLC)(FDA-approval: 01/2021)。" + }, + { + "index": 8, + "DrugCn": "阿来替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Alectinib（ALECENSA）是一种激酶抑制剂，FDA批准Alectinib用于治疗间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)(FDA-approval: 06/2018)。" + }, + { + "index": 9, + "DrugCn": "赛瑞替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Ceritinib(ZYKADIA)是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)(FDA-approval: 03/2019)。" + }, + { + "index": 10, + "DrugCn": "布格替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Brigatinib（ALUNBRIG）是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)成人患者(FDA-approval: 05/2020)。" + }, + { + "index": 11, + "DrugCn": "洛拉替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Lorlatinib（LORBRENA）是一种激酶抑制剂，可用于治疗既往接受克唑替尼和至少一种其他ALK抑制剂、或alectinib或ceritinib一线治疗后病情进展的间变性淋巴瘤激酶(ALK)阳性转移性非小细胞肺癌(NSCLC)患者(FDA-approval: 03/2021)。" + }, + { + "index": 12, + "DrugCn": "恩沙替尼", + "Response_Type": "敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NMPA", + "Efficacy_Evidence": "恩莎替尼是第二代ALK抑制剂，中国国家药监局(NMPA)批准恩莎替尼用于间变性淋巴瘤激酶（ALK）阳性的局部晚期或转移性非小细胞肺癌（NSCLC）患者的治疗(NMPA-approval: 11/2020)。" + }, + { + "index": 13, + "DrugCn": "阿法替尼,厄洛替尼,吉非替尼", + "Response_Type": "耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出MET扩增/ALK重排/ERBB2扩增可使非小细胞肺癌患者对Afatinib、Erlotini、Gefitinib产生耐药。(NCCN: Non-Small Cell Lung Cancer-Version 6.2021)。" + }, + { + "index": 14, + "DrugCn": "克唑替尼,赛瑞替尼,布格替尼,洛拉替尼,阿来替尼", + "Response_Type": "敏感", + "Indication": "子宫癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南推荐Crizotinib,Ceritinib,Brigatinib,Lorlatinib,Alectinib可用于治疗携带FALK易位的子宫的炎症性肌纤维母细胞瘤患者(NCCN: Uterine Neoplasms-Version 1.2023)。" + }, + { + "index": 15, + "DrugCn": "ASP3026", + "Response_Type": "可能敏感", + "Indication": "非小细胞肺癌", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "在一项I期临床试验中，携带ALK融合的且克唑替尼治疗耐药的15位非小细胞肺癌患者和1位成神经管细胞瘤患者，采用ASP3026治疗后，获得了50%部分缓解和44%疾病稳定的效果(PMID: 26966027)。" + }, + { + "index": 16, + "DrugCn": "恩曲替尼", + "Response_Type": "可能敏感", + "Indication": "实体瘤", + "Evidence_Source": "临床I期", + "Efficacy_Evidence": "综合两个I期临床试验的结果（ALKA-372-001和STARTRK-1），对携带ALK融合的且前期未经ALK抑制剂治疗的晚期实体瘤患者（包括非小细胞肺癌、结直肠癌、肾癌），Entrectinib (RXDX-101)治疗的客观缓解率为57%（4/7），而对于前期已经过ALK抑制剂治疗的患者都没有疗效（0/19）(PMID: 28183697)。" + } + ] + } + ], + "cnv": [ + { + "index": 0, + "Gene_Symbol": "ERBB2", + "Copy_number": 5.1, + "AMP_mut_level": "I", + "muttype": "扩增", + "drug_category": { + "c": "帕妥珠单抗 + 曲妥珠单抗 + Chemotherapy 【C 级】\n妥卡替尼 + Capecitabine + 曲妥珠单抗 【C 级】\n拉帕替尼 + capecitabine,拉帕替尼 + Letrozole 【C 级】\n恩美曲妥珠单抗 【C 级】\nMargetuximab-cmkb + Chemotherapy 【C 级】\n奈拉替尼,Capecitabine + 奈拉替尼 【C 级】\n曲妥珠单抗 【C 级】\n曲妥珠单抗 【C 级】\n曲妥珠单抗 【C 级】\nPembrolizumab + 曲妥珠单抗 + Chemotherapy 【C 级】\nFam-trastuzumab deruxtecan-nxki 【C 级】\nFam-trastuzumab deruxtecan-nxki 【C 级】\nFam-trastuzumab deruxtecan-nxki 【C 级】\n吡咯替尼 【C 级】\n伊尼妥单抗 + Vinorelbine 【C 级】\n吡咯替尼 + 曲妥珠单抗 + Docetaxel 【C 级】\n吡咯替尼 + 曲妥珠单抗 + Docetaxel 【C 级】\n曲妥珠单抗 + Chemotherapy,曲妥珠单抗 + 拉帕替尼 【C 级】\n曲妥珠单抗 + Carboplatin-Taxol 【C 级】\n曲妥珠单抗 + 帕妥珠单抗 【C 级】\nFam-trastuzumab deruxtecan-nxki 【C 级】", + "d": "阿法替尼,厄洛替尼,吉非替尼 【A 级】" + }, + "drug_content": [ + { + "index": 0, + "DrugCn": "阿法替尼,厄洛替尼,吉非替尼", + "Response_Type": "耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南指出MET扩增/ALK重排/ERBB2扩增可使非小细胞肺癌患者对Afatinib、Erlotini、Gefitinib产生耐药。(NCCN: Non-Small Cell Lung Cancer-Version 6.2021)。" + }, + { + "index": 1, + "DrugCn": "帕妥珠单抗 + 曲妥珠单抗 + Chemotherapy", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "FDA批准Pertuzumab联合曲妥珠单抗和化疗用于HER2阳性的局部晚期、炎性或早期乳腺癌(直径大于2cm或淋巴结阳性)的新辅助治疗，作为早期乳腺癌整体治疗方案的一部分；或作为具有复发高风险的HER2阳性早期乳腺癌的辅助治疗(FDA-approval: 01/2020)。" + }, + { + "index": 2, + "DrugCn": "妥卡替尼 + Capecitabine + 曲妥珠单抗", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "FDA批准Tucatinib联合曲妥珠单抗和卡培他滨用于治疗既往转移治疗中接受过一种或多种抗HER2治疗的晚期不可切除性或转移性HER2阳性乳腺癌成人患者，包括发生脑转移的患者(FDA-approval: 04/2020)。" + }, + { + "index": 3, + "DrugCn": "拉帕替尼 + capecitabine,拉帕替尼 + Letrozole", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Lapatinib是一种激酶抑制剂，FDA批准Lapatinib联合卡培他滨用于治疗过表达人表皮生长因子受体2(HER2)并且既往接受过蒽环类、紫杉类和曲妥珠单抗等治疗的晚期或转移性乳腺癌；Lapatinib联合来曲唑用于治疗过表达HER2受体适用激素治疗的绝经后妇女激素受体阳性转移性乳腺癌(FDA-approval: 12/2018)。" + }, + { + "index": 4, + "DrugCn": "恩美曲妥珠单抗", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Ado-Trastuzumab Emtansine是一种HER2靶向抗体和微管抑制剂缀合物，FDA批准单药用于治疗以下既往接受过单独或联合曲妥珠单抗和紫杉烷治疗的HER2阳性转移性乳腺癌患者：(1)既往接受过转移性疾病的先前治疗。(2)完成辅助治疗期间或之后六个月内疾病复发。；或作为既往接受紫杉烷和曲妥珠单抗治疗后仍残留浸润性疾病的HER2阳性早期乳腺癌患者的辅助治疗(FDA-approval: 09/2020)。" + }, + { + "index": 5, + "DrugCn": "Margetuximab-cmkb + Chemotherapy", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Margetuximab-cmkb是一种HER2/neu受体拮抗剂，FDA批准联合化疗用于治疗既往接受两种或两种以上抗HER2方案(其中至少一种用于转移性疾病)的转移性HER2阳性乳腺癌成人患者(FDA-approval: 12/2020)。" + }, + { + "index": 6, + "DrugCn": "奈拉替尼,Capecitabine + 奈拉替尼", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Neratinib是一种激酶抑制剂，FDA批准的适应症包括：1.单药用于经以曲妥珠单抗为基础辅助治疗的早期HER2阳性乳腺癌成人患者的延长辅助治疗。2.联合卡培他滨用于治疗既往接受过两种或两种以上的基于抗HER2治疗方案的转移性晚期或转移性HER2阳性乳腺癌患(FDA-approval: 07/2020)。" + }, + { + "index": 7, + "DrugCn": "曲妥珠单抗", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Trastuzumab是一种HER2/neu受体拮抗剂，FDA批准用于治疗HER2过表达的乳腺癌患者(FDA-approval: 11/2018)。" + }, + { + "index": 8, + "DrugCn": "曲妥珠单抗", + "Response_Type": "敏感", + "Indication": "胃食管交界癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Trastuzumab是一种HER2/neu受体拮抗剂，FDA批准用于治疗HER2过表达的转移性胃或胃食管交界处腺癌(FDA-approval: 11/2018)。" + }, + { + "index": 9, + "DrugCn": "曲妥珠单抗", + "Response_Type": "敏感", + "Indication": "胃癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Trastuzumab是一种HER2/neu受体拮抗剂，FDA批准用于治疗HER2过表达的转移性胃或胃食管交界处腺癌(FDA-approval: 11/2018)。" + }, + { + "index": 10, + "DrugCn": "Pembrolizumab + 曲妥珠单抗 + Chemotherapy", + "Response_Type": "敏感", + "Indication": "胃食管交界癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "FDA批准Pembrolizumab联合曲妥珠单抗及含氟嘧啶类和铂类化疗用于局部晚期不可切除或转移性HER2阳性的胃癌或胃食管交界处(GEJ)腺癌患者的一线治疗(FDA-approval: 10/2021)。" + }, + { + "index": 11, + "DrugCn": "Fam-trastuzumab deruxtecan-nxki", + "Response_Type": "敏感", + "Indication": "胃食管交界癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Trastuzumab Deruxtecan是一种HER2定向抗体和拓扑异构酶抑制剂偶联物，FDA批准用于治疗既往接受过基于Trastuzumab治疗的HER2阳性、局部晚期或转移性胃或胃食管交界处腺癌的成年患者(FDA-approval: 01/2021)。" + }, + { + "index": 12, + "DrugCn": "Fam-trastuzumab deruxtecan-nxki", + "Response_Type": "敏感", + "Indication": "胃癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Trastuzumab Deruxtecan是一种HER2定向抗体和拓扑异构酶抑制剂偶联物，FDA批准用于治疗既往接受过基于Trastuzumab治疗的HER2阳性、局部晚期或转移性胃或胃食管交界处腺癌的成年患者(FDA-approval: 01/2021; PMID: 32469182)。" + }, + { + "index": 13, + "DrugCn": "Fam-trastuzumab deruxtecan-nxki", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "FDA", + "Efficacy_Evidence": "Trastuzumab Deruxtecan是一种HER2定向抗体和拓扑异构酶抑制剂偶联物，FDA批准用于治疗携带HER2阳性，前期已接受过以抗HER2为基础的治疗(转移性疾病治疗或新辅助/辅助治疗）并在完成治疗期间或6个月内出现疾病复发的不可切除性或转移性乳腺癌成人患者。(FDA-approval: 05/2022)。" + }, + { + "index": 14, + "DrugCn": "吡咯替尼", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "NMPA", + "Efficacy_Evidence": "NMPA批准吡咯替尼联合卡培他滨，适用于治疗表皮生长因子受体 2 (HER2)阳性、既往未接受或接受过曲妥珠单抗的复发或转移性乳腺癌患者（使用本品前患者应接受过蒽环类或紫杉类化疗）(NMPA-approval: 08/2018)。" + }, + { + "index": 15, + "DrugCn": "伊尼妥单抗 + Vinorelbine", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "NMPA", + "Efficacy_Evidence": "伊尼妥单抗是一种重组抗人表皮生长因子受体-2人源化单克隆抗体，NMPA批准其适用于与长春瑞滨联合治疗已接受过1个或多个化疗方案的HER2阳性(免疫组化（IHC）检测显示阳性（+++）或免疫组化检测显示可疑阳性（++）同时荧光原位杂交（FISH）检测结果阳性)的转移性乳腺癌患者(NMPA-approval: 06/2020)。" + }, + { + "index": 16, + "DrugCn": "吡咯替尼 + 曲妥珠单抗 + Docetaxel", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "NMPA", + "Efficacy_Evidence": "NMPA批准Pyrotinib联合曲妥珠单抗及多西他赛，适用于治疗表皮生长因子受体2（HER2）阳性早期或局部晚期乳腺癌患者的新辅助治疗(NMPA-approval: 08/2018)。" + }, + { + "index": 17, + "DrugCn": "吡咯替尼 + 曲妥珠单抗 + Docetaxel", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "NMPA", + "Efficacy_Evidence": "NMPA批准吡咯替尼联合卡培他滨，适用于治疗表皮生长因子受体2（HER2）阳性、既往未接受或接受过曲妥珠单抗的复发或转移性乳腺癌患者。使用本品前患者应接受过蒽环类或紫杉类化疗。2.吡咯替尼与曲妥珠单抗和多西他赛联合，用于表皮生长因子受体2（HER2）阳性早期或局部晚期乳腺癌患者的新辅助治疗.3.马来酸吡咯替尼片与曲妥珠单抗和多西他赛联合，用于治疗表皮生长因子受体2（HER2）阳性、晚期阶段未接受过抗HER2治疗的复发或转移性乳腺癌患者(NMPA-approval: 11/2020)。" + }, + { + "index": 18, + "DrugCn": "曲妥珠单抗 + Chemotherapy,曲妥珠单抗 + 拉帕替尼", + "Response_Type": "敏感", + "Indication": "乳腺癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南将Trastuzumab + Chemotherapy/Trastuzumab + Lapatinib纳入HER2阳性的复发不可切除的乳腺癌患者的三线治疗方案(NCCN: Breast Cancer-Version 4.2021)。" + }, + { + "index": 19, + "DrugCn": "曲妥珠单抗 + Carboplatin-Taxol", + "Response_Type": "敏感", + "Indication": "子宫浆液性癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN指南推荐Trastuzumab + Carboplatin-Taxol用于治疗HER2阳性的子宫浆液癌/子宫乳头状浆液癌患者(NCCN: Uterine Neoplasms-Version 4.2021)。" + }, + { + "index": 20, + "DrugCn": "曲妥珠单抗 + 帕妥珠单抗", + "Response_Type": "敏感", + "Indication": "胆管癌", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN推荐Trastuzumab联合pertuzumab用于治疗HER2阳性疾病进展的胆管癌患者的后续治疗（NCCN: Hepatobiliary Cancers 1.2022）。" + }, + { + "index": 21, + "DrugCn": "Fam-trastuzumab deruxtecan-nxki", + "Response_Type": "敏感", + "Indication": "唾液腺肿瘤", + "Evidence_Source": "NCCN", + "Efficacy_Evidence": "NCCN推荐Fam-trastuzumab deruxtecan-nxki用于治疗HER2+、复发性、不可切除性或转移性唾液腺肿瘤患者的系统性治疗（NCCN: Head and Neck Cancers-Version 1.2022）。" + } + ], + "alter": "ERBB2 扩增" + }, + { + "index": 22, + "Gene_Symbol": "MYC", + "Copy_number": 6.4, + "AMP_mut_level": "II", + "muttype": "扩增", + "drug_category": { + "d": "奥希替尼 【C 级】\n埃克替尼 【D 级】\nROS1/ALK TKI 【C 级】\n卡马替尼 【D 级】" + }, + "drug_content": [ + { + "index": 22, + "DrugCn": "奥希替尼", + "Response_Type": "可能耐药", + "Indication": "肺腺癌", + "Evidence_Source": "回顾性研究", + "Efficacy_Evidence": "一项回顾性研究发现，在接受奥希替尼治疗的NSCLC患者中，存在MYC扩增的患者PFS较野生型显著降低（4.83个月 vs 12.60个月, HR = 2.95, p = 0.016）（PMID: 35643428）。" + }, + { + "index": 23, + "DrugCn": "埃克替尼", + "Response_Type": "可能耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "回顾性研究", + "Efficacy_Evidence": "一项回顾性研究发现，发现一例携带L861Q的NSCLC患者携带MYC扩增对埃克替尼原发耐药。" + }, + { + "index": 24, + "DrugCn": "ROS1/ALK TKI", + "Response_Type": "可能耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "回顾性研究", + "Efficacy_Evidence": "一例对克唑替尼耐药的ALK融合阳性肺癌患者中同样检出MYC基因扩增（PMID: 30290287）。对一例EZR-ROS1融合阳性、一线克唑替尼短期反应但二线洛拉替尼和卡博替尼治疗后最终进展的NSCLC患者，在其一线治疗进展时进行组织活检发现存在共存突变，包括TP53、AXIN1和TERT启动子突变、MYC和CCND3基因扩增，及CDKN2A/B基因缺失，其中MYC扩增在患者接受一线克唑替尼治疗前已存在，且拷贝数由4.5提高到6.5。体外细胞试验也证明，在对ROS1 TKI敏感的细胞系中过表达MYC可导致耐药（PMID: 35149545）。另一项回顾性研究中，在对克唑替尼和洛拉替尼耐药的ROS1融合阳性肺癌患者中也检出多个ROS1突变和MYC扩增共存，提示MYC扩增的潜在耐药机制（PMID: 33685866）。一例对Brigatinib和Lorlatinib耐药的EML4-ALK融合阳性肺癌患者的心包活检和胸腔积液样本同时检出YES1和MYC扩增（PMID: 35199053）。" + }, + { + "index": 25, + "DrugCn": "卡马替尼", + "Response_Type": "可能耐药", + "Indication": "非小细胞肺癌", + "Evidence_Source": "个案", + "Efficacy_Evidence": "一例82岁MET扩增的NSCLC患者对卡马替尼原发耐药，组织活检发现存在MYC扩增，同时利用患者来源的细胞（PDCs）进行功能性药物敏感性测试，结果显示MYC mRNA过度表达，并对卡马替尼产生耐药性（PMID: 36248327）。" + } + ], + "alter": "MYC 扩增" + } + ], + "hotspot": [ + { + "Chr": "chr12", + "Start": 25398284, + "End": 25398284, + "Ref": "C", + "Alt": "T", + "Func.refGene": "exonic", + "Gene.refGene": "KRAS", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "nonsynonymous SNV", + "AAChange.refGene": "KRAS:NM_004985:exon2:c.35G>A:p.G12D", + "Otherinfo1": 0.5, + "Otherinfo2": ".", + "Otherinfo3": 844, + "Otherinfo4": "chr12", + "Otherinfo5": 25398284, + "Otherinfo6": ".", + "Otherinfo7": "C", + "Otherinfo8": "T", + "Otherinfo9": ".", + "Otherinfo10": "PASS", + "Otherinfo11": "ADP=844;WT=0;HET=1;HOM=0;NC=0", + "Otherinfo12": "GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR", + "Otherinfo13": "0/1:0:844:844:475:369:43.72%:9.8E-1:64:64:431:44:336:33" + } + ], + "MET": [], + "longindel": [], + "MMR": { + "result_summary": "MSH6 p.P1082L", + "predict": "对免疫检查点抑制剂可能敏感", + "contents": [ + { + "Chr": "chr2", + "Start": 48030631, + "End": 48030631, + "Ref": "C", + "Alt": "T", + "Func.refGene": "exonic", + "Gene.refGene": "MSH6", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "nonsynonymous SNV", + "AAChange.refGene": "MSH6:NM_000179:exon5:c.3245C>T:p.P1082L", + "avsnp150": "rs191109849", + "cosmic91": "ID=COSV52274543;OCCURENCE=1(liver)", + "CLNALLELEID": 94832, + "CLNDN": "Endometrial_carcinoma|Carcinoma_of_colon|Lynch_syndrome|Lynch_syndrome_I|Hereditary_cancer-predisposing_syndrome|Hereditary_nonpolyposis_colorectal_neoplasms|not_specified|not_provided", + "CLNDISDB": "Human_Phenotype_Ontology:HP:0012114,MONDO:MONDO:0002447,MedGen:C0476089,OMIM:608089,SNOMED_CT:254878006|MONDO:MONDO:0002032,MedGen:C0699790,SNOMED_CT:269533000|MONDO:MONDO:0005835,MedGen:C4552100,Orphanet:ORPHA144|MONDO:MONDO:0007356,MedGen:C2936783,OMIM:120435|MONDO:MONDO:0015356,MedGen:C0027672,Orphanet:ORPHA140162,SNOMED_CT:699346009|MedGen:C0009405|MedGen:CN169374|MedGen:CN517202", + "CLNREVSTAT": "criteria_provided,_conflicting_interpretations", + "CLNSIG": "Conflicting_interpretations_of_pathogenicity", + "1000g2015aug_all": 0.000399361, + "1000g2015aug_eas": 0.002, + "esp6500siv2_all": 7.7e-05, + "ExAC_nontcga_ALL": 0.0001, + "gene": "MSH6", + "transcript": "NM_000179", + "exon": "exon5", + "nacid": "c.3245C>T", + "aacid": "p.P1082L", + "result_summary": "MSH6 p.P1082L" + } + ] + }, + "sum": { + "mmr_num": 1, + "chemo_drug_num": 31, + "hcs_num": 4, + "signtb_num": 6, + "signdrug_num": 33 + }, + "MSI": { + "msi_count": 18, + "msi_value": 0, + "msi_result": "MSS", + "msi_predict": "对免疫检查点抑制剂可能不敏感" + }, + "chemo": { + "druginfo": [ + { + "药物": "替莫唑胺", + "检测基因": "ABCB1", + "检测位点": "rs1128503", + "基因型": "AA", + "证据等级": "3", + "drugsort": 1, + "用药提示": "疗效较差" + }, + { + "药物": "替莫唑胺", + "检测基因": "ABCB1", + "检测位点": "rs1128503", + "基因型": "AG", + "证据等级": "3", + "drugsort": 1, + "用药提示": "疗效较差" + }, + { + "药物": "替莫唑胺", + "检测基因": "ABCB1", + "检测位点": "rs1128503", + "基因型": "GG", + "证据等级": "3", + "drugsort": 1, + "用药提示": "疗效较好" + }, + { + "药物": "环磷酰胺", + "检测基因": "CYP2B6", + "检测位点": "rs3745274", + "基因型": "GG", + "证据等级": "3", + "drugsort": 1, + "用药提示": "毒副较高,疗效较好" + }, + { + "药物": "环磷酰胺", + "检测基因": "CYP2B6", + "检测位点": "rs3745274", + "基因型": "GT", + "证据等级": "3", + "drugsort": 1, + "用药提示": "毒副较低,疗效较差" + }, + { + "药物": "环磷酰胺", + "检测基因": "CYP2B6", + "检测位点": "rs3745274", + "基因型": "TT", + "证据等级": "3", + "drugsort": 1, + "用药提示": "毒副较低,疗效较差" + }, + { + "药物": "环磷酰胺", + "检测基因": "GSTP1", + "检测位点": "rs1695", + "基因型": "AA", + "证据等级": "3", + "drugsort": 1, + "用药提示": "疗效较好" + }, + 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"疗效较好" + }, + { + "药物": "伊达比星", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + }, + { + "药物": "伊达比星", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AG", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + }, + { + "药物": "伊达比星", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "GG", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较低" + }, + { + "药物": "多柔比星", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + }, + { + "药物": "多柔比星", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AG", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + }, + { + "药物": "多柔比星", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "GG", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较低" + }, + { + "药物": "米托蒽醌", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AA", + "证据等级": "3", + "drugsort": 6, + "用药提示": "毒副较高" + }, + { + "药物": "米托蒽醌", + "检测基因": "HAS3", + "检测位点": "rs2232228", + "基因型": "AG", + 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+ "检测位点": "rs1045642", + "基因型": "AA", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较好" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "AG", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较差" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "GG", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较差" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "AA", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较好" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "AC", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效居中" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "AT", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效居中" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "CC", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较差" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "CT", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效居中" + }, + { + "药物": "昂丹司琼", + "检测基因": "ABCB1", + "检测位点": "rs2032582", + "基因型": "TT", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效居中" + }, + { + "药物": "格拉司琼", + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "AA", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较好" + }, + { + "药物": "格拉司琼", + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "AG", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较差" + }, + { + "药物": "格拉司琼", + "检测基因": "ABCB1", + "检测位点": "rs1045642", + "基因型": "GG", + "证据等级": "3", + "drugsort": 7, + "用药提示": "疗效较差" + }, + { + "药物": "门冬酰胺酶", + "检测基因": "PNPLA3", + "检测位点": "rs738409", + "基因型": "CC", + "证据等级": "3", + "drugsort": 8, + "用药提示": "毒副较低" + }, + { + "药物": "门冬酰胺酶", + "检测基因": "PNPLA3", + "检测位点": "rs738409", + "基因型": "CG", + "证据等级": "3", + "drugsort": 8, + "用药提示": "毒副较高" + }, + { + "药物": "门冬酰胺酶", + "检测基因": "PNPLA3", + "检测位点": "rs738409", + "基因型": "GG", + "证据等级": "3", + "drugsort": 8, + "用药提示": "毒副较高" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "CYP2D6*120", + "基因型": "G/del", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "CYP2D6*120", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "CYP2D6*120", + "基因型": "del/del", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "CYP2D6*60", + "基因型": "T/insTA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "CYP2D6*60", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "CYP2D6*60", + "基因型": "insTA/insTA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs1065852", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs1065852", + "基因型": "AG", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs1065852", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs267608313", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs267608313", + "基因型": "AG", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs267608313", + "基因型": "GG", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs3892097", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs3892097", + "基因型": "CT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs3892097", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030862", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030862", + "基因型": "CT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030862", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030865", + "基因型": "AA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030865", + "基因型": "AC", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030865", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030865", + "基因型": "CT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs5030865", + "基因型": "TT", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs774671100", + "基因型": "C/insA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs774671100", + "基因型": "CC", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较好" + }, + { + "药物": "他莫昔芬", + "检测基因": "CYP2D6", + "检测位点": "rs774671100", + "基因型": "insA/insA", + "证据等级": "1A", + "drugsort": 9, + "用药提示": "疗效较差" + }, + { + "药物": "依西美坦", + "检测基因": "CYP19A1", + "检测位点": "rs6493497", + "基因型": "AA", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较高" + }, + { + "药物": "依西美坦", + "检测基因": "CYP19A1", + "检测位点": "rs6493497", + "基因型": "AG", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较低" + }, + { + "药物": "依西美坦", + "检测基因": "CYP19A1", + "检测位点": "rs6493497", + "基因型": "GG", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较低" + }, + { + "药物": "来曲唑", + "检测基因": "CYP19A1", + "检测位点": "rs6493497", + "基因型": "AA", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较高" + }, + { + "药物": "来曲唑", + "检测基因": "CYP19A1", + "检测位点": "rs6493497", + "基因型": "AG", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较低" + }, + { + "药物": "来曲唑", + "检测基因": "CYP19A1", + "检测位点": "rs6493497", + "基因型": "GG", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较低" + }, + { + "药物": "米托坦", + "检测基因": "CYP2B6", + "检测位点": "rs3745274", + "基因型": "GG", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较低" + }, + { + "药物": "米托坦", + "检测基因": "CYP2B6", + "检测位点": "rs3745274", + "基因型": "TG", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较高" + }, + { + "药物": "米托坦", + "检测基因": "CYP2B6", + "检测位点": "rs3745274", + "基因型": "TT", + "证据等级": "3", + "drugsort": 9, + "用药提示": "毒副较高" + } + ], + "sum": { + "常规": "替莫唑胺,环磷酰胺,卡铂,奥沙利铂,顺铂,吉西他滨,培美曲塞,甲氨蝶呤,阿糖胞苷,依托泊苷,多西他赛,紫杉醇,长春新碱,丝裂霉素,伊达比星,多柔比星,米托蒽醌,表柔比星,昂丹司琼,格拉司琼,门冬酰胺酶,依西美坦,来曲唑,米托坦", + "谨慎": "卡培他滨,替加氟,替吉奥,氟尿嘧啶,巯嘌呤类药物（6-巯基嘌呤、6-硫鸟嘌呤、硫唑嘌呤）,伊立替康,他莫昔芬" + }, + "drugres": [ + { + "药物名称": "替莫唑胺", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般" + }, + { + "药物名称": "环磷酰胺", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "卡铂", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "奥沙利铂", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "顺铂", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "卡培他滨", + "疗效": 0, + "毒副": -891, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效一般,毒副较高" + }, + { + "药物名称": "替加氟", + "疗效": 0, + "毒副": -396, + "推荐程度": "谨慎", + "疗效和毒副总结": "毒副较高" + }, + { + "药物名称": "替吉奥", + "疗效": 0, + "毒副": -396, + "推荐程度": "谨慎", + "疗效和毒副总结": "毒副较高" + }, + { + "药物名称": "氟尿嘧啶", + "疗效": 0, + "毒副": -891, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效一般,毒副较高" + }, + { + "药物名称": "吉西他滨", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "培美曲塞", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "巯嘌呤类药物（6-巯基嘌呤、6-硫鸟嘌呤、硫唑嘌呤）", + "疗效": 0, + "毒副": -1089, + "推荐程度": "谨慎", + "疗效和毒副总结": "毒副较高" + }, + { + "药物名称": "甲氨蝶呤", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "阿糖胞苷", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "伊立替康", + "疗效": 0, + "毒副": -198, + "推荐程度": "谨慎", + "疗效和毒副总结": "毒副较高" + }, + { + "药物名称": "依托泊苷", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "多西他赛", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "紫杉醇", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "长春新碱", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "丝裂霉素", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般" + }, + { + "药物名称": "伊达比星", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "多柔比星", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "米托蒽醌", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "表柔比星", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般,毒副一般" + }, + { + "药物名称": "昂丹司琼", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般" + }, + { + "药物名称": "格拉司琼", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "疗效一般" + }, + { + "药物名称": "门冬酰胺酶", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "他莫昔芬", + "疗效": -792, + "毒副": 0, + "推荐程度": "谨慎", + "疗效和毒副总结": "疗效较差" + }, + { + "药物名称": "依西美坦", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "来曲唑", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + }, + { + "药物名称": "米托坦", + "疗效": 0, + "毒副": 0, + "推荐程度": "常规", + "疗效和毒副总结": "毒副一般" + } + ], + "combine": { + "结直肠癌": [ + { + "index": 20, + "用药方案": "奥沙利铂+亚叶酸钙+氟尿嘧啶", + "方案缩写": "FOLFOX", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "index": 21, + "用药方案": "伊立替康+亚叶酸钙+氟尿嘧啶", + "方案缩写": "FOLFIRI", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "index": 22, + "用药方案": "奥沙利铂+卡培他滨", + "方案缩写": "CAPEOX（又称Xelox）", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "index": 23, + "用药方案": "伊立替康+奥沙利铂+亚叶酸钙+氟尿嘧啶", + "方案缩写": "FOLFOXIRI", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "index": 24, + "用药方案": "伊立替康+卡培他滨", + "方案缩写": "CapIRI或XELIRI", + "source": "crc88gene", + "临床提示": "慎用" + }, + { + "index": 25, + "用药方案": "奥沙利铂+雷替曲塞", + "方案缩写": "/", + "source": "crc88gene", + "临床提示": "可选" + }, + { + "index": 26, + "用药方案": "伊立替康+雷替曲塞", + "方案缩写": "/", + "source": "crc88gene", + "临床提示": "慎用" + } + ] + } + }, + "HCS": [ + { + "Chr": "chr2", + "Start": 30143140, + "End": 30143140, + "Ref": "C", + "Alt": "A", + "Func.refGene": "exonic", + "Gene.refGene": "ALK", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "nonsynonymous SNV", + "AAChange.refGene": "ALK:NM_004304:exon1:c.386G>T:p.G129V", + "avsnp150": "rs760041708", + "cosmic91": ".", + "CLNALLELEID": 289004, + "CLNDN": "Neuroblastoma_3", + "CLNDISDB": "MONDO:MONDO:0013083,MedGen:C2751681,OMIM:613014", + "CLNREVSTAT": "criteria_provided,_conflicting_interpretations", + "CLNSIG": "Conflicting_interpretations_of_pathogenicity", + "1000g2015aug_all": ".", + "1000g2015aug_eas": ".", + "esp6500siv2_all": ".", + "ExAC_nontcga_ALL": "8.02e-05" + }, + { + "Chr": "chr5", + "Start": 112173917, + "End": 112173917, + "Ref": "C", + "Alt": "T", + "Func.refGene": "exonic", + "Gene.refGene": "APC", + "GeneDetail.refGene": ".", + "ExonicFunc.refGene": "stopgain", + "AAChange.refGene": "APC:NM_000038:exon16:c.2626C>T:p.R876X", + "avsnp150": "rs121913333", + "cosmic91": "ID=COSV57320538;OCCURENCE=1(breast),2(oesophagus),251(large_intestine),2(central_nervous_system),1(bone),1(stomach),1(kidney),1(urinary_tract),2(prostate),1(lung),4(small_intestine),3(endometrium)", + "CLNALLELEID": 212414, + "CLNDN": "Neoplasm_of_the_large_intestine|Carcinoma_of_colon|Hereditary_cancer-predisposing_syndrome|Familial_adenomatous_polyposis_1|not_specified|not_provided", + "CLNDISDB": 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"ID=COSV55497369;OCCURENCE=1(salivary_gland),28(breast),3(penis),22(liver),95(peritoneum),3(genital_tract),18(oesophagus),44(cervix),8857(large_intestine),12(central_nervous_system),453(biliary_tract),1(pleura),338(ovary),2(bone),24(NS),253(haematopoietic_and_lymphoid_tissue),130(stomach),30(soft_tissue),12(kidney),41(urinary_tract),3242(pancreas),20(gastrointestinal_tract_(site_indeterminate)),42(skin),23(prostate),1365(lung),40(thyroid),37(upper_aerodigestive_tract),7(testis),3(eye),103(small_intestine),254(endometrium)", + "CLNALLELEID": 27621, + "CLNDN": "Vascular_Tumors_Including_Pyogenic_Granuloma|Acute_myeloid_leukemia|Cerebral_arteriovenous_malformation|Neoplasm_of_stomach|Nevus_sebaceous|Epidermal_nevus|Linear_sebaceous_nevus_sequence|Juvenile_myelomonocytic_leukemia|Non-small_cell_lung_carcinoma|Neoplasm_of_the_thyroid_gland|Neoplasm_of_ovary|Neoplasm_of_the_large_intestine|Lung_carcinoma|Carcinoma_of_pancreas|Encephalocraniocutaneous_lipomatosis|RAS-associated_autoimmune_leukoproliferative_disorder|Capillary_malformation-arteriovenous_malformation_1|Rasopathy|Primary_low_grade_serous_adenocarcinoma_of_ovary|not_provided", + "CLNDISDB": ".|Human_Phenotype_Ontology:HP:0001914,Human_Phenotype_Ontology:HP:0004808,Human_Phenotype_Ontology:HP:0004843,Human_Phenotype_Ontology:HP:0005516,Human_Phenotype_Ontology:HP:0006724,Human_Phenotype_Ontology:HP:0006728,MONDO:MONDO:0018874,MeSH:D015470,MedGen:C0023467,OMIM:601626,Orphanet:ORPHA519,SNOMED_CT:17788007|Human_Phenotype_Ontology:HP:0002408,MONDO:MONDO:0007154,MedGen:C0917804,OMIM:108010,Orphanet:ORPHA46724,SNOMED_CT:234142008|Human_Phenotype_Ontology:HP:0006753,MONDO:MONDO:0021085,MedGen:C0038356,SNOMED_CT:126824007|Human_Phenotype_Ontology:HP:0010815,MedGen:C3854181|Human_Phenotype_Ontology:HP:0010816,MONDO:MONDO:0008093,MedGen:C0334082,OMIM:162900,SNOMED_CT:25201003|Human_Phenotype_Ontology:HP:0010817,MONDO:MONDO:0008097,MedGen:C4552097,OMIM:163200,Orphanet:ORPHA2612,SNOMED_CT:52298009|Human_Phenotype_Ontology:HP:0012209,MONDO:MONDO:0011908,MedGen:C0349639,OMIM:607785,Orphanet:ORPHA86834|Human_Phenotype_Ontology:HP:0030358,MONDO:MONDO:0005233,MeSH:D002289,MedGen:C0007131,SNOMED_CT:254637007|Human_Phenotype_Ontology:HP:0100031,MONDO:MONDO:0015074,MeSH:D013964,MedGen:C0040136,Orphanet:ORPHA100087|Human_Phenotype_Ontology:HP:0100615,MONDO:MONDO:0021068,MeSH:D010051,MedGen:C0919267,OMIM:167000,SNOMED_CT:123843001|Human_Phenotype_Ontology:HP:0100834,MeSH:D015179,MedGen:C0009404,SNOMED_CT:126837005|MONDO:MONDO:0005138,MedGen:C0684249|MONDO:MONDO:0005192,MeSH:C562463,MedGen:C0235974,OMIM:260350,Orphanet:ORPHA217074,SNOMED_CT:372142002|MONDO:MONDO:0013074,MedGen:C0406612,OMIM:613001,Orphanet:ORPHA2396,SNOMED_CT:238905009|MONDO:MONDO:0013767,MedGen:C2674723,OMIM:614470,Orphanet:ORPHA268114|MONDO:MONDO:0020783,MedGen:C4747394,OMIM:608354|MONDO:MONDO:0021060,MedGen:CN166718,Orphanet:ORPHA536391|MedGen:C4302356|MedGen:CN517202", + "CLNREVSTAT": "criteria_provided,_multiple_submitters,_no_conflicts", + "CLNSIG": "Pathogenic", + "1000g2015aug_all": ".", + "1000g2015aug_eas": ".", + "esp6500siv2_all": ".", + "ExAC_nontcga_ALL": "2.283e-05" + } + ], + "qc": { + "raw_reads": 23808848, + "raw_bases": 3571327200, + "clean_reads": 23800974, + "clean_bases": 3369041154, + "clean_reads_rate(%)": 99.97, + "Q20(%)": 98.29, + "Q30(%)": 94.94, + "mapped_reads": 23785389, + "mapped_rate(%)": 99.93, + "dup_reads": 4376810, + "dup_rate(%)": 18.4, + "probe_bed_size": 493464, + "target_reads": 13586590, + "capture_rate(reads)": 57.12, + "mean_depth_raw": 2496.16, + "mean_depth(dedup)": 1927.98, + "coverage(>0x)": 100, + "coverage(>10x)": 100, + "coverage(>=0.2*meanx)": 99.5, + "coverage(>=80%)": 1311 + }, + "indication": [ + { + "基因": "BRAF", + "检测内容": "突变", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌/实体瘤" + }, + { + "基因": "ERBB2", + "检测内容": "扩增", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌" + }, + { + "基因": "KRAS", + "检测内容": "突变", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌" + }, + { + "基因": "NRAS", + "检测内容": "突变", + "检测情况": "未检出变异", + "肿瘤类型": "结直肠癌" + }, + { + "基因": "NTRK1", + "检测内容": "突变/融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + }, + { + "基因": "NTRK2", + "检测内容": "融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + }, + { + "基因": "NTRK3", + "检测内容": "突变/融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + }, + { + "基因": "RET", + "检测内容": "融合", + "检测情况": "未检出变异", + "肿瘤类型": "实体瘤" + } + ], + "drugs": { + "drugs_type": { + "可能敏感": [ + "ASP3026", + "恩曲替尼" + ], + "耐药": [ + "阿法替尼", + "吉非替尼", + "厄洛替尼" + ], + "敏感": [ + "恩美曲妥珠单抗", + "Letrozole", + "奈拉替尼", + "Pembrolizumab", + "吡咯替尼", + "Chemotherapy", + "伊尼妥单抗", + "capecitabine", + "Capecitabine", + "Fam-trastuzumabderuxtecan-nxki", + "妥卡替尼", + "Docetaxel", + "拉帕替尼", + "Carboplatin-Taxol", + "Vinorelbine", + "帕妥珠单抗", + "曲妥珠单抗", + "Margetuximab-cmkb" + ], + "可能耐药": [ + "埃克替尼", + "奥希替尼", + "卡马替尼", + "ROS1/ALKTKI" + ] + }, + "drugs": { + "西妥昔单抗": "ERBITUX是一种表皮生长因子受体(EGFR)拮抗剂，其适应症包括：1.联合放疗用于治疗局部或区域晚期头颈鳞癌。2.联合铂类和氟尿嘧啶用于治疗头颈部复发性局部疾病或转移性头颈鳞癌。3.铂类治疗后进展的复发性或转移性头颈鳞癌。4.联合FOLFIRI用于K-Ras野生型、EGFR表达阳性的转移性结直肠癌的一线治疗。5.联合伊立替康用于治疗对基于伊立替康化疗耐药的K-Ras野生型、EGFR表达阳性的转移性结直肠癌患者。6.单药用于治疗对奥沙利铂和伊立替康为基础的化疗失败或对伊立替康不耐受的K-Ras野生型、EGFR表达阳性的转移性结直肠癌患者。7.联合康奈非尼用于先前治疗后携带BRAF V600E突变的转移性结直肠癌(CRC)成人患者。\\\\表皮生长因子受体（EGFR，HER1，c-ErbB-1）是一种跨膜糖蛋白，是I型受体酪氨酸激酶亚家族（包括EGFR，HER2，HER3和HER4）的成员。EGFR在包括皮肤和毛囊在内的许多正常上皮组织中组成性表达。EGFR的表达在许多人类肿瘤（包括头颈部、结肠和直肠癌）中也能检测到。西妥昔单抗(Cetuximab)可以特异性地与正常细胞和肿瘤细胞表面的EGFR结合,竞争性抑制EGFR与表皮生长因子（EGF）或其他配体（如转化生长因子-α）的结合。体外试验和体内动物研究表明，西妥昔单抗(Cetuximab)与EGFR的结合可阻断受体相关激酶的磷酸化和激活，从而抑制细胞生长，诱导细胞凋亡，降低基质金属蛋白酶和血管内皮生长因子的生成。EGFR信号转导可导致野生型Ras蛋白的激活，但在有Ras体细胞激活突变的细胞中，Ras突变蛋白处于持续激活状态，且独立于EGFR的调控。在体外，西妥昔单抗(Cetuximab)可介导针对某些类型的人类肿瘤的抗体依赖性细胞介导的细胞毒作用（ADCC）。体外试验和体内动物研究表明，西妥昔单抗(Cetuximab)可抑制表达EGFR肿瘤细胞的生长和存活。在缺乏EGFR表达的人肿瘤异种移植模型中未观察到西妥昔单抗(Cetuximab)的抗肿瘤作用。在小鼠人源肿瘤异种移植模型中，放疗或伊立替康(Irinotecan)加用西妥昔单抗(Cetuximab)后，抗肿瘤效果比单纯放疗或化疗更好。", + "曲妥珠单抗": "Herceptin是一种HER2/neu受体拮抗剂，其适应症为：1.HER2过表达的乳腺癌。2.HER2过表达的转移性胃或胃食管交界处腺癌。\\\\HER2（或c-erbB2）原癌基因编码一个185 kDa的跨膜受体蛋白，该蛋白在结构上与表皮生长因子受体有关。曲妥珠单抗/赫赛汀（Trastuzumab/Herceptin）在体外及动物实验中均显示出可抑制HER2过表达肿瘤细胞的增殖。曲妥珠单抗/赫赛汀（Trastuzumab/Herceptin）是抗体依赖性细胞毒性（ADCC）的介体。在体外研究中，与未过表达HER2的癌细胞相比，曲妥珠单抗/赫赛汀（Trastuzumab/Herceptin）介导的ADCC优先作用于过表达HER2的癌细胞。", + "妥卡替尼": "TUKYSA是一种激酶抑制剂，其适应证为：1.联合曲妥珠单抗和卡培他滨治疗既往转移治疗中接受过一种或多种抗HER2治疗的晚期不可切除性或转移性HER2阳性乳腺癌成人患者，包括发生脑转移的患者。2.联合曲妥珠单抗治疗患者之前在氟嘧啶、奥沙利铂和伊立替康化疗治疗后进展的RAS野生型，HER2阳性不可切除或转移性结直肠癌患者，。\\\\Tucatinib是HER2的酪氨酸激酶抑制剂。 在体外试验中，Tucatinib能够抑制HER2和HER3磷酸化，从而抑制下游MAPK和AKT信号通路和细胞增殖，并且在表达HER2的肿瘤细胞中显示出抗肿瘤活性。在体内研究中，Tucatinib可以抑制表达HER2肿瘤的生长。与单独使用这两种药物相比，Tucatinib和曲妥珠单抗（Trastuzumab)联合在体外试验和体内研究中均表现出增强的抗肿瘤活性。", + "帕妥珠单抗": "PERJETA是一种HER2/neu受体拮抗剂，其适应症为：1.联合曲妥珠单抗和多西紫杉醇用于治疗既往未接受过抗HER2治疗或转移性疾病化疗的HER2阳性转移性乳腺癌(MBC)。2.联合曲妥珠单抗和化疗用于：(1)HER2阳性的局部晚期、炎性或早期乳腺癌(直径大于2cm或淋巴结阳性)的新辅助治疗，作为早期乳腺癌整体治疗方案的一部分。(2)具有复发高风险的HER2阳性早期乳腺癌的辅助治疗。\\\\帕妥珠单抗（Pertuzumab）靶向细胞外人表皮生长因子受体2蛋白（HER2）的二聚化结构域（子结构域Ⅱ），从而阻断HER2与其它HER家族成员（包括EGFR、HER3和HER4）的配体依赖性异源二聚化作用。结果，帕妥珠单抗（Pertuzumab）通过两条主要信号途径（有丝分裂原激活蛋白[MAP]激酶和磷酸肌醇3激酶[PI3K]）抑制配体启动的细胞内信号传导。这些信号通路的抑制分别导致细胞生长停滞和凋亡。此外，帕妥珠单抗（Pertuzumab）介导抗体依赖性细胞介导的细胞毒性作用（ADCC）。尽管单独使用帕妥珠单抗（Pertuzumab）能抑制人肿瘤细胞的增殖，但在过表达HER2的异种移植模型中，帕妥珠单抗（Pertuzumab）和曲妥珠单抗（Trastuzumab）联合可以增强抗肿瘤活性。", + "拉帕替尼": "TYKERB是一种激酶抑制剂，其适应症为：1.联合卡培他滨用于治疗过表达人表皮生长因子受体2(HER2)并且既往接受过蒽环类、紫杉类和曲妥珠单抗等治疗的晚期或转移性乳腺癌。2.联合来曲唑用于治疗过表达HER2受体适用激素治疗的绝经后妇女激素受体阳性转移性乳腺癌。\\\\拉帕替尼（Lapatinib）是一种4-苯胺喹唑啉类抑制剂，可抑制人表皮生长因子受体（EGFR [ErbB1]）和人表皮生长因子受体2（HER2 [ErbB2]）的胞内酪氨酸激酶结构域活性（预估Kiapp值分别为3 nM和13 nM），消除半衰期大于或等于300分钟。拉帕替尼（Lapatinib）可在体外和各种动物模型中抑制ErbB驱动的肿瘤细胞生长。在一项体外研究的4种受试肿瘤细胞系中，拉帕替尼（Lapatinib）和 5-FU（卡培他滨的活性代谢物）联合用药显示出相加作用。在对曲妥珠单抗（Trastuzumab）耐受的细胞系中拉帕替尼（Lapatinib）的生长抑制作用已得到评估。拉帕替尼（Lapatinib）对于可在含曲妥珠单抗（Trastuzumab）培养基中长期生长的乳腺癌细胞系也保持显著活性。这些体外研究表明，这两种药物之间没有交叉耐药性。共表达HER2的激素受体阳性乳腺癌细胞（如雌激素受体[ER]和/或孕激素受体[PgR]）易对内分泌治疗产生耐受。同样，激素受体阳性乳腺癌细胞缺乏EGFR或HER2时会上调这些受体蛋白表达，使肿瘤对内分泌治疗耐受。", + "trastuzumab deruxtecan": "", + "EGFR-TKI": "", + "曲美替尼": "MEKINIST是一种激酶抑制剂，其适应症为：1.单药用于治疗携带BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。2.联合达拉菲尼用于：(1)携带BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。(2)携带BRAF V600E或V600K突变且完全切除后累及淋巴结的黑色素瘤患者的辅助治疗。(3)携带BRAF V600E突变的转移性非小细胞肺癌(NSCLC)。(4)没有令人满意的局部区域治疗选择的BRAF V600E突变的局部晚期或转移性间变性甲状腺癌(ATC)。(5)携带BRAF V600E突变的不可切除或转移性实体瘤成人和6岁及以上的儿童患者的治疗，且这些患者在之前的治疗后进展，没有满意的替代治疗方案。（6）需要接受系统治疗并携带BRAF V600E突变的低级别胶质瘤( LGG )患者（1岁及以上）。\\\\曲美替尼（Trametinib）是有丝分裂原激活的细胞外信号调节激酶1（MEK1）和MEK2激活以及MEK1和MEK2激酶活性的可逆抑制剂。MEK蛋白是细胞外信号相关激酶（ERK）途径的上游调控因子，可促进细胞增殖。BRAF V600E突变导致包括MEK1和MEK2在内的BRAF途径的组成性激活。曲美替尼（Trametinib）在体外和体内抑制各种BRAF V600突变阳性肿瘤细胞的生长。曲美替尼（Trametinib）和达拉非尼（Dabrafenib）靶向RAS/RAF/MEK/ERK通路中的两种不同激酶。与单独使用这两种药物相比，曲美替尼（Trametinib）和达拉非尼（Dabrafenib）联合用药可加强对BRAF V600突变阳性肿瘤细胞系生长的抑制作用，并延长对BRAF V600突变阳性肿瘤异种移植物肿瘤生长的抑制作用。", + "考比替尼": "COTELLIC是一种激酶抑制剂，其适应症为联合维莫非尼用于治疗携带BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。\\\\考比替尼(Cobimetinib)是一种靶向有丝分裂原活化蛋白激酶（MAPK）/细胞外信号调节激酶1（MEK1）和MEK2的可逆抑制剂。MEK蛋白是细胞外信号调节激酶(ERK)通路的上游调控蛋白，该通路可促进细胞增殖。BRAF V600E和K突变导致包括MEK1和MEK2在内的BRAF途径的组成性激活。在移植表达BRAF V600E肿瘤细胞系的小鼠中，考比替尼(Cobimetinib)抑制了肿瘤细胞的生长。考比替尼(Cobimetinib)和维罗非尼(Vemurafenib)靶向RAS/RAF/MEK/ERK通路的两种不同激酶。与单独使用这两种药物相比，考比替尼(Cobimetinib)和维罗非尼(Vemurafenib)联合用药在体外可增加细胞凋亡，在植入表达BRAF V600E突变的肿瘤细胞系的小鼠中可抑制肿瘤生长。此外,在小鼠肿瘤细胞移植模型中,考比替尼(Cobimetinib)还可以阻止维罗非尼(Vemurafenib)介导的野生型BRAF肿瘤细胞系的生长。", + "Ipatasertib": "Ipatasertib是一种高度选择性的口服ATP竞争性小分子AKT抑制剂.在细胞系和异种移植模型中，ipatasertib在多种癌症类型，包括前列腺癌，乳腺癌，卵巢癌，结肠直肠癌和非小细胞肺癌中都表现出了抗癌活性。", + "贝美替尼": "MEKTOVI是一种激酶抑制剂，联合康奈非尼用于治疗BRAF V600E或V600K突变的不可切除性或转移性黑色素瘤。\\\\贝美替尼(Binimetinib)是一种有丝分裂原激活的细胞外信号调节激酶1（MEK1）和MEK2活性的可逆抑制剂。MEK蛋白是细胞外信号相关激酶（ERK）途径的上游调控蛋白。在体外，贝美替尼(Binimetinib)在非细胞试验中能抑制细胞外信号相关激酶(ERK)的磷酸化，并抑制了BRAF突变型人黑素瘤细胞系的活力和MEK依赖性磷酸化。在BRAF突变的小鼠异种移植瘤模型中，贝美替尼(Binimetinib)也能抑制体内ERK磷酸化和肿瘤生长。贝美替尼(Binimetinib)和康奈非尼(Encorafenib)靶向RAS/RAF/MEK/ERK通路的两种不同激酶。与单独使用任何一种药物相比，康奈非尼(Encorafenib)和贝美替尼(Binimetinib)联合用药在体外对BRAF突变阳性细胞系产生更强的抗增殖活性，且在BRAF V600E突变型人类黑色素瘤小鼠异种移植研究中，对肿瘤生长抑制显示出更强的抗肿瘤活性。此外，与单独使用两种药物相比，联合使用贝美替尼(Binimetinib)和康奈非尼(Encorafenib)延缓了BRAF V600E突变型人黑色素瘤小鼠异种移植瘤模型耐药性的出现。", + "帕尼单抗": "Vectibix是一种表皮生长因子受体(EGFR)拮抗剂，其适应症为：1.联合FOLFOX用于RAS野生型(KRAS和NRAS均为野生型)转移性结直肠癌(mCRC)的一线治疗。2.单药用于治疗既往接受含氟嘧啶类、奥沙利铂和伊立替康化疗后疾病进展的RAS野生型mCRC。\\\\跨膜糖蛋白EGFR是I型受体酪氨酸激酶（包括EGFR，HER2，HER3和HER4）亚家族的成员。EGFR在包括皮肤和毛囊在内的正常上皮组织中组成性表达。某些人类癌症（包括结肠癌和直肠癌）中EGFR过表达。EGFR与其正常配体（例如EGF、转化生长因子-α）的相互作用导致一系列胞内蛋白的磷酸化和激活，继而调节与细胞生长、存活、运动性以及增殖相关基因的转录。KRAS（Kirsten大鼠肉瘤病毒癌基因同源物）和NRAS（神经母细胞瘤RAS病毒癌基因同源物）是RAS癌基因家族中高度相关的成员。通过EGFR的信号转导可导致野生型KRAS和NRAS蛋白激活。然而，在具有RAS体细胞激活突变的细胞中，RAS突变蛋白处于持续激活状态，不依赖EGFR的调控。帕尼单抗（Panitumumab）可以与正常细胞和肿瘤细胞上的EGFR特异性结合，并竞争性抑制EGFR配体的结合。非临床研究表明，帕尼单抗（Panitumumab）与EGFR结合可阻止配体诱导的受体自磷酸化和受体相关激酶的激活，从而抑制细胞生长、诱导细胞凋亡、减少促炎细胞因子和血管生长因子的产生以及EGFR的内在化。体外试验和体内动物研究表明，帕尼单抗（Panitumumab）可以抑制某些表达EGFR人类肿瘤细胞系的生长和存活。", + "RMC-6236": "", + "Irinotecan": "", + "司美替尼": "KOSELUGO是一种激酶抑制剂，适用于2岁及以上患有1型神经纤维瘤(NF1)、有症状的、不能手术的丛状神经纤维瘤(PN)的儿童患者。\\\\Selumetinib是丝裂原活化蛋白激酶激酶1和2（MEK1/2）的抑制剂。MEK1/2蛋白是细胞外信号相关激酶（ERK）途径的上游调节因子。MEK和ERK都是RAS调节的RAF-MEK-ERK通路的关键组成部分，该通路通常在不同类型的癌症中被激活。在产生与人类NF1基因型和表型相似的神经纤维瘤的转基因NF1小鼠模型中，口服塞洛替尼抑制ERK磷酸化，并减少神经纤维瘤的数量、体积和增殖。", + "克唑替尼": "克唑替尼是一种激酶抑制剂，其适应症为：1.间变性淋巴瘤激酶(ALK)或ROS1阳性的转移性非小细胞肺癌(NSCLC)患者。2.复发性或难治性的系统性ALK阳性间变性大细胞淋巴瘤(ALCL)的 1 岁及以上儿童患者和青少年患者(使用限制:克唑替尼对复发或难治性系统性ALK阳性间变性大细胞淋巴瘤(ALCL)老年人的安全性和有效性尚未得到证实)。3.不可切除、复发或难治性1岁及以上ALK阳性的炎症性肌纤维母细胞瘤(IMT)的成人和儿童患者。\\\\克唑替尼(Crizotinib)是一种酪氨酸激酶受体抑制剂，对应靶点包括ALK、肝细胞生长因子受体（HGFR，c-Met)、ROS1(c-cos)和Recepteur d'Origine Nantais (RON)。ALK基因易位可引起致癌融合蛋白的表达。ALK融合蛋白的形成导致基因表达和信号转导的激活和失调，可以促进表达这些蛋白的肿瘤细胞的增殖和存活。克唑替尼(Crizotinib)在使用肿瘤细胞系的细胞实验中显示出对ALK、ROS1和c-Met磷酸化的浓度依赖性抑制作用，并且在表达棘皮动物微管相关蛋白4（EML4）或核磷蛋白（NPM）-ALK融合蛋白或c-Met的肿瘤移植小鼠中显示出抗肿瘤活性。", + "恩曲替尼": "恩曲替尼是一种激酶抑制剂，其适应症为：1.ROS1阳性的转移性非小细胞肺癌(NSCLC)成人患者。2.神经营养性酪氨酸受体激酶(NTRK)基因融合阳性、无已知的获得性耐药突变、转移性或手术切除可能导致严重发病率、且治疗后进展或没有令人满意的替代疗法的成人和儿童(≥12岁)实体瘤患者。\\\\恩曲替尼（Entrectinib）是一种靶向原肌球蛋白受体酪氨酸激酶（TRK）TRKA，TRKB和TRKC（分别由神经营养酪氨酸受体激酶[NTRK]基因NTRK1、NTRK2和NTRK3编码），由原癌基因编码的酪氨酸蛋白激酶ROS1（ROS1），以及间变性淋巴瘤激酶（ALK）的抑制剂，其IC50值为0.1至2 nM。恩曲替尼（Entrectinib）还可以抑制JAK2和TNK2的活性，IC50值>5 nM。恩曲替尼（Entrectinib）的主要活性代谢产物M5对TRK、ROS1和ALK的体外活性相似。包含TRK、ROS1或ALK激酶结构域的融合蛋白可以过度激活下游信号传导通路，导致细胞增殖不受限制，凭此驱动致癌潜力。恩曲替尼（Entrectinib）在体外和体内试验中都显示出对携带NTRK、ROS1和ALK融合基因的多种肿瘤类型的癌细胞系具有抑制作用。恩曲替尼（Entrectinib）在多种动物模型（小鼠、大鼠和狗）中的稳态脑血药物浓度比值为0.4-2.2，并且在颅内植入TRKA和ALK驱动肿瘤细胞系的小鼠体内表现出抗肿瘤活性。", + "赛瑞替尼": "ZYKADIA是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)。\\\\色瑞替尼(Ceritinib)是一种激酶抑制剂。达到临床相关浓度的生化或细胞分析中，色瑞替尼(Ceritinib)抑制作用的靶点包括ALK、胰岛素样生长因子1受体(IGF-1R)、胰岛素受体(InsR)和ROS1。其中，色瑞替尼(Ceritinib)对ALK的活性最高。在体外和体内试验中，色瑞替尼(Ceritinib)可抑制ALK的自磷酸化，ALK介导的下游信号蛋白STAT3的磷酸化，以及ALK依赖性肿瘤细胞的增殖。色瑞替尼(Ceritinib)在体外实验中能抑制表达EML4-ALK和NPM-ALK融合蛋白细胞系的增殖，对小鼠和大鼠中EML4-ALK阳性非小细胞肺癌（NSCLC）异种移植瘤的生长表现出剂量依赖性抑制作用。在EML4-ALK阳性NSCLC小鼠异种移植瘤对克唑替尼(Crizotinib)耐药的情况下,色瑞替尼(Ceritinib)在临床相关浓度范围内显示出剂量依赖的抗肿瘤活性。", + "布格替尼": "ALUNBRIG是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)成人患者。\\\\布格替尼(Brigatinib)是一种酪氨酸激酶抑制剂，体外浓度达到临床相关浓度时可以抑制多种激酶的活性，包括ALK、ROS1、胰岛素样生长因子1受体（IGF-1R）和FLT-3以及EGFR缺失和点突变。在体外和体内试验中，布格替尼(Brigatinib)能抑制ALK的自磷酸化以及ALK介导的下游信号蛋白STAT3、AKT、ERK1/2和S6的磷酸化。布格替尼(Brigatinib)还抑制了表达EML4-ALK和NPM-ALK融合蛋白细胞系的体外增殖，并显示出对EML4-ALK阳性、非小细胞肺癌小鼠异种移植瘤模型生长的剂量依赖性抑制作用。在临床相关浓度(≤500nM)下，布格替尼(Brigatinib)抑制了表达EML4-ALK和17种与ALK抑制剂（包括克唑替尼Crizotinib）耐药相关突变细胞的体外活力，这些突变包括EGFR-Del (E746-A750)、ROS1-L2026M、FLT3-F691L和FLT3-D835Y。布格替尼(Brigatinib)还对4种EML4-ALK突变表现出体内抗肿瘤活性，包括在克唑替尼(Crizotinib)治疗后疾病进展的NSCLC患者中发现的G1202R和L1196M突变。布格替尼(Brigatinib)还可减轻颅内植入ALK驱动肿瘤细胞系小鼠的肿瘤负担，并延长其生存期。", + "洛拉替尼": "LORBRENA是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)成人患者。\\\\非小细胞肺癌（NSCLC）占全球肺癌患者的85%，并且仍然是特别难以治疗的疾病。间变性淋巴瘤激酶（ALK）基因重排的遗传变异可驱动许多患者的NSCLC发展（PubMed: 18097461, PubMed: 25914136）。通常情况下，ALK是一种天然的内源性酪氨酸激酶受体，在大脑发育中起着重要作用，并在神经系统的各种特异神经元上发挥活性（PubMed: 29101158, PubMed: 29067878, PubMed: 18097461）。相应地，劳拉替尼（Lorlatinib）是一种激酶抑制剂，对ALK具有体外活性，并可靶向多种其他酪氨酸激酶受体，包括ROS1、TYK1、FER、FPS、TRKA、TRKB、TRKC、FAK、FAK2和ACK。劳拉替尼（Lorlatinib）对多种ALK突变酶表现出体外活性，包括在克唑替尼（Crizotinib）和其他ALK抑制剂治疗下疾病进展的肿瘤中检测到的突变。此外，劳拉替尼（Lorlatinib）血脑屏障通透性高，能够治疗进行性或恶化性脑转移非小细胞肺癌（PubMed: 29067878）。劳拉替尼（Lorlatinib）在体内模型的整体抗肿瘤活性呈剂量依赖性，并与抑制ALK磷酸化有关。尽管多数ALK阳性转移性NSCLC患者对最初的酪氨酸激酶疗法产生响应，但是后期这些患者的病情通常会发现再度恶化（PubMed: 28122866）。然而，多项劳拉替尼（Lorlatinib）的临床试验表明，对于正在或已使用各种第一、二代酪氨酸激酶抑制剂（如克唑替尼[Crizotinib]、阿来替尼[Alectinib]或色瑞替尼[Ceritinib]）后肿瘤进展的ALK阳性转移性NSCLC患者，其可有效促进患者的肿瘤消退（PubMed: 30413381）。", + "洛普替尼": "Repotrectinib (TPX-0005) 是一种新型的ALK/ROS1/TRK抑制剂，对WT ALK、ALK(G1202R)、ALK(L1196M)的IC50分别为1.01 nM、1.26 nM、1.08 nM；同时也是一种有效的SRC抑制剂，IC50为5.3 nM。TPX-0005是一种具有口服活性的ATP竞争性抑制剂，抑制ALK、ROS1、TRKA、TRKB和TRKC重组激酶以及其相应的临床耐药突变体。在许多人类癌细胞系和工程类稳定表达致癌基因或其突变体的细胞系中，亚纳摩尔或第浓度的纳摩尔级别的TPX-0005能有效发挥其抗增殖活性，伴随着对靶标磷酸化的抑制和使其下游效应分子如ERK、AKT和STAT3失活。TPX-0005在伤口愈合实验中，抑制H2228细胞的迁移。它不仅能够抑制野生型和大部分ALK突变体，还能克服原发耐药性，通过抑制SRC抑制转移性特征。在患者来源的移植瘤模型中，TPX-0005能够引起具有致瘤性ALK、ROS1和TRKC融合的肿瘤显著消退。此外，在一系列小鼠移植瘤模型中，TPX-0005不仅仅在含有野生型致瘤性靶标的肿瘤中具有显著的抗肿瘤活性，还能通过抑制相应靶标的磷酸化，在具有溶剂前沿突变（solvent front mutations）致癌基因的肿瘤中也发挥其效力。", + "阿来替尼": "ALECENSA是一种激酶抑制剂，适用于间变性淋巴瘤激酶(ALK)阳性的转移性非小细胞肺癌(NSCLC)。\\\\阿来替尼(Alectinib)是靶向ALK和RET的酪氨酸激酶抑制剂。在非临床研究中，阿来替尼(Alectinib)抑制ALK磷酸化和ALK介导的下游信号蛋白STAT3和AKT的活化，并降低ALK融合、扩增或突变的多种细胞系中肿瘤细胞的活力。阿来替尼(Alectinib)的主要活性代谢产物M4，在体外也表现出相似的效价和活性。阿来替尼(Alectinib)和M4在体内和体外均对ALK酶的多种突变形式具有活性，包括在克唑替尼(Crizotinib)治疗的非小细胞肺癌肿瘤患者中鉴定出的某些突变。在携带ALK融合蛋白的肿瘤的小鼠模型中（包括在颅内植入ALK驱动的肿瘤细胞系的小鼠模型），使用阿来替尼(Alectinib)可产生抗肿瘤活性并延长生存期。", + "恩沙替尼": "恩沙替尼为间变性淋巴瘤激酶（ALK）抑制剂，适用于间变性淋巴瘤激酶（ALK）阳性的局部晚期或转移性非小细胞肺癌（NSCLC）患者的治疗。\\\\恩沙替尼为间变性淋巴瘤激酶（ALK）抑制剂，对ALK的半数抑制浓度（IC50）小于 0.25 nM，对 Ephrin A2 激酶（EPHA2）、MET 受体酪氨酸激酶（c-MET）亦可见抑制作用。恩沙替尼可抑制 HEK-293 细胞（过表达 EML4-ALK E13;A20）ALK 自磷酸化，也可抑制非小细胞肺癌细胞 H3122（EML4-ALK E13;A20）ALK磷酸化，同时抑制相应下游信号分子 AKT、ERK 及 mTOR 底物-核糖体蛋白（S6）的磷酸化。恩沙替尼对非小细胞肺癌细胞 H3122、H2228，淋巴瘤细胞 SUDHL-1 以及神经母细胞瘤细胞 SH-SY5Y 的 IC50 分别为 0.015 μM、0.045 μM、0.009 μM 和0.068 μM；对 c-MET 扩增的胃腺癌细胞 MKN-45 抑制作用的 IC50 为 0.156 μM；对转染了克唑替尼耐药突变体 EML4-ALK L1196M 或 C1156Y 的 Ba/F3 细胞抑制作用的 IC50 分别 0.106 μM 和 0.048 μM。", + "阿法替尼": "GILOTRIF是一种激酶抑制剂，其适应症包括：1.携带非耐药性表皮生长因子受体(EGFR)突变的转移性非小细胞肺癌(NSCLC)的一线治疗。2.铂基化疗后疾病进展的转移性鳞状非小细胞肺癌。\\\\阿法替尼（Afatinib）与EGFR（ErbB1），HER2（ErbB2）和HER4（ErbB4）的激酶结构域共价结合，并不可逆地抑制酪氨酸激酶的自磷酸化，从而导致ErbB信号下调。EGFR的某些突变，包括其激酶结构域的非耐药性突变，可使受体自磷酸化增加，导致受体有时可在无配体结合的情况下激活，并促进NSCLC中的细胞增殖。非耐药性突变定义为发生在编码EGFR激酶结构域的外显子中并能导致受体激活增强的突变，其功效可通过以下方式预测：1）阿法替尼（Afatinib）推荐剂量治疗下有临床意义的肿瘤缩小，和/或2）根据验证方案，推荐剂量下可持续的阿法替尼（Afatinib）浓度下对细胞增殖或EGFR酪氨酸激酶磷酸化的抑制作用。这些突变中最常见的是外显子21 L858R替换和外显子19缺失。在以等价于患者服用剂量的阿法替尼（Afatinib）浓度培养的野生型EGFR细胞系和表达特定的EGFR外显子19缺失突变、外显子21 L858R突变或其他较罕见非耐药性突变的细胞系中，证实了阿法替尼（Afatinib）对自磷酸化和/或体外细胞增殖的抑制作用。此外，阿法替尼（Afatinib）也会抑制过表达HER2细胞系的体外增殖。在裸鼠移植瘤模型中过表达野生型EGFR或HER2，或者EGFRL858R/T790M双突变，经阿法替尼（Afatinib）治疗后均可抑制肿瘤的生长。", + "厄洛替尼": "TARCEVA是一种激酶抑制剂，其适应症为：1.在至少一种化疗方案失败后接受一线、维持第二线或更多线治疗的表皮生长因子受体(EGFR)19号外显子缺失或21号外显子L858R置换突变的转移性非小细胞肺癌(NSCLC)。2.联合吉西他滨用于局部晚期、不可切除性或转移性胰腺癌的一线治疗。\\\\表皮生长因子受体（EGFR）在正常细胞和肿瘤细胞表面都有表达。 在一些肿瘤细胞中，通过该受体的信号传导在肿瘤细胞存活和增殖中均起作用，而与EGFR突变状态无关。厄洛替尼（Erlotinib）可逆地抑制EGFR的激酶活性，阻止受体酪氨酸残基的自磷酸化，进而抑制下游信号传导。厄洛替尼（Erlotinib）对19号外显子缺失或21号外显子（L858R）突变EGFR的结合亲和力高于野生型受体。厄洛替尼（Erlotinib）对其他酪氨酸激酶受体的抑制作用尚未完全表征。", + "吉非替尼": "IRESSA是一种酪氨酸激酶抑制剂，适用于表皮生长因子受体(EGFR)19号外显子缺失或21号外显子置换突变的转移性非小细胞肺癌(NSCLC)的一线治疗。\\\\表皮生长因子受体（EGFR）在正常细胞和肿瘤细胞表面都有表达，并在细胞生长和增殖过程中发挥作用。NSCLC细胞中的一些EGFR激活突变（19号外显子缺失或21号外显子L858R点突变）已被确认有助于促进肿瘤细胞生长、阻断凋亡、增加血管生成因子的产生以及促进肿瘤转移。吉非替尼（Gefitinib）可逆地抑制野生型和某些EGFR激活突变的激酶活性，阻止与受体相关的酪氨酸残基的自磷酸化，进而抑制下游信号传导并阻断EGFR依赖性增殖。吉非替尼（Gefitinib）对19号外显子缺失或21号外显子L858R点突变的结合亲和力要高于其对野生型EGFR的亲和力。吉非替尼（Gefitinib）还可以在临床相关浓度下抑制IGF和PDGF介导的信号传导。其他酪氨酸激酶受体的抑制作用尚未完全表征。", + "ASP3026": "", + "Chemotherapy": "", + "Capecitabine": "", + "capecitabine": "", + "Letrozole": "", + "恩美曲妥珠单抗": "KADCYLA是一种HER2靶向抗体和微管抑制剂缀合物，其适应症为：单药使用：1.以下既往接受过单独或联合曲妥珠单抗和紫杉烷治疗的HER2阳性转移性乳腺癌患者：(1)既往接受过转移性疾病的先前治疗。(2)完成辅助治疗期间或之后六个月内疾病复发。2.既往接受紫杉烷和曲妥珠单抗治疗后仍残留浸润性疾病的HER2阳性早期乳腺癌患者的辅助治疗。\\\\恩美曲妥珠单抗（Ado-trastuzumab emtansine）是靶向HER2的抗体药物偶联物。 该抗体是人源化抗HER2 IgG1曲妥珠单抗（Trastuzumab）。 小分子细胞毒素DM1是微管抑制剂。 与HER2受体的亚结构域IV结合后，恩美曲妥珠单抗（Ado-trastuzumab emtansine）经历受体介导的内在化和随后的溶酶体降解，从而导致胞内释放含DM1的细胞毒性代谢产物。 DM1与微管蛋白的结合会破坏细胞中的微管网络，从而导致细胞周期停滞和细胞凋亡。 此外，体外研究表明，与曲妥珠单抗（Trastuzumab）类似，恩美曲妥珠单抗（Ado-trastuzumab emtansine）抑制HER2受体信号传导，介导抗体依赖性细胞介导的细胞毒性，并抑制过表达HER2的人乳腺癌细胞中HER2的胞外域脱落。", + "Margetuximab-cmkb": "Margetuximab-cmkb是一种HER2/neu受体拮抗剂，适用于联合化疗治疗既往接受两种或两种以上抗HER2方案(其中至少一种用于转移性疾病)的转移性HER2阳性乳腺癌成人患者。\\\\Margetuximab-cmkb与人表皮生长因子受体2蛋白（HER2）的胞外结构域结合。与表达HER2的肿瘤细胞结合后，margetuximab-cmkb可抑制肿瘤细胞增殖，减少HER2胞外结构域的脱落，并介导抗体依赖性细胞毒性（ADCC）。在体外试验中，经修饰的margetuximab-cmkb的Fc区增加了与激活的Fc受体FCGR3A（CD16A）的结合亲和力，并减少了与抑制性Fc受体FCGR2B（CD32B）的结合。这些改变导致更强的体外ADCC和NK细胞活化作用。", + "奈拉替尼": "NERLYNX是一种激酶抑制剂，其适应症为：1.单药用于经以曲妥珠单抗为基础辅助治疗的早期HER2阳性乳腺癌成人患者的延长辅助治疗。2.联合卡培他滨用于治疗既往接受过两种或两种以上的基于抗HER2治疗方案的转移性晚期或转移性HER2阳性乳腺癌患者。\\\\来那替尼（Neratinib）是一种胞内蛋白激酶抑制剂，可以不可逆地与表皮生长因子受体（EGFR）、HER2和HER4结合。在体外试验中，来那替尼（Neratinib）降低了EGFR和HER2的自磷酸化以及下游MAPK和AKT信号传导，并在表达EGFR和/或HER2癌细胞系中显示抗肿瘤活性。来那替尼（Neratinib）的人体代谢产物M3、M6、M7和M11在体外也可以抑制EGFR、HER2和HER4的活性。在表达HER2和EGFR肿瘤细胞系的小鼠异种移植模型中，口服来那替尼（Neratinib）可以抑制肿瘤生长。", + "Pembrolizumab": "", + "Fam-trastuzumab deruxtecan-nxki": "ENHERTU是一种HER2靶向抗体和拓扑异构酶抑制剂偶联物，其适应症为：1.携带HER2阳性，前期已接受过以抗HER2为基础的治疗(转移性疾病治疗或新辅助/辅助治疗）并在完成治疗期间或6个月内出现疾病复发的不可切除性或转移性乳腺癌成人患者。2.FDA批准检测的HER2低表达(IHC 1+或IHC 2+/ISH-)且在疾病转移后接受过化疗或在完成辅助化疗期间或6个月内发生疾病转移或复发成年乳腺癌患者。3.携带HER2 (ERBB2)激活突变的不可切除或转移性非小细胞肺癌(NSCLC)成人患者。4.既往接受过基于曲妥珠单抗治疗的HER2阳性、局部进展或转移性胃或胃食管交界处腺癌的成人患者。\\\\Fam-trastuzumab deruxtecan-nxki是一种HER2定向抗体药物偶联物。该抗体为人源化抗HER2 IgG1。小分子DXd是一种拓扑异构酶I抑制剂，通过可切割的接头与抗体相连。与肿瘤细胞上的HER2结合后，Fam-trastuzumab deruxtecan-nxki通过溶酶体酶进行内化和细胞内接头裂解。释放后，膜渗透性DXd会导致DNA损伤和细胞凋亡。", + "吡咯替尼": "吡咯替尼为小分子受体酪氨酸激酶抑制剂，其适应症为：1.联合卡培他滨治疗表皮生长因子受体 2 (HER2)阳性、既往未接受或接受过曲妥珠单抗的复发或转移性乳腺癌患者，使用本品前患者应接受过蒽环类或紫杉类化疗。2.联合曲妥珠单抗及多西他赛，适用于治疗表皮生长因子受体2（HER2）阳性早期或局部晚期乳腺癌患者的新辅助治疗。3.马来酸吡咯替尼片与曲妥珠单抗和多西他赛联合，用于治疗表皮生长因子受体2（HER2）阳性、晚期阶段未接受过抗HER2治疗的复发或转移性乳腺癌患者。\\\\吡咯替尼是不可逆的小分子受体酪氨酸激酶抑制剂，显著抑制表皮生长因子受体（ErbB1/EGFR）和人表皮生长因子受体 2（ErbB2/HER2），半数抑制浓度（IC50）分别为 5.6 nM、8.1 nM。吡咯替尼可显著抑制 HER2 高表达的肿瘤细胞（乳腺癌、卵巢癌、胃癌肿瘤细胞）生长，IC50 为 1~43 nM。在多种移植瘤裸小鼠模型（乳腺癌、卵巢癌、肺癌）中，吡咯替尼可显著抑制 HER2 因子驱动的肿瘤生长，抑制 HER2 介导的下游信号通路，将肿瘤细胞阻滞在细胞周期 G1 期。", + "伊尼妥单抗": "伊尼妥单抗是一种重组抗人表皮生长因子受体-2 人源化单克隆抗体，适用于与长春瑞滨联合治疗已接受过 1 个或多个化疗方案的HER2 阳性的转移性乳腺癌患者。\\\\伊尼妥单抗是一种重/组人源化单克隆抗体，特异作用于人表皮生长因子受体-2 (HER2) 的细胞外部位。并且伊尼妥单抗可介导抗体依赖的细胞介导的细胞毒反应（ADCC）。伊尼妥单抗在体外及动物试验中均显示可抑制 HER2 阳性肿瘤细胞的增殖。HER2原癌基因或C-erbB2编码一个单一的受体样跨膜蛋白，分子量为185 kDa，其结构上与其他表皮生长因子受体类似。在原发性乳腺癌患者中观察到有 25%~30% 的患者 HER2 阳性。HER2 基因扩增可导致肿瘤细胞表面 HER2 蛋白表达增加，导致 HER2 蛋白活化。", + "Vinorelbine": "", + "Docetaxel": "", + "Carboplatin-Taxol": "", + "奥希替尼": "TAGRISSO是一种激酶抑制剂，其适应症为：1 .用于表皮生长因子受体(EGFR)19号外显子缺失或21号外显子L858R突变的非小细胞肺癌(NSCLC)成人患者肿瘤切除术后的辅助治疗。2.表皮生长因子受体(EGFR)19号外显子缺失或21号外显子L858R突变的转移性NSCLC的一线治疗。3.EGFR T790M突变阳性、EGFR TKI治疗期间或之后疾病进展的转移性NSCLC成人患者。\\\\奥西替尼（Osimertinib）是一种表皮生长因子受体（EGFR）激酶抑制剂，能以比野生型低约9倍的浓度与某些EGFR突变（T790M，L858R和外显子19缺失）不可逆地结合。口服奥西替尼（Osimertinib）后在血浆中发现两种具有药理活性的代谢物（AZ7550和AZ5104，约占前体药物的10%），其抑制作用与奥西替尼相似。AZ7550与奥西替尼（Osimertinib）的效力相似，而AZ5104对EGFR 19号外显子缺失、T790M突变（约8倍）以及野生型EGFR（约15倍）的活性较强。体外试验显示，奥西替尼（Osimertinib）在临床浓度下也能抑制HER2、HER3、HER4、ACK1和BLK的活性。在细胞培养和动物肿瘤移植瘤模型中，奥希替尼（Osimertinib）对携带EGFR突变（T790M/L858R、L858R、T790M/19号外显子缺失、19号外显子缺失）的非小细胞肺癌（NSCLC）细胞系具有抗肿瘤活性，对野生型EGFR基因扩增的抗肿瘤活性较弱。奥西替尼（Osimertinib）口服给药后高分布于多种动物（猴子，大鼠和小鼠）的脑部，其脑-血AUC比约为2：1。这些数据与一项临床前研究结果一致：在EGFR突变小鼠异种颅内移植模型（PC9；19号外显子缺失）中，与对照组相比，可观察到奥西替尼（Osimertinib）组的肿瘤消退以及存活率提高。", + "埃克替尼": "埃克替尼是一种酪氨酸激酶抑制剂，适用于治疗表皮生长因子受体(EGFR)基因具有敏感突变的局部晚期或转移性非小细胞肺癌(NSCLC)患者的一线治疗。本品单药可试用于治疗既往接受过至少一个化疗方案失败后的局部晚期或转移性非小细胞肺癌(NSCLC)，既往化疗主要是指以铂类为基础的联合化疗。\\\\埃克替尼是一种选择性表皮生长因子受体(EGFR)酪氨酸激酶抑制剂。埃克替尼抑制EGFR酪氨酸激酶活性的半数有效浓度(IC50)为5 nM，在所测试的88种激酶中，500 nM浓度的埃克替尼只对EGFR野生型及其突变型有明显的抑制作用，对其它激酶均没有抑制作用，提示埃克替尼是一个高选择性的EGFR激酶抑制剂。体外研究和动物实验表明埃克替尼可抑制多种人肿瘤细胞株的增殖。", + "ROS1/ALK TKI": "", + "卡马替尼": "TABRECTA是一种激酶抑制剂，适用于携带间质表皮转化因子(MET)基因14号外显子跳跃突变的转移性非小细胞肺癌(NSCLC)成人患者。\\\\卡马替尼（Capmatinib）是一种针对MET的激酶抑制剂，这其中就包括外显子14跳跃产生的突变。MET外显子14跳跃会导致蛋白质缺失调控域，从而降低其负调控，导致下游MET信号传导增加。卡马替尼（Capmatinib）在临床相关浓度下可抑制MET 14号外显子缺失突变驱动的肿瘤细胞生长，并在小鼠人源肺癌异种移植模型中显示出抗肿瘤活性，该模型的基因突变会导致MET 14号外显子跳跃或MET扩增。卡马替尼(Capmatinib)抑制由肝细胞生长因子结合或MET扩增触发的MET磷酸化，以及MET介导的下游信号蛋白磷酸化和MET依赖性肿瘤细胞的增殖和存活。" + } + } +} \ No newline at end of file diff --git a/xlsx/07211057_merged_file.xlsx b/xlsx/07211057_merged_file.xlsx new file mode 100644 index 0000000..39d6de0 Binary files /dev/null and b/xlsx/07211057_merged_file.xlsx differ diff --git a/xlsx/07211104_merged_file.xlsx b/xlsx/07211104_merged_file.xlsx new file mode 100644 index 0000000..39d6de0 Binary files /dev/null and b/xlsx/07211104_merged_file.xlsx differ diff --git a/xlsx/07211105_merged_file.xlsx b/xlsx/07211105_merged_file.xlsx new file mode 100644 index 0000000..39d6de0 Binary files /dev/null and b/xlsx/07211105_merged_file.xlsx differ diff --git a/xlsx/07211115_merged_file.xlsx b/xlsx/07211115_merged_file.xlsx new file mode 100644 index 0000000..39d6de0 Binary files /dev/null and b/xlsx/07211115_merged_file.xlsx differ diff --git a/xlsx/merged_file.xlsx 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