基于网络靶点收敛算法预测治疗晚期肺腺癌的候选药物-《中国医学物理学杂志》

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Title:: Prediction of drug candidates for the treatment of advanced lung adenocarcinoma based on network target convergence algorithm

文章编号:: 1005-202X（2024）04-0504-08

作者:: 刘溪; 关双; 俞成诚; 王忠; 中国中医科学院中医临床基础医学研究所，北京 1007000

Author(s):: LIU Xi; GUAN Shuang; YU Chengcheng; WANG Zhong; Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China

关键词:: 晚期肺腺癌; 预后基因; 复杂网络; 靶点收敛; 抗致癌药

Keywords:: Keywords: advanced lung adenocarcinoma prognostic gene complex network target convergence anticancer agent

分类号:: R318

DOI:: DOI:10.3969/j.issn.1005-202X.2024.04.016

文献标志码:: A

摘要:: 目的：筛选晚期肺腺癌调控网络的收敛基因集，借助关联性图谱（CMap）预测治疗晚期肺腺癌的候选药物。方法：利用TCGA数据库检索肺腺癌转录组与临床数据，使用R4.0.3软件筛选肺腺癌早晚期患者的差异基因，使用Kaplan-Meier与log秩检验识别预后基因。DAVID和KEGG数据库对预后基因进行富集分析。依据背景网络构建差异预后基因调控网络，集体影响（CI）算法计算网络收敛基因集，将基因集导入CMap获得治疗晚期肺腺癌的候选药物，进一步对候选药物进行查找和分析。结果：共获得差异表达基因3 409个，其中1 981个与生存显著相关。富集分析结果显示，预后基因主要与细胞分裂、染色体分离、有丝分裂细胞周期、DNA复制、B细胞激活、T细胞激活等生物学过程相关；CI方法筛选得到晚期肺腺癌收敛预后基因96个，通过CMap连接图计算得到排名前20的候选化合物，其中，thapsigargin和nutlin-3通过文献验证对晚期肺腺癌有潜在的治疗作用。结论：借助生物信息学、网络靶点收敛算法和CMap数据库挖掘对晚期肺腺癌具有治疗作用的药物，为发现疾病的候选治疗靶点与药物开辟了新途径和思路。

Abstract:: Abstract: Objective To identify the convergent gene sets in the regulatory network of advanced lung adenocarcinoma, and predict drug candidates for the treatment of advanced lung adenocarcinoma using connectivity map (CMap). Methods The TCGA database was used to search for the transcriptome and clinical data of lung adenocarcinoma, and R4.0.3 software to screen the differential genes of early- and advanced-stage patients, and Kaplan-Meier and log-rank tests to identify prognostic genes. The enrichment analysis of prognostic genes was carried out in DAVID and KEGG databases. The differential prognostic gene regulatory network was constructed based on the background network, and the collective influence algorithm was employed to calculate the convergent gene set which was then imported into CMap to obtain drug candidates for the treatment of advanced lung adenocarcinoma. Further investigation and analysis were conducted on the drug candidates. Results A total of 3 409 differentially expressed genes were obtained, with 1 981 genes significantly associated with survival. Enrichment analysis showed that prognostic genes were mainly related to biological processes such as cell division, chromosome segregation, mitotic cell cycle, DNA replication, B-cell activation, T-cell activation, etc. The collective influence method identified 96 convergent prognostic genes in advanced lung adenocarcinoma. The top 20 candidate compounds were obtained through CMap linkage map calculation, of which thapsigargin and nutlin-3 had been proven to have potential therapeutic effects on advanced lung adenocarcinoma through literature review. Conclusion The study leverages bioinformatics, network target convergence algorithm and CMap database to explore drugs with therapeutic effects on advanced lung adenocarcinoma, which opens up new ways and ideas for discovering candidate therapeutic targets and drugs for diseases.

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

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