ORIGINAL RESEARCH article
Front. Bioinform.
Sec. Drug Discovery in Bioinformatics
Volume 5 - 2025 | doi: 10.3389/fbinf.2025.1661601
Drug discovery for chemotherapeutic resistance based on pathway-responsive gene sets and its application in breast cancer
Provisionally accepted
DeHua Feng
Jingwen HaoLingxu LiJian ChenXinying LiuRuijie ZhangHuirui HanTianyi LiXuefeng Wang
Xia LiLei YuBing Li*
Jin Li*Limei Wang*- Hainan Medical University, Haikou, China
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Chemotherapy response variability in cancer patients necessitates novel strategies targeting chemoresistant populations. While combinatorial regimens show promise through synergistic pharmacological interactions, traditional pathway enrichment methods relying on static gene sets fail to capture drug-induced dynamic transcriptional perturbations. To address this challenge, we developed the Pathway-Responsive Gene Sets (PRGS) framework to systematically identify chemoresistance-associated pathways and guide therapeutic intervention. Comparative evaluation of three computational strategies (GSEA-like method, Hypergeometric test-based method, Bates test-based method) revealed that the GSEA-like methodology exhibited superior performance, enabling precise identification of drug-induced pathway dysregulation. Key experimental findings demonstrated PRGS's superiority over conventional Pathway Member Gene Sets (PMGS), exhibiting statistical independence (p<0.0001) and enhanced detection of chemotherapy-driven pathway dysregulation. Application of PRGS to the GDSC dataset identified 8 resistance-associated pathways. Screening of agents targeting these pathways yielded candidates with predicted anti-resistance activity. An in vitro cellular experiment demonstrated that the bortezomib-bleomycin combination exhibited synergistic cytotoxicity (IDAcomboScore=0.014) in T47D cells, highlighting the potential of PRGS-guided therapeutic strategies. This study establishes a PRGS-based methodological framework that integrates genomic perturbations with precision oncology, demonstrating its capacity to decode resistance mechanisms and guide therapeutic development through dynamic pathway analysis.
Keywords: chemotherapeutic resistance, pathway-responsive gene sets, Drug Discovery, drugcombination therapy, precision oncology
Received: 08 Jul 2025; Accepted: 06 Aug 2025.
Copyright: © 2025 Feng, Hao, Li, Chen, Liu, Zhang, Han, Li, Wang, Li, Yu, Li, Li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Bing Li, Hainan Medical University, Haikou, China
Jin Li, Hainan Medical University, Haikou, China
Limei Wang, Hainan Medical University, Haikou, China
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