Dandan Wang, Xuejian Wang, Lin Chen, Huiying Wang, Xiangfei Meng, Zhenwei Miao, Yang Zhao
{"title":"Development of an ADME gene signature for prognostic and therapeutic stratification in gastric cancer.","authors":"Dandan Wang, Xuejian Wang, Lin Chen, Huiying Wang, Xiangfei Meng, Zhenwei Miao, Yang Zhao","doi":"10.1007/s12672-025-03729-z","DOIUrl":null,"url":null,"abstract":"<p><p>A pivotal determinant of tumor therapy efficacy lies in the absorption, distribution, metabolism, and excretion (ADME) processes that govern drug disposition within the body. We intended to establish a prognostic model incorporating ADME-related genes to forecast the survival rate and therapeutic response in gastric cancer (GC) patients. By integrating Cox regression and LASSO analysis for dimensionality reduction and feature selection, we identified a stable five-gene signature with significant prognostic value. Subsequently, the stability of the model was verified. A nomogram incorporating these genes was constructed and integrated with a clinicopathological feature prediction system to improve its clinical applicability. The results revealed a robust correlation between ADME-related genes and the survival outcomes of GC patients. The ADME-based gene signature serves as a robust prognostic biomarker for evaluating the survival outcomes. Furthermore, immune cell infiltration and functional analyses demonstrated distinct patterns between the two strata, with the high-risk stratum exhibiting superior drug sensitivity. Finally, in vitro validation experiments using AGS and HGC-27 cell lines confirmed that elevated CYP2A6 expression promotes the progression of GC. This finding indicates that CYP2A6 may be a new biomarker in the therapeutic management of the disease.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1888"},"PeriodicalIF":2.9000,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12528583/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discover. Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12672-025-03729-z","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
A pivotal determinant of tumor therapy efficacy lies in the absorption, distribution, metabolism, and excretion (ADME) processes that govern drug disposition within the body. We intended to establish a prognostic model incorporating ADME-related genes to forecast the survival rate and therapeutic response in gastric cancer (GC) patients. By integrating Cox regression and LASSO analysis for dimensionality reduction and feature selection, we identified a stable five-gene signature with significant prognostic value. Subsequently, the stability of the model was verified. A nomogram incorporating these genes was constructed and integrated with a clinicopathological feature prediction system to improve its clinical applicability. The results revealed a robust correlation between ADME-related genes and the survival outcomes of GC patients. The ADME-based gene signature serves as a robust prognostic biomarker for evaluating the survival outcomes. Furthermore, immune cell infiltration and functional analyses demonstrated distinct patterns between the two strata, with the high-risk stratum exhibiting superior drug sensitivity. Finally, in vitro validation experiments using AGS and HGC-27 cell lines confirmed that elevated CYP2A6 expression promotes the progression of GC. This finding indicates that CYP2A6 may be a new biomarker in the therapeutic management of the disease.