辅助化疗
阶段(地层学)
签名(拓扑)
结直肠癌
基因签名
肿瘤科
化疗
内科学
癌症
医学
佐剂
基因
生物
基因表达
数学
乳腺癌
遗传学
古生物学
几何学
作者
Chaohan Xu,Peng Xia,Jia Li,Keeli B. Lewis,Kristen K. Ciombor,Lily Wang,J. Joshua Smith,R. Daniel Beauchamp,Steven Chen
标识
DOI:10.1016/j.xcrm.2024.101661
摘要
Identifying patients with stage II and III colon cancer who will benefit from 5-fluorouracil (5-FU)-based adjuvant chemotherapy is crucial for the advancement of personalized cancer therapy. We employ a semi-supervised machine learning approach to analyze a large dataset with 933 stage II and III colon cancer samples. Our analysis leverages gene regulatory networks to discover an 18-gene prognostic signature and to explore a 10-gene signature that potentially predicts chemotherapy benefits. The 10-gene signature demonstrates strong prognostic power and shows promising potential to predict chemotherapy benefits. We establish a robust clinical assay on the NanoString nCounter platform, validated in a retrospective formalin-fixed paraffin-embedded (FFPE) cohort, which represents an important step toward clinical application. Our study lays the groundwork for improving adjuvant chemotherapy and potentially expanding into immunotherapy decision-making in colon cancer. Future prospective studies are needed to validate and establish the clinical utility of the 10-gene signature in clinical settings.
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