Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis - Zhu, Jie; Kong, Weikaixin; Huang, Liting; Bi, Suzhen; Jiao, Xuelong; Zhu, Sujie (Frontiers in Immunology, 2023)
Colon cancer is a highly heterogenous disease. Molecular subtypes of colon cancer can provide insights into the deregulated pathways within tumor subsets, which may indicate immunity therapy and chemotherapy opportunities. The development of cancer was related to multiple signaling pathways, such as cell cycle, immune, aging, metabolism, autophagy and so on. However, in currently studies, most of constructed prognostic models were based on the single pathway genes. Herein, we identified three clinically relevant subtypes of colon cancer based on multiple prognostic cancer signaling pathway related genes. Integrative multi-omics analysis is used to explain the biological processes contributing to colon cancer aggressiveness, recurrence, and progression. It is noting that we used machine learning methods to identify the subtypes and provided a medication guidance for distinct subtypes using L1000 system. Furthermore, we established a prognostic model (MKPC score) based on gene-pairs, validating it in one internal test set and three external test sets. Risk related genes were extracted and verified by qPCR. To enable our subtyping method and MKPC score can be used by other researchers, we implemented it as an easy-to-use web-tool (https://sujiezhulab.shinyapps.io/coad/) for risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can easily be extended also for other cancer types.