Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis

Abstract

BackgroundColon cancer is a highly heterogeneous disease, and identifying molecular subtypes can provide insights into deregulated pathways within tumor subsets, which may lead to personalized treatment options. However, most prognostic models are based on single-pathway genes.MethodsIn this study, we aimed to identify three clinically relevant subtypes of colon cancer based on multiple signaling pathways-related genes. Integrative multi-omics analysis was used to explain the biological processes contributing to colon cancer aggressiveness, recurrence, and progression. Machine learning methods were employed to identify the subtypes and provide medication guidance for distinct subtypes using the L1000 platform. We developed a robust prognostic model (MKPC score) based on gene pairs and validated it in one internal test set and three external test sets. Risk-related genes were extracted and verified by qPCR.ResultsThree clinically relevant subtypes of colon cancer were identified based on multiple signaling pathways-related genes, which had significantly different survival state (Log-Rank test, p<0.05). Integrative multi-omics analysis revealed biological processes contributing to colon cancer aggressiveness, recurrence, and progression. The developed MKPC score, based on gene pairs, was robust in predicting prognosis state (Log-Rank test, p<0.05), and risk-related genes were successfully verified by qPCR (t test, p<0.05). An easy-to-use web tool was created for risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types.ConclusionIn conclusion, our study identified three clinically relevant subtypes of colon cancer and developed a robust prognostic model based on gene pairs. The developed web tool is a valuable resource for researchers and clinicians in risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types.

Immunotherapy and Cancer: The Multi-Omics Perspective

“…In addition, researchers have discovered an association between the mRNA-based expression subtypes and ICI response, while the Tumor Mutational Burden (TMB) status and transcriptome expressions can be used to guide treatment choices using platform L1000. Also, they created a classifier that can help identify the best drug for a colon cancer patient based on their gene expression [ 19 ].…”

“…Furthermore, the TCIA database (https://tcia.at/home, accessed on 18 March 2024) provides immunotherapy prediction information based on comprehensive immunogenomic analyses of next-generation sequencing data (NGS) of 20 types of cancer, including breast cancer. This information can be used to predict the immune checkpoint inhibitor (ICI) response of patients with distinct subtypes of breast cancer [19].…”

Exploring the mystery of colon cancer from the perspective of molecular subtypes and treatment

“…The gene expression subtypes of COAD and COADREAD were proposed by the Cancer Genome Atlas (TCGA) research network respectively 9 , 10 . A recent study also identified molecular subtypes of colon cancer based on multiple platforms, including molecular subtypes of COAD patients 11 , and several molecular subtypes of colon cancer based on different gene sets 12 . However, early colon cancer has some special molecular characteristics, and in these subtypes and gene sets, the prognostic information of patients is not well used, resulting in weak prognostic ability of patients.…”

“…First, it can inhibit tumorigenesis by blocking upstream signaling pathways. This includes ligand-neutralizing antibodies, decoy receptors or inhibitors that block TGFβ, NF-κB, EGFR, cMET, WNT and Notch signals 12 – 34 . In addition, effective inducers of EMT include a variety of proinflammatory signals, such as TNF-α 35 .…”

Genetic Variants in the Mitochondrial Thymidylate Biosynthesis Pathway Increase Colorectal Cancer Risk

“…In Saudi Arabia, CRC is considered the most common type of cancer in men and the third most common cancer type among women [ 3 ]. The development of CRC was related to multiple signaling pathways, including the cell cycle, immunity, aging, and metabolism [ 4 ]. Generally, the treatment of CRC depends on the stage of the tumor.…”