Research Paper Volume 13, Issue 23 pp 25518—25549
Identification of a novel immune signature for optimizing prognosis and treatment prediction in colorectal cancer
- 1 Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 2 Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
- 3 State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 4 The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China
- 5 The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 6 Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 7 Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 8 Guangdong Engineering and Technology Research Center for Disease-Model Animals, Laboratory Animal Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 9 Key Laboratory of Tropical Disease Control of the Ministry of Education, Sun Yat-Sen University, Guangzhou, Guangdong, China
- 10 Center for Precision Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
Received: September 24, 2021 Accepted: November 22, 2021 Published: December 13, 2021https://doi.org/10.18632/aging.203771
How to Cite
Copyright: © 2021 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background: Globally, colorectal cancer (CRC) is one of the most lethal malignant diseases. However, the currently approved therapeutic options for CRC failed to acquire satisfactory treatment efficacy. Tailoring therapeutic strategies for CRC individuals can provide new insights into personalized prediction approaches and thus maximize clinical benefits.
Methods: In this study, a multi-step process was used to construct an immune-related genes (IRGs) based signature leveraging the expression profiles and clinical characteristics of CRC from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. An integrated immunogenomic analysis was performed to determine the association between IRGs with prognostic significance and cancer genotypes in the tumor immune microenvironment (TIME). Moreover, we performed a comprehensive in silico therapeutics screening to identify agents with subclass-specific efficacy.
Results: The established signature was shown to be a promising biomarker for evaluating clinical outcomes in CRC. The immune risk score as calculated by this classifier was significantly correlated with over-riding malignant phenotypes and immunophenotypes. Further analyses demonstrated that CRCs with low immune risk scores achieved better therapeutic benefits from immunotherapy, while AZD4547, Cytochalasin B and S-crizotinib might have potential therapeutic implications in the immune risk score-high CRCs.
Conclusions: Overall, this IRGs-based signature not only afforded a useful tool for determining the prognosis and evaluating the TIME features of CRCs, but also shed new light on tailoring CRCs with precise treatment.