Abstract
Increasing studies have highlighted the effects of the tumor immune micro-environment (TIM) on colon cancer (CC) tumorigenesis, prognosis, and metastasis. However, there is no reliable molecular marker that can effectively estimate the immune infiltration and predict the CC relapse risk. Here, we leveraged the gene expression profile and clinical characteristics from 1430 samples, including four gene expression omnibus database (GEO) databases and the cancer genome atlas (TCGA) database, to construct an immune risk signature that could be used as a predictor of survival outcome and immune activity. A risk model consisting of 10 immune-related genes were screened out in the Lasso-Cox model and were then aggregated to generate the immune risk signature based on the regression coefficients. The signature demonstrated robust prognostic ability in discovery and validation datasets, and this association remained significant in the multivariate analysis after controlling for age, gender, clinical stage, or microsatellite instability status. Leukocyte subpopulation analysis indicated that the low-risk signature was enriched with cytotoxic cells (activated CD4/CD8+ T cell and NK cell) and depleted of myeloid-derived suppressor cells (MDSC) and regulatory T cells. Further analysis indicated patients with a low-risk signature harbored higher tumor mutation loads and lower mutational frequencies in significantly mutated genes of APC and FBXW7. Together, our constructed signature could predict prognosis and represent the TIM of CC, which promotes individualized treatment and provides a promising novel molecular marker for immunotherapy.
Highlights
Colon cancer (CC) is one of the most common cancers and remains one of the leading causes of cancer death worldwide [1]
The Lasso coefficient profile plot was produced against the log(k) sequence, and the minimize k method resulted in 10 optimal coefficients (Figures 1A,B)
The newly identified immune risk signature presumably represented the status of tumor immune micro-environment (TIM) for CC patients and served as a potential biomarker for prognosis estimation and clinical response prediction to immunotherapy
Summary
Colon cancer (CC) is one of the most common cancers and remains one of the leading causes of cancer death worldwide [1]. Despite continuous achievements in early CC detection, treatment, and management leading to reductions in the incidence and mortality, 30–50% of patients develop recurrence or metastasis within five years of treatment [2]. Conventional methods for detecting the tumor immune infiltrate, such as flow cytometry or immunohistochemistry (IHC), cannot comprehensively evaluate the immune effects due to the limitation of the number of immune markers. There has been no appropriate signature that can systematically evaluate the tumor immune micro-environment (TIM) based on immune-related genes and predict the patients’ survival or response to immunotherapies of CC patients. It’s essential to develop a reliable immune signature on the basis of a comprehensive list of immune-related genes to represent the immune status of TIM and have the prognostic ability of CC
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