Dataset Information

Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer.

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.

SUBMITTER: Li X

PROVIDER: S-EPMC7497441 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer.

Li Xinyu X Wen Dacheng D Li Xiaokang X Yao Chunli C Chong Wei W Chen Hao H

Frontiers in immunology 20200903

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 cons ...[more]

PMID: 33013820

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Dataset Information

Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer.

Publications

Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer.

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