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

被引:80
作者
Li, Xinyu [1 ,2 ]
Wen, Dacheng [3 ]
Li, Xiaokang [4 ]
Yao, Chunli [2 ,5 ]
Chong, Wei [6 ,7 ,8 ]
Chen, Hao [9 ]
机构
[1] Shandong First Med Univ & Shandong Acad Med Sci, Shandong Canc Hosp & Inst, Dept Gastrointestinal Oncol, Jinan, Peoples R China
[2] Ludwig Maximilian Univ Munich, Dept Gen Visceral & Transplant Surg, Univ Hosp, Munich, Germany
[3] Jilin Univ, Dept Gastrointestinal Nutr & Hernia Surg, Hosp 2, Changchun, Peoples R China
[4] Shandong Univ, Cheelo Coll Med, Dept Dermatol, Jinan Cent Hosp, Jinan, Peoples R China
[5] Jilin Univ, Hosp 2, Dept Dermatol, Changchun, Peoples R China
[6] Shandong First Med Univ, Shandong Prov Hosp, Dept Gastrointestinal Surg, Jinan, Peoples R China
[7] Shandong Univ, Cheeloo Coll Med, Shandong Prov Hosp, Dept Gastrointestinal Surg, Jinan, Peoples R China
[8] Shandong Prov Hosp, Key Lab Engn Shandong Prov, Jinan, Peoples R China
[9] Shandong Univ, Qilu Hosp, Clin Epidemiol Unit, Clin Res Ctr, Jinan, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2020年 / 11卷
关键词
colon cancer; immune signature; tumor mutation load; immune infiltration; significantly mutated genes; COLORECTAL-CANCER; TUMORS; BLOCKADE; IMMUNOTHERAPY;
D O I
10.3389/fimmu.2020.01678
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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 ofAPCandFBXW7. 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.
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页数:13
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