Construction and validation of an immune-related gene signature predictive of survival and response to immunotherapy for colorectal cancer

Colorectal cancer is a common malignant tumor with the second incidence rate and the third mortality rate worldwide. In this study, we identified and validated an immune-related gene signature, explored the clinical and molecular characteristics of the signature-defined risk groups, and assessed its ability in predicting prognosis, immune cell infiltration and immunotherapy responses. The Cancer Genome Atlas database was used as the training set while GSE39582 database as the validation set. Immune-related hub genes were selected by the Least Absolute Shrinkage and Selection Operator-penalized Cox regression model, and the signature was then constructed by the selected genes and their relevant coefficients. Prognostic performance of the signature and the signature-base nomogram models were assessed by time-dependent receiver operating characteristic curves and calibration plots in both training and validation cohorts. Clinical and mutation-related data were downloaded and analyzed to explore their associations with signature-defined risk groups. Proportions of infiltrated immune cells was estimated via CIBERSORT algorithm and immunotherapy response was evaluated by immunophenoscore and tumor immune dysfunction and exclusion scores. Seven among 790 immune-related differentially-expressed genes were selected and use to construct the signature. The signature and signature-base nomograms showed promising prognostic performance in both training and validation cohorts. Signature-defined high-risk group was associated with advanced disease, poor pathological prognostic factors and less active immune infiltration microenvironment. Besides, the response to immunotherapy of high-risk group was predicted to be poorer by immunophenoscore and tumor immune dysfunction and exclusion scores. Our signature proved its efficacy in predicting prognosis, tumor immune microenvironment and responses to immunotherapy in colorectal cancer.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2024-10-04
DOI
https://doi.org/10.1097/md.0000000000039798
Citations
1
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Construction and validation of an immune-related gene signature predictive of survival and response to immunotherapy for colorectal cancer

Zhiyong Yuan, Chen Li, Mingyang Chen, Miao Liu
1 citations
Medicine
Cancer Immunotherapy and Biomarkers
0.28
article

Construction and validation of an immune-related gene signature predictive of survival and response to immunotherapy for colorectal cancer

Zhiyong Yuan, Chen Li, Mingyang Chen, Miao Liu
article en
1 citations

Abstract

Colorectal cancer is a common malignant tumor with the second incidence rate and the third mortality rate worldwide. In this study, we identified and validated an immune-related gene signature, explored the clinical and molecular characteristics of the signature-defined risk groups, and assessed its ability in predicting prognosis, immune cell infiltration and immunotherapy responses. The Cancer Genome Atlas database was used as the training set while GSE39582 database as the validation set. Immune-related hub genes were selected by the Least Absolute Shrinkage and Selection Operator-penalized Cox regression model, and the signature was then constructed by the selected genes and their relevant coefficients. Prognostic performance of the signature and the signature-base nomogram models were assessed by time-dependent receiver operating characteristic curves and calibration plots in both training and validation cohorts. Clinical and mutation-related data were downloaded and analyzed to explore their associations with signature-defined risk groups. Proportions of infiltrated immune cells was estimated via CIBERSORT algorithm and immunotherapy response was evaluated by immunophenoscore and tumor immune dysfunction and exclusion scores. Seven among 790 immune-related differentially-expressed genes were selected and use to construct the signature. The signature and signature-base nomograms showed promising prognostic performance in both training and validation cohorts. Signature-defined high-risk group was associated with advanced disease, poor pathological prognostic factors and less active immune infiltration microenvironment. Besides, the response to immunotherapy of high-risk group was predicted to be poorer by immunophenoscore and tumor immune dysfunction and exclusion scores. Our signature proved its efficacy in predicting prognosis, tumor immune microenvironment and responses to immunotherapy in colorectal cancer.

MedicineVol. 103(40)
Tianjin University (CN), Shanxi Medical University (CN), Tianjin Medical University Cancer Institute and Hospital (CN), S.P.E.C.I.E.S. (US)
National Natural Science Foundation of China, Natural Science Foundation of Tianjin City, Tianjin Municipal Science and Technology Bureau, Natural Science Foundation for Young Scientists of Shanxi Province, Young Scientists Fund
No poverty
Openalex Percentile: Top 35%
Cancer Immunotherapy and Biomarkers
0.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.