Identification and validation of a metabolism-related gene signature for the prognosis of colorectal cancer: a multicenter cohort study

Author:

Han Ping1,Yang Xiudeng2,Li Lina3,Bao Jie4,Zhang Wenqiong5,Zai Shubei5,Zhu Zhaoqin5,Wu Minle5ORCID

Affiliation:

1. Department of Pharmacy , Shanghai Public Health Clinical Center, Fudan University, Shanghai, China

2. Department of Laboratory Medicine , The First Affiliated Hospital of Shaoyang University, Shaoyang, China

3. Pediatric Department , Shanghai Public Health Clinical Center, Fudan University, Shanghai, China

4. Department of Pharmacy , Anhui Provincial Corps Hospital of Chinese People's Armed Police Forces, Hefei, China

5. Department of Laboratory Medicine , Shanghai Public Health Clinical Center, Fudan University, Shanghai, China

Abstract

Abstract Objective Cell metabolism plays a vital role in the proliferation, metastasis and sensitivity to chemotherapy drugs of colorectal cancer. The purpose of this multicenter cohort study is to investigate the potential genes indicating clinical outcomes in colorectal cancer patients. Methods We analyzed gene expression profiles of colorectal cancer to identify differentially expressed genes then used these differentially expressed genes to construct prognostic signature based on the least absolute shrink-age and selection operator Cox regression model. In addition, the multi-gene signature was validated in independent datasets including our multicenter cohort. Finally, nomograms were set up to evaluate the prognosis of colorectal cancer patients. Results Seventeen metabolism-related genes were determined in the least absolute shrink-age and selection operator model to construct signature, with area under receiver operating characteristic curve for relapse-free survival, 0.741, 0.755 and 0.732 at 1, 3 and 5 year, respectively. External validation datasets, GSE14333, GSE37892, GSE17538 and the Cancer Genome Atlas cohorts, were analyzed and stratified, indicating that the metabolism-related signature was reliable in discriminating high- and low-risk colorectal cancer patients. Area under receiver operating characteristic curves for relapse-free survival in our multicenter validation cohort were 0.801, 0.819 and 0.857 at 1, 3 and 5 year, respectively. Nomograms incorporating the genetic biomarkers and clinical pathological features were set up, which yielded good discrimination and calibration in the prediction of prognosis for colorectal cancer patients. Conclusion An original metabolism-related signature was developed as a predictive model for the prognosis of colorectal cancer patients. A nomogram based on the signature was advantageous to facilitate personalized counselling and treatment of colorectal cancer patients.

Funder

Shanghai Science and Technology Development Foundation

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology,General Medicine

Reference38 articles.

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