Abstract | OBJECTIVE: 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.
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Authors | Ping Han, Xiudeng Yang, Lina Li, Jie Bao, Wenqiong Zhang, Shubei Zai, Zhaoqin Zhu, Minle Wu |
Journal | Japanese journal of clinical oncology
(Jpn J Clin Oncol)
Vol. 52
Issue 11
Pg. 1327-1336
(Nov 03 2022)
ISSN: 1465-3621 [Electronic] England |
PMID | 35848857
(Publication Type: Multicenter Study, Journal Article)
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Copyright | © The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected]. |
Chemical References |
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Topics |
- Humans
- Cohort Studies
- Gene Expression Regulation, Neoplastic
- Prognosis
- Nomograms
- Colorectal Neoplasms
(genetics)
- Biomarkers, Tumor
(genetics, metabolism)
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