J Cancer 2020; 11(20):5918-5928. doi:10.7150/jca.46328

Research Paper

Development and validation of a DNA repair gene signature for prognosis prediction in Colon Cancer

Xin Wang1,2,3*, Cong Tan1,2,3*, Min Ye1,2,3*, Xu Wang1,2,3, Weiwei Weng1,2,3, Meng Zhang1,2,3, Shujuan Ni1,2,3, Lei Wang1,2,3, Dan Huang1,2,3, Zhaohui Huang4, Midie Xu1,2,3✉, Weiqi Sheng1,2,3✉

1. Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
2. Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
3. Institute of Pathology, Fudan University, Shanghai 200032, China.
4. Wuxi Cancer Institute, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, China.
*These authors contributed equally to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Wang X, Tan C, Ye M, Wang X, Weng W, Zhang M, Ni S, Wang L, Huang D, Huang Z, Xu M, Sheng W. Development and validation of a DNA repair gene signature for prognosis prediction in Colon Cancer. J Cancer 2020; 11(20):5918-5928. doi:10.7150/jca.46328. Available from https://www.jcancer.org/v11p5918.htm

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Aberrant expression of DNA repair genes (DRGs) can be related to tumor progression and clinical outcomes in colon cancer. Here, we aimed to establish a DRGs signature to identify the vital prognostic DRGs in colon cancer. Firstly, gene set enrichment analysis (GSEA) was performed to demonstrate the association between abnormal expression level of DRGs and tumorigenesis. Then, a total of 476 DRGs were obtained for detecting candidate biomarkers in randomly selected 295 cases from The Cancer Genome Atlas (TCGA) colon cancer cohort. Eleven genes were screened by LASSO Cox regression analyses to develop the prognostic model. Then, the prognostic model and the expression levels of the eleven genes were validated using the internal validation dataset (the rest 125 cases in TCGA cohort) and an external validation dataset (obtained from Gene Expression Omnibus dataset). Further analysis revealed the independent prognostic capacity of the prognostic model in relation to other clinical characteristics. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Furthermore, we provided a nomogram for interpreting the clinical application of the 11-DRG signature. In conclusion, we propose a newly developed 11-DRG signature as a practical prognostic predictor for patients with colon cancer, which can facilitate the individualized counselling and treatment.

Keywords: colon cancer, DNA repair, prognosis, TCGA, GEO