Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer

• Published in: Pathology oncology research 2021-03, Vol.27, p.596899-596899
• Main Authors: Wang, Lin, Li, Xueping, Zhao, Lan, Jiang, Longyang, Song, Xinyue, Qi, Aoshuang, Chen, Ting, Ju, Mingyi, Hu, Baohui, Wei, Minjie, He, Miao, Zhao, Lin
• Format: Article
• Language: English
• Subjects: Apoptosis; Biomarkers; Biomarkers, Tumor - genetics; Chemotherapy; Computational Biology - methods; Data mining; Datasets; DNA damage; DNA repair; DNA Repair Enzymes - genetics; Epigenetics; Esophageal cancer; Esophageal Neoplasms - genetics; Esophageal Neoplasms - pathology; Esophageal Squamous Cell Carcinoma - genetics; Esophageal Squamous Cell Carcinoma - pathology; Female; Follow-Up Studies; Gene expression; Gene Expression Regulation, Neoplastic; Genomes; Genomics; Humans; Inhibitor drugs; Male; Medical prognosis; Medical research; Metastasis; Middle Aged; Patients; Prognosis; Proteins; Society Journal Archive; Statistical analysis; Survival analysis; Survival Rate; Targeted cancer therapy; Transcriptome; Tumors
• ISSN: 1532-2807; 1219-4956; 1532-2807
• DOI: 10.3389/pore.2021.596899

Esophageal cancer (ESCA) is a leading cause of cancer-related mortality, with poor prognosis worldwide. DNA damage repair is one of the hallmarks of cancer. Loss of genomic integrity owing to inactivation of DNA repair genes can increase the risk of cancer progression and lead to poor prognosis. We aimed to identify a novel gene signature related to DNA repair to predict the prognosis of ESCA patients. Based on gene expression profiles of ESCA patients from The Cancer Genome Atlas and gene set enrichment analysis, 102 genes related to DNA repair were identified as candidates. After stepwise Cox regression analysis, we established a five-gene prognostic model comprising DGCR8, POM121, TAF9, UPF3B, and BCAP31. Kaplan-Meier survival analysis confirmed a strong correlation between the prognostic model and survival. Moreover, we verified the clinical value of the prognostic signature under the influence of different clinical parameters. We found that small-molecule drugs (trametinib, selumetinib, and refametinib) could help to improve patient survival. In summary, our study provides a novel and promising prognostic signature based on DNA-repair-related genes to predict survival of patients with ESCA. Systematic data mining provides a theoretical basis for further exploring the molecular pathogenesis of ESCA and identifying therapeutic targets.