A novel five-gene signature for predicting prognosis in liver cancer

Abstract

Purpose Liver cancer is one of the most common malignant tumors in China, ranked 5th among the malignant common tumors in the world, which is still difficult to diagnose early and treat effectively. Therefore, exploring some indicators for prognostic prediction is imperative in the treatment of liver cancer. Methods Liver cancer data was obtained from The Cancer Genome Atlas (TCGA). We obtained differentially expressed genes (DEGs) by R software from TCGA database. Risk scores were acquired to assess the weighted gene-expression levels by Cox regression analysis and predict the prognosis of patients with liver cancer. Using the KEGG and GO databases, pathway enrichment was performed by identifying the analysis of DEGs. The display of receiver-operating characteristic (ROC) curves and area under the curve (AUC) could show the validity and the prognostic value of this model in liver cancer. Results In total, 1897 DEGs of transcriptome genes in liver cancer and 1197 DEGs of clinical data were extracted from the TCGA database. We identified a novel five-gene signature associated with liver cancer, including CDCA8, NR0B1, GAGE2A, AC018641.1, and SPANXC. Among of them, CDCA8 and NR0B1 were negatively related to 5-year OS, displaying a worse prognosis (P < 0.05). In particular, we also found that GAGE2A is related to lymphatic metastasis from the clinical data analysis in liver cancer. Receiver-operating characteristic (ROC) curve assessed the accuracy and sensitivity of the gene signature. In the heat map, each of the five genes for patients was presented with the distribution of the risk score. Conclusions We figured out a novel five-gene signature for the prognosis of patients with liver cancer, which may be an effective predictor for patients’ prognosis in the future.

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