A Novel Five-Gene Signature for Prognosis Prediction in Hepatocellular Carcinoma - Su, Lisa; Zhang, Genhao; Kong, Xiangdong (Frontiers in Oncology, 2021)
Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In the present study, we aimed to identify an effective prognostic marker to stratify HCC patients and predict the prognosis of HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify DEGs between tumor and nontumor samples in HCC patients and a total of 37 DEGs (5 upregulated and 32 downregulated) were identified as common DEGs. Next, we systematically explored the relationship between the expression of 37 common DEGs in tumor tissues and overall survival (OS) rate of HCC patients in TCGA-LIHC dataset and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the prognostic value of the signature was validated in ICGC and another independent clinical samples cohort of 59 frozen tumor samples with qRT-PCR data, and the results demonstrated that the signature had a good performance in predicting the OS rate of HCC patients. What is more, the signature was an independent risk factor for HCC patients when considering other clinical factors in the three cohorts. Finally, we found the signature was significantly associated with HCC immune microenvironment. In conclusion, the prognostic five-gene signature identified in our present study could efficiently classify HCC patients into subgroups with high and low risk of shorter OS time and help clinicians make decisions for individualized treatment.