Abstract
Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes. In this study, our purpose was to explore an effective prognostic marker for HCC. Five cohort profile datasets from GEO (GSE25097, GSE36376, GSE62232, GSE76427 and GSE101685) were integrated with TCGA-LIHC and GTEx dataset to identify differentially expressed genes (DEGs) between normal and cancer tissues in HCC patients, then 5 upregulated differentially expressed genes and 32 downregulated DEGs were identified as common DEGs in total. 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 and constructed a novel prognostic model composed of five genes (AURKA, PZP, RACGAP1, ACOT12 and LCAT). Furthermore, the predicted performance of the five-gene signature was verified in ICGC and another independent clinical samples cohort, and the results demonstrated that the signature performed well in predicting the OS rate of patients with HCC. What is more, the signature was an independent hazard 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 patients with HCC into subgroups with low and high risk of longer overall survival time and help clinicians make decisions for individualized treatment.
Highlights
Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes [1]
Statistically significant variables obtained from univariable Cox regression analysis were input into multivariate Cox regression analysis, and the results revealed that HBV infection, risk score, NASH and recurrence were statistically relevant to overall survival (OS) of HCC patients, while the risk score (HR = 4.663, 95%CI 1.716-21.387, P = 0.047) was only independent prognostic factors (Figure 7D)
The TNM staging system and the prognostic scoring systems of American Joint Committee on Cancer are implemented to assess the prognosis of HCC patients, in current predictive methods each system cannot always be effective in predicting the prognosis according to the losing sight of different genetic and epigenetic backdrops of tumors [20]
Summary
Hepatocellular carcinoma (HCC) has been a global health issue and attracted wide attention due to its high incidence and poor outcomes [1]. It is reported that HCC results in nearly 850,000 new cases and more than 600,000 death every year [2], which seriously increases the disease burden in the worldwide. Signature for Prediction in Hepatocellular Carcinoma checkpoint inhibitors, HCC patients could access potential treatment strategies at early and intermediate stages of HCC prognosis [10]. Over half of HCC patients are in advanced stage when diagnosed, only 15% of which are suitable for curative therapies, and the five-year survival rate remains very low, no more than 20%, according to lacking of biomarkers for diagnosis at early stage and the high frequency of recurrence [11, 12]. It is necessary for us to seek novel prognostic markers for improving the poor outcomes of HCC patients
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