Peng-Fei Chen1, Qing-He Li2, Li-Rong Zeng1, Xue-Ying Yang3, Pai-Lan Peng1, Jian-Hua He1, Bin Fan2. 1. Department of Gastroenterology, The Central Hospital of Enshi Autonomous Prefecture, Enshi, China. 2. Department of Hepatobiliary Surgery, The Central Hospital of Enshi Autonomous Prefecture, Enshi, China. 3. Department of Medical Records, The Central Hospital of Enshi Autonomous Prefecture, Enshi, China.
Abstract
OBJECTIVE: To develop an independent prognostic signature for patients with hepatocellular carcinoma (HCC). METHODS: HCC gene expression profile the cancer genome atlas-liver hepatocellular carcinoma and GSE14520 were used as discovery and test set, respectively. Differentially expressed genes (DEGs) were identified between HCC tissues and adjacent normal liver tissues. Univariate Cox proportional hazards regression analysis was performed to identify DEGs correlated with survival of HCC patients. A 4-gene-based signature was constructed based on a least absolute shrinkage and selection operator Cox penalized regression model. The predictive value of the signature was analyzed and validated. RESULTS: Two hundred sixty-three DEGs were identified between HCC and adjacent liver tissues. After univariate survival analysis, 90 DEGs were found to be significantly correlated with the overall survival (OS) of HCC patients, of which 4 genes (KPNA2, CDC20, SPP1, and TOP2A) with non-zero coefficient were used to construct a prognostic signature. The 4-gene signature was significantly associated with the age (P = 0.046), grade ( P = 0.022), and T stage ( P = 0.023) of HCC patients in the discovery set and it also significantly associated with TNM stage ( P = 0.033), and serum alpha-fetoprotein lever ( P = 0.034). Patients in the 4-gene low-risk group were associated with better OS and recurrence-free survival (RFS) than those in the high-risk group in the discovery and test set. Meanwhile, the 4-gene signature is an independent prognostic factor regarding OS and RFS in the discovery and test set. CONCLUSION: We developed a 4-gene-based signature, which could be a candidate prognostic factor for patients with HCC.
OBJECTIVE: To develop an independent prognostic signature for patients with hepatocellular carcinoma (HCC). METHODS: HCC gene expression profile the cancer genome atlas-liver hepatocellular carcinoma and GSE14520 were used as discovery and test set, respectively. Differentially expressed genes (DEGs) were identified between HCC tissues and adjacent normal liver tissues. Univariate Cox proportional hazards regression analysis was performed to identify DEGs correlated with survival of HCC patients. A 4-gene-based signature was constructed based on a least absolute shrinkage and selection operator Cox penalized regression model. The predictive value of the signature was analyzed and validated. RESULTS: Two hundred sixty-three DEGs were identified between HCC and adjacent liver tissues. After univariate survival analysis, 90 DEGs were found to be significantly correlated with the overall survival (OS) of HCC patients, of which 4 genes (KPNA2, CDC20, SPP1, and TOP2A) with non-zero coefficient were used to construct a prognostic signature. The 4-gene signature was significantly associated with the age (P = 0.046), grade ( P = 0.022), and T stage ( P = 0.023) of HCC patients in the discovery set and it also significantly associated with TNM stage ( P = 0.033), and serum alpha-fetoprotein lever ( P = 0.034). Patients in the 4-gene low-risk group were associated with better OS and recurrence-free survival (RFS) than those in the high-risk group in the discovery and test set. Meanwhile, the 4-gene signature is an independent prognostic factor regarding OS and RFS in the discovery and test set. CONCLUSION: We developed a 4-gene-based signature, which could be a candidate prognostic factor for patients with HCC.