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. K E Y W O R D S 4-gene-based signature, hepatocellular carcinoma, prognostic significance J Cell Biochem. 2019;120:9117-9124.wileyonlinelibrary.com/journal/jcb

The present study aimed to identify differentially expressed genes (DEGs) in colorectal cancer (CRC) and provide novel prognostic biomarkers for CRC. The microarray dataset GSE41258 was used to screen DEGs of CRC. Subsequently, a protein-protein interaction network of DEGs and Gene Ontology analysis were performed to identify hub genes and associated biological processes. Nebulette (NEBL) and complement C1q like 1 (C1QL1) were validated using reverse transcription-quantitative polymerase chain reaction in patients with CRC. Survival analysis was performed for the two hub genes. GSE41258 dataset included 182 CRC samples and 54 normal tissues. A total of 759 DEGs, including 279 upregulated and 480 downregulated were screened between both groups. NEBL and C1QL1 were identified as the two hub genes and upregulated genes involved in various biological processes, including ‘regulation of biological quality’ and ‘response to stimulus’, respectively. Additionally, the overexpression of NEBL and C1QL1 in experimental validation was consistent with the aforementioned bioinformatics analysis results. Survival analysis suggested that overexpressed NEBL in patients with CRC was associated with a positive prognosis for overall survival. In conclusion, CRC was associated with a large group of DEGs. From the upregulated genes, overexpressed NEBL in patients CRC indicated a positive prognosis for overall survival and may be used as a prognostic biomarker for patients with CRC.