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Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world. There is an urgent need to understand the molecular background of HCC to facilitate the identification of biomarkers and discover effective therapeutic targets. Published transcriptomic studies have reported a large number of genes that are individually significant for HCC. However, reliable biomarkers remain to be determined. In this study, built on max-linear competing risk factor models, we developed a machine learning analytical framework to analyze transcriptomic data to identify the most miniature set of differentially expressed genes (DEGs). By analyzing 9 public whole-transcriptome datasets (containing 1184 HCC samples and 672 nontumor controls), we identified 5 critical differentially expressed genes (DEGs) (ie, CCDC107, CXCL12, GIGYF1, GMNN, and IFFO1) between HCC and control samples. The classifiers built on these 5 DEGs reached nearly perfect performance in identification of HCC. The performance of the 5 DEGs was further validated in a US Caucasian cohort that we collected (containing 17 HCC with paired nontumor tissue). The conceptual advance of our work lies in modeling gene-gene interactions and correcting batch effect in the analytic framework. The classifiers built on the 5 DEGs demonstrated clear signature patterns for HCC. The results are interpretable, robust, and reproducible across diverse cohorts/populations with various disease etiologies, indicating the 5 DEGs are intrinsic variables that can describe the overall features of HCC at the genomic level. The analytical framework applied in this study may pave a new way for improving transcriptome profiling analysis of human cancers. [ABSTRACT FROM AUTHOR]

Cyclin-dependent kinase regulatory subunit 2 (CKS2) is a member of the cell cycle-dependent protein kinase subunit family, which is implicated as an oncogene in various malignancies. However, the clinical significance, oncogenic functions, and related mechanisms of CKS2 in hepatocellular carcinoma (HCC) remain largely unclear. In the present study, expression features and prognostic value of CKS2 were evaluated in the bioinformatic databases and HCC tissues. The effects of CKS2 on the malignant phenotypes of HCC cells were explored in vitro. According to the analyses of three bioinformatic databases, mRNA levels of CKS2 were elevated in HCC tissues compared with the normal tissues. Immunohistochemical assays found that high CKS2 expression was closely associated with liver cirrhosis (P=0.019), poor differentiation (P=0.02), portal vein invasion (P<0.001), TNM stage (P=0.019), tumor metastasis (P=0.008), and recurrence (P=0.003). The multivariate regression analyses suggested that CKS2 was an independent prognostic factor for overall survival (HR=2.088, P=0.014) and disease-free survival (HR=2.511, P=0.002) of HCC patients. Moreover, the bioinformatic analyses indicated that CKS2 might be associated with the malignant phenotypes in HCC progression. In addition, in vitro assays showed that CKS2 expression was higher in HCC cell lines than in normal liver cells. Knockdown of CKS2 remarkably repressed the proliferation, colony formation (P=0.0003), chemoresistance, migration (P=0.0047), and invasion (P=0.0012) of HCC cells. Taken together, overexpression of CKS2 was significantly correlated with poor prognosis of HCC patients and the malignant phenotypes of HCC cells, suggesting that it was a novel prognostic biomarker and potential target of HCC. [ABSTRACT FROM AUTHOR]

DEP domain containing 1 (DEPDC1) protein is a novel oncoantigen upregulated in multiple types of cancers which present oncogenic activity and high immunogenicity. However, the function and therapeutic potential of DEPDC1 in hepatocellular carcinoma (HCC) remain unclear. In the present study, we showed that DEPDC1 was frequently upregulated in HCC and associated with cancer diagnosis and poor prognosis for HCC patients. Moreover, DEPDC1 promotes HCC cell proliferation in vitro as well as carcinogenesis in vivo. Notably, DEPDC1 overexpression also increases the neoplasm metastasis ability of HCC cells both in vivo and in vitro. Gene set enrichment analysis results showed that DEPDC1 expression is positively correlated with K‐RAS signal pathway, pathways in cancer and WNT/β‐catenin signal pathway, all of which are closely associated with specific cancer‐related gene sets. Our study provides the basis for further investigation of the molecular mechanism by which DEPDC1 promotes the development and metastasis of HCC. High expression level of DEPDC1 in HCC promotes tumor cell proliferation and metastasis and can serve as a biomarker for HCC diagnosis and prognostic evaluation. [ABSTRACT FROM AUTHOR]