Prognostic genes of hepatocellular carcinoma based on gene coexpression network analysis

Abstract

Hepatocellular carcinoma (HCC) is the most common subtype in liver cancer whose prognosis is affected by malignant progression associated with complex gene interactions. However, there is currently no available biomarkers associated with HCC progression in clinical application. In our study, RNA sequencing expression data of 50 normal samples and 374 tumor samples was analyzed and 9225 differentially expressed genes were screened. Weighted gene coexpression network analysis was then conducted and the blue module we were interested was identified by calculating the correlations between 17 gene modules and clinical features. In the blue module, the calculation of topological overlap was applied to select the top 30 genes and these 30 genes were divided into the green group (11 genes) and the yellow group (19 genes) through searching whether these genes were validated by in vitro or in vivo experiments. The genes in the green group which had never been validated by any experiments were recognized as hub genes. These hub genes were subsequently validated by a new data set GSE76427 and KM Plotter Online Tool, and the results indicated that 10 genes (FBXO43, ARHGEF39, MXD3, VIPR1, DNASE1L3, PHLDA1, CSRNP1, ADR2B, C1RL, and CDC37L1) could act as prognosis and progression biomarkers of HCC. In summary, 10 genes who have never been mentioned in HCC were identified to be associated with malignant progression and prognosis of patients. These findings may contribute to the improvement of the therapeutic decision, risk stratification, and prognosis prediction for HCC patients. K E Y W O R D S biomarker, hepatocellular carcinoma, malignant progression, weighted gene coexpression network analysis

Immunological and clinicopathological characteristics of C1RL in 2120 glioma patients

“…C1RL had not been mentioned in cancer until a report indicating signi cant associations of non-Hodgkin lymphoma and diffuse large B-cell lymphoma with the C1RL gene in 2012 [15]. In recent years, C1RL has been reported to be a prognostic biomarker in hepatocellular carcinoma [13] and renal cell cancer [14]. Our results showed evidence that C1RL is highly expressed in glioma samples and predicts a poor prognosis.…”

“…Complement C1r subcomponent like (C1RL) was found to be a prognostic marker in hepatocellular carcinoma [13] and renal cell cancer [14]. A gene-based analysis showed signi cant associations between non-Hodgkin lymphoma or diffuse large B-cell lymphoma and the C1RL gene [15].…”

A Key mRNA-miRNA-lncRNA Competing Endogenous RNA Triple Sub-network Linked to Diagnosis and Prognosis of Hepatocellular Carcinoma

“…Therefore, we tried to establish a prognosis/diagnosis-associated mRNA-miRNA-lncRNA ceRNA triple sub-network in hepatocellular carcinoma. By performing survival (OS and RFS) analysis using TCGA hepatocellular carcinoma data, nine genes including three novel genes (CELSR3, GPSM2 and CHEK1) and six "known" genes [CLEC3B (26), DNASE1L3 (27), PTTG1 (28,29), KIF2C (30), XPO5 (31,32) and UBE2S (33,34)] were identified as prognosisassociated genes in hepatocellular carcinoma. The prognostic values of the three novel genes in hepatocellular carcinoma have not been investigated so far.…”

“…By intersecting OS-associated genes and RFSassociated genes, 9 genes (CLEC3B, DNASE1L3, PTTG1, CELSR3, GPSM2, KIF2C, XPO5, UBE2S, and CHEK1) were defined as candidate genes, which were commonly appeared in OS-associated gene set and RFS-associated gene set ( Figure 1A). After reviewing the published literatures and previous studies, we found that 6 of 9 genes [CLEC3B (26), DNASE1L3 (27), PTTG1 (28,29), KIF2C (30), XPO5 (31,32), and UBE2S (33,34)] have been demonstrated to act as promising prognostic biomarkers for hepatocellular carcinoma. The rest three genes (CELSR3, GPSM2, and CHEK1) have not been studied for their prognostic values in hepatocellular carcinoma so far.…”

Computational Inference of Gene Co-Expression Networks for the identification of Lung Carcinoma Biomarkers: An Ensemble Approach

“…Finally, in Xu et al [29] (2019), Xu et al study Hepatocellular carcinoma, a very common subtype of liver cancer. The authors conducted a WGCNA to identify complex gene interactions that affect prognosis.…”