Gene network analysis reveals a novel 22-gene signature of carbon metabolism in hepatocellular carcinoma.

Although much progress has been made in understanding cancer cellular metabolism adaptation, the co-regulations between genes of metabolism and cancer pathways and their interactions remain poorly characterized. Here, we applied gene co-expression network analysis to 1509 metabolic gene expression data generated from 120 HCC and 180 non-tumor human liver tissues by microarray. Our analyses reveal that metabolism genes can be classified into different co-expression modules based on their associations with HCC related traits. The co-regulation mechanism of the carbon metabolism genes in normal liver tissues was interrupted during the processes of carcinogenesis. In parallel, we performed RNAseq analysis of HCC and non-tumor human liver tissues, and identified a unique 22-carbon-metabolism-gene-signature of increased expression. This gene signature was further verified in multiple microarray data sets, and its prognostic value was also proven by HCC patients' survival data from TCGA. Additionally, the tumorigenic function of two representative genes, CS and ACSS1, were validated experimentally by cell growth and spheroid formation assays. The current study provides evidence for the reprogramming of the co-regulation network between carbon metabolism and cancer pathway genes in HCC. In addition, this study also reveals a unique 22-carbon-metabolism-gene-expression-signature in HCC. Strategies targeting these genes may represent new therapeutic approaches for HCC treatment.

Identification of speckle-type POZ protein somatic mutations in African American prostate cancer.

The speckle-type POZ protein (SPOP) is a tumor suppressor in prostate cancer (PCa). SPOP somatic mutations have been reported in up to 15% of PCa of those of European descent. However, the genetic roles of SPOP in African American (AA)-PCa are currently unknown. We sequenced the SPOP gene to identify somatic mutations in 49 AA prostate tumors and identified three missense mutations (p.Y87C, p.F102S, and p.G111E) in five AA prostate tumors (10%) and one synonymous variant (p.I106I) in one tumor. Intriguingly, all of mutations and variants clustered in exon six, and all of the mutations altered conserved amino acids. Moreover, two mutations (p.F102S and p.G111E) have only been identified in AA-PCa to date. Quantitative real-time polymerase chain reaction analysis showed a lower level of SPOP expression in tumors carrying SPOP mutations than their matched normal prostate tissues. In addition, SPOP mutations and novel variants were detected in 5 of 27 aggressive PCa and one of 22 less aggressive PCa (P < 0.05). Further studies with increased sample size are needed to validate the clinicopathological significance of these SPOP mutations in AA-PCa.