Identification of cellular genes showing differential expression associated with hepatitis B virus infection

AIM: To investigate the impact of hepatitis B virus (HBV) infection on cellular gene expression, by conducting both in vitro and in vivo studies. METHODS: Knockdown of HBV was targeted by stable expression of short hairpin RNA (shRNA) in huH-1 cells. Cellular gene expression was compared using a human 30K cDNA microarray in the cells and quantified by real-time reverse transcription-polymerase chain reaction (RT-PCR) (qRT-PCR) in the cells, hepatocellular carcinoma (HCC) and surrounding non-cancerous liver tissues (SL). RESULTS: The expressions of HBsAg and HBx protein were markedly suppressed in the cells and in HBx transgenic mouse liver, respectively, after introduction of shRNA. Of the 30K genes studied, 135 and 103 genes were identified as being down- and up-regulated, respectively, by at least twofold in the knockdown cells. Functional annotation revealed that 85 and 62 genes were classified into four up-regulated and five down-regulated functional categories, respectively. When gene expression levels were compared between HCC and SL, eight candidate genes that were confirmed to be up- or down-regulated in the knockdown cells by both microarray and qRT-PCR analyses were not expressed as expected from HBV reduction in HCC, but had similar expression patterns in HBV- and hepatitis C virus-associated cases. In contrast, among the eight genes, only APM2 was constantly repressed in HBV non-associated tissues irrespective of HCC or SL. CONCLUSION: The signature of cellular gene expression should provide new information regarding the pathophysiological mechanisms of persistent hepatitis and hepatocarcinogenesis that are associated with HBV infection.

Challenges of incorporating gene expression data to predict HCC prognosis in the age of systems biology

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide.The recurrence of HCC after curative treatments is currently a major hurdle.Identification of subsets of patients with distinct prognosis provides an opportunity to tailor therapeutic approaches as well as to select the patients with specific sub-phenotypes for targeted therapy.Thus,the development of gene expression profiles to improve the prediction of HCC prognosis is important for HCC management.Although several gene signatures have been evaluated for the prediction of HCC prognosis,there is no consensus on the predictive power of these signatures.Using systematic approaches to evaluate these signatures and combine them with clinicopathologic information may provide more accurate prediction of HCC prognosis.Recently,Villanueva et al developed a composite prognostic model incorporating gene expression patterns in both tumor and adjacent tissues to predict HCC recurrence.In this commentary,we summarize the current progress in using gene signatures to predict HCC prognosis,and discuss the importance,existing issues and future research directions in this field.

Identification of a TSPY co-expression network associated with DNA hypomethylation and tumor gene expression in somatic cancers

Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.

Malignant field expression signatures in biopsy samples at diagnosis predict the likelihood of lethal disease in patients with localized prostate cancer

Aim:Overtreatment of early-stage low-risk prostate cancer patients represents a significant problem in disease management and has significant socio-economic implications.Changes in prostate cancer screening and treatment practices in the United States have been associated with the recent decline in overall incidence and concomitant significant increase of the annual incidence of metastatic prostate cancer has been documented.Therefore,development of genetic and molecular markers of clinically significant disease in patients diagnosed with low grade localized prostate cancer would have a major impact in disease management.Methods:Identification of gene expression signatures(GES)associated with lethal prostate cancer has been performed using microarray analyses of biopsy specimens obtained at the time of diagnosis from 281 patients with Gleason 6(G6)and G7 tumors in a Swedish watchful waiting cohort with up to 30 years follow-up.The performance of GES has been validated in independent cohort of 568 prostate cancer patients of the Cancer Genome Anatomy Project Prostate Cancer database.Results:GES c omprising 98 genes identified 89%and 100%of all death events 4 years after diagnosis in G7 and G6 patients,respectively.At 6 years follow-up,83%and 100%of all deaths events were captured in G7 and G6 patients,respectively.Remarkably,the 98-gene signature appears to perform successfully in patients stratification with as little as 2%of cancer cells in a specimen,strongly indicating that it captures a malignant field effect in human prostates harboring cancer cells of different degrees of aggressiveness.In G6 and G7 tumors from prostate cancer patients of age 65 or younger,GES identified 86%of all death events during the entire follow-up period.In G6 and G7 tumors from prostate cancer patients of age 70 or younger,GES identified 90%of all death events 6 years after diagnosis.Conclusion:Classification performance of the reported in this study 98-genes GES of lethal prostate cancer appeared suitable to meet design and feasibility requirements of a prospective 4 to 6 years clinical trial,which is essential for regulatory approval of diagnostic and prognostic tests in clinical setting.Prospectively validated GES of lethal PC in biopsy specimens of G6 and G7 tumors will help physicians to identify,at the time of diagnosis,patients who should be considered for exclusion from active surveillance programs and who would most likely benefit from immediate curative interventions.