Leptin Receptor Somatic Mutations Are Frequent in HCV-Infected Cirrhotic Liver and Associated With Hepatocellular Carcinoma
ABSTRACT Hepatocellular carcinoma (HCC) develops in patients with chronic hepatitis or cirrhosis via a stepwise accumulation of various genetic alterations. To explore the genetic basis of HCC development in hepatitis C virus (HCV)-associated chronic liver disease, we evaluated genetic variants that accumulate in non-tumor cirrhotic liver.
We determined the whole-exome sequences of 7 tumors and background cirrhotic liver tissues from 4 patients with HCV infection. We then performed additional sequencing of selected exomes of mutated genes, identified by whole-exome sequencing, and of representative tumor-related genes on samples from 22 cirrhotic livers with HCV infection. We performed in vitro and in vivo functional studies for 1 of the mutated genes.
Whole-exome sequencing demonstrated that somatic mutations accumulated in various genes in HCV-infected cirrhotic liver tissues. Among the identified genes, the leptin receptor gene (LEPR) was one of the most frequently mutated in tumor and non-tumor cirrhotic liver tissue. Selected exome sequencing analyses detected LEPR mutations in 12 of 22 (54.5%) non-tumorous cirrhotic livers. In vitro, 4 of 7 (57.1%) LEPR mutations found in cirrhotic livers reduced phosphorylation of signal transducer and activator of transcription 3 to inactivate LEPR-mediated signaling. Moreover, 40% of Lepr-deficient (C57BL/KsJ-db/db) mice developed liver tumors following administration of thioacetamide, compared with none of the control mice.
Based on analysis of liver tissues samples from patients, somatic mutations accumulate in LEPR in cirrhotic liver with chronic HCV infection. These mutations could disrupt LEPR signaling and increase susceptibility to hepatocarcinogenesis.
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ABSTRACT: Recent advances in sequencing technology have allowed us to profile genome-wide mutations of various cancer types, revealing huge heterogeneity of cancer genome variations. However, its heterogeneous landscape of somatic mutations according to liver cancer progression is not fully understood. Here, we profiled the mutations and gene expressions of early and advanced hepatocellular carcinoma (HCC) related with Hepatitis B-viral infection. Integrative analysis was performed with whole-exome sequencing and gene expression profiles of the 12 cases of early and advanced HCCs and paired non-tumoral adjacent liver tissues. A total of 293 tumor-specific somatic variants and 202 non-tumoral variants were identified. The tumor-specific variants were found to be enriched at chromosome 1q particularly in the advanced HCC, compared to the non-tumoral variants. Functional enrichment analysis revealed frequent mutations at the genes encoding cytoskeleton organization, cell adhesion, and cell cycle-related genes. In addition, to elucidate actionable somatic mutations, we performed an integrative analysis of gene mutations and gene expression profiles together. This revealed the 48 mutated genes which were differentially mutated with concomitant gene expression enrichment. Of these, CTNNB1 was found to have a pivotal role in the differential progression of the HCC subgroup. In conclusion, our integrative analysis of whole-exome sequencing and transcriptome profiles could provide actionable mutations which might play pivotal roles in the heterogeneous progression of HCC.PLoS ONE 12/2014; 9(12):e115152. DOI:10.1371/journal.pone.0115152 · 3.53 Impact Factor
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ABSTRACT: Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.PLoS ONE 07/2014; 9(7):e100854. DOI:10.1371/journal.pone.0100854 · 3.53 Impact Factor