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Genomic and Epigenomic Heterogeneity of Hepatocellular Carcinoma.

ABSTRACT: Understanding the intratumoral heterogeneity of hepatocellular carcinoma is instructive for developing personalized therapy and identifying molecular biomarkers. Here we applied whole-exome sequencing to 69 samples from 11 patients to resolve the genetic architecture of subclonal diversification. Spatial genomic diversity was found in all 11 hepatocellular carcinoma cases, with 29% of driver mutations being heterogeneous, including TERT, ARID1A, NOTCH2, and STAG2. Similar with other cancer types, TP53 mutations were always shared between all tumor regions, that is, located on the "trunk" of the evolutionary tree. In addition, we found that variants within several drug targets such as KIT, SYK, and PIK3CA were mutated in a fully clonal manner, indicating their therapeutic potentials for hepatocellular carcinoma. Temporal dissection of mutational signatures suggested that mutagenic processes associated with exposure to aristolochic acid and aflatoxin might play a more important role in early, as opposed to late, stages of hepatocellular carcinoma development. Moreover, we observed extensive intratumoral epigenetic heterogeneity in hepatocellular carcinoma based on multiple independent analytical methods and showed that intratumoral methylation heterogeneity might play important roles in the biology of hepatocellular carcinoma cells. Our results also demonstrated prominent heterogeneity of intratumoral methylation even in a stable hepatocellular carcinoma genome. Together, these findings highlight widespread intratumoral heterogeneity at both the genomic and epigenomic levels in hepatocellular carcinoma and provide an important molecular foundation for better understanding the pathogenesis of this malignancy. Cancer Res; 77(9); 2255-65. ©2017 AACR.

SUBMITTER: Lin DC

PROVIDER: S-EPMC5413372 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Genomic and Epigenomic Heterogeneity of Hepatocellular Carcinoma.

Lin De-Chen DC Mayakonda Anand A Dinh Huy Q HQ Huang Pinbo P Lin Lehang L Liu Xiaoping X Ding Ling-Wen LW Wang Jie J Berman Benjamin P BP Song Er-Wei EW Yin Dong D Koeffler H Phillip HP

Cancer research 20170220 9

Understanding the intratumoral heterogeneity of hepatocellular carcinoma is instructive for developing personalized therapy and identifying molecular biomarkers. Here we applied whole-exome sequencing to 69 samples from 11 patients to resolve the genetic architecture of subclonal diversification. Spatial genomic diversity was found in all 11 hepatocellular carcinoma cases, with 29% of driver mutations being heterogeneous, including TERT, ARID1A, NOTCH2, and STAG2. Similar with other cancer types ...[more]

PMID: 28302680

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Project description:BackgroundHepatocellular carcinoma (HCC) often presents with multiple nodules within the liver, with limited effective interventions. The high genetic heterogeneity of HCC might be the major cause of treatment failure. We aimed to characterize genomic heterogeneity, infer clonal evolution, investigate RNA expression pattern and explore tumour immune microenvironment profile of multifocal HCC.Patients and methodsWhole-exome sequencing and RNA sequencing were carried out in 34 tumours and 6 adjacent normal liver tissue samples from 6 multifocal HCC patients. Protein expression of Ki67, AFP, P53, Survivin and CD8 was detected by immunohistochemistry. Fluorescence in situ hybridization was carried out to validate the amplification status of sorafenib-targeted genes.ResultsWe deciphered genomic and transcriptional heterogeneity among tumours in each multifocal HCC patient including mutational profiles, copy number alterations, tumour evolutionary trajectory and tumour immune microenvironment profiles. Of note, sorafenib-targeted alterations were identified in the trunk of phylogenetic tree in only one out of the six patients, which may explain the relative low treatment response rate to sorafenib in clinical practice. Moreover, we demonstrated RNA expression patterns and tumour immune microenvironment profiles of all nodules. We found that RNA expression pattern was associated with Edmondson-Steiner grading. Based on the differential expression of 66 reported immune markers, unsupervised hierarchical clustering analysis of 34 nodules identified immune subsets: one low expression cluster with seven nodules and one high expression cluster with 11 nodules. CD8+ T cells were more enriched in nodules of the high expression cluster.ConclusionsOur study provided a detailed view of genomic and transcriptional heterogeneity, clonal evolution and immune infiltration of multifocal HCC. The heterogeneity of druggable targets and immune landscape might help interpret the clinical responsiveness to targeted drugs and immunotherapy for multifocal HCC patients.

Project description:Genome-wide DNA copy number profiles of multiple hepatocellular carcinoma tumors and non-tumor liver tissues from the same patients. Introduction: Hepatocellular Carcinoma (HCC) is the second cause of cancer-related death worldwide. Understanding tumor heterogeneity is relevant for the pathogenesis and treatment of this neoplasm. Particularly, whether multinodular tumors result from intrahepatic metastasis (IM or clonal tumors) or de novo cancers (synchronic tumors) have direct implications in treatment decisionmaking for resection and transplantation. We aimed to assess the genomic heterogeneity of multifocal HCC using single-nucleotide polymorphism (SNP) and gene expression analyses. Methods: Among 544 HCC patients consecutively transplanted at Mount Sinai Hospital between 1990- 2007, we selected 18 patients with a total of 42 multinodular tumors (2-3 non-satellite foci HCCs) for this molecular study. Formalin-fixed blocks were collected for each tumor along with corresponding clinico-pathological data. SNP array and gene expression profiling was generated. Clonality was defined by measuring the similarity of genome-wide copy number variation (CNV) profiles between two nodules. Unsupervised hierarchical clustering based on gene expression data was performed to measure genetic proximity between each tumor. Prediction of previously published signatures was performed using Nearest Template Prediction (NTP). Association of clonality with clinic-pathological parameters was assessed. Results: A total of 42 tumors have been analyzed (10 patients- 2 tumors; 8- 3 tumors). Most patients were male (17/18, 95%) with median age of 53-yr-old (range 39–67), HCV (10/18, 56%) or HBV infection (6/18, 33%). Median tumor size was 3 cm (range 1.5-6.5), satellites were present in 3 (17%) and vascular invasion in 11 patients (61%), respectively. CNV profiles predicted clonal tumors in 38% (6/16) and non-clonality in 62% of cases (10/16). CNV profiles of the remaining 2 cases were not informative. Clonal tumors were significantly associated with HCV infected patients (5/6 vs 3/10, p=0.007), whereas all HBV-induced HCC were synchronic tumors (0/6 vs 6/10, p=0.03). Furthermore, clonal tumors were significantly associated with presence of satellites and shorter time-torecurrence. Assessment of genetic proximity based on gene expression revealed that each clonal tumor showed proximity to its paired tumor and clustered around the same node (6/6,100%) as opposed to non-clonal (2/9,22%). When exploring molecular subclasses within clonal tumors (intrahepatic metastases), while half of them retained the molecular fingerprint, the other half switch to more aggressive subclasses. Conversely, all non-clonal tumors within the same patient belonged to distinct molecular subclasses. Conclusion: Multinodular HCCs undergoing transplantation are molecularly heterogeneous. Using CNV profiling we identified clonal multinodular tumors (true intrahepatic metastasis) in 40% of cases and de novo tumors in 60%. Clonal tumors were significantly associated with HCV infection, satellites and recurrence. Genetic proximity was observed in clonal tumors, but molecular subclasses prediction revealed that intrahepatic metastases share more aggressive subclasses in half of cases.

Project description:Understanding the heterogeneity of dysregulated pathways associated with the development of hepatocellular carcinoma (HCC) may provide prognostic and therapeutic avenues for disease management. As HCC involves a complex process of genetic and epigenetic modifications, we evaluated expression of both polyadenylated transcripts and microRNAs from HCC and liver samples derived from two cohorts of patients undergoing either partial hepatic resection or liver transplantation. Copy number variants were inferred from whole genome low-pass sequencing data, and a set of 56 cancer-related genes were screened using an oncology panel assay. HCC was associated with marked transcriptional deregulation of hundreds of protein-coding genes. In the partially resected livers, diminished transcriptional activity was observed in genes associated with drug catabolism and increased expression in genes related to inflammatory responses and cell proliferation. Moreover, several long noncoding RNAs and microRNAs not previously linked with HCC were found to be deregulated. In liver transplant recipients, down-regulation of genes involved in energy production and up-regulation of genes associated with glycolysis were detected. Numerous copy number variants events were observed, with hotspots on chromosomes 1 and 17. Amplifications were more common than deletions and spanned regions containing genes potentially involved in tumorigenesis. Colony stimulating factor 1 receptor (CSF1R), fibroblast growth factor receptor 3 (FGFR3), fms-like tyrosine kinase 3 (FLT3), nucleolar phosphoprotein B23 (NPM1), platelet-derived growth factor receptor alpha polypeptide (PDGFRA), phosphatase and tensin homolog (PTEN), G-protein-coupled receptors-like receptor Smoothened (SMO), and tumor protein P53 (TP53) were mutated in all tumors; another 26 cancer-related genes were mutated with variable penetrance. Conclusion: Our results underscore the marked molecular heterogeneity between HCC tumors and reinforce the notion that precision medicine approaches are needed for management of individual HCC. These data will serve as a resource to generate hypotheses for further research to improve our understanding of HCC biology. (Hepatology Communications 2018; 00:000-000).

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Genomic and Epigenomic Heterogeneity of Hepatocellular Carcinoma.

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Genomic and Epigenomic Heterogeneity of Hepatocellular Carcinoma.

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