Unknown,Transcriptomics,Genomics,Proteomics

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A signature of 6 genes highlights defects on cell growth and specific metabolic pathways in murine and human hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) represents a major health problem as it afflicts an increasing number of patients worldwide. Albeit most of the risk factors for HCC are known, this is a deadly syndrome with a life expectancy at the time of diagnosis of less than 1 year. Definition of the molecular principles governing the neoplastic transformation of the liver is an urgent need to facilitate the clinical management of patients, based on innovative methods to detect the disease in its early stages and on more efficient therapies. In the present study we have combined the analysis of a murine model and human samples of HCC to identify genes differentially expressed early in the process of hepatocarcinogenesis, using a microarray based approach. Expression of 190 genes was impaired in murine HCC from which 65 were further validated by low-density array RT PCR. The expression of the best 45 genes was then investigated in human samples resulting in 18 genes which expression was significantly modified in HCC. Among them, JUN, methionine adenosyltransferase 1A and 2A, phosphoglucomutase 1, and acyl CoA dehydrogenase short branched chain indicate defective cell proliferation as well as one carbon pathway, glucose and fatty acid metabolism, both in HCC and cirrhotic liver, a well known preneoplastic condition. These alterations were further confirmed in public transcriptomic datasets from other authors. In addition, vasodilator stimulated phosphoprotein, an actin-associated protein involved in cytoskeleton remodelling, was also found to be increased in the liver and serum of cirrhotic and HCC patients. In addition to revealing the impairment of central metabolic pathways for liver homeostasis, further studies may probe the potential value of the reported genes for the early detection of HCC. Transcriptomic analysis of tumors from MAT1A deficient mice

ORGANISM(S): Mus musculus

SUBMITTER: Paul SchrM-CM-6der

PROVIDER: E-GEOD-25457 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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A signature of six genes highlights defects on cell growth and specific metabolic pathways in murine and human hepatocellular carcinoma.

Schröder Paul C PC Segura Víctor V Riezu José Ignacio JI Sangro Bruno B Mato José M JM Prieto Jesús J Santamaría Enrique E Corrales Fernando J FJ

Functional & integrative genomics 20110512 3

Hepatocellular carcinoma (HCC) represents a major health problem as it afflicts an increasing number of patients worldwide. Albeit most of the risk factors for HCC are known, this is a deadly syndrome with a life expectancy at the time of diagnosis of less than 1 year. Definition of the molecular principles governing the neoplastic transformation of the liver is an urgent need to facilitate the clinical management of patients, based on innovative methods to detect the disease in its early stages ...[more]

PMID: 21562899

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Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.

Project description:Although hepatocellular carcinoma (HCC) has been subjected to continuous investigation and its symptoms are well-known, early stage diagnosis of this disease remains difficult and the survival rate after diagnosis is typically very low (3−5%). Early and accurate detection of metabolic changes in the sera of patients with liver cirrhosis can help improve the prognosis of HCC and lead to a better understanding of its mechanism at the molecular level, thus providing patients with in-time treatment of the disease. In this study, we compared metabolite levels in sera of 40 HCC patients and 49 cirrhosis patients from Egypt by using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometer (UPLC-QTOF MS). Following data preprocessing, the most relevant ions in distinguishing HCC cases from cirrhotic controls are selected by statistical methods. Putative metabolite identifications for these ions are obtained through mass-based database search. The identities of some of the putative identifications are verified by comparing their MS/MS fragmentation patterns and retention times with those from authentic compounds. Finally, the serum samples are reanalyzed for quantitation of selected metabolites as candidate biomarkers of HCC. This quantitation was performed using isotope dilution by selected reaction monitoring (SRM) on a triple quadrupole linear ion trap (QqQLIT) coupled to UPLC. Statistical analysis of the UPLC-QTOF data identified 274 monoisotopic ion masses with statistically significant differences in ion intensities between HCC cases and cirrhotic controls. Putative identifications were obtained for 158 ions by mass based search against databases. We verified the identities of selected putative identifications including glycholic acid (GCA), glycodeoxycholic acid (GDCA), 3β, 6β-dihydroxy-5β-cholan-24-oic acid, oleoyl carnitine, and Phe-Phe. SRM-based quantitation confirmed significant differences between HCC and cirrhotic controls in metabolite levels of bile acid metabolites, long chain carnitines and small peptide. Our study provides useful insight into appropriate experimental design and computational methods for serum biomarker discovery using LC−MS/MS based metabolomics. This study has led to the identification of candidate biomarkers with significant changes in metabolite levels between HCC cases and cirrhotic controls. This is the first MS-based metabolic biomarker discovery study on Egyptian subjects that led to the identification of candidate metabolites that discriminate early stage HCC from patients with liver cirrhosis.

Project description:Background & Aims. Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods. To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results. We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded AUROCs of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Conclusions. 5mC markers derived from cfDNA robustly identify HCC within a cirrhotic liver background indicating that further validation is warranted. Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.

Dataset Information

A signature of 6 genes highlights defects on cell growth and specific metabolic pathways in murine and human hepatocellular carcinoma.

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A signature of six genes highlights defects on cell growth and specific metabolic pathways in murine and human hepatocellular carcinoma.

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