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Integrative Epigenomic and Genomic Profiling of HCC Patients to Identify Key Driver Signaling Pathways of HCC Progression and Poor Outcome

ABSTRACT: Globally, hepatocellular carcinoma (HCC) accounts for 70-85% of primary liver cancers and is the second leading cause of male cancer death. Among patients with HCC there is widespread heterogeneity, yet just a single standard therapeutic, Sorafenib, which is only effective in patients with overactive MAP kinase signaling. Identifying homogeneous subgroups of HCC patients will improve our ability to develop more effective targeted treatment modalities derived from specific signaling pathways that lead to poor survival. Recently, many 'omics based studies have further described the current problem of cancer heterogeneity. Genomics is the application of high-throughput methods to analyze the expression of genes at a global level, while epigenomics focuses on epigenetic modifications, such as DNA methylation changes, across the genome. Though genome-wide analysis by various 'omics methods is popular, the integration of the data is uncommon. We hypothesize that the integration of patient expression data will reveal distinct epigenetic and genomic modifications in subsets of HCC patients that lead to poor outcome. In this study, we employed Illumina or Affymetrix array platforms to analyze paired tumor and non-tumor tissue specimens from 82 HCC patients in an integrative approach incorporating DNA methylation, somatic DNA copy number alteration (SCNA) and expression of mRNA and microRNA genes. First we performed a class comparison analysis between tumor and non-tumor patients to identify 2,173 differentially methylated genes (Illumina 27k BeadChip). Of those genes, only 621 overlapped with tumor-specific genes differentially expressed in the same patients (Affymetrix array). We further narrowed that tumor-specific gene list by removing only a subset of genes that correlated with methylation data. An epigenetic-driven gene signature of 46 genes was established using a correlation coefficient of -0.185 corresponding to the 95th percentile of the 1000-fold random distribution. In a similar manner, an SCNA-related gene signature made up of 2,722 tumor-specific genes was established using a correlation coefficient of 0.3 corresponding to the 99th percentile of the 1000-fold random distribution. The gene signatures do not significantly overlap and each has the ability to cluster HCC patients with poor outcome apart from patients with better prognosis. Moving forward, we plan to focus on key signaling pathways derived from integrated gene and miRNA expression data that are responsible for poor prognosis in patients. Upon identification, driver pathways will be validated in vitro and in vivo to elucidate the mechanisms of HCC progression and poor outcome.

ORGANISM(S): Homo sapiens

PROVIDER: GSE52423 | GEO | 2025/10/01

REPOSITORIES: GEO

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Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.

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Integrative Epigenomic and Genomic Profiling of HCC Patients to Identify Key Driver Signaling Pathways of HCC Progression and Poor Outcome

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