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Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma.

ABSTRACT: Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro-oncogenic pathways in primary tumors (PT) and adjacent non-malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome-wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow integrated differentially expressed gene selection, gene ontology enrichment, computational classification, survival predictions, image analysis and experimental validation methods. We developed a 24-ribosomal gene-based HCC classifier (RGC), which is prognostically significant in both PT and AT. The RGC gene overexpression in PT was associated with a poor prognosis in the training (hazard ratio = 8.2, P = 9.4 × 10-6 ) and cross-cohort validation (hazard ratio = 2.63, P = 0.004) datasets. The multivariate survival analysis demonstrated the significant and independent prognostic value of the RGC. The RGC displayed a significant prognostic value in AT of the training (hazard ratio = 5.0, P = 0.03) and cross-validation (hazard ratio = 1.9, P = 0.03) HCC groups, confirming the accuracy and robustness of the RGC. Our experimental and bioinformatics analyses suggested a key role for c-MYC in the pro-oncogenic pattern of ribosomal biogenesis co-regulation in PT and AT. Microarray, quantitative RT-PCR and quantitative immunohistochemical studies of the PT showed that DKK1 in PT is the perspective biomarker for poor HCC outcomes. The common co-transcriptional pattern of ribosome biogenesis genes in PT and AT from HCC patients suggests a new scalable prognostic system, as supported by the model of tumor-like metabolic redirection/assimilation in non-malignant AT. The RGC, comprising 24 ribosomal genes, is introduced as a robust and reproducible prognostic model for stratifying HCC patient risks. The adjacent non-malignant liver tissue alone, or in combination with HCC tissue biopsy, could be an important target for developing predictive and monitoring strategies, as well as evidence-based therapeutic interventions, that aim to reduce the risk of post-surgery relapse in HCC patients.

SUBMITTER: Grinchuk OV

PROVIDER: S-EPMC5748488 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma.

Grinchuk Oleg V OV Yenamandra Surya P SP Iyer Ramakrishnan R Singh Malay M Lee Hwee Kuan HK Lim Kiat Hon KH Chow Pierce Kah-Hoe PK Kuznetsov Vladamir A VA

Molecular oncology 20171212 1

Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro-oncogenic pathways in primary tumors (PT) and adjacent non-malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome-wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow ...[more]

PMID: 29117471

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Project description:BackgroundLiver cancer is one of the major causes of cancer death worldwide, with significantly higher incidence and mortality among the male patients. Although sex hormones and their receptors could contribute to such sex differences, the story is incomplete. Genes on the male-specific region of the Y chromosome could play a role(s) in this cancer. TSPY is the putative gene for the gonadoblastoma locus on the Y chromosome (GBY) that is ectopically expressed in a subset of male hepatocellular carcinomas (HCCs). Although various studies showed that TSPY expression is associated with poor prognosis in the patients and its overexpression promotes cell proliferation of various cancer cell lines, it remains unclear how TSPY contributes to the clinical outcomes of the HCC patients. Identifying the downstream genes and pathways of TSPY actions would provide novel insights on its contribution(s) to male predominance in this deadly cancer.ResultsTo determine the effects of TSPY on HCC, a TSPY transgene was introduced to the HCC cell line, HuH-7, and studied with RNA-Seq transcriptome analysis. The results showed that TSPY upregulates various genes associated with cell-cycle and cell-viability, and suppresses cell-death related genes. To correlate the experimental observations with those of clinical specimens, transcriptomes of male HCCs with high TSPY expression were analyzed with reference to those with silent TSPY expression from the Cancer Genome Atlas (TCGA). The comparative analysis identified 49 genes, which showed parallel expression patterns between HuH-7 cells overexpressing TSPY and clinical specimens with high TSPY expression. Among these 49 genes, 16 likely downstream genes could be associated with survival rates in HCC patients. The major upregulated targets were cell-cycle related genes and growth factor receptor genes, including CDC25B and HMMR, whose expression levels are negatively correlated with the patient survival rates. In contrast, PPARGC1A, SLC25A25 and SOCS2 were downregulated with TSPY expression, and possess favorable prognoses for HCC patients.ConclusionWe demonstrate that TSPY could exacerbate the oncogenesis of HCC by differentially upregulate the expression of pro-oncogenic genes and downregulate those of anti-oncogenic genes in male HCC patients, thereby contributing to the male predominance in this deadly cancer.

Project description:Background & aimsLifestyle and environmental-related exposures are important risk factors for hepatocellular carcinoma (HCC), suggesting that epigenetic dysregulation significantly underpins HCC. We profiled 30 surgically resected tumours and the matched adjacent normal tissues to understand the aberrant epigenetic events associated with HCC.MethodsWe identified tumour differential enhancers and the associated genes by analysing H3K27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) and Hi-C/HiChIP data from the resected tumour samples of 30 patients with early-stage HCC. This epigenome dataset was analysed with previously reported genome and transcriptome data of the overlapping group of patients from the same cohort. We performed patient-specific differential expression testing using multiregion sequencing data to identify genes that undergo both enhancer and gene expression changes. Based on the genes selected, we identified two patient groups and performed a recurrence-free survival analysis.ResultsWe observed large-scale changes in the enhancer distribution between HCC tumours and the adjacent normal samples. Many of the gain-in-tumour enhancers showed corresponding upregulation of the associated genes and vice versa, but much of the enhancer and gene expression changes were patient-specific. A subset of the upregulated genes was activated in a subgroup of patients' tumours. Recurrence-free survival analysis revealed that the patients with a more robust upregulation of those genes showed a worse prognosis.ConclusionsWe report the genomic enhancer signature associated with differential prognosis in HCC. Findings that cohere with oncofoetal reprogramming in HCC were underpinned by genome-wide enhancer rewiring. Our results present the epigenetic changes in HCC that offer the rational selection of epigenetic-driven gene targets for therapeutic intervention or disease prognostication in HCC.Impact and implicationsLifestyle and environmental-related exposures are the important risk factors of hepatocellular carcinoma (HCC), suggesting that tumour-associated epigenetic dysregulations may significantly underpin HCC. We profiled tumour tissues and their matched normal from 30 patients with early-stage HCC to study the dysregulated epigenetic changes associated with HCC. By also analysing the patients' RNA-seq and clinical data, we found the signature genes - with epigenetic and transcriptomic dysregulation - associated with worse prognosis. Our findings suggest that systemic approaches are needed to consider the surrounding cellular environmental and epigenetic changes in HCC tumours.

Project description:Background:The prognosis of hepatocellular carcinoma (HCC) patients remains poor. Identifying prognostic markers to stratify HCC patients might help to improve their outcomes. Methods:Six gene expression profiles (GSE121248, GSE84402, GSE65372, GSE51401, GSE45267 and GSE14520) were obtained for differentially expressed genes (DEGs) analysis between HCC tissues and non-tumor tissues. To identify the prognostic genes and establish risk score model, univariable Cox regression survival analysis and Lasso-penalized Cox regression analysis were performed based on the integrated DEGs by robust rank aggregation method. Then Kaplan-Meier and time-dependent receiver operating characteristic (ROC) curves were generated to validate the prognostic performance of risk score in training datasets and validation datasets. Multivariable Cox regression analysis was used to identify independent prognostic factors in liver cancer. A prognostic nomogram was constructed based on The Cancer Genome Atlas (TCGA) dataset. Finally, the correlation between DNA methylation and prognosis-related genes was analyzed. Results:A twelve-gene signature including SPP1, KIF20A, HMMR, TPX2, LAPTM4B, TTK, MAGEA6, ANX10, LECT2, CYP2C9, RDH16 and LCAT was identified, and risk score was calculated by corresponding coefficients. The risk score model showed a strong diagnosis performance to distinguish HCC from normal samples. The HCC patients were stratified into high-risk and low-risk group based on the cutoff value of risk score. The Kaplan-Meier survival curves revealed significantly favorable overall survival in groups with lower risk score (P?<?0.0001). Time-dependent ROC analysis showed well prognostic performance of the twelve-gene signature, which was comparable or superior to AJCC stage at predicting 1-, 3-, and 5-year overall survival. In addition, the twelve-gene signature was independent with other clinical factors and performed better in predicting overall survival after combining with age and AJCC stage by nomogram. Moreover, most of the prognostic twelve genes were negatively correlated with DNA methylation in HCC tissues, which SPP1 and LCAT were identified as the DNA methylation-driven genes. Conclusions:We identified a twelve-gene signature as a robust marker with great potential for clinical application in risk stratification and overall survival prediction in HCC patients.

Dataset Information

Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma.

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Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma.

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