The increasing worldwide prevalence of Hepatocellular carcinoma (HCC), characterized by resistance to conventional chemotherapy, poor prognosis and eventually mortality, place it as a prime target ...for new modes of prevention and treatment. Hepatitis C Virus (HCV) is the predominant risk factor for HCC in the US and Europe. Multiple epidemiological studies showed that sustained virological responses (SVR) following treatment with the powerful direct acting antivirals (DAAs), which have replaced interferon-based regimes, do not eliminate tumor development. We aimed to identify an HCV-specific pathogenic mechanism that persists post SVR following DAAs treatment. We demonstrate that HCV infection induces genome-wide epigenetic changes by performing chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) for histone post-translational modifications that are epigenetic markers for active and repressed chromatin. The changes in histone modifications correlate with reprogramed host gene expression and alter signaling pathways known to be associated with HCV life cycle and HCC. These epigenetic alterations require the presence of HCV RNA or/and expression of the viral proteins in the cells. Importantly, the epigenetic changes induced following infection persist as an "epigenetic signature" after virus eradication by DAAs treatment, as detected using in vitro HCV infection models. These observations led to the identification of an 8 gene signature that is associated with HCC development and demonstrate persistent epigenetic alterations in HCV infected and post SVR liver biopsy samples. The epigenetic signature was reverted in vitro by drugs that inhibit epigenetic modifying enzyme and by the EGFR inhibitor, Erlotinib. This epigenetic "scarring" of the genome, persisting following HCV eradication, suggest a novel mechanism for the persistent pathogenesis of HCV after its eradication by DAAs. Our study offers new avenues for prevention of the persistent oncogenic effects of chronic hepatitis infections using specific drugs to revert the epigenetic changes to the genome.
Motivation: Determining the functional impact of non-coding disease-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) is challenging. Many of ...these SNPs are likely to be regulatory SNPs (rSNPs): variations which affect the ability of a transcription factor (TF) to bind to DNA. However, experimental procedures for identifying rSNPs are expensive and labour intensive. Therefore, in silico methods are required for rSNP prediction. By scoring two alleles with a TF position weight matrix (PWM), it can be determined which SNPs are likely rSNPs. However, predictions in this manner are noisy and no method exists that determines the statistical significance of a nucleotide variation on a PWM score. Results: We have designed an algorithm for in silico rSNP detection called is-rSNP. We employ novel convolution methods to determine the complete distributions of PWM scores and ratios between allele scores, facilitating assignment of statistical significance to rSNP effects. We have tested our method on 41 experimentally verified rSNPs, correctly predicting the disrupted TF in 28 cases. We also analysed 146 disease-associated SNPs with no known functional impact in an attempt to identify candidate rSNPs. Of the 11 significantly predicted disrupted TFs, 9 had previous evidence of being associated with the disease in the literature. These results demonstrate that is-rSNP is suitable for high-throughput screening of SNPs for potential regulatory function. This is a useful and important tool in the interpretation of GWAS. Availability: is-rSNP software is available for use at: www.genomics.csse.unimelb.edu.au/is-rSNP Contact: gmaci@csse.unimelb.edu.au; adam.kowalczyk@nicta.com.au Supplementary information: Supplementary data are available at Bioinformatics online.
Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly ...understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.
Purpose: The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical
and pathologic features.
Experimental Design: Microarray gene ...expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian
tube. K -means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed
genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated
the array-based findings. Patient survival within k -means groups was evaluated using Cox proportional hazards models. Class prediction validated k -means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against
unsupervised clustering results.
Results: Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant
potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced
stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal
cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive
stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature
could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration.
Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends.
Conclusion: Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.
RATIONALE:The high morbidity/mortality of atherosclerosis is typically precipitated by plaque rupture and consequent thrombosis. However, research on underlying mechanisms and therapeutic approaches ...is limited by the lack of animal models that reproduce plaque instability observed in humans.
OBJECTIVE:Development and use of a mouse model of plaque rupture that reflects the end stage of human atherosclerosis.
METHODS AND RESULTS:On the basis of flow measurements and computational fluid dynamics, we applied a tandem stenosis to the carotid artery of apolipoprotein E–deficient mice on high-fat diet. At 7 weeks postoperatively, we observed intraplaque hemorrhage in ≈50% of mice, as well as disruption of fibrous caps, intraluminal thrombosis, neovascularization, and further characteristics typically seen in human unstable plaques. Administration of atorvastatin was associated with plaque stabilization and downregulation of monocyte chemoattractant protein-1 and ubiquitin. Microarray profiling of mRNA and microRNA (miR) and, in particular, its combined analysis demonstrated major differences in the hierarchical clustering of genes and miRs among nonatherosclerotic arteries, stable, and unstable plaques and allows the identification of distinct genes/miRs, potentially representing novel therapeutic targets for plaque stabilization. The feasibility of the described animal model as a discovery tool was established in a pilot approach, identifying a disintegrin and metalloprotease with thrombospondin motifs 4 (ADAMTS4) and miR-322 as potential pathogenic factors of plaque instability in mice and validated in human plaques.
CONCLUSIONS:The newly described mouse model reflects human atherosclerotic plaque instability and represents a discovery tool toward the development and testing of therapeutic strategies aimed at preventing plaque rupture. Distinctly expressed genes and miRs can be linked to plaque instability.
OBJECTIVE—Traditional risk factors for coronary artery disease (CAD) fail to adequately distinguish patients who have atherosclerotic plaques susceptible to instability from those who have more ...benign forms. Using plasma lipid profiling, this study aimed to provide insight into disease pathogenesis and evaluate the potential of lipid profiles to assess risk of future plaque instability.
METHODS AND RESULTS—Plasma lipid profiles containing 305 lipids were measured on 220 individuals (matched healthy controls, n=80; stable angina, n=60; unstable coronary syndrome, n=80) using electrospray-ionisation tandem mass spectrometry. ReliefF feature selection coupled with an L2-regularized logistic regression based classifier was used to create multivariate classification models which were verified via 3-fold cross-validation (1000 repeats). Models incorporating both lipids and traditional risk factors provided improved classification of unstable CAD from stable CAD (C-statistic=0.875, 95% CI 0.874–0.877) compared with models containing only traditional risk factors (C-statistic=0.796, 95% CI 0.795–0.798). Many of the lipids identified as discriminatory for unstable CAD displayed an association with disease acuity (severity), suggesting that they are antecedents to the onset of acute coronary syndrome.
CONCLUSION—Plasma lipid profiling may contribute to a new approach to risk stratification for unstable CAD.
Emerging evidence suggests that poor glycemic control mediates post-translational modifications to the H3 histone tail. We are only beginning to understand the dynamic role of some of the diverse ...epigenetic changes mediated by hyperglycemia at single loci, yet elevated glucose levels are thought to regulate genome-wide changes, and this still remains poorly understood. In this article we describe genome-wide histone H3K9/K14 hyperacetylation and DNA methylation maps conferred by hyperglycemia in primary human vascular cells. Chromatin immunoprecipitation (ChIP) as well as CpG methylation (CpG) assays, followed by massive parallel sequencing (ChIP-seq and CpG-seq) identified unique hyperacetylation and CpG methylation signatures with proximal and distal patterns of regionalization associative with gene expression. Ingenuity knowledge-based pathway and gene ontology analyses indicate that hyperglycemia significantly affects human vascular chromatin with the transcriptional up-regulation of genes involved in metabolic and cardiovascular disease. We have generated the first installment of a reference collection of hyperglycemia-induced chromatin modifications using robust and reproducible platforms that allow parallel sequencing-by-synthesis of immunopurified content. We uncover that hyperglycemia-mediated induction of genes and pathways associated with endothelial dysfunction occur through modulation of acetylated H3K9/K14 inversely correlated with methyl-CpG content.
Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little overlap, indicating that the ...results from any one study are unstable. It has been suggested that the underlying pathways are essentially identical, and that the expression of gene sets, rather than that of individual genes, may be more informative with respect to prognosis and understanding of the underlying biological process.
We sought to examine the stability of prognostic signatures based on gene sets rather than individual genes. We classified breast cancer cases from five microarray studies according to the risk of metastasis, using features derived from predefined gene sets. The expression levels of genes in the sets are aggregated, using what we call a set statistic. The resulting prognostic gene sets were as predictive as the lists of individual genes, but displayed more consistent rankings via bootstrap replications within datasets, produced more stable classifiers across different datasets, and are potentially more interpretable in the biological context since they examine gene expression in the context of their neighbouring genes in the pathway. In addition, we performed this analysis in each breast cancer molecular subtype, based on ER/HER2 status. The prognostic gene sets found in each subtype were consistent with the biology based on previous analysis of individual genes.
To date, most analyses of gene expression data have focused at the level of the individual genes. We show that a complementary approach of examining the data using predefined gene sets can reduce the noise and could provide increased insight into the underlying biological pathways.
Recent evidence on the genomic integrity of non-malignant cells surrounding carcinoma cells has reinvigorated the discussion about the origin of the altered phenotype exhibited by carcinoma ...associated fibroblasts. Many hypotheses have been proposed for the origin of these altered cells, including standard connective tissue acute phase and stress response, fibroblast senescence, reciprocal interactions with the cancer cells, fibroblast specific somatic mutations, differentiation precursors and infiltrating mesenchymal stem cells. Here we review the definition of CAF phenotype and the evidence for each of those hypotheses, in the context of our current understanding of cancer etiology.
Gene-expression profiling has revolutionized the way we think about cancer and confers the ability to observe the synchronous expression of thousands of genes. The use of putative genome-level ...expression profiles has allowed biologists to observe the complex interactions of genes that constitute recognized biologic pathways. We used gastric and ovarian datasets to identify gene-expression signatures and determine any functional significance.
Microarray data of 94-tumor and 45-benign samples derived from patients with gastric cancer were interrogated using Hierarchical Ordered Partitioning and Collapsing Hybrid analysis identifying clusters of coexpressed genes. Clusters were further characterized with respect to biologic significance, gene ontology, and ability to discriminate between normal and tumor tissue. Tumor tissues were separated into epithelial and stromal compartments and immunohistochemical analysis performed to further elucidate specific cell lineages expressing genes contained in the signature.
We identified a "stromal-response" expression signature, highly enriched for inflammatory, extracellular matrix, cytokine, and growth factor proteins. The majority of genes in the signature are expressed in the tumor-associated stroma but were absent in associated premalignant conditions. In gastric cancer, this module almost perfectly differentiates tumor from nonmalignant gastric tissue and hence can be regarded as a highly tumor-specific gene-expression signature.
We show that these genes are consistently coexpressed across a range of independent gastric datasets as well as other cancer types suggesting a conserved functional role in cancer. In addition, we show that this signature can be a surrogate marker for M2 macrophage activity and has significant prognostic implications in gastric and ovarian high-grade serous cancer.
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