MicroRNA-Based Classification of Hepatocellular Carcinoma and Oncogenic Role of miR-517a
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE20596 | GEO | 2011/02/17
SECONDARY ACCESSION(S): PRJNA124713
REPOSITORIES: GEO
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Project description:Hepatocellular carcinoma (HCC) is a complex and heterogeneous tumor due to activation of multiple cellular pathways and molecular alterations. Herein, we report the first molecular classification of 89 HCC based on the expression of 358 microRNAs and integrative genomic analysis. Three main subclasses of HCC were identified : two of them were associated with beta-catenin mutations or aggressive phenotype. A subset of the subclass of aggressive tumors (8/89, 9%) showed overexpression of a cluster of microRNAs located on chr19q13.41 (C19MC locus. We showed that miR 517a, representing C19MC, promoted cell proliferation, migration and invasion in vitro and induced the development of aggressive tumors in vivo suggesting its role as a novel oncogenic driver in HCC. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2011-02-17 | E-GEOD-20596 | biostudies-arrayexpress
Project description:Background & Aims: Hepatocellular carcinoma (HCC) is the second most lethal cancer due to lack of effective therapies. Although promising, HCC molecular classification, which enriches potential responders to specific therapies, has not yet been assessed in clinical trials of anti-HCC drugs. We aimed to overcome these challenges by developing clinicopathological surrogate indices of HCC molecular classification. Methods: HCC classification defined in our previous transcriptome meta-analysis (S1, S2, and S3 subclasses) was implemented in an FDA-approved diagnostic platform (Elements assay, NanoString). Ninety-six HCC tumors (training set) were assayed to develop molecular subclass-predictive indices based on clinicopathological features, which were independently validated in 99 HCC tumors (validation set). Molecular deregulations associated with the histopathological features were determined by pathway analysis. Sample sizes for HCC clinical trials enriched with specific molecular subclasses were determined. Results: HCC subclass-predictive indices were: steatohepatitic (SH)-HCC variant and immune cell infiltrate for S1 subclass, macrotrabecular/compact pattern, lack of pseudoglandular pattern, and high serum alpha-fetoprotein (>400 ng/mL) for S2 subclass, and microtrabecular pattern, lack of SH-HCC and clear cell variants, and lower histological grade for S3 subclass. Macrotrabecular/compact pattern, a predictor of S2 subclass, was associated with activation of therapeutically targetable oncogene YAP and stemness markers EPCAM/KRT19. BMP4 was associated with pseudoglandular pattern. Subclass-predictive indices-based patient enrichment reduced clinical trial sample sizes from 121, 184, and 53 to 30, 43, and 22 for S1, S2, and S3 subclass-targeting therapies, respectively. Conclusions: HCC molecular subclasses can be enriched by clinicopathological indices tightly associated with deregulation of therapeutically targetable molecular pathways.
2015-06-17 | GSE59548 | GEO
Project description:Global gene expression patterns of 91 human hepatocellular carcinomas (HCC) were analyzed to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Total RNAs were isolated from frozen liver tissue using CsCl density gradient centrifugation methods. Total RNA from 18 normal livers were pooled and used as reference in entire microarray experiments. To obtain gene expression profile data from human HCC, 20 μg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using dye-swap strategy to eliminate dye labeling bias. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with survival of the patients. This association was validated by five independent supervised learning methods. Genes most strongly associated with survival were identified by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and anti-apoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification suggesting an etiological involvement of these processes in accelerating the progression of HCC. The biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g. HIF1a) for selective treatment(s) of HCC patients.
2004-10-28 | E-GEOD-1898 | biostudies-arrayexpress
Project description:Triple-negative breast cancer (TNBC) is regarded as the most aggressive subtype of breast cancer lacking targeted therapies. This is attributed to its high heterogeneity that complicates elucidation of its molecular aberrations. Here, we report identification of specific proteome expression profiles pertaining to two TNBC subclasses, basal A and basal B, through in-depth proteomics analysis of breast cancer cells. We observed that kinases and proteases displayed unique expression patterns within the subclasses, similar to whole proteome clusters. Systematic analyses of protein-protein interaction and co-regulation networks of these kinases and proteases unraveled dysregulated pathways and plausible targets for each TNBC subclass. Among these, we identified kinases AXL, PEAK1 and TGFBR2, and proteases FAP, UCHL1 and MMP2/14, as specific targets for basal B subclass, which represents the more aggressive TNBC cell lines. Our study thus highlights intricate mechanisms and distinct targets within TNBC, and emphasizes that these have to be exploited in a subclass-specific manner rather than a one-for-all TNBC therapy.
2020-03-03 | PXD017025 | Pride
Project description:The distinct phenotypic and prognostic subclasses of human hepatocellular carcinoma (HCC) are difficult to reproduce in animal experiments. Here we have used in vivo gene targeting to insert an enhancer-promoter element at an imprinted chromosome 12 locus in mice, thereby converting ~1 in 20,000 normal hepatocytes into a focus of HCC with a single genetic modification. A 300 kb chromosomal domain containing multiple mRNAs, snoRNAs and microRNAs was activated surrounding the integration site. An identical domain was activated at the syntenic locus in a specific molecular subclass of spontaneous human HCCs with a similar histological phenotype, which was associated with partial loss of DNA methylation. These findings demonstrate the accuracy of in vivo gene targeting in modeling human cancer, and suggest future applications in studying various tumors in diverse animal species. In addition, similar insertion events produced by randomly integrating vectors could be a concern for liver-directed human gene therapy. Three individual liver tumor samples and their adjacent normal-looking liver tissue were used for miRNA array analysis
2012-07-02 | E-GEOD-35402 | biostudies-arrayexpress
Project description:The distinct phenotypic and prognostic subclasses of human hepatocellular carcinoma (HCC) are difficult to reproduce in animal experiments. Here we have used in vivo gene targeting to insert an enhancer-promoter element at an imprinted chromosome 12 locus in mice, thereby converting ~1 in 20,000 normal hepatocytes into a focus of HCC with a single genetic modification. A 300 kb chromosomal domain containing multiple mRNAs, snoRNAs and microRNAs was activated surrounding the integration site. An identical domain was activated at the syntenic locus in a specific molecular subclass of spontaneous human HCCs with a similar histological phenotype, which was associated with partial loss of DNA methylation. These findings demonstrate the accuracy of in vivo gene targeting in modeling human cancer, and suggest future applications in studying various tumors in diverse animal species. In addition, similar insertion events produced by randomly integrating vectors could be a concern for liver-directed human gene therapy. Three individual liver tumor tissue and their adjacent normal liver tissue were used for mRNA array analysis
2012-07-02 | E-GEOD-35403 | biostudies-arrayexpress
Project description:Global gene expression patterns of 91 human hepatocellular carcinomas (HCC) were analyzed to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Total RNAs were isolated from frozen liver tissue using CsCl density gradient centrifugation methods. Total RNA from 18 normal livers were pooled and used as reference in entire microarray experiments. To obtain gene expression profile data from human HCC, 20 μg of total RNAs from tissues were used to drive fluorescently (Cy-5 or Cy-3) labeled cDNA. At least two hybridizations were carried out for each tissue using dye-swap strategy to eliminate dye labeling bias. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with survival of the patients. This association was validated by five independent supervised learning methods. Genes most strongly associated with survival were identified by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and anti-apoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification suggesting an etiological involvement of these processes in accelerating the progression of HCC. The biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g. HIF1a) for selective treatment(s) of HCC patients. Keywords: other
2004-10-28 | GSE1898 | GEO
Project description:The distinct phenotypic and prognostic subclasses of human hepatocellular carcinoma (HCC) are difficult to reproduce in animal experiments. Here we have used in vivo gene targeting to insert an enhancer-promoter element at an imprinted chromosome 12 locus in mice, thereby converting ~1 in 20,000 normal hepatocytes into a focus of HCC with a single genetic modification. A 300 kb chromosomal domain containing multiple mRNAs, snoRNAs and microRNAs was activated surrounding the integration site. An identical domain was activated at the syntenic locus in a specific molecular subclass of spontaneous human HCCs with a similar histological phenotype, which was associated with partial loss of DNA methylation. These findings demonstrate the accuracy of in vivo gene targeting in modeling human cancer, and suggest future applications in studying various tumors in diverse animal species. In addition, similar insertion events produced by randomly integrating vectors could be a concern for liver-directed human gene therapy.
2012-07-03 | GSE35403 | GEO
Project description:The distinct phenotypic and prognostic subclasses of human hepatocellular carcinoma (HCC) are difficult to reproduce in animal experiments. Here we have used in vivo gene targeting to insert an enhancer-promoter element at an imprinted chromosome 12 locus in mice, thereby converting ~1 in 20,000 normal hepatocytes into a focus of HCC with a single genetic modification. A 300 kb chromosomal domain containing multiple mRNAs, snoRNAs and microRNAs was activated surrounding the integration site. An identical domain was activated at the syntenic locus in a specific molecular subclass of spontaneous human HCCs with a similar histological phenotype, which was associated with partial loss of DNA methylation. These findings demonstrate the accuracy of in vivo gene targeting in modeling human cancer, and suggest future applications in studying various tumors in diverse animal species. In addition, similar insertion events produced by randomly integrating vectors could be a concern for liver-directed human gene therapy.
2012-07-03 | GSE35402 | GEO
Project description:Background: Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods: Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results: Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the 3 putative subclasses (ANOVA, Bonferonni correction, p < 0.05) identified 6,934 differentially regulated genes. K means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the 3 subclasses. Leave one out cross validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusions: Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes. Expression data from 98 children with septic shock and 32 normal controls were generated using whole blood-derived RNA samples representing the first 24 hours of admission to the pediatric intensive care unit. The controls were used for normalization. Subsequently, we used the expression data to derive expression-based subclasses of patients using discovery oriented expression and statistical filters, followed by unsupervised hierarchical clustering.
2011-01-13 | E-GEOD-26440 | biostudies-arrayexpress