Identification of hypoxia-induced HIF1A targets in melanocytes reveals a molecular profile associated with poor prognosis for melanoma
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE86555 | GEO | 2017/02/20
SECONDARY ACCESSION(S): PRJNA342181
REPOSITORIES: GEO
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Project description:Hypoxia and HIF1? signaling direct tissue-specific gene responses regulating tumor progression, invasion, and metastasis. By integrating HIF1? knockdown and hypoxia-induced gene expression changes, this study identifies a melanocyte-specific, HIF1?-dependent/hypoxia-responsive gene expression signature. Integration of these gene expression changes with HIF1? ChIP-Seq analysis identifies 81 HIF1? direct target genes in melanocytes. The expression levels for 10 of the HIF1? direct targets - GAPDH, PKM, PPAT, DARS, DTWD1, SEH1L, ZNF292, RLF, AGTRAP, and GPC6 - are significantly correlated with reduced time of disease-free status in melanoma by logistic regression (P-value = 0.0013) and ROC curve analysis (AUC = 0.826, P-value < 0.0001). This HIF1?-regulated profile defines a melanocyte-specific response under hypoxia, and demonstrates the role of HIF1? as an invasive cell state gatekeeper in regulating cellular metabolism, chromatin and transcriptional regulation, vascularization, and invasion.
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Project description:ChIP-seq profiling of HIF1A binding in mouse immortalized melanocyte cell line melan-Ink4a-Arf null cells
2017-02-20 | GSE86554 | GEO
Project description:These datasets describe a melanocyte specific, HIF1A-Dependent / Hypoxia-Responsive gene expression signature defined by the regulation of genes critical to metabolism, chromatin and transcriptional regulation, vascularization and cellular invasivness. These genes provide lineage specific targets for refinement of diagnostic markers associated with primary melanoma tumor metastatic potential, and also provides novel molecular targets for therapeutic strategies targeting metastatic disease progression.
2017-02-20 | GSE86553 | GEO
Project description:Identification of hypoxia-induced HIF1A targets in melanocytes reveals a molecular profile associated with poor prognosis for melanoma
| PRJNA342181 | ENA
Project description:Melanoma is one of the most aggressive cancers. Hypoxic microenvironment affects multiple cellular pathways and contributes to tumor progression. The purpose of the research was to investigate the association between hypoxia and melanoma, and identify the prognostic value of hypoxia-related genes. Based on the GSVA algorithm, gene expression profile collected from The Cancer Genome Atlas (TCGA) was used for calculating the hypoxia score. The Kaplan-Meier plot suggested that a high hypoxia score was correlated with the inferior survival of melanoma patients. Using differential gene expression analysis and WGCNA, a total of 337 overlapping genes associated with hypoxia were determined. Protein-protein interaction network and functional enrichment analysis were conducted, and Lasso Cox regression was performed to establish the prognostic gene signature. Lasso regression showed that seven genes displayed the best features. A novel seven-gene signature (including ABCA12, PTK6, FERMT1, GSDMC, KRT2, CSTA, and SPRR2F) was constructed for prognosis prediction. The ROC curve inferred good performance in both the TCGA cohort and validation cohorts. Therefore, our study determined the prognostic implication of the hypoxia score in melanoma and showed a novel seven-gene signature to predict prognosis, which may provide insights into the prognosis evaluation and clinical decision making.
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Project description:Transcriptional and epigenetic characterization of melanocytes and melanoma cells isolated from their in vivo context promises to unveil key differences between these developmentally related normal and cancer cell populations. We therefore engineered an enhanced Danio rerio (zebrafish) melanoma model with fluorescently labeled melanocytes to allow for isolation of normal (wild type) and premalignant (BRAFV600E-mutant) populations for comparison to fully transformed BRAFV600E-mutant, p53 loss-of-function melanoma cells. Using fluorescence-activated cell sorting to isolate these populations, we performed high-quality RNA- and ATAC-seq on sorted zebrafish melanocytes vs. melanoma cells, which we provide as a resource here. Melanocytes had consistent transcriptional and accessibility profiles, as did melanoma cells. Comparing melanocytes and melanoma, we note 4128 differentially expressed genes and 56,936 differentially accessible regions with overall gene expression profiles analogous to human melanocytes and the pigmentation melanoma subtype. Combining the RNA- and ATAC-seq data surprisingly revealed that increased chromatin accessibility did not always correspond with increased gene expression, suggesting that though there is widespread dysregulation in chromatin accessibility in melanoma, there is a potentially more refined gene expression program driving cancerous melanoma. These data serve as a resource to identify candidate regulators of the normal vs. diseased states in a genetically controlled in vivo context.
| S-EPMC8727958 | biostudies-literature
Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets.
2010-07-20 | GSE15366 | GEO
Project description:Background - Hepatocellular carcinomas (HCCs) are heterogeneous tumors with respect to etiology, cell of origin and biology. The course of the disease is unpredictable and is in part dependent on the tumor microenvironment. One of the microenvironmental factors is hypoxia, which is known to promote aggressiveness in other malignant tumors. We hypothesized that certain regions in HCC exist with chronic hypoxia and a characteristic gene expression pattern. Moreover, during the development of HCC there is an important contribution of this chronic hypoxia on prognosis via this gene expression. Until now, most research has been performed in acute hypoxic models (< 24 hours). Methods – Human hepatoblastoma cells HepG2 were cultured in either normoxic (20% O2) or hypoxic (2% O2) conditions for 72 hrs, the time it takes to adapt to chronic hypoxia. After 3 days the cells were harvested and analyzed by microarray technology. The highly significant differentially expressed genes were selected and used to assess the clinical value of our in vitro chronic hypoxia gene signature in four published patient studies. Three of these independent microarray studies on HCC patients were used as training sets to determine a minimal prognostic gene set and one study was used for validation. Gene expression analysis and correlation with clinical outcome was assessed with the bioinfomatic method of Goeman et al (). Results – In the HepG2 cells, 3592 genes were differentially expressed in cells cultured at 2% oxygen for 72 hrs. Out of these, 265 showed a high significant change (2-fold change and p=0.0001). The level of gene expression after 72 hrs was different from the acute hypoxic response (during the first 24 hours) and represented chronicity. Using computational methods we identified 7 out of the 265 highly significant genes that showed correlation with prognosis in all three different training sets and this was independently validated in a 4th dataset. With our approach we could include the largest number of HCC patients in one single study. Conclusion – We identified a 7-gene signature, which is associated with chronic hypoxia and predicts prognosis in patients with HCC. In the future this signature could be used as a diagnostic tool. In addition, chronic hypoxia gene expression information can be used in the search for new therapeutic targets. Two conditions were compared and each sample has a biological replicate. Samples are hybridized in dye-swap, resulting in 4 hybridizations.
2010-07-20 | E-GEOD-15366 | biostudies-arrayexpress
Project description:Most expression quantitative trait locus (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type-specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to linkage disequilibrium (LD) pruning and 4997 eGenes (FDR < 0.05). Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissue types, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were unique to melanocytes compared to those of GTEx skin tissues or TCGA melanomas. The melanocyte data set also identified trans-eQTLs, including those connecting a pigmentation-associated functional SNP with four genes, likely through cis-regulation of IRF4 Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as in melanoma-associated variants identified through genome-wide association studies. Melanocyte eQTLs also colocalized with melanoma GWAS variants in five known loci. Finally, a transcriptome-wide association study using melanocyte eQTLs uncovered four novel susceptibility loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings, and present a robust database for genomic research of melanoma risk and melanocyte biology.
| S-EPMC6211648 | biostudies-literature
Project description:ObjectiveTo investigate the value of Hypoxia-inducible factor 1 A (HIF1A) in predicting lymph node metastasis (LNM) stage and clinical outcomes of papillary thyroid cancer (PTC) patients.Materials and methodsThe HIF1A gene expression analysis in PTC was performed by bioinformatics approaches followed by evaluating its protein level using immunohistochemistry analysis. The role of HIF1A in predicting the LNM stage was evaluated by logistic regression analysis, nomogram construction, and receiver operating characteristic (ROC) analysis. We performed survival analyses to determine its prognostic value. Enrichment analysis was conducted, and immune cell infiltration and stromal content were evaluated to examine the underlying mechanism of HIF1A in PTC.ResultsHIF1A transcription and protein levels were significantly high in PTC tissue (P < 0.05). Its overexpression predicted high LNM risk and unfavorable prognosis for PTC patients (P < 0.05). Cox regression analysis revealed HIF1A as an independent prognostic biomarker for the disease-free interval (DFI) (P < 0.01). In addition, HIF1A was positively related to tumor-suppressive immunity but was negatively correlated with anti-tumor immunity. HIF1A upregulation was also associated with increased stromal content.ConclusionsHIF1A overexpression is an independent predictor for worse DFI in PTC. The HIF1A expression may affect the prognosis of PTC patients through immune- and stroma-related pathways. Our study provides new insight into the role of HIF1A in PTC biology and clinical management.
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