Dataset Information

A 17 gene panel for non-small-cell lung cancer prognosis identified through integrative epigenomic-transcriptomic analyses of hypoxia-induced epithelial-mesenchymal transition.

ABSTRACT: As a critical feature of the tumor microenvironment, hypoxia is known to be a potent inducer of tumor metastasis, and it has been proposed that the initial steps in metastasis involve epithelial-mesenchymal transition (EMT). The strong correlation among hypoxia, EMT, and metastasis suggests that integrative assessment of gene expression and the DNA modification program of hypoxia-induced EMT via high-throughput sequencing technologies may increase our understanding of the molecular basis of tumor invasion and metastasis. Here, we present the genomewide transcriptional and epigenetic profiles of non-small-cell lung cancer (NSCLC) cells under normoxic and hypoxic conditions. We demonstrate that hypoxia induces EMT along with dynamic alterations of transcriptional expression and epigenetic modifications in both A549 and HCC827 cells. After training using a dataset from patients with invasive and noninvasive lung adenocarcinomas with an artificial neural network algorithm, a characteristic 17-gene panel was identified, consisting of genes involved in EMT, hypoxia response, glycometabolism, and epigenetic modifications. This 17-gene signature clearly stratified NSCLC patients with significant differences in overall survival across three independent datasets. Our study may be suitable as a basis for further selection of gene signatures to potentially guide prognostic stratification in patients with NSCLC.

SUBMITTER: Chen YL

PROVIDER: S-EPMC6599842 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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A 17 gene panel for non-small-cell lung cancer prognosis identified through integrative epigenomic-transcriptomic analyses of hypoxia-induced epithelial-mesenchymal transition.

Chen Yue-Lei YL Zhang Yihe Y Wang Junwen J Chen Na N Fang Weiying W Zhong Jianing J Liu Yi Y Qin Rui R Yu Xinxin X Sun Zhongsheng Z Sun Zhongsheng Z Gao Fei F

Molecular oncology 20190529 7

As a critical feature of the tumor microenvironment, hypoxia is known to be a potent inducer of tumor metastasis, and it has been proposed that the initial steps in metastasis involve epithelial-mesenchymal transition (EMT). The strong correlation among hypoxia, EMT, and metastasis suggests that integrative assessment of gene expression and the DNA modification program of hypoxia-induced EMT via high-throughput sequencing technologies may increase our understanding of the molecular basis of tumo ...[more]

PMID: 30973670

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Project description:While recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer taxonomy and defining driver events.Here, we applied a powerful integrative network algorithm to matched DNA methylation and RNA-Seq data for 724 estrogen receptor (ER)-positive (ER+) breast cancers and 111 normal adjacent tissue specimens from The Cancer Genome Atlas (TCGA) project, in order to identify putative epigenetic driver events and to explore the resulting molecular taxonomy. This revealed the existence of nine functionally deregulated epigenetic hotspots encompassing a total of 146 genes, which we were able to validate in independent data sets encompassing over 1000 ER+ breast cancers. Integrative clustering of the matched messenger RNA (mRNA) and DNA methylation data over these genes resulted in only two clusters, which correlated very strongly with the luminal-A and luminal B subtypes. Overall, luminal-A and luminal-B breast cancers shared the same epigenetically deregulated hotspots but with luminal-B cancers exhibiting increased aberrant DNA methylation patterns relative to normal tissue. We show that increased levels of DNA methylation and mRNA expression deviation from the normal state define a marker of poor prognosis. Our data further implicates epigenetic silencing of WNT signalling antagonists and bone morphogenetic proteins (BMP) as key events underlying both luminal subtypes but specially of luminal-B breast cancer. Finally, we show that DNA methylation changes within the identified epigenetic interactome hotspots do not exhibit mutually exclusive patterns within the same cancer sample, instead exhibiting coordinated changes within the sample.Our results indicate that the integrative DNA methylation and transcriptomic landscape of ER+ breast cancer is surprisingly homogeneous, defining two main subtypes which strongly correlate with luminal-A/B subtype status. In particular, we identify WNT and BMP signalling as key epigenetically deregulated tumour suppressor pathways in luminal ER+ breast cancer, with increased deregulation seen in luminal-B breast cancer.

Project description:Background Environmental health research has recently undergone a dramatic shift, with ongoing technological advancements allowing for broader coverage of exposure and molecular biology signatures. Approaches to integrate such measures are still needed to increase understanding between systems-level exposure and biology. Objectives We address this gap by evaluating placental tissues to identify novel chemical-biological interactions associated with preeclampsia. This study tests the hypothesis that understudied chemicals are present in the human placenta and associated with preeclampsia-relevant disruptions, including overall case status (preeclamptic vs. normotensive patients) and underlying transcriptomic/epigenomic signatures. Methods A non-targeted analysis based on high-resolution mass spectrometry was used to analyze placental tissues from a cohort of 35 patients with preeclampsia (n = 18) and normotensive (n = 17) pregnancies. Molecular feature data were queried against chemicals within the U.S. Environmental Protection Agency’s DSSTox database, and prioritized for confirmation based on association with preeclampsia case status and confidence of chemical identification. All molecular features were evaluated for relationships to mRNA, microRNA, and CpG methylation (i.e., multi-omic) signature alterations involved in preeclampsia. Results A total of 183 molecular features were identified with significantly differentiated abundance in placental extracts of preeclamptic patients; these features clustered into distinct chemical groupings using unsupervised methods. Of these features, 53 were identified (mapping to 40 distinct chemicals) using chemical standards, fragmentation spectra, and chemical metadata. In general, human metabolites had the largest feature intensities and strongest associations with preeclampsia-relevant multi-omic changes. Exogenous drugs were second most abundant and had fewer associations with multi-omic changes. Other exogenous chemicals (non-drugs) were least abundant and had the fewest associations with multi-omic changes. Conclusions These global data trends suggest that human metabolites are heavily intertwined with biological processes involved in preeclampsia etiology, while exogenous chemicals may still impact select transcriptomic/epigenomic processes. This study serves as a demonstration of merging systems exposures with systems biology to better understand chemical-disease relationships.

Dataset Information

A 17 gene panel for non-small-cell lung cancer prognosis identified through integrative epigenomic-transcriptomic analyses of hypoxia-induced epithelial-mesenchymal transition.

Publications

A 17 gene panel for non-small-cell lung cancer prognosis identified through integrative epigenomic-transcriptomic analyses of hypoxia-induced epithelial-mesenchymal transition.

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