Discovery pipeline for epigenetically deregulated miRNAs in cancer: integration of primary miRNA transcription.
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ABSTRACT:
SUBMITTER: Hulf T
PROVIDER: S-EPMC3037319 | biostudies-other | 2011
REPOSITORIES: biostudies-other
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Project description:BackgroundEpithelial ovarian cancer (EOC) is one of the most lethal gynecological malignancies among women worldwide. Early diagnosis of EOC could help in ovarian cancer management. MicroRNAs, a class of small non-coding RNA molecules, are known to be involved in post-transcriptional regulation of ~60% of human genes. Aberrantly expressed miRNAs associated with disease progression are confined in lipid or lipoprotein and secreted as extracellular miRNA in body fluid such as plasma, serum, and urine. MiRNAs are stably present in the circulation and recently have gained an importance to serve as a minimally invasive biomarker for early detection of epithelial ovarian cancer.MethodsGenome-wide methylation pattern of six EOC and two normal ovarian tissue samples revealed differential methylation regions of miRNA gene promoter through MeDIP-NGS sequencing. Based on log2FC and p-value, three hypomethylated miRNAs (miR-205, miR-200c, and miR-141) known to have a potential role in ovarian cancer progression were selected for expression analysis through qRT-PCR. The expression of selected miRNAs was analyzed in 115 tissue (85 EOC, 30 normal) and 65 matched serum (51 EOC and 14 normal) samples.ResultsAll three miRNAs (miR-205, miR-200c, and miR-141) showed significantly higher expression in both tissue and serum cohorts when compared with normal controls (p < 0.0001). The receiver operating characteristic curve analysis of miR-205, miR-200c, and miR-141 has area under the curve (AUC) values of 87.6 (p < 0.0001), 78.2 (p < 0.0001), and 86.0 (p < 0.0001), respectively; in advance-stage serum samples, however, ROC has AUC values of 88.1 (p < 0.0001), 78.9 (p < 0.0001), and 86.7 (p < 0.0001), respectively, in early-stage serum samples. The combined diagnostic potential of the three miRNAs in advance-stage serum samples and early-stage serum samples has AUC values of 95.9 (95% CI: 0.925-1.012; sensitivity = 96.6% and specificity = 80.0%) and 98.1 (95% CI: 0.941-1.021; sensitivity = 90.5% and specificity = 100%), respectively.ConclusionOur data correlate the epigenetic deregulation of the miRNA genes with their expression. In addition, the miRNA panel (miR-205 + miR-200c + miR-141) has a much higher AUC, sensitivity, and specificity to predict EOC at an early stage in both tissue and serum samples.
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Project description:BackgroundMicroRNAs (miRNAs) plays an essential role in the pathogenesis of colon cancer. This study aims to identify and verify key miRNAs that may serve as potential biomarkers for early diagnosis and treatment of colon cancer.MethodsTwo miRNA microarray datasets (GSE53339 and GSE126093) were downloaded from the Gene Expression Omnibus (GEO) database, and the common differentially expressed miRNAs (DEMis) of both were identified by the "limma" package and the intersect function in R. Then, the miRwalk online tool was used to predict the target genes of the common DEMis and perform Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on those DEMis. The miRNA-gene network was constructed using Cytoscape software to identify key miRNAs and validated using quantitative real-time PCR (qRT-PCR) and The Cancer Genome Atlas (TCGA) dataset information for experimental and external database validation, respectively. In addition, we explored the correlation between key miRNAs and infiltrating immune cells and immunotherapy biomarkers.ResultsFourteen common DEMis were identified from the GEO database, and five targeted genes were predicted. A microRNA-gene network was subsequently constructed to identify three key miRNAs (miR-363-3p, miR-520e, and miR-330-5p). Both qRT-PCR and external database validation confirmed our findings. In addition, we found that miR-520e was significantly associated with infiltrating immune cells and established immune checkpoints.ConclusionOur study identified three key miRNAs that influence the development of colon cancer. In addition, further studies suggest that infiltrating immune cells may play an essential role in the pathogenesis of colon cancer. These findings assist in early diagnosis and precision-targeted therapies.
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Project description:The availability of increasing volumes of multi-omics profiles across many cancers promises to improve our understanding of the regulatory mechanisms underlying cancer. The main challenge is to integrate these multiple levels of omics profiles and especially to analyze them across many cancers. Here we present AMARETTO, an algorithm that addresses both challenges in three steps. First, AMARETTO identifies potential cancer driver genes through integration of copy number, DNA methylation and gene expression data. Then AMARETTO connects these driver genes with co-expressed target genes that they control, defined as regulatory modules. Thirdly, we connect AMARETTO modules identified from different cancer sites into a pancancer network to identify cancer driver genes. Here we applied AMARETTO in a pancancer study comprising eleven cancer sites and confirmed that AMARETTO captures hallmarks of cancer. We also demonstrated that AMARETTO enables the identification of novel pancancer driver genes. In particular, our analysis led to the identification of pancancer driver genes of smoking-induced cancers and 'antiviral' interferon-modulated innate immune response.Software availabilityAMARETTO is available as an R package at https://bitbucket.org/gevaertlab/pancanceramaretto.
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