Dataset Information

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

ABSTRACT: PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).

SUBMITTER: Singh G

PROVIDER: S-EPMC5761873 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

Singh Garima G Roy Jyoti J Rout Pratiti P Mallick Bibekanand B

PloS one 20180110 1

PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western ...[more]

PMID: 29320577

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Project description:Purpose: The aim of this study is to identify known and novel small RNAs (Piwi-interacting RNAs and microRNAs) in normal ovary and epithelial ovarian malignancies by adopting high-throughput RNA sequencing (RNA-Seq) and unveil their possible functions in neoplastic pathways of the two most frequently observed and highly lethal subtypes of epithelial ovarian cancers, endometrioid ovarian cancer (ENOCa) and serous ovarian cancer (SOCa). The study has been performed in normal ovarian tissues as well as malignant tissues of these cancer subtypes. Methods: 1 µg of total RNA was used as the starting material for library preparation as prescribed by Illumina Truseq small RNA library protocol. Small RNA sequencing was carried out by Genotypic Technology, Bangalore, India on Illumina Next-Seq 500 platform. Library preparation was done by performing 3' and 5' adapter ligation followed by reverse transcription of cDNA and amplification of the library. The construct of the library was fractionated to select 16-40 nucleotide insert of small RNAs using PAGE. The quality check of the library was done in Agilent Technologies 2100 Bioanalyzer using a DNA-specific chip, such as High Sensitivity DNA. The sequence reads that passed through Quality Check by FastQC and aligned to the human genome (hg19) were further analysed using in-house pipelines and set of known and novel piRNAs and miRNAs were identified. The sets of known piRNAs and miRNAs identified were assessed for their involvement in neoplastic processes of ovarian cancer subtypes by performing target analysis and GO enrichment studies. Results: Using an in-house prediction pipeline, we mapped about 10-15 million sequence reads per sample to the human genome (hg19) and detected 256, 234 and 219 annotated piRNAs in ENOCa, SOCa, and normal ovary respectively; whereas the average number of known miRNAs present in each sample was estimated to be 480. The annotated piRNAs obtained from each sample exhibited varied length distribution between 26-32 nts. Conclusions: For the first time, our study reported the presence of piRNAs in ENOCa, SOCa and normal ovarian tissue from the next-gen sequencing of small RNAs of 16-40 nts length. The extensive catalogue of human EOCa small RNAs (both piRNAs and miRNAs) detected in this study provides a useful resource to dissect complex neoplastic events that are possibly mediated by these ncRNAs, especially by piRNAs. Moreover, these piRNAs could be used as probable small RNA biomarkers for the EOCa.

Project description:Despite recent advances in cancer management, colorectal cancer (CRC) remains the third most common cancer and a major health-care problem worldwide. MicroRNAs have recently emerged as key regulators of cancer development and progression by targeting multiple cancer-related genes; however, such regulatory networks are not well characterized in CRC. Thus, the aim of this study was to perform global messenger RNA (mRNA) and microRNA expression profiling in the same CRC samples and adjacent normal tissues and to identify potential miRNA-mRNA regulatory networks. Our data revealed 1273 significantly upregulated and 1902 downregulated genes in CRC. Pathway analysis revealed significant enrichment in cell cycle, integrated cancer, Wnt (wingless-type MMTV integration site family member), matrix metalloproteinase, and TGF-β pathways in CRC. Pharmacological inhibition of Wnt (using XAV939 or IWP-2) or TGF-β (using SB-431542) pathways led to dose- and time-dependent inhibition of CRC cell growth. Similarly, our data revealed up- (42) and downregulated (61) microRNAs in the same matched samples. Using target prediction and bioinformatics, ~77% of the upregulated genes were predicted to be targeted by microRNAs found to be downregulated in CRC. We subsequently focused on EZH2 (enhancer of zeste homolog 2 ), which was found to be regulated by hsa-miR-26a-5p and several members of the let-7 (lethal-7) family in CRC. Significant inverse correlation between EZH2 and hsa-miR-26a-5p (R(2)=0.56, P=0.0001) and hsa-let-7b-5p (R(2)=0.19, P=0.02) expression was observed in the same samples, corroborating the belief of EZH2 being a bona fide target for these two miRNAs in CRC. Pharmacological inhibition of EZH2 led to significant reduction in trimethylated histone H3 on lysine 27 (H3K27) methylation, marked reduction in cell proliferation, and migration in vitro. Concordantly, small interfering RNA-mediated knockdown of EZH2 led to similar effects on CRC cell growth in vitro. Therefore, our data have revealed several hundred potential miRNA-mRNA regulatory networks in CRC and suggest targeting relevant networks as potential therapeutic strategy for CRC.

Project description:The complex regulatory network between microRNAs and gene expression remains unclear domain of active research. We proposed to address in part this complex regulation with a novel approach for the genome-wide identification of biomodules derived from paired microRNA and mRNA profiles, which could reveal correlations associated with a complex network of de-regulation in human cancer. Two published expression datasets for 68 samples with 11 distinct types of epithelial cancers and 21 samples of normal tissues were used, containing microRNA expression (Lu et al. Nature Letters 2005) and gene expression (Ramaswarmy et al. PNAS 2001) profiles, respectively. As results, the microRNA expression used jointly with mRNA expression can provide better classifiers of epithelial cancers against normal epithelial tissue than either dataset alone (p=1×10(-10), F-Test). We identified a combination of six microRNA-mRNA biomodules that optimally classified epithelial cancers from normal epithelial tissue (total accuracy = 93.3%; 95% confidence intervals: 86% - 97%), using penalized logistic regression (PLR) algorithm and three-fold cross-validation. Three of these biomodules are individually sufficient to cluster epithelial cancers from normal tissue using mutual information distance. The biomodules contain 10 distinct microRNAs and 98 distinct genes, including well known tumor markers such as miR-15a, miR-30e, IRAK1, TGFBR2, DUSP16, CDC25B and PDCD2. In addition, there is a significant enrichment (Fisher's exact test p=3×10(-10)) between putative microRNA-target gene pairs reported in five microRNA target databases and the inversely correlated micro-RNA-mRNA pairs in the biomodules. Further, microRNAs and genes in the biomodules were found in abstracts mentioning epithelial cancers (Fisher Exact Test, unadjusted p<0.05). Taken together, these results strongly suggest that the discovered microRNA-mRNA biomodules correspond to regulatory mechanisms common to human epithelial cancer samples. In conclusion, we developed and evaluated a novel comprehensive method to systematically identify, on a genome scale, microRNA-mRNA expression biomodules common to distinct cancers of the same tissue. These biomodules also comprise novel microRNA and genes as well as an imputed regulatory network, which may accelerate the work of cancer biologists as large regulatory maps of cancers can be drawn efficiently for hypothesis generation.

Project description:Background: Ovarian cancer (OC) is the most lethal malignancy in the female reproductive system. Growing evidences demonstrates that competing endogenous RNA (ceRNA) network play crucial roles in the occurrence and progression of tumors. Therefore, we aimed to explore and identify novel mRNA-miRNA-lncRNA ceRNA networks associated with prognosis of OC. Methods: The differentially expressed gene (DEGs) of four expression profiles datasets (GSE5438, GSE40595, GSE38666 and GSE26712) were collected from Gene Expression Omnibus (GEO) database and analyzed with NetworkAnalyst. Intersection of DEGs were further employed for Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis. Protein-protein interaction (PPI) network and hub genes of DEGs were also identified. The expression levels and survival analysis of the hub genes in OC and their upstream miRNAs and lncRNAs were performed by various bioinformatics databases. More importantly, ceRNA networks were constructed based on mRNA-miRNA-lncRNA in OC. Results: A total of 178 DEGs including 38 upregulated and 140 downregulated genes from intersected DEGs of four expression profiles were identified in OC. Functional enrichment analysis suggested that the commonly DEGs were enriched in regulating enzyme inhibitor activity, glycosaminoglycan and G protein-coupled receptor binding, cell morphogenesis, and involved in pathways including metabolic process, proteoglycans in cancer. Top 10 hub genes with higher connectivity degree were selected for subsequent expression and prognosis analysis. After take expression levels and prognostic roles of hub genes and their upstream miRNAs and lncRNAs in OC into consideration, 2 mRNAs (TACC3 and CXCR4), 2 miRNAs (hsa-miR-425-5p and hsa-miR-146a-5p) and 3 lncRNAs (FUT8-AS1, LINC00665 and LINC01535) were significantly associated with the poor prognosis of OC. The mRNA-miRNA-lncRNA networks (TACC3-hsa-miR-425-5p-FUT8-AS1 and CXCR4-hsa-miR-146a-5p-LINC00665/LINC01535) were eventually constructed in OC based on ceRNA mechanism. Conclusion: We successfully constructed novel ceRNA network associated with the prognosis of ovarian cancer, which may provide a new strategy for early diagnosis and therapeutic intervention of OC.

Dataset Information

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

Publications

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

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