Identifying mRNA targets of microRNA in clear cell renal cell carcinoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE16441 | GEO | 2011/02/28
SECONDARY ACCESSION(S): PRJNA116271
REPOSITORIES: GEO
Similar Datasets
Project description:A bioinformatic approach to identify targets of microRNA in cancer. Keywords: Patient sample study Samples GSM413237-GSM413270: Total RNA from 17 RCC tumors and 17 corresponding non-tumor samples was hybridized against a common reference RNA (Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000;406:747-752) for gene expression analysis. Samples GSM413271-GSM413304: MicroRNA from 17 RCC tumors and 17 corresponding non-tumor samples were hybridized on a single channel platform for miRNA expression analysis.
2011-02-28 | E-GEOD-16441 | biostudies-arrayexpress
Project description:BackgroundMicroRNA regulate mRNA levels in a tissue specific way, either by inducing degradation of the transcript or by inhibiting translation or transcription. Putative mRNA targets of microRNA identified from seed sequence matches are available in many databases. However, such matches have a high false positive rate and cannot identify tissue specificity of regulation.ResultsWe describe a simple method to identify direct mRNA targets of microRNA dysregulated in cancers from expression level measurements in patient matched tumor/normal samples. The word "direct" is used here in a strict sense to: a) represent mRNA which have an exact seed sequence match to the microRNA in their 3'UTR, b) the seed sequence match is strictly conserved across mouse, human, rat and dog genomes, c) the mRNA and microRNA expression levels can distinguish tumor from normal with high significance and d) the microRNA/mRNA expression levels are strongly and significantly anti-correlated in tumor and/or normal samples. We apply and validate the method using clear cell Renal Cell Carcinoma (ccRCC) and matched normal kidney samples, limiting our analysis to mRNA targets which undergo degradation of the mRNA transcript because of a perfect seed sequence match. Dysregulated microRNA and mRNA are first identified by comparing their expression levels in tumor vs normal samples. Putative dysregulated microRNA/mRNA pairs are identified from these using seed sequence matches, requiring that the seed sequence be conserved in human/dog/rat/mouse genomes. These are further pruned by requiring a strong anti-correlation signature in tumor and/or normal samples. The method revealed many new regulations in ccRCC. For instance, loss of miR-149, miR-200c and mir-141 causes gain of function of oncogenes (KCNMA1, LOX), VEGFA and SEMA6A respectively and increased levels of miR-142-3p, miR-185, mir-34a, miR-224, miR-21 cause loss of function of tumor suppressors LRRC2, PTPN13, SFRP1, ERBB4, and (SLC12A1, TCF21) respectively. We also found strong anti-correlation between VEGFA and the miR-200 family of microRNA: miR-200a*, 200b, 200c and miR-141. Several identified microRNA/mRNA pairs were validated on an independent set of matched ccRCC/normal samples. The regulation of SEMA6A by miR-141 was verified by a transfection assay.ConclusionsWe describe a simple and reliable method to identify direct gene targets of microRNA in any cancer. The constraints we impose (strong dysregulation signature for microRNA and mRNA levels between tumor/normal samples, evolutionary conservation of seed sequence and strong anti-correlation of expression levels) remove spurious matches and identify a subset of robust, tissue specific, functional mRNA targets of dysregulated microRNA.
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Project description:Although several studies have reported that microRNA (miR)-92b-3p is involved in various cellular processes related to carcinogenesis, its physiological role in clear cell renal cell carcinoma (ccRCC) remains unclear. To clarify the role of miR-92b-3p in ccRCC, we compared miR-92b-3p expression levels in ccRCC tissues and adjacent normal renal tissues. Significant upregulation of miR-92b-3p was observed in ccRCC tissues. Overexpression of miR-92b-3p using a miRNA mimic promoted proliferation, migration, and invasion activities of ACHN cells. Functional inhibition of miR-92b-3p by a hairpin miRNA inhibitor suppressed Caki-2 cell growth and invasion activities in vitro. Mechanistically, it was found that miR-92b-3p directly targeted the TSC1 gene, a known upstream regulator of mTOR. Overexpression of miR-92b-3p decreased the protein expression of TSC1 and enhanced the downstream phosphorylation of p70S6 kinase, suggesting that the mTOR signaling pathway was activated by miR-92b-3p in RCC cells. Importantly, a multivariate Cox proportion hazard model, based on TNM staging and high levels of miR-92b-3p, revealed that miR-92b-3p expression (high vs. low hazard ratio, 2.86; 95% confidence interval, 1.20-6.83; P = .018) was a significant prognostic factor for overall survival of ccRCC patients with surgical management. Taken together, miR-92b-3p was found to act as an oncomiR, promoting cell proliferation by downregulating TSC1 in ccRCC.
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Project description:Clear-cell renal cell carcinomas (ccRCC) can be divided into four transcriptomic subtypes, two of which have a favorable and two an unfavorable prognosis. To assess mechanisms driving these subtypes, we investigated their miRNA expression patterns. miRNAs are master regulators of mRNAs, that are widely deregulated in cancer. Unsupervised clustering in our dataset (n = 128) and The Cancer Genome Atlas (TCGA) validation set identified two distinct miRNA clusters that overlapped with the transcriptomic subtypes, underscoring the validity of these subtypes on a multi-omics level and suggesting a driving role for miRNAs. Discriminatory miRNAs for the favorable subtypes repressed epithelial-to-mesenchymal transition, based on gene set enrichment analysis and target-mRNA expression levels. Strikingly, throughout the entire dataset, miRNAs associated with favorable subtypes were also associated with longer overall survival after diagnosis, and miRNAs associated with unfavorable subtypes with shorter overall survival (Pearson r = -0.54, p<0.0001). These findings indicate a general shift in miRNA expression between more and less aggressive tumors. This adds to current literature, which usually suggests only a small subset of miRNAs as markers of aggressive disease. In conclusion, this study reveals distinct mRNA expression patterns underlying transcriptomic ccRCC-subtypes, whereby miRNAs associated with favorable subtypes counteract epithelial-to-mesenchymal transition. There is a general shift in miRNA expression in ccRCC, between more and less aggressive tumors.
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Project description:Intratumoral heterogeneity (IH) has been recently described as an important contributor to tumor growth through a branched rather than a linear pattern of tumor evolution for renal cell carcinoma. As to whether the miRNA profiling of the different and heterogeneous areas is the same or not, it is not known. This study analyzed the differences and similarities of the miRNA profiles in histologically distinct regions within several RCC tumors. The observed differences may have great implications for the development of predictive biomarkers and the identification of druggable targets with improvement of combinatorial therapeutic approaches for the effective treatment of kidney cancer, as well as for the identification of circulating malignant cells that can be useful to detect tumor recurrences.
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Project description:Clear-cell renal cell carcinomas (ccRCCs) are genetically heterogeneous tumors presenting diverse clinical courses. Epithelial-mesenchymal transition (EMT) is a crucial process involved in initiation of metastatic cascade. The aim of our study was to identify an integrated miRNA/mRNA signature associated with metastasis and prognosis in ccRCC through targeted approach based on analysis of miRNAs/mRNAs associated with EMT. A cohort of 230 ccRCC was included in our study and further divided into discovery, training and validation cohorts. EMT markers were evaluated in ccRCC tumor samples, which were grouped accordingly to EMT status. By use of large-scale miRNA/mRNA expression profiling, we identified miRNA/mRNA with significantly different expression in EMT-positive tumors and selected 41 miRNAs/mRNAs for training phase of the study to evaluate their diagnostic and prognostic potential. Fifteen miRNAs/mRNAs were analyzed in the validation phase, where all evaluated miRNA/mRNA candidates were confirmed to be significantly deregulated in tumor tissue. Some of them significantly differed in metastatic tumors, correlated with clinical stage, with Fuhrman grade and with overall survival. Further, we established an EMT-based stage-independent prognostic scoring system enabling identification of ccRCC patients at high-risk of cancer-related death. Finally, we confirmed involvement of miR-429 in EMT regulation in RCC cells in vitro.
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Project description:To evaluate the potential application of computed tomography (CT) radiomics in the prediction of BRCA1-associated protein 1 (BAP1) mutation status in patients with clear-cell renal cell carcinoma (ccRCC). In this retrospective study, clinical and CT imaging data of 54 patients were retrieved from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma database. Among these, 45 patients had wild-type BAP1 and nine patients had BAP1 mutation. The texture features of tumor images were extracted using the Matlab-based IBEX package. To produce class-balanced data and improve the stability of prediction, we performed data augmentation for the BAP1 mutation group during cross validation. A model to predict BAP1 mutation status was constructed using Random Forest Classification algorithms, and was evaluated using leave-one-out-cross-validation. Random Forest model of predict BAP1 mutation status had an accuracy of 0.83, sensitivity of 0.72, specificity of 0.87, precision of 0.65, AUC of 0.77, F-score of 0.68. CT radiomics is a potential and feasible method for predicting BAP1 mutation status in patients with ccRCC.
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Project description:While opioids constitute the major component of perioperative analgesic regimens for surgery in general, a variety of evidence points to an association between perioperative opioid exposure and longer term oncologic outcomes. The mechanistic details underlying these effects are not well understood. In this study, we focused on clear cell renal cell carcinoma (ccRCC) and utilized RNA sequencing and outcome data from both The Cancer Genome Atlas, as well as a local patient cohort to identify survival-associated gene coexpression networks. We then projected drug-induced transcriptional profiles from in vitro cancer cells to predict drug effects on these networks and recurrence-free, cancer-specific, and overall survival. The opioid receptor agonist, leu-enkephalin, was predicted to have antisurvival effects in ccRCC, primarily through Th2 immune- and NRF2-dependent macrophage networks. Conversely, the antagonist, naloxone, was predicted to have prosurvival effects, primarily through angiogenesis, fatty acid metabolism, and hemopoesis pathways. Eight coexpression networks associated with survival endpoints in ccRCC were identified, and master regulators of the transition from the normal to disease state were inferred, a number of which are linked to opioid pathways. These results are the first to suggest a mechanism for opioid effects on cancer outcomes through modulation of survival-associated coexpression networks. While we focus on ccRCC, this methodology may be employed to predict opioid effects on other cancer types and to personalize analgesic regimens in patients with cancer for optimal outcomes. SIGNIFICANCE: This study suggests a possible molecular mechanism for opioid effects on cancer outcomes generally, with implications for personalization of analgesic regimens.
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2022-04-16 | GSE200852 | GEO
Project description:With the recent research development, the importance of microRNAs (miRNAs) in renal clear cell carcinoma (CCRCC) has become widely known. The purpose of this study is to screen out the potential biomarkers of renal clear cell carcinoma (CCRCC) by microarray analysis. The miRNA chip (GSE16441) and mRNA chip (GSE66270) related to CCRCC were downloaded from the Gene Expression Omnibus (GEO) database. After data filtering and pretreating, R platform and a series of analysis tools (funrich3.1.3, string, Cytoscape_ 3.2.1, David, etc.) were used to analyze chip data and identify the specific and highly sensitive biomarkers. Finally, by constructing the miRNA -mRNA interaction network, it was determined that five miRNAs (hsa-mir-199a-5p, hsa-mir-199b-5p, hsa-mir-532-3p and hsa-mir-429) and two key genes (ETS1 and hapln1) are significantly related to the overall survival rate of patients.
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