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Computational identification of mutually exclusive transcriptional drivers dysregulating metastatic microRNAs in prostate cancer.

ABSTRACT: Androgen-ablation therapies, which are the standard treatment for metastatic prostate cancer, invariably lead to acquired resistance. Hence, a systematic identification of additional drivers may provide useful insights into the development of effective therapies. Numerous microRNAs that are critical for metastasis are dysregulated in metastatic prostate cancer, but the underlying molecular mechanism is poorly understood. We perform an integrative analysis of transcription factor (TF) and microRNA expression profiles and computationally identify three master TFs, AR, HOXC6 and NKX2-2, which induce the aberrant metastatic microRNA expression in a mutually exclusive fashion. Experimental validations confirm that the three TFs co-dysregulate a large number of metastasis-associated microRNAs. Moreover, their overexpression substantially enhances cell motility and is consistently associated with a poor clinical outcome. Finally, the mutually exclusive overexpression between AR, HOXC6 and NKX2-2 is preserved across various tissues and cancers, suggesting that mutual exclusivity may represent an intrinsic characteristic of driver TFs during tumorigenesis.

SUBMITTER: Xue M

PROVIDER: S-EPMC5394245 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Computational identification of mutually exclusive transcriptional drivers dysregulating metastatic microRNAs in prostate cancer.

Xue Mengzhu M Liu Haiyue H Zhang Liwen L Chang Hongyuan H Liu Yuwei Y Du Shaowei S Yang Yingqun Y Wang Peng P

Nature communications 20170411

Androgen-ablation therapies, which are the standard treatment for metastatic prostate cancer, invariably lead to acquired resistance. Hence, a systematic identification of additional drivers may provide useful insights into the development of effective therapies. Numerous microRNAs that are critical for metastasis are dysregulated in metastatic prostate cancer, but the underlying molecular mechanism is poorly understood. We perform an integrative analysis of transcription factor (TF) and microRN ...[more]

PMID: 28397780

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Project description:BackgroundDuring alternative splicing, the inclusion of an exon in the final mRNA molecule is determined by nuclear proteins that bind cis-regulatory sequences in a target pre-mRNA molecule. A recent study suggested that the regulatory codes of individual RNA-binding proteins may be nearly immutable between very diverse species such as mammals and insects. The model system Drosophila melanogaster therefore presents an excellent opportunity for the study of alternative splicing due to the availability of quality EST annotations in FlyBase.MethodsIn this paper, we describe an in silico analysis pipeline to extract putative exonic splicing regulatory sequences from a multiple alignment of 15 species of insects. Our method, ESTs-to-ESRs (E2E), uses graph analysis of EST splicing graphs to identify mutually exclusive (ME) exons and combines phylogenetic measures, a sliding window approach along the multiple alignment and the Welch's t statistic to extract conserved ESR motifs.ResultsThe most frequent 100% conserved word of length 5 bp in different insect exons was "ATGGA". We identified 799 statistically significant "spike" hexamers, 218 motifs with either a left or right FDR corrected spike magnitude p-value < 0.05 and 83 with both left and right uncorrected p < 0.01. 11 genes were identified with highly significant motifs in one ME exon but not in the other, suggesting regulation of ME exon splicing through these highly conserved hexamers. The majority of these genes have been shown to have regulated spatiotemporal expression. 10 elements were found to match three mammalian splicing regulator databases. A putative ESR motif, GATGCAG, was identified in the ME-13b but not in the ME-13a of Drosophila N-Cadherin, a gene that has been shown to have a distinct spatiotemporal expression pattern of spliced isoforms in a recent study.ConclusionsAnalysis of phylogenetic relationships and variability of sequence conservation as implemented in the E2E spikes method may lead to improved identification of ESRs. We found that approximately half of the putative ESRs in common between insects and mammals have a high statistical support (p < 0.01). Several Drosophila genes with spatiotemporal expression patterns were identified to contain putative ESRs located in one exon of the ME exon pairs but not in the other.

Dataset Information

Computational identification of mutually exclusive transcriptional drivers dysregulating metastatic microRNAs in prostate cancer.

Publications

Computational identification of mutually exclusive transcriptional drivers dysregulating metastatic microRNAs in prostate cancer.

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