Dataset Information

Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data.

ABSTRACT:

Background

Cancer is a complex disease with a lucid etiology and in understanding the causation, we need to appreciate this complexity.

Objective

Here we are aiming to gain insights into the genetic associations of prostate cancer through a network-based systems approach using the BC3Net algorithm.

Methods

Specifically, we infer a prostate cancer Gene Regulatory Network (GRN) from a large-scale gene expression data set of 333 patient RNA-seq profiles obtained from The Cancer Genome Atlas (TCGA) database.

Results

We analyze the functional components of the inferred network by extracting subnetworks based on biological process information and interpret the role of known cancer genes within each process. Fur-thermore, we investigate the local landscape of prostate cancer genes and discuss pathological associa-tions that may be relevant in the development of new targeted cancer therapies.

Conclusion

Our network-based analysis provides a practical systems biology approach to reveal the collective gene-interactions of prostate cancer. This allows a close interpretation of biological activity in terms of the hallmarks of cancer.

SUBMITTER: Moore D

PROVIDER: S-EPMC6446481 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data.

Moore Daniel D Simoes Ricardo de Matos RM Dehmer Matthias M Emmert-Streib Frank F

Current genomics 20190101 1

<h4>Background</h4>Cancer is a complex disease with a lucid etiology and in understanding the causation, we need to appreciate this complexity.<h4>Objective</h4>Here we are aiming to gain insights into the genetic associations of prostate cancer through a network-based systems approach using the BC3Net algorithm.<h4>Methods</h4>Specifically, we infer a prostate cancer Gene Regulatory Network (GRN) from a large-scale gene expression data set of 333 patient RNA-seq profiles obtained from The Cance ...[more]

PMID: 31015790

Similar Datasets

Project description:BackgroundAlternative splicing is a ubiquitous post-transcriptional regulation mechanism in most eukaryotic genes. Aberrant splicing isoforms and abnormal isoform ratios can contribute to cancer development. Kinase genes are key regulators of multiple cellular processes. Many kinases are found to be oncogenic and have been intensively investigated in the study of cancer and drugs. RNA-Seq provides a powerful technology for genome-wide study of alternative splicing in cancer besides the conventional gene expression profiling. But this potential has not been fully demonstrated yet.MethodsWe characterized the transcriptome profile of prostate cancer using RNA-Seq data from viewpoints of both differential expression and differential splicing, with an emphasis on kinase genes and their splicing variations. We built a pipeline to conduct differential expression and differential splicing analysis, followed by functional enrichment analysis. We performed kinase domain analysis to identify the functionally important candidate kinase gene in prostate cancer, and calculated the expression levels of isoforms to explore the function of isoform switching of kinase genes in prostate cancer.ResultsWe identified distinct gene groups from differential expression and splicing analyses, which suggested that alternative splicing adds another level to gene expression regulation. Enriched GO terms of differentially expressed and spliced kinase genes were found to play different roles in regulation of cellular metabolism. Function analysis on differentially spliced kinase genes showed that differentially spliced exons of these genes are significantly enriched in protein kinase domains. Among them, we found that gene CDK5 has isoform switching between prostate cancer and benign tissues, which may affect cancer development by changing androgen receptor (AR) phosphorylation. The observation was validated in another RNA-Seq dataset of prostate cancer cell lines.ConclusionsOur work characterized the expression and splicing profiles of kinase genes in prostate cancer and proposed a hypothetical model on isoform switching of CDK5 and AR phosphorylation in prostate cancer. These findings bring new understanding to the role of alternatively spliced kinases in prostate cancer and also demonstrate the use of RNA-Seq data in studying alternative splicing in cancer.

Dataset Information

Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data.

Background

Objective

Methods

Results

Conclusion

Publications

Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data.

Similar Datasets

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