Dataset Information

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes.

ABSTRACT: High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ-confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ-confined and metastatic prostate cancer.

SUBMITTER: Hicks C

PROVIDER: S-EPMC5391982 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes.

Hicks Chindo C Ramani Ritika R Sartor Oliver O Bhalla Ritu R Miele Lucio L Dlamini Zodwa Z Gumede Njabulo N

Biomarker insights 20170316

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ-confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene s ...[more]

PMID: 28469398

Similar Datasets

Project description:Pathway analysis of large-scale omics data assists us with the examination of the cumulative effects of multiple functionally related genes, which are difficult to detect using the traditional single gene/marker analysis. So far, most of the genomic studies have been conducted in a single domain, e.g., by genome-wide association studies (GWAS) or microarray gene expression investigation. A combined analysis of disease susceptibility genes across multiple platforms at the pathway level is an urgent need because it can reveal more reliable and more biologically important information.We performed an integrative pathway analysis of a GWAS dataset and a microarray gene expression dataset in prostate cancer. We obtained a comprehensive pathway annotation set from knowledge-based public resources, including KEGG pathways and the prostate cancer candidate gene set, and gene sets specifically defined based on cross-platform information. By leveraging on this pathway collection, we first searched for significant pathways in the GWAS dataset using four methods, which represent two broad groups of pathway analysis approaches. The significant pathways identified by each method varied greatly, but the results were more consistent within each method group than between groups. Next, we conducted a gene set enrichment analysis of the microarray gene expression data and found 13 pathways with cross-platform evidence, including "Fc gamma R-mediated phagocytosis" (P GWAS = 0.003, P expr < 0.001, and P combined = 6.18 × 10(-8)), "regulation of actin cytoskeleton" (P GWAS = 0.003, P expr = 0.009, and P combined = 3.34 × 10(-4)), and "Jak-STAT signaling pathway" (P GWAS = 0.001, P expr = 0.084, and P combined = 8.79 × 10(-4)).Our results provide evidence at both the genetic variation and expression levels that several key pathways might have been involved in the pathological development of prostate cancer. Our framework that employs gene expression data to facilitate pathway analysis of GWAS data is not only feasible but also much needed in studying complex disease.

Dataset Information

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes.

Publications

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets