7 research outputs found
Connections between risk SNP, biological CRC genes and drugs indicated for other diseases.
<p>Connections between risk SNP, biological CRC genes and drugs indicated for other diseases.</p
Use of Genome-Wide Association Studies for Cancer Research and Drug Repositioning
<div><p>Although genome-wide association studies have identified many risk loci associated with colorectal cancer, the molecular basis of these associations are still unclear. We aimed to infer biological insights and highlight candidate genes of interest within GWAS risk loci. We used an <i>in silico</i> pipeline based on functional annotation, quantitative trait loci mapping of cis-acting gene, PubMed text-mining, protein-protein interaction studies, genetic overlaps with cancer somatic mutations and knockout mouse phenotypes, and functional enrichment analysis to prioritize the candidate genes at the colorectal cancer risk loci. Based on these analyses, we observed that these genes were the targets of approved therapies for colorectal cancer, and suggested that drugs approved for other indications may be repurposed for the treatment of colorectal cancer. This study highlights the use of publicly available data as a cost effective solution to derive biological insights, and provides an empirical evidence that the molecular basis of colorectal cancer can provide important leads for the discovery of new drugs.</p></div
Summary of connections between risk SNPs, biological candidate genes from each risk locus, genes from the PPI network and approved CRC drugs.
<p>Black lines indicate connections.</p
Biological genes in the CRC risk loci with a score≥2.
<p>Biological genes in the CRC risk loci with a score≥2.</p
Detailed summary of the connections between risk SNPs, biological candidate genes from each risk locus, genes from the PPI network and drugs indicated for other diseases.
<p>Detailed summary of the connections between risk SNPs, biological candidate genes from each risk locus, genes from the PPI network and drugs indicated for other diseases.</p
An overview of the study design.
<p>One hundred and forty-seven candidate genes were obtained from 50 CRC risk loci. A bioinformatics pipeline was developed for the prioritization of these candidate genes. Seven criteria were used to score the genes: (1) CRC risk missense variant; (2) <i>cis</i>-eQTL; (3) PubMed text mining; (4) PPI; (5) cancer somatic mutation; (6) knockout mouse phenotype; and (7) functional enrichment. Extent of overlap with target genes for approved CRC drugs was also assessed.</p
Summary of 50 colorectal cancer GWAS risk alleles obtained from National Human Genome Research Institute.
<p>Summary of 50 colorectal cancer GWAS risk alleles obtained from National Human Genome Research Institute.</p