Systematic pathway enrichment analysis of a genome-wide association study on breast cancer survival reveals an influence of genes involved in cell adhesion and calcium signaling on the patients' clinical outcome

对一项关于乳腺癌生存的全基因组关联研究进行系统性通路富集分析,揭示了参与细胞黏附和钙信号传导的基因对患者临床结局的影响。

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Abstract

Genome-wide association studies (GWASs) may help to understand the effects of genetic polymorphisms on breast cancer (BC) progression and survival. However, they give only a focused view, which cannot capture the tremendous complexity of this disease. Therefore, we investigated data from a previously conducted GWAS on BC survival for enriched pathways by different enrichment analysis tools using the two main annotation databases Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The goal was to identify the functional categories (GO terms and KEGG pathways) that are consistently overrepresented in a statistically significant way in the list of genes generated from the single nucleotide polymorphism (SNP) data. The SNPs with allelic p-value cut-offs 0.005 and 0.01 were annotated to the genes by excluding or including a 20 kb up-and down-stream sequence of the genes and analyzed by six different tools. We identified eleven consistently enriched categories, the most significant ones relating to cell adhesion and calcium ion binding. Moreover, we investigated the similarity between our GWAS and the enrichment analyses of twelve published gene expression signatures for breast cancer prognosis. Five of them were commonly used and commercially available, five were based on different aspects of metastasis formation and two were developed from meta-analyses of published prognostic signatures. This comparison revealed similarities between our GWAS data and the general and the specific brain metastasis gene signatures as well as the Oncotype DX signature. As metastasis formation is a strong indicator of a patient's prognosis, this result reflects the survival aspect of the conducted GWAS and supports cell adhesion and calcium signaling as important pathways in cancer progression.

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