组织特异性基因网络中的共表达将癌症易感基因座中的基因与已知的体细胞驱动基因联系起来。

IF 2.1 4区 医学 Q3 GENETICS & HEREDITY BMC Medical Genomics Pub Date : 2024-07-15 DOI:10.1186/s12920-024-01941-4
Carlos G Urzúa-Traslaviña, Tijs van Lieshout, Floranne Boulogne, Kevin Domanegg, Mahmoud Zidan, Olivier B Bakker, Annique Claringbould, Jeroen de Ridder, Wilbert Zwart, Harm-Jan Westra, Patrick Deelen, Lude Franke
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引用次数: 0

摘要

背景:癌症的遗传背景仍然十分复杂,对其进行整合具有挑战性。已知基因中的许多体细胞突变可导致和驱动癌症,而癌症的全基因组关联研究(GWAS)则揭示了许多与癌症相关的种系风险因素。然而,已知的体细胞驱动基因与来自 GWAS 基因位点的定位候选基因之间的重叠却少得令人吃惊。我们假设,来自多个独立癌症 GWAS 位点的基因应显示出组织特异性共调模式,并汇聚到癌症特异性驱动基因上:结果:我们对近期乳腺癌、前列腺癌、结直肠癌和皮肤癌的强效 GWAS 进行了研究,估算了基因间的共表达,随后优先选择了与癌症 GWAS 易感基因座中的基因有显著共表达的基因。我们观察到,优先选择的基因强烈富集了 COSMIC、IntOGen 和 Dietlein 等人定义的癌症驱动基因:我们展示了癌症基因组学研究发现的风险位点内的基因是如何通过组织特异性共表达网络与已知癌症驱动基因联系起来的。这提供了一个重要的解释,说明了为什么看似不相关的几组基因携带种系风险因子或体细胞突变,但最终会导致同一种类型的疾病。
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Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes.

Background: The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.

Results: We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.

Conclusion: We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

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来源期刊
BMC Medical Genomics
BMC Medical Genomics 医学-遗传学
CiteScore
3.90
自引率
0.00%
发文量
243
审稿时长
3.5 months
期刊介绍: BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.
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