Department of Paramedicine, Amol School of Paramedical Sciences, Mazandaran University of Medical Sciences, Sari, Iran.
Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Cancer Rep (Hoboken). 2024 Jun;7(6):e2107. doi: 10.1002/cnr2.2107.
Background: Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with cancer risk. GWAS data are important for cancer prevention and understanding the underlying mechanisms of cancer.
This study aimed to investigate the genetic association between different types of cancer using GWAS data and a bioinformatics approach.
The significant GWAS variants associated with more than one cancer type were identified. Common linkage disequilibrium (LD) variants between different types of cancer were identified by 1000 genomes phase 3 LD data. Haplotype blocks were identified by analyzing 1000 Genomes phase 3 genotyping data in the GWAS populations. Subsequent analyses included functional SNP analyses and TCGA gene expression. The results associated with significant GWAS variants (P<5E-8) showed the following haplotype associations in European population: GT rs4808075-rs8170 haplotype on BABAM1 with breast and ovarian cancers, GC rs16857609-rs11693806 haplotype on DIRC3 with breast and thyroid cancers, GCG rs380286-rs401681-rs31487 haplotype on CLPTM1L with skin and lung cancers, GGG rs4430796-rs11651052-rs11263763 haplotype on HNF1B with prostate and endometrial cancers, and GT rs10505477-rs6983267 haplotype on CASC8 associated with colorectal and prostate cancers. All these genes had significantly different expressions in tumor tissues (P<1E-3). In addition, the rs11693806 variant is located in the hsa-miR-873-5p binding site and has an enhancing effect on the hsa-miR-873-5p:DIRC3 interaction.
These novel haplotype structures and miRNA:lncRNA interactions are important for understanding the common genetic link between cancers. These results can potentially be used in genetic panels.
背景：全基因组关联研究（GWAS）已经确定了数百种与癌症风险相关的遗传变异。GWAS 数据对于癌症预防和理解癌症的潜在机制非常重要。
本研究旨在使用 GWAS 数据和生物信息学方法研究不同类型癌症之间的遗传关联。
确定了与多种癌症类型相关的显著 GWAS 变异。通过 1000 基因组相位 3 LD 数据确定了不同类型癌症之间常见的连锁不平衡（LD）变异。通过分析 GWAS 人群中的 1000 基因组相位 3 基因分型数据确定了单倍型块。随后的分析包括功能 SNP 分析和 TCGA 基因表达。与显著 GWAS 变异（P<5E-8）相关的结果显示，欧洲人群中存在以下单倍型关联：BABAM1 上的 GT rs4808075-rs8170 单倍型与乳腺癌和卵巢癌相关，DIRC3 上的 GC rs16857609-rs11693806 单倍型与乳腺癌和甲状腺癌相关，CLPTM1L 上的 GCG rs380286-rs401681-rs31487 单倍型与皮肤癌和肺癌相关，HNF1B 上的 GGG rs4430796-rs11651052-rs11263763 单倍型与前列腺癌和子宫内膜癌相关，CASC8 上的 GT rs10505477-rs6983267 单倍型与结直肠癌和前列腺癌相关。所有这些基因在肿瘤组织中的表达均有显著差异（P<1E-3）。此外，rs11693806 变异位于 hsa-miR-873-5p 结合位点，对 hsa-miR-873-5p:DIRC3 相互作用具有增强作用。
这些新的单倍型结构和 miRNA:lncRNA 相互作用对于理解癌症之间的共同遗传联系非常重要。这些结果可潜在用于遗传面板。
