Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.

中文翻译：

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Case-Case 全基因组分析确定了赋予乳腺癌风险的亚型信息变异。


乳腺癌包括几种亚型，具有不同的特征性生物学、病理学和临床特征。阐明亚型特异性遗传病因可以提供对乳腺癌异质性的见解，以促进开发改进的预防和治疗方法。在这项研究中，我们通过将病例-病例全基因组关联研究 （CC-GWAS） 方法应用于乳腺癌协会联盟的汇总统计数据，对五种乳腺癌亚型进行了成对病例-病例比较。该方法确定了 13 个具有统计学意义的基因座和 8 个提示性基因座，其中大多数是通过三阴性乳腺癌 （TNBC） 和管腔 A 乳腺癌之间的比较确定的。在考虑了先前报道的乳腺癌易感性变异后，12 个位点中先导变异的关联仍然具有统计学意义，其中两个是全基因组显著的。与管腔癌相比，在几个基因座（例如 3q26.31/TNFSF10、8q22.3/NACAP1/GRHL2 和 8q23.3/LINC00536/TRPS1）的几个基因座精细定位涉及推定的功能/因果变异和风险基因。功能研究进一步确定 rs16867605 在 8q22.3 处是调节 GRHL2 增强子活性的 SNP。得出亚型信息多基因风险评分 （PRS），亚型信息量高 PRS 的患者被诊断为 TNBC 而不是管腔癌的风险增加高达 2 倍。在调整了源自癌症基因组图谱和非洲血统乳腺癌遗传联盟中传统病例对照 GWAS 的 TNBC PRS 后，CC-GWAS PRS 仍然具有统计学意义。 CC-GWAS PRS 还与乳腺癌患者的总生存期和疾病特异性生存期相关。总体而言，这些发现促进了我们对乳腺癌亚型遗传病因的理解，尤其是 TNBC。意义： 乳腺癌亚型信息遗传风险变异的发现促进了我们对乳腺癌病因异质性的理解，这可能会加速识别靶点和个性化预防和治疗策略。