Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Department of Epidemiology, Zhejiang Chinese Medical University, Zhejiang, China.
Br J Cancer. 2022 Nov;127(8):1507-1514. doi: 10.1038/s41416-022-01923-2. Epub 2022 Jul 26.
The aetiologic role of circulating proteins in the development of breast cancer subtypes is not clear. We aimed to examine the potential causal effects of circulating proteins on the risk of breast cancer by intrinsic-like subtypes within the Mendelian randomisation (MR) framework.
MR was performed using summary statistics from two sources: the INTERVAL protein quantitative trait loci (pQTL) Study (1890 circulating proteins and 3301 healthy individuals) and the Breast Cancer Association Consortium (BCAC; 106,278 invasive cases and 91,477 controls). The inverse-variance (IVW)-weighted method was used as the main analysis to evaluate the associations between genetically predicted proteins and the risk of five different intrinsic-like breast cancer subtypes and the weighted median MR method, the Egger regression, the MR-PRESSO, and the MRLocus method were performed as secondary analysis.
We identified 98 unique proteins significantly associated with the risk of one or more subtypes (Benjamini-Hochberg false discovery rate < 0.05). Among them, 51 were potentially specific to luminal A-like subtype, 14 to luminal B/Her2-negative-like, 11 to triple negative, 3 to luminal B-like, and 2 to Her2-enriched-like breast cancer (n = 81). Associations for three proteins (ICAM1, PLA2R1 and TXNDC12) showed evident heterogeneity across the subtypes. For example, higher levels of genetically predicted ICAM1 (per unit of increase) were associated with an increased risk of luminal B/HER2-negative-like cancer (OR = 1.06, 95% CI = 1.03-1.08, BH-FDR = 2.43 × 10) while inversely associated with triple-negative breast cancer with borderline significance (OR = 0.97, 95% CI = 0.95-0.99, BH-FDR = 0.065, P < 0.005).
Our study found potential causal associations with the risk of subtypes of breast cancer for 98 proteins. Associations of ICAM1, PLA2R1 and TXNDC12 varied substantially across the subtypes. The identified proteins may partly explain the heterogeneity in the aetiology of distinct subtypes of breast cancer and facilitate the personalised risk assessment of the malignancy.
循环蛋白在乳腺癌亚型发展中的病因作用尚不清楚。我们旨在通过孟德尔随机化(MR)框架内的内在相似亚型,研究循环蛋白对乳腺癌风险的潜在因果影响。
使用来自两个来源的汇总统计数据进行 MR 分析:INTERVAL 蛋白定量性状基因座(pQTL)研究(1890 种循环蛋白和 3301 名健康个体)和乳腺癌协会联盟(BCAC;106278 例浸润性病例和 91477 例对照)。主要分析采用逆方差(IVW)加权法,评估遗传预测蛋白与五种不同内在相似乳腺癌亚型风险之间的关联,同时进行加权中位数 MR 法、Egger 回归、MR-PRESSO 和 MRLocus 法分析。
我们确定了 98 种与一种或多种亚型风险显著相关的独特蛋白(Benjamini-Hochberg 假发现率 < 0.05)。其中,51 种可能与 luminal A 样亚型特异相关,14 种与 luminal B/Her2 阴性样相关,11 种与三阴性相关,3 种与 luminal B 样相关,2 种与 Her2 富集样相关(n = 81)。三种蛋白(ICAM1、PLA2R1 和 TXNDC12)的关联在各亚型间存在明显异质性。例如,遗传预测 ICAM1 水平(每单位增加)升高与 luminal B/HER2 阴性样乳腺癌风险增加相关(OR = 1.06,95%CI = 1.03-1.08,BH-FDR = 2.43 × 10),而与三阴性乳腺癌呈负相关,具有边缘显著性(OR = 0.97,95%CI = 0.95-0.99,BH-FDR = 0.065,P < 0.005)。
本研究发现了 98 种与乳腺癌亚型风险相关的潜在因果关系的蛋白。ICAM1、PLA2R1 和 TXNDC12 的关联在各亚型间存在显著差异。所鉴定的蛋白可能部分解释了不同乳腺癌亚型发病机制的异质性,并促进了恶性肿瘤的个体化风险评估。