PO.CL09.04 · 临床研究
BMI特异性和亚型特异性的分子聚类揭示尼日利亚与美国队列乳腺癌中不同的肥胖机制
BMI- and subtype-specific molecular clusters reveal distinct obesity mechanisms in breast cancer across Nigerian and U.S. cohorts
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景：肥胖是乳腺癌的主要危险因素，但其生物学机制在非洲人群中仍未得到充分表征。我们假设，独特的肥胖相关分子特征将区分肥胖与正常体重的尼日利亚女性，并揭示美国女性中亚型特异性的模式。
方法：对46例尼日利亚女性（MEND）的肿瘤进行了靶向基因表达谱分析（NanoString，785个基因），并分析了Women's Circle of Health Study（WCHS；n=367；非洲和欧洲血统）的公开基因表达数据。使用R（v4.5.0）中的基因集变异分析，结合KEGG和Reactome基因集，计算肥胖相关通路（糖酵解、炎症、细胞外基质（ECM）重塑、脂肪因子信号、胰岛素/IGF1信号、缺氧、胆固醇生物合成）的富集评分。二分网络聚类识别共现的机制簇。采用Firth逻辑回归检验MEND中簇归属与BMI的关联，采用标准逻辑回归检验WCHS中簇归属与亚型和血统的关联，并对协变量进行校正（MEND：年龄、亚型、绝经状态；WCHS：年龄）。
结果：MEND参与者平均48.7（10.6）岁；WCHS平均54.07（11.99）岁。在MEND中，出现三个簇（Q=0.14，p<0.05）：簇1（缺氧、胆固醇生物合成）、簇2（ECM重塑、脂肪因子、胰岛素/IGF1信号）和簇3（糖酵解、炎症）。超重/肥胖女性归属簇2的几率更高（aOR=5.4，95% CI：1.3-31.3），而正常体重女性富集于簇1（0.12，0.02-0.54）。在WCHS中，六个富集评分产生三个簇（Q=0.10，p<0.05）：簇1（炎症、缺氧）、簇2（ECM重塑、胰岛素/IGF1信号）和簇3（脂肪因子信号、糖酵解）。簇归属不随血统而异，但亚型关联（以Luminal A为参照）十分显著：簇1与Luminal A强关联（Luminal B：0.33，0.18-0.61；HER2：0.15，0.06-0.34；三阴性：0.19，0.11-0.34），簇2与Luminal B（3.47，1.8-6.9）和HER2（4.09，1.9-8.99）关联，簇3与三阴性（3.15，1.78-5.73）关联。
结论：肥胖相关机制因BMI和亚型而异。ECM重塑和生长因子信号在肥胖相关肿瘤中占主导，而缺氧和脂质代谢则表征正常体重肿瘤。亚型特异性聚类提示存在超越BMI的异质性。这些发现凸显了精准预防和治疗的机会，包括代谢通路靶向以及在高风险亚型中潜在使用GLP-1受体激动剂。
披露：使用生成式AI（Microsoft Copilot）协助语言编辑；作者审阅并核实了所有内容。
查看英文原文 English abstract
Background: Obesity is a major breast cancer risk factor, yet its biological mechanisms remain poorly characterized in African populations. We hypothesized that distinct obesity-associated molecular signatures would differentiate obese from normal-weight Nigerian women and reveal subtype-specific patterns in U.S. women.
Methods: Targeted gene expression profiling (NanoString, 785 genes) was performed on tumors from 46 Nigerian women (MEND), and publicly available gene expression data from Women's Circle of Health Study (WCHS; n=367; African and European ancestry) were analyzed. Enrichment scores for obesity-related pathways (glycolysis, inflammation, Extracellular matrix (ECM) remodeling, adipokine signaling, insulin/IGF1 signaling, hypoxia, cholesterol biosynthesis) were computed using Gene Set Variation Analysis in R (v4.5.0) with KEGG and Reactome gene sets. Bipartite network clustering identified co-occurring mechanism clusters. Associations were tested for cluster membership with BMI using Firth logistic regression for MEND, and with subtype and ancestry using standard logistic regression for WCHS, adjusting for covariates (MEND: age, subtype, menopausal status; WCHS: age).
Results: MEND participants averaged 48.7 (10.6) years; WCHS averaged 54.07 (11.99) years. In MEND, three clusters emerged (Q=0.14, p<0.05): Cluster 1 (hypoxia, cholesterol biosynthesis), Cluster 2 (ECM remodeling, adipokine, insulin/IGF1 signaling), and Cluster 3 (glycolysis, inflammation). Overweight/obese women had higher odds of Cluster 2 (aOR=5.4, 95% CI: 1.3-31.3), while normal-weight women were enriched for Cluster 1 (0.12, 0.02-0.54). In WCHS, six enrichment scores yielded three clusters (Q=0.10, p<0.05): Cluster 1 (inflammation, hypoxia), Cluster 2 (ECM remodeling, insulin/IGF1 signaling), and Cluster 3 (adipokine signaling, glycolysis). Cluster membership did not differ by ancestry, but subtype associations (Luminal A reference) were striking: Cluster 1 strongly associated with Luminal A (Luminal B: 0.33, 0.18-0.61; HER2: 0.15, 0.06-0.34; Triple Neg: 0.19, 0.11-0.34), Cluster 2 with Luminal B (3.47, 1.8-6.9) and HER2 (4.09, 1.9-8.99), and Cluster 3 with Triple Negative (3.15, 1.78-5.73).
Conclusions: Obesity-linked mechanisms differ by BMI and subtype. ECM remodeling and growth factor signaling dominate obesity-related tumors, while hypoxia and lipid metabolism characterize normal-weight tumors. Subtype-specific clustering suggests heterogeneity beyond BMI. Findings highlight opportunities for precision prevention and treatment, including metabolic pathway targeting and potential use of GLP-1 receptor agonists in high-risk subtypes.
Disclosure: Generative AI (Microsoft Copilot) was used to assist with language editing; authors reviewed and verified all content.
利益披露 Disclosure
O. Osazuwa-Peters, None..
J. K. Byemerwa, None..
O. Salako, None..
A. Daramola, None..
O. Alatise, None..
G. Ogun, None..
T. Akinyemiju, None.