Background: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements across benign lobules and breast cancers (BCs), and how well DSP aligns with standard immunoassays. Methods: We performed a pilot using tissues from the Mayo Clinic BBD cohort using TMAs representing four contexts: terminal duct lobular units (TDLUs) from BBD biopsies preceding BC and matched BBD-controls, subsequent BCs, and BC-associated TDLUs. We profiled 79 proteins by DSP (37 retained after QC) and benchmarked against chromogenic IHC and OPAL immunofluorescence. Reproducibility was evaluated using intraclass correlation coefficients (ICCs), cross-platform agreement (weighted kappa), marker correlations, and mixed-effects models with false-discovery-rate (FDR) control. Results: We analyzed 368 BBD-TDLU cores (88 cases; 88 controls), 204 BC cores and 110 BC-associated TDLU cores. ICCs were highest in BC tissues, and lower in BC-associated TDLUs and BBD-TDLUs. Agreement was slight–to-fair in TDLUs but moderate (ER/PR) to substantial (BCL2) in BC. DSP recapitulated expected immunologic correlations (CD45 with T-cell, B-cell, and macrophage markers) and tissue-type gradients (BC > BC-associated TDLUs > BBD-TDLUs). Exploratory case–control differences in BBD-TDLUs did not persist after FDR control. Conclusions: TMA-based DSP is feasible in archival breast tissues and yields biologically coherent, cross-platform-benchmarked profiles that are particularly robust in BC, while conserving scarce TDLUS and clarifying current limits of single-marker risk stratification from benign lobules. These data provide a foundation for refined sampling and expanded panels in future TDLU-focused studies.
背景：在小叶良性乳腺疾病（BBD）活检中发现风险生物标志物受到组织稀缺及终末导管小叶单位（TDLUs）微观解剖异质性的限制。本研究旨在验证基于组织微阵列（TMA）的节组织空间数字化分析（DSP）技术能否在良性小叶和乳腺癌（BCs）组织中提供可重复且生物学一致的蛋白质测量结果，并评估DSP与标准免疫检测方法的一致性。方法：我们利用梅奥诊所BBD队列的组织样本开展试点研究，构建了代表四种组织背景的TMA：来自后续发生BC的BBD活检样本及其匹配BBD对照样本的TDLUs、后续发生的BCs组织以及BC相关TDLUs。通过DSP技术检测了79种蛋白质（质控后保留37种），并以显色免疫组化（IHC）和OPAL免疫荧光技术作为基准进行比对。采用组内相关系数（ICCs）、跨平台一致性（加权Kappa）、标志物相关性分析以及错误发现率（FDR）校正的混合效应模型评估可重复性。结果：我们分析了368个BBD-TDLU样本核心（88例病例；88例对照）、204个BC样本核心和110个BC相关TDLU样本核心。ICC值在BC组织中最高，在BC相关TDLUs和BBD-TDLUs中较低。TDLUs中的一致性为轻微至一般，而在BC中为中等（ER/PR）至高度一致（BCL2）。DSP重现了预期的免疫相关性（CD45与T细胞、B细胞及巨噬细胞标志物）和组织类型梯度（BC > BC相关TDLUs > BBD-TDLUs）。BBD-TDLUs中探索性的病例对照差异在FDR校正后未持续存在。结论：基于TMA的DSP技术在存档乳腺组织中具有可行性，能产生生物学一致且经跨平台验证的蛋白表达谱，尤其在BC组织中表现稳健，同时节约了稀缺的TDLUs样本资源，并明确了当前基于良性小叶单标志物风险分层的局限性。这些数据为未来针对TDLUs的研究中优化采样策略和扩展检测指标奠定了基础。
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