PO.PS01.05 · 人群科学
基质标志物多重免疫荧光染色的可靠性：病理学家评估与定量图像分析的比较
Reliability of stromal markers multiplex immunofluorescent staining: Pathologist assessment compared to quantitative image analysis
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摘要 Abstract
中文摘要
目的：既往研究表明基质在乳腺肿瘤发生中的重要性。然而，目前尚无关于无癌女性乳腺组织中基质标志物α-平滑肌肌动蛋白（alphaSMA）、成纤维细胞活化蛋白（FAP）、基质金属肽酶（MMP14）、腱生蛋白-C（TNC）和钙周期蛋白（s100A6）表达的数据。我们比较了专家病理学家与自动图像分析对组织学正常的终末导管小叶单位组织芯中这些标志物免疫荧光（IF）表达的评估。我们还评估了这些标志物在每位女性的多个组织芯之间的同质性。
方法：我们纳入了护士健康研究（NHS）和NHSII队列中73名活检确诊为良性乳腺疾病的无癌女性。IF使用商品化抗体进行（alphaSMA：1:400稀释；FAP：1:50；MMP14：1:150；TNC：1:200；s100A6：1:300）。对每个组织芯，由病理学家和inForm v2.6.0量化阳性百分比。以病理学家评分为金标准，采用Spearman相关（针对分类阳性：0、>0-<1、1-10、>10-50和>50%）以及敏感性/特异性（针对1%、10%和25%阈值的二分类阳性）评估两种方法之间的相关性。
结果：分别有149个和134个组织芯获得了病理学家和inForm读数；105个组织芯同时具有手动和自动读数。每位女性可用组织芯（中位数=3，范围1-6）之间表达的相关性对于FAP、MMP14和S100A6较强（组内相关系数[ICC]分别为0.69、0.72、0.63），对alphaSMA为中等（ICC=0.35），对TNC较差（ICC=0.21）。病理学家与inForm之间的相关性对于s100A6、FAP和MMP14较强（分别为0.77、0.70和0.78），对alphaSMA（0.37）和TNC（0.42）为中等。采用1%阈值时，TNC的敏感性最低（0.30），其他标志物的敏感性介于0.84-0.93之间。特异性介于0.43-0.98之间，alphaSMA的估计值最低。使用10%和25%阈值时，所有标志物的敏感性下降，而特异性上升。
结论：我们的研究结果表明，alphaSMA、FAP、MMP14、TNC和s100A6的计算评估与手动评估的相关性各不相同。这些发现支持在大规模流行病学研究中使用计算平台进行基质标志物的IF评估，并支持开展预试验以确定定义染色阳性的适当阈值的重要性。
查看英文原文 English abstract
Purpose: Prior studies show the importance of stroma in breast tumorigenesis. However, there is no data on the expression of stromal markers alpha-smooth muscle actin (alphaSMA), fibroblast activation protein (FAP), matrix metallo-peptidase (MMP14), tenascin-C (TNC), and calcyclin (s100A6) in the breast tissue of cancer-free women. We compared the immunofluorescence (IF) expression assessment of these markers in histologically normal terminal duct-lobular unit tissue cores between an expert pathologist and an automated image analysis. We also assessed the homogeneity of these markers across multiple cores pertaining to each woman.
Methods: We included 73 cancer-free women with biopsy-confirmed benign breast disease in the Nurses' Health Study (NHS) and NHSII cohorts. IF was conducted with commercial antibodies (alphaSMA: 1:400 dilution; FAP: 1:50; MMP14: 1:150; TNC: 1:200; s100A6: 1:300). For each core, the % positivity was quantified by the pathologist and inForm v2.6.0. Using the pathologist scores as the gold standard, correlations between the two methods were evaluated with Spearman correlation (for categorical positivity: 0, >0 -<1, 1- 10, >10-50, and >50%) and sensitivity/specificity (for binary positivity with 1%, 10% and 25% cut-offs).
Results: Pathologist and inForm readings were available for 149 and 134 cores, respectively; 105 cores had both manual and automated readings. The correlation in the expression across available cores for a woman (median=3, range 1-6) was strong for FAP, MMP14, and S100A6 (Intra-class correlation [ICC]=0.69, 0.72, 0.63, respectively), moderate for alphaSMA (ICC=0.35), and poor for TNC (ICC=0.21). Correlation between pathologist and inForm was strong for s100A6, FAP, and MMP14 (0.77, 0.70, and 0.78, respectively) and moderate for alphaSMA (0.37) and TNC (0.42). With a 1% cut-off, sensitivity was the lowest for TNC (0.30) and ranged between 0.84-0.93 for other markers. Specificity ranged between 0.43-0.98 with the lowest estimates for alphaSMA. Sensitivity declined for all markers while using 10% and 25% cut-offs, while specificity increased.
Conclusion: Our findings show that computational assessments for alphaSMA, FAP, MMP14, TNC, and s100A6 exhibit variable correlations with manual assessment. These findings support the use of computational platforms for IF evaluation of stromal markers in large-scale epidemiologic studies and the importance of pilot studies for identification of appropriate cut-offs for defining staining positivity.
利益披露 Disclosure
L. Yaghjyan, None..
Y. D. Guzman-Arocho, None..
Y. J. Heng, None..
B. R. Sardella, None..
G. Murtazaalieva, None..
G. A. Colditz, None..
D. Fu, None..
K. Patel, None..
B. Rosner, None..
M. Ratcliffe, None..
R. M. Tamimi, None.