Reliability of stromal markers multiplex immunofluorescent staining: Pathologist assessment compared to quantitative image analysis

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.