Abstract P2-05-06: Analytical and clinical validation of a fully automated tissue-based quantitative assay (MetaSite <i>Breast</i>™) to detect the likelihood of distant metastasis in hormone receptor (HR)-positive, HER2-negative early stage breast cancer (ESBC)
Authors: MJ Donovan, JG Jones, DR Entenberg, JS Condeelis, TM D'alfonso, M Gustavson, A Molinaro, MH Oktay, X Xue, JA Sparano, MA Peterson, O Podznyakova, TE Rohan, AP Shuber, FB Gertler, A Ly, ME Divelbiss, DA Hamilton
Journal: Cancer Research (2017)

Abstract Background: MetaSite Breast™ is a validated assay to predict risk of distant breast cancer metastasis in patients with HR+/HER2- ESBC. The assay measures the number of MetaSites defined as tumor microanatomic structures composed of MENA protein expressing tumor cells in contact with CD31+ endothelial cells and CD68+ macrophages. Previous studies have demonstrated that an increased number of these microanatomic structures is associated with distant metastasis (DM) in HR+/HER2- ESBC independent of clinicopathologic features. Analytical validation of MetaSite Breast™ demonstrated precision of 97-99% (repeat image analysis of the same slide) and performance of 91-96% (staining and image analysis of serial tumor sections). We sought to further understand the importance of the MetaSite in predicting distant breast cancer metastasis utilizing a fully automated prognostic assay in an independent large patient cohort. Methods: We conducted a nested case-control study within a cohort of 3,760 patients diagnosed between 1980 and 2000 with invasive breast cancer from the Kaiser Permanente Northwest health care system. Cases (n=259) were women who developed a subsequent distant metastasis; controls, selected using incidence density sampling, were matched closely to cases (1:1) on age at and calendar year of primary diagnosis. Of the 481 patient tumor samples evaluated in this study, 57% were HR+/HER2-, 19% were triple negative (TN), and 15% were HER2+ disease. Multivariate models were adjusted for clinical factors including: lymph node status, tumor size, tumor grade, and HRT; as well as matching variables: age and year of diagnosis. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression. Results: In the HR+/HER2- group, MetaSite Score (MS) ranged from 0-357 and the mean was 44.6. MS was a significant predictor of DM (P=0.039) in patients with HR+/HER2- disease. Cut-points based on tertiles of MS in all 259 controls defined intermediate (13-41) and high (&amp;gt;41) risk groups that were significantly associated with risk of DM versus the low risk group (OR=2.24; 95%CI=1.23-4.13, P=0.009) and (OR=2.94; 95%CI=1.62-5.41, P=0.0005), respectively. Univariate estimates of absolute risk of DM with cutoffs based on 90% sensitivity and specificity were 9.4% for the low risk group (MS&amp;lt;7), 14.1% for the intermediate (MS=7-91), and 23.4% for the high (MS&amp;gt;91). When adjusted for clinical factors, estimates of absolute risk of DM were 6.6%, 14.1%, and 33.0% for the low, intermediate, and high risk groups, respectively. A binary cut-point for the high risk group was determined (MS&amp;gt;14) and was significant with a 2-fold higher risk of DM versus the low risk group and adjusted for clinical covariates (P=0.036). MS was not positively associated with DM in TN or HER2+ disease. Conclusions: MetaSite Breast™ significantly predicted the risk of distant breast cancer metastasis in ESBC patients with HR+/HER2-disease, independent of classical clinicopathologic features. Citation Format: Donovan MJ, Jones JG, Entenberg DR, Condeelis JS, D'alfonso TM, Gustavson M, Molinaro A, Oktay MH, Xue X, Sparano JA, Peterson MA, Podznyakova O, Rohan TE, Shuber AP, Gertler FB, Ly A, Divelbiss ME, Hamilton DA. Analytical and clinical validation of a fully automated tissue-based quantitative assay (MetaSite Breast™) to detect the likelihood of distant metastasis in hormone receptor (HR)-positive, HER2-negative early stage breast cancer (ESBC) [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-05-06.