Background: Identification of HER2 protein overexpression and/or amplification of the HER2 gene are required to qualify breast cancer patients for HER2 targeted therapies. In situ hybridization (ISH) assays that identify HER2 gene amplification function as a stand-alone test for determination of HER2 status and rely on the manual quantification of the number of HER2 genes and copies of chromosome 17 to determine HER2 amplification. Methods: To assist pathologists, we have developed the uPath HER2 Dual ISH Image Analysis for Breast (uPath HER2 DISH IA) algorithm, as an adjunctive aid in the determination of HER2 gene status in breast cancer specimens. The objective of this study was to compare uPath HER2 DISH image analysis vs manual read scoring of VENTANA HER2 DISH-stained breast carcinoma specimens with ground truth (GT) gene status as the reference. Three reader pathologists reviewed 220, formalin-fixed, paraffin-embedded (FFPE) breast cancer cases by both manual and uPath HER2 DISH IA methods. Scoring results from manual read (MR) and computer-assisted scores (image analysis, IA) were compared against the GT gene status generated by consensus of a panel of pathologists. The differences in agreement rates of HER2 gene status between manual, computer-assisted, and GT gene status were determined. Results: The positive percent agreement (PPA) and negative percent agreement (NPA) rates for image analysis (IA) vs GT were 97.2% (95% confidence interval [CI]: 95.0, 99.3) and 94.3% (95% CI: 90.8, 97.3) respectively. Comparison of agreement rates showed that the lower bounds of the 95% CIs for the difference of PPA and NPA for IA vs MR were -0.9% and -6.2%, respectively. Further, inter- and intra-reader agreement rates in the IA method were observed with point estimates of at least 96.7%. Conclusions: Overall, our data show that the uPath HER2 DISH IA is non-inferior to manual scoring and supports its use as an aid for pathologists in routine diagnosis of breast cancer.
Background: Identification of HER2 protein overexpression and/or amplification of the HER2 gene are required to qualify breast cancer patients for HER2 targeted therapies. In situ hybridization (ISH) assays that identify HER2 gene amplification function as a stand-alone test for determination of HER2 status and rely on the manual quantification of the number of HER2 genes and copies of chromosome 17 to determine HER2 amplification. Methods: To assist pathologists, we have developed the uPath HER2 Dual ISH Image Analysis for Breast (uPath HER2 DISH IA) algorithm, as an adjunctive aid in the determination of HER2 gene status in breast cancer specimens. The objective of this study was to compare uPath HER2 DISH image analysis vs manual read scoring of VENTANA HER2 DISH-stained breast carcinoma specimens with ground truth (GT) gene status as the reference. Three reader pathologists reviewed 220, formalin-fixed, paraffin-embedded (FFPE) breast cancer cases by both manual and uPath HER2 DISH IA methods. Scoring results from manual read (MR) and computer-assisted scores (image analysis, IA) were compared against the GT gene status generated by consensus of a panel of pathologists. The differences in agreement rates of HER2 gene status between manual, computer-assisted, and GT gene status were determined. Results: The positive percent agreement (PPA) and negative percent agreement (NPA) rates for image analysis (IA) vs GT were 97.2% (95% confidence interval [CI]: 95.0, 99.3) and 94.3% (95% CI: 90.8, 97.3) respectively. Comparison of agreement rates showed that the lower bounds of the 95% CIs for the difference of PPA and NPA for IA vs MR were -0.9% and -6.2%, respectively. Further, inter- and intra-reader agreement rates in the IA method were observed with point estimates of at least 96.7%. Conclusions: Overall, our data show that the uPath HER2 DISH IA is non-inferior to manual scoring and supports its use as an aid for pathologists in routine diagnosis of breast cancer.
Authors: Mithun Vinod Shah; Anne E Wiktor; Reid G Meyer; Kathleen S Tenner; Karla V Ballman; Stefan J Green; William R Sukov; Rhett P Ketterling; Edith A Perez; Robert B Jenkins Journal: J Clin Oncol Date: 2016-10-10 Impact factor: 44.544
Authors: Laurent Arnould; Patrick Arveux; Jerome Couturier; Marion Gelly-Marty; Catherine Loustalot; Francette Ettore; Christine Sagan; Martine Antoine; Frederique Penault-Llorca; Berangere Vasseur; Pierre Fumoleau; Bruno P Coudert Journal: Clin Cancer Res Date: 2007-11-01 Impact factor: 12.531
Authors: Leonard M da Silva; Emilio M Pereira; Paulo Go Salles; Ran Godrich; Rodrigo Ceballos; Jeremy D Kunz; Adam Casson; Julian Viret; Sarat Chandarlapaty; Carlos Gil Ferreira; Bruno Ferrari; Brandon Rothrock; Patricia Raciti; Victor Reuter; Belma Dogdas; George DeMuth; Jillian Sue; Christopher Kanan; Leo Grady; Thomas J Fuchs; Jorge S Reis-Filho Journal: J Pathol Date: 2021-04-27 Impact factor: 7.996
Authors: Michael F Press; Guido Sauter; Marc Buyse; Hélène Fourmanoir; Emmanuel Quinaux; Denice D Tsao-Wei; Wolfgang Eiermann; Nicholas Robert; Tadeusz Pienkowski; John Crown; Miguel Martin; Vicente Valero; John R Mackey; Valerie Bee; Yanling Ma; Ivonne Villalobos; Anaamika Campeau; Martina Mirlacher; Mary-Ann Lindsay; Dennis J Slamon Journal: J Clin Oncol Date: 2016-10-10 Impact factor: 44.544