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Independent Prognostic Value of Intratumoral Heterogeneity and Immune Response Features by Automated Digital Immunohistochemistry Analysis in Early Hormone Receptor-Positive Breast Carcinoma

This study by Zilenaite and colleagues evaluated the prognostic value of digital image analysis using HALO on analysis of hormone receptor positive breast cancer IHC biomarkers including ER, PR, HER2, and Ki67 combined with information on tumor heterogeneity and immune response. HALO AI was used for tissue classification to differentiate tumor, stroma, and background (necrosis, artifacts, glass). For quantitative analysis of breast cancer biomarker expression and localization, the Multiplex IHC module of HALO was used. The authors demonstrate that prognostic modeling in hormone receptor positive breast cancer is possible using the computational approach presented here. They also show that the addition of tumor heterogeneity data improved their prognostic model.

Zilenaite D, Rasmusson A, Augulis R, Besusparis J, Laurinavicience A, Plancoulaine B, Ostapenko V, Laurinavicius A

Frontiers in Oncology | First published 16 June 2020| DOI