Detecting phenotypical subtypes of breast cancer with multiplexed immunohistochemistry

Abstract

Treatment for breast cancer has benefited significantly from advances in molecular biology. IHC tests for protein receptors ER, PR, and Her2 have lead to a new patient classification system. Traditional approaches to assessing multiple proteins use serial sections, staining for one protein per serial section. Multiple proteins can be assessed in the same tissue section, determining phenotype on a per‐cell basis, possibly revealing significant subtypes and leading to more targeted and more effective treatments and therapies.Multispectral imaging (MSI) was performed on two sets of a 712‐core TMA (356 patients, in duplicate). One set was stained for ER and ki67, the second for ER, PR and Her2 (both plus counterstain). IHC signals were spectrally unmixed from each other and counterstain. Machine‐learning‐based automated image analysis was performed to locate cancer cells, segment subcellular compartments, and extract IHC signals on a per‐cell basis. Per‐cell co‐expression subtypes were detected using flow‐cytometry data analysis software. Percent double and triple positivity were determined, revealing subtypes. Correlation between subtypes and clinical outcomes will be the topic of future publications.MSI and analysis software, coupled with flow‐cytometry analysis tools, can be used to reveal molecular subtypes, which may lead to new targeted strategies for breast cancer research and clinical care.