Presentation by Arman Rahman, Assistant Professor, UCD School of Medicine, Ireland

Prognostic Stratification of Low vs. High-Risk Breast Cancer Patients via Master Regulator Analysis (OncoMasTR) Using Digital Pathology and Image Analysis

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Novel multi-marker imaging approaches can now provide unprecedented insights into the tumor microenvironment.

Significant progress has been made in the digital pathology arena, particularly in respect of brightfield and fluorescent imaging. Critically, the cellular context of molecular alterations occurring at DNA, RNA, or protein level within tumor tissue is now being more fully appreciated. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumor microenvironment, including the potential interplay between various cell types. POI’s Tissue Imaging Platform is working to develop new tissue-based multiplexed tests that can predict personalized, risk-stratified treatment regimens across a variety of cancer tissue types. Dr Rahman shares data on a novel prognostic signature encompassing a set of master transcriptional regulators (MTRs), termed OncoMasTR, along with immune infiltrates in the tumour microenvironment and its utility as biomarkers in early-stage breast cancer patients.