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Updated: Dec 25, 2025

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
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Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM, a Prognostic Biomarker for
David Entenberg1,2,3, Maja H Oktay1,2,3,4, Timothy D'Alfonso5
1Department of Anatomy and Structural Biology, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY 10461, USA.
Abstract:
Metastasis causes ~90% of breast cancer mortality. However, standard prognostic tests based mostly on proliferation genes do not measure metastatic potential. Tumor MicroEnvironment of Metastasis (TMEM), an immunohistochemical biomarker for doorways on blood vessels that support tumor cell dissemination is prognostic for metastatic outcome in breast cancer patients. Studies quantifying TMEM doorways have involved manual scoring by pathologists utilizing static digital microscopy: a labor-intensive process unsuitable for use in clinical practice. We report here a validation study evaluating a new quantitative digital pathology (QDP) tool (TMEM-DP) for identification and quantification of TMEM doorways that closely mimics pathologists' workflow and reduces pathologists' variability to levels suitable for use in a clinical setting. Blinded to outcome, QDP was applied to a nested case-control study consisting of 259 matched case-control pairs. Sixty subjects of these were manually scored by five pathologists, digitally recorded using whole slide imaging (WSI), and then used for algorithm development and optimization. Validation was performed on the remainder of the cohort. TMEM-DP shows excellent reproducibility and concordance and reduces pathologist time from ~60 min to ~5 min per case. Concordance between manual scoring and TMEM-DP was found to be >0.79. These results show that TMEM-DP is capable of accurately identifying and scoring TMEM doorways (also known as MetaSite score) equivalent to pathologists.
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