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Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis

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 dissemina...

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Autores principales: Entenberg, David, Oktay, Maja H., D’Alfonso, Timothy, Ginter, Paula S., Robinson, Brian D., Xue, Xiaonan, Rohan, Thomas E., Sparano, Joseph A., Jones, Joan G., Condeelis, John S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226227/
https://www.ncbi.nlm.nih.gov/pubmed/32244564
http://dx.doi.org/10.3390/cancers12040846
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author Entenberg, David
Oktay, Maja H.
D’Alfonso, Timothy
Ginter, Paula S.
Robinson, Brian D.
Xue, Xiaonan
Rohan, Thomas E.
Sparano, Joseph A.
Jones, Joan G.
Condeelis, John S.
author_facet Entenberg, David
Oktay, Maja H.
D’Alfonso, Timothy
Ginter, Paula S.
Robinson, Brian D.
Xue, Xiaonan
Rohan, Thomas E.
Sparano, Joseph A.
Jones, Joan G.
Condeelis, John S.
author_sort Entenberg, David
collection PubMed
description 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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spelling pubmed-72262272020-05-18 Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis Entenberg, David Oktay, Maja H. D’Alfonso, Timothy Ginter, Paula S. Robinson, Brian D. Xue, Xiaonan Rohan, Thomas E. Sparano, Joseph A. Jones, Joan G. Condeelis, John S. Cancers (Basel) Article 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. MDPI 2020-03-31 /pmc/articles/PMC7226227/ /pubmed/32244564 http://dx.doi.org/10.3390/cancers12040846 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Entenberg, David
Oktay, Maja H.
D’Alfonso, Timothy
Ginter, Paula S.
Robinson, Brian D.
Xue, Xiaonan
Rohan, Thomas E.
Sparano, Joseph A.
Jones, Joan G.
Condeelis, John S.
Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis
title Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis
title_full Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis
title_fullStr Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis
title_full_unstemmed Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis
title_short Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM: A Prognostic Biomarker for Metastasis
title_sort validation of an automated quantitative digital pathology approach for scoring tmem: a prognostic biomarker for metastasis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226227/
https://www.ncbi.nlm.nih.gov/pubmed/32244564
http://dx.doi.org/10.3390/cancers12040846
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