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Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression

SIMPLE SUMMARY: The assessment of tumor-infiltrating lymphocytes (TILs) is gaining acceptance as a robust biomarker to help predict prognosis and treatment response. We evaluated TILs in whole-slide images (WSIs) of breast cancer tissue specimens stained with hematoxylin and eosin (H&E) from the...

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Autores principales: Fassler, Danielle J., Torre-Healy, Luke A., Gupta, Rajarsi, Hamilton, Alina M., Kobayashi, Soma, Van Alsten, Sarah C., Zhang, Yuwei, Kurc, Tahsin, Moffitt, Richard A., Troester, Melissa A., Hoadley, Katherine A., Saltz, Joel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105398/
https://www.ncbi.nlm.nih.gov/pubmed/35565277
http://dx.doi.org/10.3390/cancers14092148
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author Fassler, Danielle J.
Torre-Healy, Luke A.
Gupta, Rajarsi
Hamilton, Alina M.
Kobayashi, Soma
Van Alsten, Sarah C.
Zhang, Yuwei
Kurc, Tahsin
Moffitt, Richard A.
Troester, Melissa A.
Hoadley, Katherine A.
Saltz, Joel
author_facet Fassler, Danielle J.
Torre-Healy, Luke A.
Gupta, Rajarsi
Hamilton, Alina M.
Kobayashi, Soma
Van Alsten, Sarah C.
Zhang, Yuwei
Kurc, Tahsin
Moffitt, Richard A.
Troester, Melissa A.
Hoadley, Katherine A.
Saltz, Joel
author_sort Fassler, Danielle J.
collection PubMed
description SIMPLE SUMMARY: The assessment of tumor-infiltrating lymphocytes (TILs) is gaining acceptance as a robust biomarker to help predict prognosis and treatment response. We evaluated TILs in whole-slide images (WSIs) of breast cancer tissue specimens stained with hematoxylin and eosin (H&E) from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). Our approach utilized computational pathology to characterize the abundance and spatial distribution of TIL infiltrates in breast cancer WSIs. This work (1) examines the relationship between the global abundance and spatial features of TIL infiltrates with clinical outcomes in order to (2) evaluate their significance as prognostic biomarkers in a multifactorial analysis of progression-free interval in the TCGA BRCA and UNC CBCS datasets. Our findings present a paradigm for pathologists to assess the risk of recurrence in breast cancer by using computational pathology to spatially map, quantify, and interpret TILs in the tumor microenvironment. ABSTRACT: Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.
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spelling pubmed-91053982022-05-14 Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression Fassler, Danielle J. Torre-Healy, Luke A. Gupta, Rajarsi Hamilton, Alina M. Kobayashi, Soma Van Alsten, Sarah C. Zhang, Yuwei Kurc, Tahsin Moffitt, Richard A. Troester, Melissa A. Hoadley, Katherine A. Saltz, Joel Cancers (Basel) Article SIMPLE SUMMARY: The assessment of tumor-infiltrating lymphocytes (TILs) is gaining acceptance as a robust biomarker to help predict prognosis and treatment response. We evaluated TILs in whole-slide images (WSIs) of breast cancer tissue specimens stained with hematoxylin and eosin (H&E) from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). Our approach utilized computational pathology to characterize the abundance and spatial distribution of TIL infiltrates in breast cancer WSIs. This work (1) examines the relationship between the global abundance and spatial features of TIL infiltrates with clinical outcomes in order to (2) evaluate their significance as prognostic biomarkers in a multifactorial analysis of progression-free interval in the TCGA BRCA and UNC CBCS datasets. Our findings present a paradigm for pathologists to assess the risk of recurrence in breast cancer by using computational pathology to spatially map, quantify, and interpret TILs in the tumor microenvironment. ABSTRACT: Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer. MDPI 2022-04-26 /pmc/articles/PMC9105398/ /pubmed/35565277 http://dx.doi.org/10.3390/cancers14092148 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fassler, Danielle J.
Torre-Healy, Luke A.
Gupta, Rajarsi
Hamilton, Alina M.
Kobayashi, Soma
Van Alsten, Sarah C.
Zhang, Yuwei
Kurc, Tahsin
Moffitt, Richard A.
Troester, Melissa A.
Hoadley, Katherine A.
Saltz, Joel
Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression
title Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression
title_full Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression
title_fullStr Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression
title_full_unstemmed Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression
title_short Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression
title_sort spatial characterization of tumor-infiltrating lymphocytes and breast cancer progression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9105398/
https://www.ncbi.nlm.nih.gov/pubmed/35565277
http://dx.doi.org/10.3390/cancers14092148
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