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An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma

OBJECTIVE: Previous studies have reported a close relationship between malignant mesothelioma (MM) and the immune matricial microenvironment (IMM). One of the major problems in these studies is the lack of adequate adjustment for potential confounders. Therefore, the aim of this study was to identif...

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Autores principales: Balancin, Marcelo Luiz, Teodoro, Walcy Rosolia, Farhat, Cecilia, de Miranda, Tomas Jurandir, Assato, Aline Kawassaki, de Souza Silva, Neila Aparecida, Velosa, Ana Paula, Falzoni, Roberto, Ab'Saber, Alexandre Muxfeldt, Roden, Anja C., Capelozzi, Vera Luiza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333849/
https://www.ncbi.nlm.nih.gov/pubmed/32391978
http://dx.doi.org/10.1002/cam4.3111
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author Balancin, Marcelo Luiz
Teodoro, Walcy Rosolia
Farhat, Cecilia
de Miranda, Tomas Jurandir
Assato, Aline Kawassaki
de Souza Silva, Neila Aparecida
Velosa, Ana Paula
Falzoni, Roberto
Ab'Saber, Alexandre Muxfeldt
Roden, Anja C.
Capelozzi, Vera Luiza
author_facet Balancin, Marcelo Luiz
Teodoro, Walcy Rosolia
Farhat, Cecilia
de Miranda, Tomas Jurandir
Assato, Aline Kawassaki
de Souza Silva, Neila Aparecida
Velosa, Ana Paula
Falzoni, Roberto
Ab'Saber, Alexandre Muxfeldt
Roden, Anja C.
Capelozzi, Vera Luiza
author_sort Balancin, Marcelo Luiz
collection PubMed
description OBJECTIVE: Previous studies have reported a close relationship between malignant mesothelioma (MM) and the immune matricial microenvironment (IMM). One of the major problems in these studies is the lack of adequate adjustment for potential confounders. Therefore, the aim of this study was to identify and quantify risk factors such as IMM and various tumor characteristics and their association with the subtype of MM and survival. METHODS: We examined IMM and other tumor markers in tumor tissues from 82 patients with MM. These markers were evaluated by histochemistry, immunohistochemistry, immunofluorescence, and morphometry. Logistic regression analysis, cluster analysis, and Cox regression analysis were performed. RESULTS: Hierarchical cluster analysis revealed two clusters of MM that were independent of clinicopathologic features. The high‐risk cluster included MM with high tumor cellularity, high type V collagen (Col V) fiber density, and low CD8(+) T lymphocyte density in the IMM. Our results showed that the risk of death was increased for patients with MM with high tumor cellularity (OR = 1.63, 95% CI = 1.29‐2.89, P = .02), overexpression of Col V (OR = 2.60, 95% CI = 0.98‐6.84, P = .04), and decreased CD8 T lymphocytes (OR = 1.001, 95% CI = 0.995‐1.007, P = .008). The hazard ratio for the high‐risk cluster was 2.19 (95% CI = 0.54‐3.03, P < .01) for mortality from MM at 40 months. CONCLUSION: Morphometric analysis of Col V, CD8(+) T lymphocytes, and tumor cellularity can be used to identify patients with high risk of death from MM.
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spelling pubmed-73338492020-07-07 An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma Balancin, Marcelo Luiz Teodoro, Walcy Rosolia Farhat, Cecilia de Miranda, Tomas Jurandir Assato, Aline Kawassaki de Souza Silva, Neila Aparecida Velosa, Ana Paula Falzoni, Roberto Ab'Saber, Alexandre Muxfeldt Roden, Anja C. Capelozzi, Vera Luiza Cancer Med Cancer Prevention OBJECTIVE: Previous studies have reported a close relationship between malignant mesothelioma (MM) and the immune matricial microenvironment (IMM). One of the major problems in these studies is the lack of adequate adjustment for potential confounders. Therefore, the aim of this study was to identify and quantify risk factors such as IMM and various tumor characteristics and their association with the subtype of MM and survival. METHODS: We examined IMM and other tumor markers in tumor tissues from 82 patients with MM. These markers were evaluated by histochemistry, immunohistochemistry, immunofluorescence, and morphometry. Logistic regression analysis, cluster analysis, and Cox regression analysis were performed. RESULTS: Hierarchical cluster analysis revealed two clusters of MM that were independent of clinicopathologic features. The high‐risk cluster included MM with high tumor cellularity, high type V collagen (Col V) fiber density, and low CD8(+) T lymphocyte density in the IMM. Our results showed that the risk of death was increased for patients with MM with high tumor cellularity (OR = 1.63, 95% CI = 1.29‐2.89, P = .02), overexpression of Col V (OR = 2.60, 95% CI = 0.98‐6.84, P = .04), and decreased CD8 T lymphocytes (OR = 1.001, 95% CI = 0.995‐1.007, P = .008). The hazard ratio for the high‐risk cluster was 2.19 (95% CI = 0.54‐3.03, P < .01) for mortality from MM at 40 months. CONCLUSION: Morphometric analysis of Col V, CD8(+) T lymphocytes, and tumor cellularity can be used to identify patients with high risk of death from MM. John Wiley and Sons Inc. 2020-05-11 /pmc/articles/PMC7333849/ /pubmed/32391978 http://dx.doi.org/10.1002/cam4.3111 Text en © 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Cancer Prevention
Balancin, Marcelo Luiz
Teodoro, Walcy Rosolia
Farhat, Cecilia
de Miranda, Tomas Jurandir
Assato, Aline Kawassaki
de Souza Silva, Neila Aparecida
Velosa, Ana Paula
Falzoni, Roberto
Ab'Saber, Alexandre Muxfeldt
Roden, Anja C.
Capelozzi, Vera Luiza
An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
title An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
title_full An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
title_fullStr An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
title_full_unstemmed An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
title_short An integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
title_sort integrative histopathologic clustering model based on immuno‐matrix elements to predict the risk of death in malignant mesothelioma
topic Cancer Prevention
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333849/
https://www.ncbi.nlm.nih.gov/pubmed/32391978
http://dx.doi.org/10.1002/cam4.3111
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