NEILA APARECIDA DE SOUZA SILVA

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Instituto Central, Hospital das Clínicas, Faculdade de Medicina

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Autor: BALANCIN, Marcelo Luiz ×

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  • article 10 Citação(ões) na Scopus
    An integrative histopathologic clustering model based on immuno-matrix elements to predict the risk of death in malignant mesothelioma
    (2020) BALANCIN, Marcelo Luiz; TEODORO, Walcy Rosolia; FARHAT, Cecilia; MIRANDA, Tomas Jurandir de; ASSATO, Aline Kawassaki; SILVA, Neila Aparecida de Souza; VELOSA, Ana Paula; FALZONI, Roberto; AB'SABER, Alexandre Muxfeldt; RODEN, Anja C.; CAPELOZZI, Vera Luiza
    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.