Mast Cell-related Prognosis Signature Characterizes Immune Landscape and Predicts Prognosis of Ovarian Cancer.

Autor:	Li Q; Department of Intensive Care Unit, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China., Guan T; Department of Obstetrics and Gynecology, the Nanhua Hospital Affiliated to Nanhua University, Hengyang, P.R. China., Mao J; Department of Emergency Medicine, the Nanhua Hospital Affiliated to Nanhua University, Hengyang, P.R. China., King BP; Department of Microbiology, Immunology and Pathology, Des Moines University College of Osteopathic Medicine, West Des Moines, IA, U.S.A., Johnson K; Department of Microbiology, Immunology and Pathology, Des Moines University College of Osteopathic Medicine, West Des Moines, IA, U.S.A., Mayberry TG; Department of Microbiology, Immunology and Pathology, Des Moines University College of Osteopathic Medicine, West Des Moines, IA, U.S.A.; Department of Surgery, University of Missouri School of Medicine, Columbia, MO, U.S.A., Cowan BC; Department of Microbiology, Immunology and Pathology, Des Moines University College of Osteopathic Medicine, West Des Moines, IA, U.S.A.; Department of Surgery, University of Missouri School of Medicine, Columbia, MO, U.S.A., Wakefield MR; Department of Surgery, University of Missouri School of Medicine, Columbia, MO, U.S.A.; Ellis Fischel Cancer Center, University of Missouri School of Medicine, Columbia, MO, U.S.A., Fang Y; Department of Microbiology, Immunology and Pathology, Des Moines University College of Osteopathic Medicine, West Des Moines, IA, U.S.A.; yuijiang.fang@dmu.edu.; Department of Surgery, University of Missouri School of Medicine, Columbia, MO, U.S.A.; Ellis Fischel Cancer Center, University of Missouri School of Medicine, Columbia, MO, U.S.A., Zhao Q; Department of Intensive Care Unit, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China; zhaoqy@sysucc.org.cn.
Jazyk:	angličtina
Zdroj:	Anticancer research [Anticancer Res] 2024 Jul; Vol. 44 (7), pp. 2775-2786.
DOI:	10.21873/anticanres.17089
Abstrakt:	Background/aim: Ovarian cancer (OVC) is a common, aggressive, and heterogeneous malignancy, with a widely variable prognosis. With the advances of modern immunology, mast cells (MCs) have been shown to play a significant role in the prognosis of some malignant tumors. However, the role of mast cells in the prognosis of OVC is unknown. Materials and Methods: In this study, MC-associated prognostic genes (MRGs) were used to classify OVC from The Cancer Genome Atlas (TCGA)-OVC cohort. Genes were evaluated using univariate cox regression analysis. Twenty-nine prognostic gene signatures were identified using LASSO-COX analysis. COX regression models and principal component analysis (PCA) algorithms were used to construct MRG scores and individual MRGs patterns. External validation was performed in the TCGA-breast cancer (BRCA) and IMvigor210 cohorts. Immunity analysis based on MRGs was performed using CIBERSORT, and GSVA methods, and immunotherapy response was evaluated using the TIDE website. Results: Using TCGA-OVC data, we established a model for constructing MRG scores based on the twenty-nine identified prognostic gene signatures using the PCA algorithm. MRG scores were found to be strongly correlated with immune cell infiltration and were excellent predictors of prognosis in patients with OVC. Low MRG scores were associated with better prognosis and better response to immunotherapy and chemotherapy. Conclusion: MC-related prognosis signature characterizes the immune landscape and predicts the prognosis of OVC. Understanding the correlation between MC-related gene signatures and immunotherapy and chemotherapy may improve the development of personalized clinical treatment strategies. (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)
Databáze:	MEDLINE
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