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Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer

BACKGROUND: Emerging evidence has highlighted the biological significance of pyroptosis in tumor tumorigenesis and progression. Nonetheless, the potential roles of pyroptosis in tumor immune microenvironment and target therapy of ovarian cancer (OC) remain unknown. METHODS: In this study, with a ser...

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Autores principales: Gao, Lingling, Ying, Feiquan, Cai, Jing, Peng, Minggang, Xiao, Man, Sun, Si, Zeng, Ya, Xiong, Zhoufang, Cai, Liqiong, Gao, Rui, Wang, Zehua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883900/
https://www.ncbi.nlm.nih.gov/pubmed/36707884
http://dx.doi.org/10.1186/s13048-022-01065-2
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author Gao, Lingling
Ying, Feiquan
Cai, Jing
Peng, Minggang
Xiao, Man
Sun, Si
Zeng, Ya
Xiong, Zhoufang
Cai, Liqiong
Gao, Rui
Wang, Zehua
author_facet Gao, Lingling
Ying, Feiquan
Cai, Jing
Peng, Minggang
Xiao, Man
Sun, Si
Zeng, Ya
Xiong, Zhoufang
Cai, Liqiong
Gao, Rui
Wang, Zehua
author_sort Gao, Lingling
collection PubMed
description BACKGROUND: Emerging evidence has highlighted the biological significance of pyroptosis in tumor tumorigenesis and progression. Nonetheless, the potential roles of pyroptosis in tumor immune microenvironment and target therapy of ovarian cancer (OC) remain unknown. METHODS: In this study, with a series of bioinformatic and machine learning approaches, we comprehensively evaluated genetic alterations and transcriptome profiles of pyroptosis-associated genes (PYAGs) with TCGA-OV datasets. Consensus molecular clustering was performed to determine pyroptosis-associated clusters (PACs) and gene clusters in OC. Subsequently, component analysis algorithm (PCA) was employed to construct Pyrsig score and a highly accurate nomogram was established to evaluate its efficacy. Meanwhile, we systematically performed association analysis for these groups with prognosis, clinical features, TME cell-infiltrating characteristics, drug response and immunotherapeutic efficacy. Immunohistochemistry was conducted to verify molecular expression with clinical samples. RESULTS: The somatic mutations and copy number variation (CNV) of 51 PYRGs in OC samples were clarified. Two distinct PACs (PAC1/2) and three gene clusters (A/B/C) were identified based on 1332 OC samples, PAC1 and gene cluster A were significantly associated with favorable overall survival (OS), clinicopathological features and TME cell-infiltrating characteristics. Subsequently, Pyrsig score was successfully established to demonstrate the prognostic value and immune characteristics of pyroptosis in OC, low Pyrsig score, characterized by activated immune cell infiltration, indicated prolonged OS, increased sensitivity of some chemotherapeutic drugs and enhanced efficacy of anti-PD-L1 immunotherapy, Consequently, a nomogram was successfully established to improve the clinical applicability and stability of Pyrsig score. With clinical OC samples, GSDMD and GZMB proteins were validated highly expressed in OC and associated with immune infiltration and Pyrsig score, GZMB and CD8 proteins were regarded as independent prognostic factors of OC. CONCLUSION: This work revealed pyroptosis played a non-negligible role in prognosis value, clinicopathological characteristics and tumor immune infiltration microenvironment in OC, which provided novel insights into identifying and characterizing landscape of tumor immune microenvironment, thereby guiding more effective prognostic evaluation and tailored immunotherapy strategies of OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-022-01065-2.
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spelling pubmed-98839002023-01-29 Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer Gao, Lingling Ying, Feiquan Cai, Jing Peng, Minggang Xiao, Man Sun, Si Zeng, Ya Xiong, Zhoufang Cai, Liqiong Gao, Rui Wang, Zehua J Ovarian Res Research BACKGROUND: Emerging evidence has highlighted the biological significance of pyroptosis in tumor tumorigenesis and progression. Nonetheless, the potential roles of pyroptosis in tumor immune microenvironment and target therapy of ovarian cancer (OC) remain unknown. METHODS: In this study, with a series of bioinformatic and machine learning approaches, we comprehensively evaluated genetic alterations and transcriptome profiles of pyroptosis-associated genes (PYAGs) with TCGA-OV datasets. Consensus molecular clustering was performed to determine pyroptosis-associated clusters (PACs) and gene clusters in OC. Subsequently, component analysis algorithm (PCA) was employed to construct Pyrsig score and a highly accurate nomogram was established to evaluate its efficacy. Meanwhile, we systematically performed association analysis for these groups with prognosis, clinical features, TME cell-infiltrating characteristics, drug response and immunotherapeutic efficacy. Immunohistochemistry was conducted to verify molecular expression with clinical samples. RESULTS: The somatic mutations and copy number variation (CNV) of 51 PYRGs in OC samples were clarified. Two distinct PACs (PAC1/2) and three gene clusters (A/B/C) were identified based on 1332 OC samples, PAC1 and gene cluster A were significantly associated with favorable overall survival (OS), clinicopathological features and TME cell-infiltrating characteristics. Subsequently, Pyrsig score was successfully established to demonstrate the prognostic value and immune characteristics of pyroptosis in OC, low Pyrsig score, characterized by activated immune cell infiltration, indicated prolonged OS, increased sensitivity of some chemotherapeutic drugs and enhanced efficacy of anti-PD-L1 immunotherapy, Consequently, a nomogram was successfully established to improve the clinical applicability and stability of Pyrsig score. With clinical OC samples, GSDMD and GZMB proteins were validated highly expressed in OC and associated with immune infiltration and Pyrsig score, GZMB and CD8 proteins were regarded as independent prognostic factors of OC. CONCLUSION: This work revealed pyroptosis played a non-negligible role in prognosis value, clinicopathological characteristics and tumor immune infiltration microenvironment in OC, which provided novel insights into identifying and characterizing landscape of tumor immune microenvironment, thereby guiding more effective prognostic evaluation and tailored immunotherapy strategies of OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-022-01065-2. BioMed Central 2023-01-27 /pmc/articles/PMC9883900/ /pubmed/36707884 http://dx.doi.org/10.1186/s13048-022-01065-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gao, Lingling
Ying, Feiquan
Cai, Jing
Peng, Minggang
Xiao, Man
Sun, Si
Zeng, Ya
Xiong, Zhoufang
Cai, Liqiong
Gao, Rui
Wang, Zehua
Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
title Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
title_full Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
title_fullStr Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
title_full_unstemmed Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
title_short Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
title_sort identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883900/
https://www.ncbi.nlm.nih.gov/pubmed/36707884
http://dx.doi.org/10.1186/s13048-022-01065-2
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