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A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers

BACKGROUND: In recent years, it has been proved that necroptosis plays an important role in the occurrence, development, invasion, metastasis and drug resistance of malignant tumors. Hence, further evaluation and targeting of necroptosis may be of clinical benefit for gynecologic cancers (GCs). METH...

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Autores principales: Zheng, Jianfeng, Cai, Xintong, Zhang, Yu, Wang, Huihui, Liu, Li, Tang, Fengling, Liu, Linying, Sun, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650890/
https://www.ncbi.nlm.nih.gov/pubmed/36357839
http://dx.doi.org/10.1186/s12885-022-10166-6
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author Zheng, Jianfeng
Cai, Xintong
Zhang, Yu
Wang, Huihui
Liu, Li
Tang, Fengling
Liu, Linying
Sun, Yang
author_facet Zheng, Jianfeng
Cai, Xintong
Zhang, Yu
Wang, Huihui
Liu, Li
Tang, Fengling
Liu, Linying
Sun, Yang
author_sort Zheng, Jianfeng
collection PubMed
description BACKGROUND: In recent years, it has been proved that necroptosis plays an important role in the occurrence, development, invasion, metastasis and drug resistance of malignant tumors. Hence, further evaluation and targeting of necroptosis may be of clinical benefit for gynecologic cancers (GCs). METHODS: To compare consistency and difference, we explored the expression pattern and prognostic value of necroptosis-related genes (NRGs) in pan-GC analysis through Linear regression and Empirical Bayesian, Univariate Cox analysis, and public databases from TCGA and Genotype-Tissue Expression (GTEx), including CESC, OV, UCEC, and UCS. We explored the copy number variation (CNV), methylation level and enrichment pathways of NRGs in the four GCs. Based on LASSO Cox regression analysis or principal component analysis, we established the prognostic NRG-signature or necroptosis-score for the four GCs. In addition, we predicted and compared functional pathways, tumor mutational burden (TMB), somatic mutation features, immunity status, immunotherapy, chemotherapeutic drug sensitivity of the NRG-signature based on NRGs. We also examined the expression level of several NRGs in OV samples that we collected using Quantitative Real-time PCR. RESULTS: We confirmed the presence of NRGs in expression, prognosis, CNV, and methylation for four GCs, thus comparing the consistency and difference among the four GCs. The prognosis and independent prognostic value of the risk signatures based on NRGs were determined. Through the results of subclass mapping, we found that GC patients with lower risk score may be more sensitive to PDL1 response and more sensitive to immune checkpoint blockade therapy. Drug susceptibility analysis showed that, 51, 45, 64, and 29 drugs with differences between risk groups were yielded in CESC, OV, UCEC, and UCS respectively. For OV, the expression differences of several NRGs in the tissues we collected were similar to that in TCGA. CONCLUSION: Our comprehensive analysis of NRGs and NRG-signature demonstrated their similarity and difference, as well as their potential roles in prognosis and could guide therapeutic strategies, thus improving the outcome of GC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10166-6.
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spelling pubmed-96508902022-11-15 A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers Zheng, Jianfeng Cai, Xintong Zhang, Yu Wang, Huihui Liu, Li Tang, Fengling Liu, Linying Sun, Yang BMC Cancer Research BACKGROUND: In recent years, it has been proved that necroptosis plays an important role in the occurrence, development, invasion, metastasis and drug resistance of malignant tumors. Hence, further evaluation and targeting of necroptosis may be of clinical benefit for gynecologic cancers (GCs). METHODS: To compare consistency and difference, we explored the expression pattern and prognostic value of necroptosis-related genes (NRGs) in pan-GC analysis through Linear regression and Empirical Bayesian, Univariate Cox analysis, and public databases from TCGA and Genotype-Tissue Expression (GTEx), including CESC, OV, UCEC, and UCS. We explored the copy number variation (CNV), methylation level and enrichment pathways of NRGs in the four GCs. Based on LASSO Cox regression analysis or principal component analysis, we established the prognostic NRG-signature or necroptosis-score for the four GCs. In addition, we predicted and compared functional pathways, tumor mutational burden (TMB), somatic mutation features, immunity status, immunotherapy, chemotherapeutic drug sensitivity of the NRG-signature based on NRGs. We also examined the expression level of several NRGs in OV samples that we collected using Quantitative Real-time PCR. RESULTS: We confirmed the presence of NRGs in expression, prognosis, CNV, and methylation for four GCs, thus comparing the consistency and difference among the four GCs. The prognosis and independent prognostic value of the risk signatures based on NRGs were determined. Through the results of subclass mapping, we found that GC patients with lower risk score may be more sensitive to PDL1 response and more sensitive to immune checkpoint blockade therapy. Drug susceptibility analysis showed that, 51, 45, 64, and 29 drugs with differences between risk groups were yielded in CESC, OV, UCEC, and UCS respectively. For OV, the expression differences of several NRGs in the tissues we collected were similar to that in TCGA. CONCLUSION: Our comprehensive analysis of NRGs and NRG-signature demonstrated their similarity and difference, as well as their potential roles in prognosis and could guide therapeutic strategies, thus improving the outcome of GC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10166-6. BioMed Central 2022-11-10 /pmc/articles/PMC9650890/ /pubmed/36357839 http://dx.doi.org/10.1186/s12885-022-10166-6 Text en © The Author(s) 2022 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
Zheng, Jianfeng
Cai, Xintong
Zhang, Yu
Wang, Huihui
Liu, Li
Tang, Fengling
Liu, Linying
Sun, Yang
A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
title A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
title_full A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
title_fullStr A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
title_full_unstemmed A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
title_short A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
title_sort comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650890/
https://www.ncbi.nlm.nih.gov/pubmed/36357839
http://dx.doi.org/10.1186/s12885-022-10166-6
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