Cargando…

Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma

Melanoma is a skin cancer with great metastatic potential, which is responsible for the major deaths in skin cancer. Although the prognosis of melanoma patients has been improved with the comprehensive treatment, for patients with metastasis, the complexity and heterogeneity of diffuse diseases make...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Rong-zhi, Mao, Min, Zheng, Jie, Liang, Hai-qi, Liu, Feng-ling, Zhou, Gui-you, Huang, Yao-qing, Zeng, Fan-yue, Li, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806975/
https://www.ncbi.nlm.nih.gov/pubmed/33441929
http://dx.doi.org/10.1038/s41598-020-80858-1
_version_ 1783636644438474752
author Huang, Rong-zhi
Mao, Min
Zheng, Jie
Liang, Hai-qi
Liu, Feng-ling
Zhou, Gui-you
Huang, Yao-qing
Zeng, Fan-yue
Li, Xu
author_facet Huang, Rong-zhi
Mao, Min
Zheng, Jie
Liang, Hai-qi
Liu, Feng-ling
Zhou, Gui-you
Huang, Yao-qing
Zeng, Fan-yue
Li, Xu
author_sort Huang, Rong-zhi
collection PubMed
description Melanoma is a skin cancer with great metastatic potential, which is responsible for the major deaths in skin cancer. Although the prognosis of melanoma patients has been improved with the comprehensive treatment, for patients with metastasis, the complexity and heterogeneity of diffuse diseases make prognosis prediction and systematic treatment difficult and ineffective. Therefore, we established a novel personalized immune-related gene pairs index (IRGPI) to predict the prognosis of patients with metastatic melanoma, which was conducive to provide new insights into clinical decision-making and prognostic monitoring for metastatic melanoma. Through complex analysis and filtering, we identified 24 immune-related gene pairs to build the model and obtained the optimal cut-off value from receiver operating characteristic curves, which divided the patients into high and low immune-risk groups. Meantime, the Kaplan–Meier analysis, Cox regression analysis and subgroup analysis showed that IRGPI had excellent prognostic value. Furthermore, IRGPI was shown that was closely associated with immune system in the subsequent tumor microenvironment analysis and gene set enrichment analysis. In addition, we broken through the data processing limitations of traditional researches in different platforms through the application of gene pairs, which would provide great credibility for our model. We believe that our research would provide a new perspective for clinical decision-making and prognostic monitoring in metastatic melanoma.
format Online
Article
Text
id pubmed-7806975
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-78069752021-01-14 Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma Huang, Rong-zhi Mao, Min Zheng, Jie Liang, Hai-qi Liu, Feng-ling Zhou, Gui-you Huang, Yao-qing Zeng, Fan-yue Li, Xu Sci Rep Article Melanoma is a skin cancer with great metastatic potential, which is responsible for the major deaths in skin cancer. Although the prognosis of melanoma patients has been improved with the comprehensive treatment, for patients with metastasis, the complexity and heterogeneity of diffuse diseases make prognosis prediction and systematic treatment difficult and ineffective. Therefore, we established a novel personalized immune-related gene pairs index (IRGPI) to predict the prognosis of patients with metastatic melanoma, which was conducive to provide new insights into clinical decision-making and prognostic monitoring for metastatic melanoma. Through complex analysis and filtering, we identified 24 immune-related gene pairs to build the model and obtained the optimal cut-off value from receiver operating characteristic curves, which divided the patients into high and low immune-risk groups. Meantime, the Kaplan–Meier analysis, Cox regression analysis and subgroup analysis showed that IRGPI had excellent prognostic value. Furthermore, IRGPI was shown that was closely associated with immune system in the subsequent tumor microenvironment analysis and gene set enrichment analysis. In addition, we broken through the data processing limitations of traditional researches in different platforms through the application of gene pairs, which would provide great credibility for our model. We believe that our research would provide a new perspective for clinical decision-making and prognostic monitoring in metastatic melanoma. Nature Publishing Group UK 2021-01-13 /pmc/articles/PMC7806975/ /pubmed/33441929 http://dx.doi.org/10.1038/s41598-020-80858-1 Text en © The Author(s) 2021 Open Access This 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/.
spellingShingle Article
Huang, Rong-zhi
Mao, Min
Zheng, Jie
Liang, Hai-qi
Liu, Feng-ling
Zhou, Gui-you
Huang, Yao-qing
Zeng, Fan-yue
Li, Xu
Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
title Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
title_full Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
title_fullStr Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
title_full_unstemmed Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
title_short Development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
title_sort development of an immune-related gene pairs index for the prognosis analysis of metastatic melanoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806975/
https://www.ncbi.nlm.nih.gov/pubmed/33441929
http://dx.doi.org/10.1038/s41598-020-80858-1
work_keys_str_mv AT huangrongzhi developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT maomin developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT zhengjie developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT lianghaiqi developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT liufengling developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT zhouguiyou developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT huangyaoqing developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT zengfanyue developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma
AT lixu developmentofanimmunerelatedgenepairsindexfortheprognosisanalysisofmetastaticmelanoma