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Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes
BACKGROUND: Necroptosis is crucial for organismal development and pathogenesis. To date, the role of necroptosis in skin cutaneous melanoma (SKCM) is yet unveiled. In addition, the part of melanin pigmentation was largely neglected in the bioinformatic analysis. In this study, we aimed to construct...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979066/ https://www.ncbi.nlm.nih.gov/pubmed/35387121 http://dx.doi.org/10.3389/fonc.2022.852803 |
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author | Niu, Zehao Wang, Xin Xu, Yujian Li, Yan Gong, Xiaojing Zeng, Quan Zhang, Biao Xi, Jiafei Pei, Xuetao Yue, Wen Han, Yan |
author_facet | Niu, Zehao Wang, Xin Xu, Yujian Li, Yan Gong, Xiaojing Zeng, Quan Zhang, Biao Xi, Jiafei Pei, Xuetao Yue, Wen Han, Yan |
author_sort | Niu, Zehao |
collection | PubMed |
description | BACKGROUND: Necroptosis is crucial for organismal development and pathogenesis. To date, the role of necroptosis in skin cutaneous melanoma (SKCM) is yet unveiled. In addition, the part of melanin pigmentation was largely neglected in the bioinformatic analysis. In this study, we aimed to construct a novel prognostic model based on necroptosis-related genes and analysis the pigmentation phenotype of patients to provide clinically actionable information for SKCM patients. METHODS: We downloaded the SKCM data from the TCGA and GEO databases in this study and identified the differently expressed and prognostic necroptosis-related genes. Patients’ pigmentation phenotype was evaluated by the GSVA method. Then, using Lasso and Cox regression analysis, a novel prognostic model was constructed based on the intersected genes. The risk score was calculated and the patients were divided into two groups. The survival differences between the two groups were compared using Kaplan-Meier analysis. The ROC analysis was performed and the area under curves was calculated to evaluate the prediction performances of the model. Then, the GO, KEGG and GSEA analyses were performed to elucidate the underlying mechanisms. Differences in the tumor microenvironment, patients’ response to immune checkpoint inhibitors (ICIs) and pigmentation phenotype were analyzed. In order to validate the mRNA expression levels of the selected genes, quantitative real-time PCR (qRT-PCR) was performed. RESULTS: Altogether, a novel prognostic model based on four genes (BOK, CD14, CYLD and FASLG) was constructed, and patients were classified into high and low-risk groups based on the median risk score. Low-risk group patients showed better survival status. The model showed high accuracy in the training and the validation cohort. Pathway and functional enrichment analysis indicated that immune-related pathways were differently activated in the two groups. In addition, immune cells infiltration patterns and sensitivity of ICIs showed a significant difference between patients from two risk groups. The pigmentation score was positively related to the risk score in pigmentation phenotype analysis. CONCLUSION: In conclusion, this study established a novel prognostic model based on necroptosis-related genes and revealed the possible connections between necroptosis and melanin pigmentation. It is expected to provide a reference for clinical treatment. |
format | Online Article Text |
id | pubmed-8979066 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89790662022-04-05 Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes Niu, Zehao Wang, Xin Xu, Yujian Li, Yan Gong, Xiaojing Zeng, Quan Zhang, Biao Xi, Jiafei Pei, Xuetao Yue, Wen Han, Yan Front Oncol Oncology BACKGROUND: Necroptosis is crucial for organismal development and pathogenesis. To date, the role of necroptosis in skin cutaneous melanoma (SKCM) is yet unveiled. In addition, the part of melanin pigmentation was largely neglected in the bioinformatic analysis. In this study, we aimed to construct a novel prognostic model based on necroptosis-related genes and analysis the pigmentation phenotype of patients to provide clinically actionable information for SKCM patients. METHODS: We downloaded the SKCM data from the TCGA and GEO databases in this study and identified the differently expressed and prognostic necroptosis-related genes. Patients’ pigmentation phenotype was evaluated by the GSVA method. Then, using Lasso and Cox regression analysis, a novel prognostic model was constructed based on the intersected genes. The risk score was calculated and the patients were divided into two groups. The survival differences between the two groups were compared using Kaplan-Meier analysis. The ROC analysis was performed and the area under curves was calculated to evaluate the prediction performances of the model. Then, the GO, KEGG and GSEA analyses were performed to elucidate the underlying mechanisms. Differences in the tumor microenvironment, patients’ response to immune checkpoint inhibitors (ICIs) and pigmentation phenotype were analyzed. In order to validate the mRNA expression levels of the selected genes, quantitative real-time PCR (qRT-PCR) was performed. RESULTS: Altogether, a novel prognostic model based on four genes (BOK, CD14, CYLD and FASLG) was constructed, and patients were classified into high and low-risk groups based on the median risk score. Low-risk group patients showed better survival status. The model showed high accuracy in the training and the validation cohort. Pathway and functional enrichment analysis indicated that immune-related pathways were differently activated in the two groups. In addition, immune cells infiltration patterns and sensitivity of ICIs showed a significant difference between patients from two risk groups. The pigmentation score was positively related to the risk score in pigmentation phenotype analysis. CONCLUSION: In conclusion, this study established a novel prognostic model based on necroptosis-related genes and revealed the possible connections between necroptosis and melanin pigmentation. It is expected to provide a reference for clinical treatment. Frontiers Media S.A. 2022-03-21 /pmc/articles/PMC8979066/ /pubmed/35387121 http://dx.doi.org/10.3389/fonc.2022.852803 Text en Copyright © 2022 Niu, Wang, Xu, Li, Gong, Zeng, Zhang, Xi, Pei, Yue and Han https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Niu, Zehao Wang, Xin Xu, Yujian Li, Yan Gong, Xiaojing Zeng, Quan Zhang, Biao Xi, Jiafei Pei, Xuetao Yue, Wen Han, Yan Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes |
title | Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes |
title_full | Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes |
title_fullStr | Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes |
title_full_unstemmed | Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes |
title_short | Development and Validation of a Novel Survival Model for Cutaneous Melanoma Based on Necroptosis-Related Genes |
title_sort | development and validation of a novel survival model for cutaneous melanoma based on necroptosis-related genes |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979066/ https://www.ncbi.nlm.nih.gov/pubmed/35387121 http://dx.doi.org/10.3389/fonc.2022.852803 |
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