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Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling

Cutaneous melanoma is an aggressive malignancy with high heterogeneity. Several studies have been performed to identify cutaneous melanoma subtypes based on genomic profiling. However, few classifications based on assessments of immune-associated genes have limited clinical implications for cutaneou...

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Autores principales: Yu, Jie, Xie, Minyue, Ge, Shengfang, Chai, Peiwei, Zhou, Yixiong, Ruan, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735560/
https://www.ncbi.nlm.nih.gov/pubmed/33330057
http://dx.doi.org/10.3389/fonc.2020.580029
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author Yu, Jie
Xie, Minyue
Ge, Shengfang
Chai, Peiwei
Zhou, Yixiong
Ruan, Jing
author_facet Yu, Jie
Xie, Minyue
Ge, Shengfang
Chai, Peiwei
Zhou, Yixiong
Ruan, Jing
author_sort Yu, Jie
collection PubMed
description Cutaneous melanoma is an aggressive malignancy with high heterogeneity. Several studies have been performed to identify cutaneous melanoma subtypes based on genomic profiling. However, few classifications based on assessments of immune-associated genes have limited clinical implications for cutaneous melanoma. Using 470 cutaneous melanoma samples from The Cancer Genome Atlas (TCGA), we calculated the enrichment levels of 29 immune-associated gene sets in each sample and hierarchically clustered them into Immunity High (Immunity_H, n=323, 68.7%), Immunity Medium (Immunity_M, n=135, 28.7%), and Immunity Low (Immunity_L, n=12, 2.6%) based on the ssGSEA score. The ESTIMATE algorithm was used to calculate stromal scores (range: -1,800.51–1,901.99), immune scores (range: -1,476.28–3,780.33), estimate scores (range: -2,618.28–5,098.14) and tumor purity (range: 0.216–0.976) and they were significantly correlated with immune subtypes (Kruskal–Wallis test, P < 0.001). The Immunity_H group tended to have higher expression levels of HLA and immune checkpoint genes (Kruskal–Wallis test, P < 0.05). The Immunity_H group had the highest level of naïve B cells, resting dendritic cells, M1 macrophages, resting NK cells, plasma cells, CD4 memory activated T cells, CD8 T cells, follicular helper T cells and regulatory T cells, and the Immunity_L group had better overall survival. The GO terms identified in the Immunity_H group were mainly immune related. In conclusion, immune signature-associated cutaneous melanoma subtypes play a role in cutaneous melanoma prognosis stratification. The construction of immune signature-associated cutaneous melanoma subtypes predicted possible patient outcomes and provided possible immunotherapy candidates.
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spelling pubmed-77355602020-12-15 Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling Yu, Jie Xie, Minyue Ge, Shengfang Chai, Peiwei Zhou, Yixiong Ruan, Jing Front Oncol Oncology Cutaneous melanoma is an aggressive malignancy with high heterogeneity. Several studies have been performed to identify cutaneous melanoma subtypes based on genomic profiling. However, few classifications based on assessments of immune-associated genes have limited clinical implications for cutaneous melanoma. Using 470 cutaneous melanoma samples from The Cancer Genome Atlas (TCGA), we calculated the enrichment levels of 29 immune-associated gene sets in each sample and hierarchically clustered them into Immunity High (Immunity_H, n=323, 68.7%), Immunity Medium (Immunity_M, n=135, 28.7%), and Immunity Low (Immunity_L, n=12, 2.6%) based on the ssGSEA score. The ESTIMATE algorithm was used to calculate stromal scores (range: -1,800.51–1,901.99), immune scores (range: -1,476.28–3,780.33), estimate scores (range: -2,618.28–5,098.14) and tumor purity (range: 0.216–0.976) and they were significantly correlated with immune subtypes (Kruskal–Wallis test, P < 0.001). The Immunity_H group tended to have higher expression levels of HLA and immune checkpoint genes (Kruskal–Wallis test, P < 0.05). The Immunity_H group had the highest level of naïve B cells, resting dendritic cells, M1 macrophages, resting NK cells, plasma cells, CD4 memory activated T cells, CD8 T cells, follicular helper T cells and regulatory T cells, and the Immunity_L group had better overall survival. The GO terms identified in the Immunity_H group were mainly immune related. In conclusion, immune signature-associated cutaneous melanoma subtypes play a role in cutaneous melanoma prognosis stratification. The construction of immune signature-associated cutaneous melanoma subtypes predicted possible patient outcomes and provided possible immunotherapy candidates. Frontiers Media S.A. 2020-11-30 /pmc/articles/PMC7735560/ /pubmed/33330057 http://dx.doi.org/10.3389/fonc.2020.580029 Text en Copyright © 2020 Yu, Xie, Ge, Chai, Zhou and Ruan http://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
Yu, Jie
Xie, Minyue
Ge, Shengfang
Chai, Peiwei
Zhou, Yixiong
Ruan, Jing
Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling
title Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling
title_full Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling
title_fullStr Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling
title_full_unstemmed Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling
title_short Hierarchical Clustering of Cutaneous Melanoma Based on Immunogenomic Profiling
title_sort hierarchical clustering of cutaneous melanoma based on immunogenomic profiling
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735560/
https://www.ncbi.nlm.nih.gov/pubmed/33330057
http://dx.doi.org/10.3389/fonc.2020.580029
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