Cargando…
Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment
BACKGROUND: Cutaneous tumors are commonly seen in clinical practice, and malignant melanoma (MM) is the leading cause of cutaneous tumor-induced death. The tumor microenvironment (TME), a critical part of tumorigenesis, has been a research hotspot in recent years. However, the effects of the MM micr...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843331/ https://www.ncbi.nlm.nih.gov/pubmed/36660621 http://dx.doi.org/10.21037/atm-22-5761 |
_version_ | 1784870370533179392 |
---|---|
author | Yan, Lin Yu, Zhiyu Wang, Huakang Qu, Caijie Wang, Yuyang Yao, Han Shi, Tongxin Li, Yang |
author_facet | Yan, Lin Yu, Zhiyu Wang, Huakang Qu, Caijie Wang, Yuyang Yao, Han Shi, Tongxin Li, Yang |
author_sort | Yan, Lin |
collection | PubMed |
description | BACKGROUND: Cutaneous tumors are commonly seen in clinical practice, and malignant melanoma (MM) is the leading cause of cutaneous tumor-induced death. The tumor microenvironment (TME), a critical part of tumorigenesis, has been a research hotspot in recent years. However, the effects of the MM microenvironment components remain elusive. This study aimed to analyze the various components in the TME of MM to identify factors affecting the tumorigenesis, progression, and metastasis of MM and the survival of MM patients. We also aimed to identify biomarkers related to TME rehabilitation to provide a new direction for MM treatment. METHODS: We used bioinformatics to analyze the RNA-seq and somatic mutation data of 473 MM patients from The Cancer Genome Atlas database. Firstly, the patients’ immunity and stroma were separately scored by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) method. According to the median score, the participants were split into high- and low-score groups. Then, Gene Set Enrichment Analysis (GSEA) was performed, showing that high-expression genes were highly abundant in biological and metabolic activities associated with the immune system. RESULTS: Differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were identified and intersected to obtain the key immune-related genes PSMB8, FAM216B, DYSF, and FAM131C. PSMB8 was finally selected as the preferred immune-related prognostic marker; it was positively associated with overall survival and therefore considered a protective gene for MM patients. The GSEA analysis showed that PSMB8 with high expression had greater gene abundance in biological and metabolic processes related to immune system. In addition, CIBERSORT analysis showed an association between the proportion of tumor-infiltrating immune cells and PSMB8 expression. CONCLUSIONS: Our results suggest that PSMB8 might be associated with tumorigenesis and MM progression and could serve as a biomarker for the TME rehabilitation of MM. Our findings provide a new perspective and direction for the treatment of MM. |
format | Online Article Text |
id | pubmed-9843331 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-98433312023-01-18 Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment Yan, Lin Yu, Zhiyu Wang, Huakang Qu, Caijie Wang, Yuyang Yao, Han Shi, Tongxin Li, Yang Ann Transl Med Original Article BACKGROUND: Cutaneous tumors are commonly seen in clinical practice, and malignant melanoma (MM) is the leading cause of cutaneous tumor-induced death. The tumor microenvironment (TME), a critical part of tumorigenesis, has been a research hotspot in recent years. However, the effects of the MM microenvironment components remain elusive. This study aimed to analyze the various components in the TME of MM to identify factors affecting the tumorigenesis, progression, and metastasis of MM and the survival of MM patients. We also aimed to identify biomarkers related to TME rehabilitation to provide a new direction for MM treatment. METHODS: We used bioinformatics to analyze the RNA-seq and somatic mutation data of 473 MM patients from The Cancer Genome Atlas database. Firstly, the patients’ immunity and stroma were separately scored by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) method. According to the median score, the participants were split into high- and low-score groups. Then, Gene Set Enrichment Analysis (GSEA) was performed, showing that high-expression genes were highly abundant in biological and metabolic activities associated with the immune system. RESULTS: Differentially expressed genes (DEGs) and differentially mutated genes (DMGs) were identified and intersected to obtain the key immune-related genes PSMB8, FAM216B, DYSF, and FAM131C. PSMB8 was finally selected as the preferred immune-related prognostic marker; it was positively associated with overall survival and therefore considered a protective gene for MM patients. The GSEA analysis showed that PSMB8 with high expression had greater gene abundance in biological and metabolic processes related to immune system. In addition, CIBERSORT analysis showed an association between the proportion of tumor-infiltrating immune cells and PSMB8 expression. CONCLUSIONS: Our results suggest that PSMB8 might be associated with tumorigenesis and MM progression and could serve as a biomarker for the TME rehabilitation of MM. Our findings provide a new perspective and direction for the treatment of MM. AME Publishing Company 2022-12 /pmc/articles/PMC9843331/ /pubmed/36660621 http://dx.doi.org/10.21037/atm-22-5761 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Yan, Lin Yu, Zhiyu Wang, Huakang Qu, Caijie Wang, Yuyang Yao, Han Shi, Tongxin Li, Yang Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
title | Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
title_full | Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
title_fullStr | Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
title_full_unstemmed | Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
title_short | Bioinformatics analysis identifies PSMB8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
title_sort | bioinformatics analysis identifies psmb8 as a key gene in the cutaneous malignant melanoma tumor microenvironment |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843331/ https://www.ncbi.nlm.nih.gov/pubmed/36660621 http://dx.doi.org/10.21037/atm-22-5761 |
work_keys_str_mv | AT yanlin bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT yuzhiyu bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT wanghuakang bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT qucaijie bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT wangyuyang bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT yaohan bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT shitongxin bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment AT liyang bioinformaticsanalysisidentifiespsmb8asakeygeneinthecutaneousmalignantmelanomatumormicroenvironment |