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Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis
Skin cutaneous melanoma (SKCM) is the most aggressive type of skin cancer, with a high rate of metastasis and mortality; however, identification of biomarkers for the treatment of SKCM is required. Cluster of differentiation (CD)38 has emerged as an effective target for therapeutic drugs in several...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405635/ https://www.ncbi.nlm.nih.gov/pubmed/32774485 http://dx.doi.org/10.3892/ol.2020.11873 |
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author | Wang, Xianwang Wang, Pengli Ge, Lei Wang, Juan Naqvi, Syed Manzar Abbas Shah Hu, Shujuan |
author_facet | Wang, Xianwang Wang, Pengli Ge, Lei Wang, Juan Naqvi, Syed Manzar Abbas Shah Hu, Shujuan |
author_sort | Wang, Xianwang |
collection | PubMed |
description | Skin cutaneous melanoma (SKCM) is the most aggressive type of skin cancer, with a high rate of metastasis and mortality; however, identification of biomarkers for the treatment of SKCM is required. Cluster of differentiation (CD)38 has emerged as an effective target for therapeutic drugs in several types of cancer, such as chronic lymphocytic leukemia and multiple myeloma. In the present study, to determine the contribution of CD38 to the diagnosis of SKCM, Gene Expression Profiling Interactive Analysis 2 and University of Alabama Cancer Database online tools were used to analyze The Cancer Genome Atlas-SKCM dataset. Moreover, Search Tool for the Retrieval of Interacting Genes/Proteins and GeneMANIA databases were used to determine protein-protein interaction networks and potential functions. To the best of our knowledge, the results of the present study indicated for the first time that high expression levels of CD38 were a favorable diagnostic factor for SKCM. Moreover, a correlation between CD38 expression levels and the survival probability of patients with SKCM was identified. Integrative analysis predicted that nine genes were correlated with CD38 in SKCM, and the similarity of these genes in SKCM expression and a survival heatmap was verified. Gene ontology enrichment analysis using the Metascape tool revealed that CD38 and its correlated genes were significantly enriched in lymphocyte activation and T cell differentiation regulation. Collectively, the bioinformatics analysis revealed that CD38 might serve as a potential diagnostic predictor for SKCM. |
format | Online Article Text |
id | pubmed-7405635 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-74056352020-08-06 Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis Wang, Xianwang Wang, Pengli Ge, Lei Wang, Juan Naqvi, Syed Manzar Abbas Shah Hu, Shujuan Oncol Lett Articles Skin cutaneous melanoma (SKCM) is the most aggressive type of skin cancer, with a high rate of metastasis and mortality; however, identification of biomarkers for the treatment of SKCM is required. Cluster of differentiation (CD)38 has emerged as an effective target for therapeutic drugs in several types of cancer, such as chronic lymphocytic leukemia and multiple myeloma. In the present study, to determine the contribution of CD38 to the diagnosis of SKCM, Gene Expression Profiling Interactive Analysis 2 and University of Alabama Cancer Database online tools were used to analyze The Cancer Genome Atlas-SKCM dataset. Moreover, Search Tool for the Retrieval of Interacting Genes/Proteins and GeneMANIA databases were used to determine protein-protein interaction networks and potential functions. To the best of our knowledge, the results of the present study indicated for the first time that high expression levels of CD38 were a favorable diagnostic factor for SKCM. Moreover, a correlation between CD38 expression levels and the survival probability of patients with SKCM was identified. Integrative analysis predicted that nine genes were correlated with CD38 in SKCM, and the similarity of these genes in SKCM expression and a survival heatmap was verified. Gene ontology enrichment analysis using the Metascape tool revealed that CD38 and its correlated genes were significantly enriched in lymphocyte activation and T cell differentiation regulation. Collectively, the bioinformatics analysis revealed that CD38 might serve as a potential diagnostic predictor for SKCM. D.A. Spandidos 2020-10 2020-07-15 /pmc/articles/PMC7405635/ /pubmed/32774485 http://dx.doi.org/10.3892/ol.2020.11873 Text en Copyright: © Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Wang, Xianwang Wang, Pengli Ge, Lei Wang, Juan Naqvi, Syed Manzar Abbas Shah Hu, Shujuan Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
title | Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
title_full | Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
title_fullStr | Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
title_full_unstemmed | Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
title_short | Identification of CD38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
title_sort | identification of cd38 as a potential biomarker in skin cutaneous melanoma using bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405635/ https://www.ncbi.nlm.nih.gov/pubmed/32774485 http://dx.doi.org/10.3892/ol.2020.11873 |
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