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Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach

Cutaneous melanoma is the most aggressive type of skin cancer which its incidence has significantly increased in recent years worldwide. Thus, more investigations are required to identify the underlying mechanisms of melanoma malignant transformation and metastasis. In this context, long noncoding R...

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Autores principales: Shahmoradi, Mozhdeh, Rezvani, Zahra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868446/
https://www.ncbi.nlm.nih.gov/pubmed/33613027
http://dx.doi.org/10.1177/1177932220988508
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author Shahmoradi, Mozhdeh
Rezvani, Zahra
author_facet Shahmoradi, Mozhdeh
Rezvani, Zahra
author_sort Shahmoradi, Mozhdeh
collection PubMed
description Cutaneous melanoma is the most aggressive type of skin cancer which its incidence has significantly increased in recent years worldwide. Thus, more investigations are required to identify the underlying mechanisms of melanoma malignant transformation and metastasis. In this context, long noncoding RNAs (lncRNAs) are a new type of noncoding transcripts that their dysregulations are associated with almost all cancers including melanoma. However, the precise functional roles of most of the significantly altered lncRNAs in melanoma have not yet been fully inspected. In this study, a comprehensive list of lncRNAs was interrogated across cutaneous melanoma samples to identify the significantly altered/dysregulated lncRNAs. To this end, lncRNAs were filtered in several steps and the selected lncRNAs projected to a bioinformatic and systems biology analysis using several publicly available databases and tools such as GEPIA and cBioPortal. According to our results, 30 lncRNAs were notably altered/dysregulated in cutaneous melanoma most of which were co-expressed with each other. Also, co-expression/alteration and differential expression analyses led to the selection of 12 out of these 30 lncRNAs as cutaneous melanoma key lncRNAs. Furthermore, functional demonstrated that these 12 lncRNAs might be involved in melanoma-relevant biological processes and pathways. In addition, the end result of our analyses demonstrated that these lncRNAs are associated with the clinicopathological features of melanoma patients. These 12 lncRNAs need to be further investigated in future studies to characterize their exact roles in melanoma development and to identify their potential for being used as drug targets and/or biomarkers for cutaneous melanoma.
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spelling pubmed-78684462021-02-19 Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach Shahmoradi, Mozhdeh Rezvani, Zahra Bioinform Biol Insights Original Research Cutaneous melanoma is the most aggressive type of skin cancer which its incidence has significantly increased in recent years worldwide. Thus, more investigations are required to identify the underlying mechanisms of melanoma malignant transformation and metastasis. In this context, long noncoding RNAs (lncRNAs) are a new type of noncoding transcripts that their dysregulations are associated with almost all cancers including melanoma. However, the precise functional roles of most of the significantly altered lncRNAs in melanoma have not yet been fully inspected. In this study, a comprehensive list of lncRNAs was interrogated across cutaneous melanoma samples to identify the significantly altered/dysregulated lncRNAs. To this end, lncRNAs were filtered in several steps and the selected lncRNAs projected to a bioinformatic and systems biology analysis using several publicly available databases and tools such as GEPIA and cBioPortal. According to our results, 30 lncRNAs were notably altered/dysregulated in cutaneous melanoma most of which were co-expressed with each other. Also, co-expression/alteration and differential expression analyses led to the selection of 12 out of these 30 lncRNAs as cutaneous melanoma key lncRNAs. Furthermore, functional demonstrated that these 12 lncRNAs might be involved in melanoma-relevant biological processes and pathways. In addition, the end result of our analyses demonstrated that these lncRNAs are associated with the clinicopathological features of melanoma patients. These 12 lncRNAs need to be further investigated in future studies to characterize their exact roles in melanoma development and to identify their potential for being used as drug targets and/or biomarkers for cutaneous melanoma. SAGE Publications 2021-02-03 /pmc/articles/PMC7868446/ /pubmed/33613027 http://dx.doi.org/10.1177/1177932220988508 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Shahmoradi, Mozhdeh
Rezvani, Zahra
Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach
title Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach
title_full Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach
title_fullStr Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach
title_full_unstemmed Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach
title_short Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach
title_sort functional prediction of long noncoding rnas in cutaneous melanoma using a systems biology approach
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868446/
https://www.ncbi.nlm.nih.gov/pubmed/33613027
http://dx.doi.org/10.1177/1177932220988508
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