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Bioinformatics and biology insights · 2021

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

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Shahmoradi Mozhdeh, Rezvani Zahra

Аннотация

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.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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