ArticleMedicine2017
Bioinformatics analysis to identify the critical genes, microRNAs and long noncoding RNAs in melanoma.
Article in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Identification of Core Genes and Pathways in Melanoma Metastasis via Bioinformatics Analysis.International journal of molecular sciences · 2022Article
- Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection.Computers in biology and medicine · 2021Article
- Construction of a Ferroptosis-Related Gene Signature for Predicting Survival and Immune Microenvironment in Melanoma Patients.International journal of general medicine · 2021Article
- Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach.Bioinformatics and biology insights · 2021Article
- Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Melanoma.Frontiers in oncology · 2020Article
- Deep sequencing of small RNAs reveals the repertoire of miRNAs and piRNAs in Biomphalaria glabrata.Memorias do Instituto Oswaldo Cruz · 2020Article
- Identification of Signatures of Prognosis Prediction for Melanoma Using a Hypoxia Score.Frontiers in genetics · 2020Article
- Bioinformatics Analysis Identifies MicroRNAs and Target Genes Associated with Prognosis in Patients with Melanoma.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- Integrative analysis of competing endogenous RNA network focusing on long noncoding RNA associated with progression of cutaneous melanoma.Cancer medicine · 2018Article
- The cytomegalovirus protein US31 induces inflammation through mono-macrophages in systemic lupus erythematosus by promoting NF-κB2 activation.Cell death & disease · 2018Article
- Long non-coding RNA PANDAR promotes melanoma cell invasion through regulating epithelial-mesenchymal transition.International journal of clinical and experimental pathology · 2018Article
- MYBPC2 and MYL1 as Significant Gene Markers for Rhabdomyosarcoma.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Melanoma, which is usually induced by ultraviolet light exposure and the following DNA damage, is the most dangerous skin cancer. The purpose of the present study was to screen key molecules involved in melanoma.Microarray data of E-MTAB-1862 were downloaded from the ArrayExpress database, which included 21 primary melanoma samples and 11 benign nevus samples. In addition, the RNASeq version 2 and microRNA (miRNA) sequencing data of cutaneous melanoma were downloaded from The Cancer Genome Atlas database. After identifying the differentially expressed genes (DEGs) using Limma package, enrichment analysis and protein-protein interaction (PPI) network analysis were performed separately for them using DAVID software and Cytoscape software. In addition, survival analysis and regulatory network analysis were further performed by log-rank test and Cytoscape software, respectively. Moreover, real-time reverse transcription polymerase chain reaction (RT-PCR) was performed to further verify the expression patterns of several selected DEGs.A total of 382 DEGs were identified in primary melanoma samples, including 206 upregulated genes and 176 downregulated genes. Functional enrichment analysis showed that COL17A1 was enriched in epidermis development. In the PPI network, CXCL8 (degree = 29) and STAT1 (degree = 28) had higher degrees and could interact with each other. Survival analysis showed that 21 DEGs, 55 long noncoding RNAs (lncRNAs) and 32 miRNAs were found to be associated with prognosis. Furthermore, several regulatory relationships were found in the lncRNA-gene regulatory network (such as RP11-361L15.4 targeting COL17A1) and the miRNA-gene regulatory network (such as hsa-miR-375 targeting CCL27 and hsa-miR-375 targeting insulin-like growth factor 1 receptor [IGF1R]). Real-time RT-PCR results showed that the overall direction of differential expression was consistent except COL17A1.CXCL8 interacted with STAT1, CCL27, and IGF1R targeted by hsa-miR-375, and COL17A1 targeted by RP11-361L15.4 might function in the development and progression of melanoma, which should be verified by more detailed experiments.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.