ArticleOncoTargets and therapy2018
Identification of epigenetically altered genes and potential gene targets in melanoma using bioinformatic methods.
Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Down-regulated expression of miR-582 predicts poor prognosis and facilitates melanoma progression by targeting FOXC1.Archives of dermatological research · 2022Article
- Identification of aberrantly methylated differentially expressed genes and pro-tumorigenic role of KIF2C in melanoma.Frontiers in genetics · 2022Article
- Comparison of miRNA-101a-3p and miRNA-144a-3p regulation with the key genes of alpaca melanocyte pigmentation.BMC molecular biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to analyze epigenetically and genetically altered genes in melanoma to get a better understanding of the molecular circuitry of melanoma and identify potential gene targets for the treatment of melanoma. The microarray data of GSE31879, including mRNA expression profiles (seven melanoma and four melanocyte samples) and DNA methylation profiles (seven melanoma and five melanocyte samples), were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated positions (DMPs) were screened using the linear models for microarray data (limma) package in melanoma compared with melanocyte samples. Gene ontology (GO) and pathway enrichment analysis of the DEGs were carried out using the Database for Annotation, Visualization, and Integrated Discovery. Moreover, differentially methylated genes (DMGs) were identified, and a transcriptional regulatory network was constructed using the University of California Santa Cruz genome browser database. A total of 1,215 DEGs (199 upregulated and 1,016 downregulated) and 14,094 DMPs (10,450 upregulated and 3,644 downregulated) were identified in melanoma compared with melanocyte samples. Additionally, the upregulated and downregulated DEGs were significantly associated with different GO terms and pathways, such as pigment cell differentiation, biosynthesis, and metabolism. Furthermore, the transcriptional regulatory network showed that DMGs such as Aristaless-related homeobox (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.