Open AccessPredicting amplification ofMYCNusing CpG methylation biomarkers in neuroblastoma
Author(s) -
Abdulazeez Giwa,
Sophia Catherine Rossouw,
Azeez Ayomide Fatai,
Junaid Gamieldien,
Alan Christoffels,
Hocine Bendou
Publication year - 2021
Publication title -
future oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.857
H-Index - 72
eISSN - 1744-8301
pISSN - 1479-6694
DOI - 10.2217/fon-2021-0522
Subject(s) - neuroblastoma , dna methylation , epigenetics , medicine , methylation , cpg site , oncology , cancer research , gene , biology , genetics , gene expression , cell culture
Background: Neuroblastoma is the most common extracranial solid tumor in childhood. Amplification of MYCN in neuroblastoma is a predictor of poor prognosis. Materials and methods: DNA methylation data from the TARGET data matrix were stratified into MYCN amplified and non-amplified groups. Differential methylation analysis, clustering, recursive feature elimination (RFE), machine learning (ML), Cox regression analysis and Kaplan–Meier estimates were performed. Results and Conclusion: 663 CpGs were differentially methylated between the two groups. A total of 25 CpGs were selected by RFE for clustering and ML, and a 100% clustering accuracy was obtained. ML validation on three external datasets produced high accuracy scores of 100%, 97% and 93%. Eight survival-associated CpGs were also identified. Therapeutic interventions may need to be targeted to patient subgroups.