Identification of novel prognostic markers of survival time in high-risk neuroblastoma using gene expression profiles

dc.contributor.authorGiwa, Abdulazeez
dc.contributor.authorFatai, Azeez A.
dc.contributor.authorGamieldien, Junaid
dc.date.accessioned2021-01-05T07:28:40Z
dc.date.available2021-01-05T07:28:40Z
dc.date.issued2020
dc.description.abstractNeuroblastoma is the most common extracranial solid tumor in childhood. Patients in high-risk group often have poor outcomes with low survival rates despite several treatment options. This study aimed to identify a genetic signature from gene expression profiles that can serve as prognostic indicators of survival time in patients of high-risk neuroblastoma, and that could be potential therapeutic targets. RNA-seq count data was downloaded from UCSC Xena browser and samples grouped into Short Survival (SS) and Long Survival (LS) groups. Differential gene expression (DGE) analysis, enrichment analyses, regulatory network analysis and machine learning (ML) prediction of survival group were performed. Forty differentially expressed genes (DEGs) were identified including genes involved in molecular function activities essential for tumor proliferation. DEGs used as features for prediction of survival groups included EVX2, NHLH2, PRSS12, POU6F2, HOXD10, MAPK15, RTL1, LGR5, CYP17A1, OR10AB1P, MYH14, LRRTM3, GRIN3A, HS3ST5, CRYAB and NXPH3. An accuracy score of 82% was obtained by the ML classification models. SMIM28 was revealed to possibly have a role in tumor proliferation and aggressiveness. Our results indicate that these DEGs can serve as prognostic indicators of survival in high-risk neuroblastoma patients and will assist clinicians in making better therapeutic and patient management decisions. © 2020 Giwa et al.en_US
dc.identifier.citationGiwa, A. et al. (2020). Identification of novel prognostic markers of survival time in high-risk neuroblastoma using gene expression profiles. Oncotarget ,11(46), 4293-4305en_US
dc.identifier.issn1949-2553
dc.identifier.uri10.18632/ONCOTARGET.27808
dc.identifier.urihttp://hdl.handle.net/10566/5544
dc.language.isoenen_US
dc.publisherImpact Journalsen_US
dc.subjectDifferential gene expressionen_US
dc.subjectGene regulatory networksen_US
dc.subjectMachine learningen_US
dc.subjectNeuroblastomaen_US
dc.subjectPrognostic markersen_US
dc.titleIdentification of novel prognostic markers of survival time in high-risk neuroblastoma using gene expression profilesen_US
dc.typeArticleen_US

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