Plasma nanoDSF Denaturation Profile at Baseline Is Predictive of Glioblastoma EGFR Status.
biomarker
cancer
differential scanning fluorimetry
glioblastoma
machine learning
neuro-oncology
neurophysiopathology
plasma profiling
Journal
Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829
Informations de publication
Date de publication:
26 Jan 2023
26 Jan 2023
Historique:
received:
09
10
2022
revised:
05
01
2023
accepted:
18
01
2023
entrez:
11
2
2023
pubmed:
12
2
2023
medline:
12
2
2023
Statut:
epublish
Résumé
Glioblastoma (GBM) is the most frequent and aggressive primary brain tumor in adults. Recently, we demonstrated that plasma denaturation profiles of glioblastoma patients obtained using Differential Scanning Fluorimetry can be automatically distinguished from healthy controls with the help of Artificial Intelligence (AI). Here, we used a set of machine-learning algorithms to automatically classify plasma denaturation profiles of glioblastoma patients according to their EGFR status. We found that Adaboost AI is able to discriminate
Identifiants
pubmed: 36765718
pii: cancers15030760
doi: 10.3390/cancers15030760
pmc: PMC9913157
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Cancéropôle PACA
ID : Recherche Translationnelle - GPP
Organisme : French National Alliance for Life Sciences and Health
ID : ITMO Cancer MIC - AI4OP
Organisme : French National Cancer Institute
ID : INCa-DGOS-Inserm_12560
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