The Metabolomic Approach for the Screening of Endometrial Cancer: Validation from a Large Cohort of Women Scheduled for Gynecological Surgery.
endometrial cancer
ensemble machine learning
metabolomics
oncological screening
Journal
Biomolecules
ISSN: 2218-273X
Titre abrégé: Biomolecules
Pays: Switzerland
ID NLM: 101596414
Informations de publication
Date de publication:
02 09 2022
02 09 2022
Historique:
received:
17
07
2022
revised:
24
08
2022
accepted:
30
08
2022
entrez:
23
9
2022
pubmed:
24
9
2022
medline:
28
9
2022
Statut:
epublish
Résumé
Endometrial cancer (EC) is the most common gynecological neoplasm in high-income countries. Five-year survival rates are related to stage at diagnosis, but currently, no validated screening tests are available in clinical practice. The metabolome offers an unprecedented overview of the molecules underlying EC. In this study, we aimed to validate a metabolomics signature as a screening test for EC on a large study population of symptomatic women. Serum samples collected from women scheduled for gynecological surgery (
Identifiants
pubmed: 36139068
pii: biom12091229
doi: 10.3390/biom12091229
pmc: PMC9496630
pii:
doi:
Substances chimiques
Glyceraldehyde 3-Phosphate
142-10-9
Glutamic Acid
3KX376GY7L
Serine
452VLY9402
Phenylalanine
47E5O17Y3R
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
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