Early detection of gastric cancer beyond endoscopy - new methods.


Journal

Best practice & research. Clinical gastroenterology
ISSN: 1532-1916
Titre abrégé: Best Pract Res Clin Gastroenterol
Pays: Netherlands
ID NLM: 101120605

Informations de publication

Date de publication:
Historique:
received: 27 11 2020
accepted: 08 02 2021
entrez: 12 5 2021
pubmed: 13 5 2021
medline: 22 5 2021
Statut: ppublish

Résumé

Early detection of gastric cancer is remaining a challenge. This review summarizes current knowledge on non-invasive methods that could be used for the purpose. The role of traditional cancer markers such as CEA, CA 72-4, CA 19-9, CA 15-3, and CA 12-5 lies mainly in therapy monitoring than early detection. Most extensive studied biomarkers (pepsinogens, ABC method) are aiming at the detection of precancerous lesions with modest sensitivity for cancer. Tests based on the detection of cancer-specific methylation patterns (PanSeer), circulating proteins and mutations in circulating tumour DNA (CancerSEEK), as well as miRNA panels have demonstrated promising results bringing those closer to practice. More extensive research is required before tests based on the detection of circulating tumour cells, extracellular vesicles and cell-free RNA could reach the practice. Detection of volatile organic compounds in the human breath is a promising development; sensor technologies for this purpose could be very attractive in screening settings.

Identifiants

pubmed: 33975677
pii: S1521-6918(21)00007-X
doi: 10.1016/j.bpg.2021.101731
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

101731

Informations de copyright

Copyright © 2021 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest None.

Auteurs

Mārcis Leja (M)

Institute of Clinical and Preventive Medicine, University of Latvia, 1 Gailezera iela iela, LV1079, Riga, Latvia. Electronic address: marcis.leja@lu.lv.

Aija Linē (A)

Latvian Biomedical Research and Study Centre, Latvia. Electronic address: aija@biomed.lu.lv.

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Classifications MeSH