A novel urinary microRNA biomarker panel for detecting gastric cancer.
Biomarker
Gastric cancer
Urinary miRNA
miR-6807-5p
miR-6856-5p
Journal
Journal of gastroenterology
ISSN: 1435-5922
Titre abrégé: J Gastroenterol
Pays: Japan
ID NLM: 9430794
Informations de publication
Date de publication:
Dec 2019
Dec 2019
Historique:
received:
05
04
2019
accepted:
19
06
2019
pubmed:
27
6
2019
medline:
30
9
2020
entrez:
27
6
2019
Statut:
ppublish
Résumé
Gastric cancer (GC) is one of the most common causes of cancer deaths worldwide; however, reliable and non-invasive screening methods for GC are not established. Therefore, we conducted this study to develop a biomarker for GC detection, consisting of urinary microRNAs (miRNAs). We matched 306 participants by age and sex [153 pairs consisting of patients with GC and healthy controls (HCs)], then randomly divided them across three groups: (1) the discovery cohort (4 pairs); (2) the training cohort (95 pairs); and (3) the validation cohort (54 pairs). There were 22 urinary miRNAs with significantly aberrant expressions between the two groups in the discovery cohort. Upon multivariate analysis of the training cohort, urinary expression levels of miR-6807-5p and miR-6856-5p were significantly independent biomarkers for diagnosis of GC, in addition to Helicobacter pylori (H. pylori) status. A diagnostic panel that combined these 2 miRNAs and H. pylori status distinguished between HC and GC samples with an area under the curve (AUC) = 0.736. In the validation cohort, urinary miR-6807-5p and miR-6856-5p showed significantly higher expression levels in the GC group, and the combination biomarker panel of miR-6807-5p, miR-6856-5p, and H. pylori status also showed excellent performance (AUC = 0.885). In addition, this biomarker panel could distinguish between HC and stage I GC patients with an AUC = 0.748. Urinary expression levels of miR-6807-5p and miR-6856-5p significantly decreased to undetectable level after curative resection of GC. This novel biomarker panel enables early and non-invasive detection of GC.
Sections du résumé
BACKGROUND
BACKGROUND
Gastric cancer (GC) is one of the most common causes of cancer deaths worldwide; however, reliable and non-invasive screening methods for GC are not established. Therefore, we conducted this study to develop a biomarker for GC detection, consisting of urinary microRNAs (miRNAs).
METHODS
METHODS
We matched 306 participants by age and sex [153 pairs consisting of patients with GC and healthy controls (HCs)], then randomly divided them across three groups: (1) the discovery cohort (4 pairs); (2) the training cohort (95 pairs); and (3) the validation cohort (54 pairs).
RESULTS
RESULTS
There were 22 urinary miRNAs with significantly aberrant expressions between the two groups in the discovery cohort. Upon multivariate analysis of the training cohort, urinary expression levels of miR-6807-5p and miR-6856-5p were significantly independent biomarkers for diagnosis of GC, in addition to Helicobacter pylori (H. pylori) status. A diagnostic panel that combined these 2 miRNAs and H. pylori status distinguished between HC and GC samples with an area under the curve (AUC) = 0.736. In the validation cohort, urinary miR-6807-5p and miR-6856-5p showed significantly higher expression levels in the GC group, and the combination biomarker panel of miR-6807-5p, miR-6856-5p, and H. pylori status also showed excellent performance (AUC = 0.885). In addition, this biomarker panel could distinguish between HC and stage I GC patients with an AUC = 0.748. Urinary expression levels of miR-6807-5p and miR-6856-5p significantly decreased to undetectable level after curative resection of GC.
CONCLUSIONS
CONCLUSIONS
This novel biomarker panel enables early and non-invasive detection of GC.
Identifiants
pubmed: 31240436
doi: 10.1007/s00535-019-01601-w
pii: 10.1007/s00535-019-01601-w
doi:
Substances chimiques
Biomarkers, Tumor
0
MicroRNAs
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1061-1069Subventions
Organisme : Japan Agency for Medical Research and Development
ID : JP19lm0203005j0003
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