miR-122 and miR-21 are Stable Components of miRNA Signatures of Early Lung Cancer after Validation in Three Independent Cohorts.


Journal

The Journal of molecular diagnostics : JMD
ISSN: 1943-7811
Titre abrégé: J Mol Diagn
Pays: United States
ID NLM: 100893612

Informations de publication

Date de publication:
20 Oct 2023
Historique:
received: 30 06 2023
revised: 15 09 2023
accepted: 28 09 2023
pubmed: 22 10 2023
medline: 22 10 2023
entrez: 21 10 2023
Statut: aheadofprint

Résumé

Several panels of circulating miRNAs have been reported as potential biomarkers of early lung cancer, yet the overlap of components between different panels is limited, and the universality of proposed biomarkers has been minimal across proposed panels. To assess the stability of the diagnostic potential of plasma miRNA signature of early lung cancer among different cohorts, a panel of 24 miRNAs tested in the frame of one lung cancer screening study (MOLTEST-2013, Poland) was validated with material collected in the frame of two other screening studies (MOLTEST-BIS, Poland; and SMAC, Italy) using the same standardized analytical platform (the miRCURY LNA miRNA PCR assay). On analysis of selected miRNAs, two associated with lung cancer development, miR-122 and miR-21, repetitively differentiated healthy participants from individuals with lung cancer. Additionally, miR-144 differentiated controls from cases specifically in subcohorts with adenocarcinoma. Other tested miRNAs did not overlap in the three cohorts. Classification models based on neither a single miRNA nor multicomponent miRNA panels (24-mer and 7-mer) showed classification performance sufficient for a standalone diagnostic biomarker (AUC, 0.75, 0.70, and 0.53 in MOLTEST-2013, SMAC, and MOLTEST-BIS, respectively, in the 7-mer model). The performance of classification in the MOLTEST-BIS cohort with the lowest contribution of adenocarcinomas was increased when only this cancer type was considered (AUC, 0.60 in 7-mer model).

Identifiants

pubmed: 37865291
pii: S1525-1578(23)00245-3
doi: 10.1016/j.jmoldx.2023.09.010
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Disclosure Statement None declared.

Auteurs

Joanna Zyla (J)

Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland.

Rafal Dziadziuszko (R)

Medical University of Gdansk, Gdansk, Poland.

Michal Marczyk (M)

Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland; Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.

Magdalena Sitkiewicz (M)

Medical University of Gdansk, Gdansk, Poland.

Magdalena Szczepanowska (M)

Medical University of Gdansk, Gdansk, Poland.

Edoardo Bottoni (E)

Humanitas Research Hospital, Milan, Italy.

Giulia Veronesi (G)

School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy; Department of Thoracic Surgery, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Witold Rzyman (W)

Medical University of Gdansk, Gdansk, Poland.

Joanna Polanska (J)

Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland. Electronic address: joanna.polanska@polsl.pl.

Piotr Widlak (P)

Medical University of Gdansk, Gdansk, Poland. Electronic address: piotr.widlak@gumed.edu.pl.

Classifications MeSH