Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection
D'Ambrosi, Silvia (Amsterdam UMC. University Medical Center)
Giannoukakos, Stavros (Centro de Investigación Biomédica de la Universidad de Granada)
Antunes-Ferreira, Mafalda (Amsterdam UMC. University Medical Center)
Pedraz-Valdunciel, Carlos (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Bracht, Jillian (Hospital Universitari Dexeus - Grup Quirónsalud)
Potie, Nicolas (Centro de Investigación Biomédica de la Universidad de Granada)
Giménez-Capitán, Ana (Hospital Universitari Dexeus - Grup Quirónsalud)
Hackenberg, Michael (Centro de Investigación Biomédica de la Universidad de Granada)
Fernandez Hilario, Alberto (Universidad de Granada)
Molina-Vila, Miguel Ángel (Hospital Universitari Dexeus - Grup Quirónsalud)
Rosell, Rafael (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Würdinger, Thomas (Amsterdam UMC. University Medical Center)
Koppers-Lalic, Danijela (Leiden University)
Universitat Autònoma de Barcelona

Fecha:	2023
Resumen:	Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0. 88 and 0. 81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0. 92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Biomarkers ; Cancer diagnosis ; Circular RNA ; Liquid biopsy ; Lung cancer ; Messenger RNA ; Platelets
Publicado en:	International journal of molecular sciences, Vol. 24 (march 2023) , ISSN 1422-0067

DOI: 10.3390/ijms24054881
PMID: 36902312

17 p, 2.3 MB

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