Digital multiplexed analysis of circular RNAs in FFPE and fresh non‐small cell lung cancer specimens

Autor: Carlos Pedraz‐Valdunciel, Stavros Giannoukakos, Nicolas Potie, Ana Giménez‐Capitán, Chung‐Ying Huang, Michael Hackenberg, Alberto Fernandez‐Hilario, Jill Bracht, Martyna Filipska, Erika Aldeguer, Sonia Rodríguez, Trever G. Bivona, Sarah Warren, Cristina Aguado, Masaoki Ito, Andrés Aguilar‐Hernández, Miguel Angel Molina‐Vila, Rafael Rosell
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Molecular Oncology, Vol 16, Iss 12, Pp 2367-2383 (2022)
Druh dokumentu: article
ISSN: 1878-0261
1574-7891
DOI: 10.1002/1878-0261.13182
Popis: Although many studies highlight the implication of circular RNAs (circRNAs) in carcinogenesis and tumor progression, their potential as cancer biomarkers has not yet been fully explored in the clinic due to the limitations of current quantification methods. Here, we report the use of the nCounter platform as a valid technology for the analysis of circRNA expression patterns in non‐small cell lung cancer (NSCLC) specimens. Under this context, our custom‐made circRNA panel was able to detect circRNA expression both in NSCLC cells and formalin‐fixed paraffin‐embedded (FFPE) tissues. CircFUT8 was overexpressed in NSCLC, contrasting with circEPB41L2, circBNC2, and circSOX13 downregulation even at the early stages of the disease. Machine learning (ML) approaches from different paradigms allowed discrimination of NSCLC from nontumor controls (NTCs) with an 8‐circRNA signature. An additional 4‐circRNA signature was able to classify early‐stage NSCLC samples from NTC, reaching a maximum area under the ROC curve (AUC) of 0.981. Our results not only present two circRNA signatures with diagnosis potential but also introduce nCounter processing following ML as a feasible protocol for the study and development of circRNA signatures for NSCLC.
Databáze: Directory of Open Access Journals
Externí odkaz: