Circulating Coding and Long Non-Coding RNAs as Potential Biomarkers of Idiopathic Pulmonary Fibrosis
Stefania Di Mauro, Alessandra Scamporrino, Mary Fruciano, Agnese Filippello, Evelina Fagone, Elisa Gili, Francesca Scionti, Giacomo Purrazzo, Antonino Di Pino, Roberto Scicali, Maria Teresa Di Martino, Roberta Malaguarnera, Lorenzo Malatino, Francesco Purrello, Carlo Vancheri, Salvatore Piro
Abstract
Background: Idiopathic Pulmonary Fibrosis (IPF) is a chronic degenerative disease with a median survival of 2–5 years after diagnosis. Therefore, IPF patient identification represents an important and challenging clinical issue. Current research is still searching for novel reliable non-invasive biomarkers. Therefore, we explored the potential use of long non-coding RNAs (lncRNAs) and mRNAs as biomarkers for IPF. Methods: We first performed a whole transcriptome analysis using microarray (n = 14: 7 Control, 7 IPF), followed by the validation of selected transcripts through qPCRs in an independent cohort of 95 subjects (n = 95: 45 Control, 50 IPF). Diagnostic performance and transcript correlation with functional/clinical data were also analyzed. Results: 1059 differentially expressed transcripts were identified. We confirmed the downregulation of FOXF1 adjacent non-coding developmental regulatory RNA (FENDRR) lncRNA, hsa_circ_0001924 circularRNA, utrophin (UTRN) and Y-box binding protein 3 (YBX3) mRNAs. The two analyzed non-coding RNAs correlated with Forced Vital Capacity (FVC)% and Diffusing Capacity of the Lung for carbon monoxide (DLCO)% functional data, while coding RNAs correlated with smock exposure. All analyzed transcripts showed excellent performance in IPF identification with Area Under the Curve values above 0.87; the most outstanding one was YBX3: AUROC 0.944, CI 95% = 0.895–0.992, sensitivity = 90%, specificity = 88.9%, p-value = 1.02 × 10−13. Conclusions: This study has identified specific transcript signatures in IPF suggesting that validated transcripts and microarray data could be useful for the potential future identification of RNA molecules as non-invasive biomarkers for IPF.