Biomarkers via liquid biopsy for distinguishing malignant from benign pulmonary ground-glass nodule

The differentiation between benign and malignant pulmonary ground-glass nodules (GGNs) has always been a current clinical hotspot issue. Patients with pulmonary GGNs from 8 centers were enrolled to identify biomarkers for malignancy and benignity discrimination, and an integrated biomarker panel comprising two miRNA, one long non-coding RNA (lncRNA), and one circular RNA (cirRNA) identified by multivariate logistic regression analysis were established. The classifier had area under the receiver-operating characteristic (ROC) curve (AUC) of 0.88, 87.8% sensitivity and 70% specificity, being significantly higher compared with the Mayo model (AUC of 0.72), Brock model (AUC of 0.70), and Herder model (AUC of 0.82) (all <i>p</i> < 0.05). Moreover, relative expression of <i>miR1246</i> and <i>miR-122</i> gradually increased from adenocarcinoma <i>in situ</i> (AIS) to minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). The classifier was validated in two independent sets of patients. It has been proved that the integration of three kinds of non-coding RNAs (ncRNAs) could more accurately identify early staged lung cancer among indeterminate GGNs.