Plasma extracellular vesicle long RNA profiling identifies a diagnostic signature for stage I lung adenocarcinoma

• Published in: Translational lung cancer research Vol. 11; no. 4; pp. 572 - 587
• Main Authors: Guo, Wei, Huai, Qilin, Liu, Tiejun, Zhang, Guochao, Liang, Naixin, Ma, Qianli, Liu, Xiang, Tan, Fengwei, Xue, Qi, Gao, Shugeng, Gao, Yibo, He, Jie
• Format: Journal Article
• Language: English
• Published: China AME Publishing Company 01.04.2022
• Subjects: Original; Extracellular vesicles (EVs); long RNAs; lung adenocarcinoma (LUAD); biomarker; diagnostic signature
• ISSN: 2218-6751; 2226-4477
• DOI: 10.21037/tlcr-21-729

The early diagnosis of lung adenocarcinoma (LUAD) is particularly challenging. Recent studies have reported that extracellular vesicles (EVs) include both small and long RNA. However, the profile and diagnosis-related significance of EV long RNA (exLR) profiles for early LUAD remain unclear. A case-control analysis was carried out involving 110 participants, including 64 stage I LUAD cases, 24 benign pulmonary nodule (BPN) cases, and 22 healthy controls (HCs). The analysis was performed on the plasma samples' exLR profile based on exLR sequencing. The d-signature was identified using the least absolute shrinkage and selection operator (LASSO) method and a training set (n=48), and validation was completed through use of an internal validation set (n=32) and an external validation set (n=30). A diagnostic signature (d-signature) encompassing 8 exLR markers (NFKBIA, NDUFB10, SLC7A7, ARPC5, SEPTIN9, HMGN1, H4C2, and lnc-PLA2G1B-2:3) was identified for the detection of LUAD. This d-signature exhibited a high level of accuracy, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.991 in the training group, 0.921 in the internal validation group, and 0.9 in the external validation group. Moreover, the d-signature could distinguish adenocarcinomas (AIS) and minimally invasive adenocarcinomas (MIA) from the noncancerous controls (NCs), with AUCs of 0.934 and 0.909, respectively, in the combined cohorts. This study initially characterized the plasma exLR profile of early LUAD and reported on an exLR-based diagnostic signature for the detection of LUAD. This d-signature could be a promising noninvasive biomarker for the early detection and routine screening of LUAD.