Exosomal microRNA Panels for Detecting Early-Stage Non-Small Cell Lung Cancer
Young Jun Kim, Da Hyun Kang, Hyunmin Cho, Chaeuk Chung, Jeong Eun Lee, Yong-Beom Shin

TL;DR
This study identifies a panel of four exosomal microRNAs that can help detect early-stage non-small cell lung cancer non-invasively, improving early diagnosis.
Contribution
The novel contribution is the development of a four-miRNA panel using a self-devised UDR platform for early NSCLC detection.
Findings
A four-miRNA panel achieved a diagnostic accuracy (ROC) over 0.93 for early-stage NSCLC.
Bioinformatics analysis linked the miRNAs to key target genes like VEGFA, BCL2, and PTEN.
The UDR platform optimized miRNA selection for non-invasive early detection of lung cancer.
Abstract
Background: Early diagnosis of lung cancer requires lung nodule biopsies, which can lead to severe complications. This study aimed to identify optimized panels of exosomal microRNAs (miRNAs) for non-invasive diagnosis of early-stage non-small cell lung cancer (NSCLC). Materials and Methods: This study comprised four phases: discovery, validation, optimization, and confirmation. In the discovery phase, next-generation sequencing profiled 2656 exosomal miRNAs in serum samples (n = 76) from patients with benign lung nodules and stage-specific NSCLC. The validation phase used qPCR to analyze selected miRNAs in serum samples (n = 75). The optimization phase employed a self-devised diagnostic platform, the “up-down ratio (UDR),” to identify miRNA panels. The confirmation phase involved miRNA–target gene interaction and enrichment analyses. Results: The discovery phase identified 15 candidate…
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Taxonomy
TopicsExtracellular vesicles in disease · MicroRNA in disease regulation · Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
