Blood RNA Panel Predicts Lung Cancer Risk Years Before Diagnosis

Blood-based molecular markers could help stratify long-term risk before clinical disease becomes apparent.

Researchers at the University of Hawaiʻi at Mānoa (Honolulu, HI, USA) identified a panel of 31 small non-coding RNAs (sncRNAs) in circulating plasma exosomes that was associated with future lung cancer risk. The 31-sncRNA signature comprised 15 microRNAs, eight PIWI-interacting RNAs, seven tRNA-derived fragments, and one tRNA half. The panel was developed as a blood-based molecular signature for assessing risk during the preclinical period before lung cancer becomes clinically apparent.

To develop the signature, the researchers analyzed pre-diagnostic plasma samples from participagmnts in the Multiethnic Cohort (MEC). Circulating plasma exosomes were examined to identify RNA molecules associated with a later lung cancer diagnosis, and the resulting 31-sncRNA signature was then evaluated using a random forest classifier in held-out testing.

The classifier achieved an area under the curve (AUC) of 0.97, with 93% sensitivity, 100% specificity, and 95% overall accuracy in held-out testing. The sncRNA-derived risk score also remained strongly associated with subsequent lung cancer after adjustment for age, sex, ethnicity, smoking intensity, and smoking duration, indicating that the molecular signature provided risk information beyond these established factors.

The association remained detectable five to 10 years before clinical diagnosis. The study, “A Panel of Circulating Exosomal sncRNAs Associated With Lung Cancer Risk up to 10 Years in Advance,” was published in Advanced Science. Institutions and study groups involved included the University of Hawaiʻi at Mānoa John A. Burns School of Medicine, the University of Hawaiʻi Cancer Center, and the Multiethnic Cohort Study. The research team is pursuing patent protection for the biomarker panel and its potential clinical application.

“A central question in this study was whether a molecular signal of future lung cancer could already be present in blood many years before diagnosis,” said Zhuokun Feng, MD, the study’s first author. 

“Our goal was not simply to distinguish patients with established lung cancer from cancer-free individuals, but to identify molecular signals that may indicate high lung cancer risk years before clinical diagnosis,” said Youping Deng, PhD, senior and corresponding author of the study.

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