Small RNAs for Early Lung Cancer Detection

Low-dose computed tomography (LDCT) screening can significantly reduce lung cancer deaths, but it is not widely used in the USA or Europe because people often don’t stick with it, and it is not yet widely available.

Researchers aimed to develop a blood test for the early detection of lung cancer that can be deployed in the primary care setting.

The study recruited 1,189 patients(pts) meeting the 2013 USPSTF screening criteria for lung cancer and collected stabilized whole blood. Ultra-deep small RNA sequencing was performed to remove highly abundant erythroid RNAs, opening bandwidth for detecting less abundant species originating from plasma or the immune cellular compartment. They utilized 100 random data splits to train and evaluate logistic regression classifiers using small RNA expressions. They discovered an 18-small RNA feature consensus signature known as “miLung,” and validated this in an independent cohort of 246 pts. Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin.

The study involved 1,189 pts who met the 2013 USPSTF lung cancer screening criteria and collected stabilized whole blood samples. They conducted ultra-deep small RNA sequencing, which involved removing highly abundant erythroid RNAs to focus on detecting less common RNA species from either plasma or the immune cellular compartment. Using 100 random data splits, they trained and evaluated logistic regression classifiers based on small RNA expression. This approach led to the discovery of an 18-small RNA feature consensus signature called “miLung.” They further validated this signature in an independent cohort of 246 pts. To understand the origin of these small RNAs, blood cell sorting and tumor tissue sequencing were conducted to identify their source.

The study developed diagnostic models, and the median ROC AUC in the discovery cohort was 0.86 (95% CI 0.84-0.86). In the validation cohort, they observed a generalized performance of 0.84. The diagnostic performance exhibited a stage-dependent increase, ranging from 0.73 (95% CI 0.71-0.76) for Stage I to 0.90 (95% CI 0.89-0.90) for Stage IV. This investigation identified a specific ribosomal RNA fragment from the L1 stalk that is shed by tumors and found in plasma. This RNA fragment emerged as a prominent predictor of lung cancer. Importantly, following curative surgery, they observed a decrease in the levels of this RNA fragment. 

The study also explored the potential for small RNA analysis using dried blood spot collection and sequencing in additional experiments. These findings suggest that home-based sampling methods facilitate small RNA analysis. 

Source: https://ascopubs.org/doi/abs/10.1200/JCO.2023.41.16_suppl.3035 

Clinical Trial: https://www.clinicaltrials.gov/study/NCT03452514