Abstract
The ability to differentiate between benign, suspicious, and malignant pulmonary nodules is imperative for definitive intervention in patients with early stage lung cancers. Here, we report that plasma protein functional effector sncRNAs (pfeRNAs) serve as non-invasive biomarkers for determining both the existence and the nature of pulmonary nodules in a three-stage study that included the healthy group, patients with benign pulmonary nodules, patients with suspicious nodules, and patients with malignant nodules. Following the standards required for a clinical laboratory improvement amendments (CLIA)-compliant laboratory-developed test (LDT), we identified a pfeRNA classifier containing 8 pfeRNAs in 108 biospecimens from 60 patients by sncRNA deep sequencing, deduced prediction rules using a separate training cohort of 198 plasma specimens, and then applied the prediction rules to another 230 plasma specimens in an independent validation cohort. The pfeRNA classifier could (1) differentiate patients with or without pulmonary nodules with an average sensitivity and specificity of 96.2% and 97.35% and (2) differentiate malignant versus benign pulmonary nodules with an average sensitivity and specificity of 77.1% and 74.25%. Our biomarkers are cost-effective, non-invasive, sensitive, and specific, and the qPCR-based method provides the possibility for automatic testing of robotic applications.
Highlights
Lung cancer remains the leading cause of cancer-related deaths in the United States and worldwide [1]
To construct protein functional effector sncRNAs (pfeRNAs) classifiers that could determine both the existence and the nature of pulmonary nodules, we examined the plasma levels of 16 candidates that showed more than a three-fold change between healthy controls, those with benign plus suspicious pulmonary nodules, and patients with malignant pulmonary nodules
The healthy controls and patients with benign pulmonary nodules were determined by the physician to be free of any cancer, patients with early stage NSCLC were determined by the physician to be free of any other cancer, and patients with Stage III/IV NSCLC were excluded from the study
Summary
Lung cancer remains the leading cause of cancer-related deaths in the United States and worldwide [1]. With the growing popularity of CT screening, physicians are increasingly faced with the clinical dilemma of identifying incidental pulmonary nodules in asymptomatic smokers. Its high false-positive rate leads to additional follow-up procedures, patient anxiety about indeterminate nodules, risk of over-diagnosis, differences in selection criteria, and radiation exposure [2,3]. Even with functional imaging and predictive tools based on state-of-the-art algorithms, confirmation of malignancy by imaging alone remains a diagnostic challenge. While there are integrated prediction models for pulmonary nodules [4,5,6], the considerable overlap in the clinical characteristics makes it difficult for physicians to distinguish patients with benign and malignant pulmonary nodules. Developing and validating a novel strategy rooted in molecular signatures of blood would represent a real step forward in non-invasive biomarkers
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