Validation of a Proteomic Signature of Lung Cancer Risk from Bronchial Specimens of Risk-Stratified Individuals

SIMPLE SUMMARY: Lung cancer remains one of the deadliest cancers, with the worst survival rate. Cells from the airway lining of patients at high risk for lung cancer differentially express proteins that may serve as biomarkers for early detection of lung cancer. Previously, we identified candidate proteins in patients at high risk for lung cancer. In the present study, we validated several proteins in an independent cohort of 179 patients. Patients without lung cancer were stratified at low and high risk using an established risk model. Several proteins were found to be significantly overexpressed in the normal airways of individuals at high risk for lung cancer compared to the low-risk group. Our goal is to deliver a signature of risk that may provide the basis for lung cancer risk assessment and possibly novel future prevention strategies. ABSTRACT: A major challenge in lung cancer prevention and cure hinges on identifying the at-risk population that ultimately develops lung cancer. Previously, we reported proteomic alterations in the cytologically normal bronchial epithelial cells collected from the bronchial brushings of individuals at risk for lung cancer. The purpose of this study is to validate, in an independent cohort, a selected list of 55 candidate proteins associated with risk for lung cancer with sensitive targeted proteomics using selected reaction monitoring (SRM). Bronchial brushings collected from individuals at low and high risk for developing lung cancer as well as patients with lung cancer, from both a subset of the original cohort (batch 1: n = 10 per group) and an independent cohort of 149 individuals (batch 2: low risk (n = 32), high risk (n = 34), and lung cancer (n = 83)), were analyzed using multiplexed SRM assays. ALDH3A1 and AKR1B10 were found to be consistently overexpressed in the high-risk group in both batch 1 and batch 2 brushing specimens as well as in the biopsies of batch 1. Validation of highly discriminatory proteins and metabolic enzymes by SRM in a larger independent cohort supported their use to identify patients at high risk for developing lung cancer.