Predictors of Lung Nodule Malignancy

University Of Colorado Denver, Aurora CO

Investigators

Linked publications & trials

Abstract

Our overarching goal is to develop biomarkers that are useful in informing clinical management of CT detected lung nodules of indeterminate etiology. Biomarkers assayed in non-invasively obtained biospecimens need to be developed to enhance the performance of currently evolving lung cancer risk models which are based solely on demographics, clinical and imaging characteristics. We hypothesize: 1. Biomarkers measurable in non-invasively obtained specimens can discriminate between benign and malignant lung nodules detected by CT. 2. These biomarkers can be incorporated into a prediction model to aid clinical decision making and potentially improve outcomes by shortening time to diagnosis of lung cancer, decreasing biopsy and/or surgery for benign disease, reducing patient anxiety and decreasing costs. In the current SPORE grant period, we have developed several promising biomarkers and carried out initial validation steps. We now are in the position to assess these prospectively and simultaneously in a population in which they would have immediate clinical applicability, through the following Specific Aims: 1. Develop and test novel measurement tools for the following biomarkers in non-invasively obtained specimens, including: a) Epithelial chromosomal imbalances; b) Circulating protein levels; c) Exhaled breath volatile organic compounds; d) miRNA expression patterns. 2. Compare the performance of the individual biomarkers singly and in combinations in discriminating benign from malignant nodules in a cohort of subjects with indeterminate lung nodules referred to specialty clinics for evaluation. 3. Develop a model based on biomarker outcomes, smoking history, clinical and imaging features for the prediction of malignancy in CT detected lung nodules. We envision that at the end of this project, the above predictive model can be subjected to further prospective validation in independent cohorts of patients with indeterminate CT detected lung nodules, in which changes in specific outcomes (time to diagnosis, invasive procedures for benign disease, costs) can be simulated.