Developing new non-invasive methods for the diagnosis of lung cancer

To significantly reduce the deaths from lung cancer, more accurate diagnostic tests are urgently needed to detect the disease early enough and benefit from a surgical cure. We recently identified 164 novel candidate protein markers in lung cancer from extensive shotgun proteomic profiling of Stage 1 lung cancers. These candidate protein biomarkers are abundantly expressed in Stage 1 lung cancer tissues but not in normal counterparts. While standard ELISA-based assays to validate these candidates can be done, this approach is low throughput, very slow and expensive. In this application, we propose to develop and validate a non-invasive diagnostic test for lung cancer based on the detection of autoantibodies directed against our candidate protein biomarkers that are markedly differentially expressed in lung cancer and present in the circulation. More specifically, we propose to establish an assay to detect and quantitate lung cancer autoantibodies directed against new proteomic biomarker candidates. We will validate the diagnostic efficacy of our autoantibody signature in blood samples taken from individuals with Stage 1 lung cancer or matched nodules controls and integrate these findings in the diagnostic setting of patients presenting with lung nodules. Establishing this new approach may ultimately lead to improving the accuracy of the diagnosis of lung cancer when the disease is surgically curable.