Year of Award:
Molecular & Cellular Analysis Technologies
Other PI or Project Leader:
SCRIPPS RESEARCH INSTITUTE
Currently, the clinical diagnosis of non-small cell lung cancer (NSCLC) relies on a number of imaging modalities followed by a tissue confirmation with an invasive procedure. This process is somewhat imprecise because a patient's pathologic diagnosis after surgery may be discordant from pre-operative assessment and may contribute to poor patient prognosis since accurately staging early cancers is essential to good outcome. We hypothesize that rigorously validating the recently developed High Definition Circulating Tumor Cell (HD- CTC) Fluid Biopsy in a controlled clinical cohort of patients undergoing evaluation for lung cancer will improve the accuracy of detection and prognosis in early-stage, malignant nodules of the lung with non-small cell lung cancer histology. We will capitalize on NIH-supported proof of concept data, which has demonstrated that the HD-CTC Fluid Biopsy is capable of detecting disease derived cells in the majority of patients at the time of diagnosis. These data now motivate us to investigate the performance of the assay 'the day before diagnosis' with the expectation of achieving similar results in a more realistic, prospectively designed, clinical study with matched controls consisting of patients who have non-malignant lung nodules. Our aim is to accurately establish the test characteristics of the HD-CTC fluid biopsy in a group of patients undergoing evaluation for lung cancer and to identify those patients with malignant nodules that have detectable HD-CTCs to determine whether the fluid biopsy can augment 1) clinical staging prior to definitive treatment and 2) prognosis after definitive diagnosis and treatment. We will significantly enhance the test by developing single cell molecular analysis to provide definitive characterization. Integrating non-invasive, reliable and accurate circulating biomarkers with the current standard of care will not only allow for the development of more accurate clinical prediction models that are cost-effective, but may also augment our understanding of tumor biology and metastasis using a clinical, in vivo model of early non-small cell lung cancer.