Sputum Biomarkers to Improve CT Screening for the Early Detection of Lung Cancer in Veterans
Abstract
Lung cancer is caused by tobacco smoking, and the number one cancer killer in Veterans. Because finding lung cancer at its early stages by low-dose computed tomography (LDCT) can greatly reduce the related deaths, LDCT is now used for the early detection of lung cancer. Medicare pays for LDCT procedures. However, LDCT greatly increases the number of uncertain lung nodules in Veterans, whereas only a small fraction of lung nodules are cancers. Many Veterans with benign lung nodules will have unnecessary, harmful, and very expensive treatments that carry their own morbidity and mortality. It is very urgent to develop noninvasive ways that can separate benign growths from lung cancers in Veterans who have uncertain lung nodules, so that the Veterans with benign growths can be spared from harmful diagnostic and therapeutic procedures and the Veterans with lung cancer can immediately receive effective treatments. Since sputum and blood samples are the most easily accessible and noninvasively obtained materials, we have focused on the development of lung cancer biomarkers in the samples for more than 15 years. We have developed small non-coding RNA (snoRNA) biomarkers in sputum with 65% sensitivity and 89% specificity for lung cancer. We have identified a sputum supernatant protein biomarker for lung cancer. We have shown that combined analysis of the two classes of molecular biomarkers (small ncRNAs and DNA methylation) has a synergistic effect. We have developed peripheral blood mononuclear cells (PBMC) miRNAs as new circulating biomarkers for lung cancer. Our previous findings have been reported in peer-reviewed cancer journals and VA Research Currents; Association for Cancer Research-News Release; News Features of The Journal of the National Cancer Institute. Since lung cancer is a heterogeneous disease, it is unlikely that any single biomarker platform in a single tissue or any single approach will achieve the performance required to be used in the clinical settings. The objective of this application is to develop a parsimonious model by integrating the multilayered biomarkers across sputum and blood samples with radiographic and clinical variables of smokers for identifying lung cancer among the indeterminate pulmonary nodules. Our project will address the following areas of research emphasis: (1) Identify or develop noninvasive or minimally invasive tools to improve detection of the initial stages of lung cancer. (2) Identify, develop, and/or build upon already existing tools for screening or early detection of lung cancer. (3) Identify innovative strategies for prevention and treatment of early and/or localized lung cancer. As soon as we complete this 2-year retrospective and idea development project, collaborations among translational research scientists and clinical investigators are in place for fast translation of these findings from bench to bedside. We will prospectively validate the parsimonious assay in a LDCT lung cancer screening program. Future use of the prediction model for excluding lung cancer in a CT screening positive setting will spare Veterans with benign growths from harmful diagnostic and therapeutic procedures, and enable effective treatments to be immediately initiated for lung cancer. This simple prediction model will complement LDCT for the early detection of lung cancer, and hence reduce lung cancer-associated mortality in Veterans. Therefore, the success of the study will help eradicate deaths from lung cancer to better the health and welfare of Veterans.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 07, 2017
- Source ID
- W81XWH1710254
Entities
People
- Feng Jiang
Organizations
- United States Army
- University of Maryland, Baltimore