The early detection of lung cancer by low-dose computed tomography (LDCT) followed by effective treatments, including immunotherapy, can reduce the mortality. LDCT is now recommended for lung cancer screening in smokers. However, more than 25% of smokers screened by LDCT have indeterminate pulmonary nodules (PNs), of which only 4% are finally diagnosed to be lung cancers, whereas more than 95% are benign diseases, resulting in over-diagnosis. As a result, large numbers of smokers with indeterminate PNs are referred for invasive biopsies and expensive 2-year multiple follow-up examinations, which carry their own morbidity and mortality. Therefore, there is an unmet clinical need for accurately distinguishing malignant PN (lung cancer) from benign PN in smokers with LDCT-found PNs. However, none of biomarkers and radiological features of PNs provides sufficient diagnostic values required in the clinics for accurately identifying malignant PNs. The objective of this proposed project is to develop a test for specifically differentiating malignant from benign PN. The target population of this test will be smokers with LDCT-found PNs. Its future use in the clinics will spare smokers with benign PNs from invasive biopsies and expensive multiple follow-up examinations, while facilitating effective treatments to be instantly initiated for lung cancer. Therefore, the test could complement LDCT for the early detection lung cancer, and thereby reduce the mortality and cost.

Public Health Relevance

Here we propose to develop an easy and cost-effective test for accurately distinguishing malignant from benign lung nodules. Future use of the test will complement CT screening for the early detection of lung cancer, and ultimately reduce lung cancer-associated deaths.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21CA240556-02
Application #
9970448
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Sorbara, Lynn R
Project Start
2019-07-02
Project End
2021-06-30
Budget Start
2020-07-01
Budget End
2021-06-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Maryland Baltimore
Department
Pathology
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201