Title: Mathematical modeling about early diagnosis of lung cancer
with exosomal miRs
Abstract: Lung cancer, primarily non-small-cell lung cancer
(NSCLC), is the leading cause of cancer deaths in the United States and
worldwide. While early detection significantly improves five-year survival,
there are no reliable diagnostic tools for early detection. Several exosomal
microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as
potential biomarkers for early detection. In this talk, I want to talk about a
mathematical model for early stage of NSCLC with emphasis on the role of the
three highest overexpressed miRs, namely miR-21, miR-205 and miR-155.
Simulations of the model provide quantitative relationships between the tumor
volume and the total mass of each of the above miRs in the tumor. Because of the
positive correlation between these miRs in the tumor tissue and in the blood,
the results may be viewed as a step toward establishing miRs 21, 205 and 155 as
reliable serum biomarkers for early detection of NSCLC.
