Lung cancer is the leading cause of cancer deaths worldwide, with more than 1.3 million deaths every year. Small cell lung cancer (SCLC) is a subtype of lung cancer that comprises ~15% of all lung cancers and results in over 200,000 deaths worldwide each year. Most people diagnosed with SCLC have a history of heavy smoking, which strongly correlates tobacco use with this cancer. Unfortunately, SCLC has a very poor prognosis, with a 5-year survival rate of less than 5%.
Our overarching goal is to gain a better understanding of the mechanisms underlying the development of SCLC. It is our belief that we will be able to use this knowledge to eventually design new and improved diagnosis and treatment options for this deadly cancer. To achieve this goal, we use a two-pronged approach: first, we have developed a mouse model for human SCLC in which mice are genetically engineered and manipulated to grow lung cancer that is very similar to human SCLC. In parallel, in a back-and-forth strategy with the mouse model, we use tumor samples and cell lines from SCLC patients.
Here, our specific goals are to discover and validate biomarkers for SCLC and to identify novel chemoprevention approaches for SCLC. To this end, we have employed an integrative bioinformatics approach to identify drugs known to efficiently treat other diseases that may work in SCLC based on the gene expression profiles of these tumors. We surmise that the targets of these drugs may be biomarkers for SCLC; these candidate biomarkers will be tested in mice and on human samples, with the hope that they will rapidly be used in the clinic for diagnosis and early detection of SCLC. In addition, the drugs identified through our bioinformatics pipeline will be tested on the mutant mice developing SCLC to determine if these drugs may be used to prevent the development and progression of SCLC.