I teach undergraduate and graduate courses on cell/molecular biology and cancer. My research focuses on understanding the mechanisms by which cancers begin and then later acquire the ability to metastasize. We also study these same mechanisms during tissue regeneration to better understand their normal contexts. By understanding what drives cancer and what prevents complete tissue regeneration, we aim to develop novels therapeutic strategies.
Although the average lifetime risk of pancreatic cancer is only about 1 in 65 persons, less than 7% of patients will survive beyond five years from the time of initial diagnosis. This dire prognosis can primarily be attributed to three factors. First, pancreatic cancer is very difficult to diagnose early due to nearly asymptomatic progression. Second, even when it is diagnosed early, the tumor cells rarely respond to conventional chemotherapies or targeted therapies. Finally, it has been reported that tumor cells may disseminate away from the pancreatic primary tumor (a process known as metastasis) even before a tumor in this tissue is detectable by conventional imaging modalities.
One of the primary goals in my laboratory is to identify new biomarkers for diagnosing pancreatic cancer at the earliest stages that can also double as therapeutic targets for sensitizing primary and metastatic pancreatic cancer cells to standard-of-care therapies. We are applying a two-pronged approach: first, working to establish and use a new clinical sample prep methodology and second, using bioinformatics on patient and cell samples to identify new molecular targets.
These efforts have led to our recent development of an improved method (in collaboration with researchers at Claremont BioSolutions and UC San Diego) for extracting high-quality RNA from patient samples, and the identification of cell surface integrin alpha 1 (ITGA1) as a marker of pre-cancerous pancreatic lesions that drives chemotherapy resistance in metastatic tumor cells. We are currently working to identify unique vulnerabilities in ITGA1-expressing pancreatic cancer cells that may be leveraged for diagnostic or therapeutic purposes. Since millions of clinical tumor samples have been banked, we are also using these new methods to retrospectively profile pancreatic tumors and identify additional molecular signatures that can predict favorable patient responses to available therapies.