The number of cells in an adult multicellular organism such as a human being is under very tight control and, under normal circumstances, there is a balance between new cell production and cell death. Roughly speaking, cancer results when there is excessive cell division or reduced cell death due to some malfunctioning in the cell number control system. A possible approach to cancer therapy is to quickly and robustly induce the death of cancer cells, and earlier work has used an engineering approach to explain the rationale behind the dramatically successful induction of human cancer cell death by a therapeutic molecule. The goal here is to extend these results to the domain of canine cancers by first modeling them and then conducting therapeutic experiments on canine tumors grown on the backs of mice. Since the work is driven by the goal of improving cancer treatment, the potential societal benefits of this project could be enormous. The project will be carried out at the Center for Bioinformatics and Genomic Systems Engineering (CBGSE) at Texas A & M University, where widespread dissemination of the research results, imparting truly interdisciplinary hands-on education to graduate students, and beneficially targeting minorities and minority institutions, are top priorities.
The malfunctioning of the cell-cycle control system, an essential characteristic of cancer, can be attributed to different signaling breakdowns at many different locations in a signaling pathway. As a result, a proper design of cancer therapy should first attempt to identify the location and type of malfunction in the pathway and then arrive at a drug combination that is particularly well suited for it. Unfortunately, with the notable exception of the recent attempts at targeted immunotherapy, most of the approaches to cancer therapy do not follow such a systematic procedure. Thus, for most of cancers, there is a critical need for precisely identifying the failure point(s) in the pathway, hopefully leading to a more targeted therapy with a better likelihood of success. Many of the cancer therapies to date have mostly focused on blocking the pathways essential to cell proliferation. However, often, even if the drugs are initially successful in treating the cancer, the success is usually short lived as the cancer cell can activate some other pathways not targeted by the drug. An alternative approach to treat cancer would be to use drugs that are capable of inducing cell death. Chemotherapeutic drugs targeting cell death also display drug resistance which occurs when the cancer cells figure out mechanisms to evade the cell death inducing activity of the drug. If, however, one could identify molecules along the cell death pathway that can play a decisive role in ensuring cell death, regardless of the upstream signaling breakdown(s), then targeting such molecules with drugs would provide a robust strategy for treating cancer. In very recent work, the research team has utilized mathematical modeling and experimentation to demonstrate remarkable success in achieving robust cell killing for human breast cancer, pancreatic cancer and melanoma cell lines. This was done via the modulation of a gene called STAT3 using drug combination cocktails containing Cryptotanshinone, a traditional Chinese herb derivative. Motivated by this preliminary success, the goal here is to carry out similar modeling for osteosarcoma and demonstrate therapeutic success on cell lines and mice implanted canine cancer xenografts in a veterinarian's lab. Success with the latter is likely to move the results closer to the domain of drug development for clinical applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
