The long-term research goal of our lab is to explore the mechanisms that tumor cells suppress or avert immunogenic cell death (ICD) and discover potential targets to enhance the efficacy of current therapies. We will initially focus on NRAS mutant melanoma, and will extend our work to other types of solid tumors as the research program grows. Our current projects can be divided into these 3 fields:
- Develop efficacious treatment strategies against mutated NRAS in melanoma. Melanoma is the deadliest skin cancer. Moreover, the incidence of melanoma in the US increased rapidly over the last 2 decades. Although targeted therapy and immunotherapy have significantly improved overall survival for late-stage melanoma patients with BRAF mutations, more than a quarter of melanoma patients who harbor NRAS mutations have poor prognosis and bleak disease outcomes. These are largely due to the lack of FDA-approved targeted therapies. Thus, there is a critical need to devise novel approaches against NRAS mutant melanoma. Our current research has largely focused on developing novel therapeutic rationales for treating NRAS mutant melanoma. Based on the preliminary data which obtained by a CRISPR/cas9-based genome-wide screen, we have several projects which may provide novel combinations of agents against the 'undruggable' target, NRAS, in melanoma. The most recent work resulted in a paper published on Cancer Research and a filed provisional patent based on the methods disclosed in the paper.
- Explore the mechanism of ICD suppression in tumor cells. Inducing tumor cell death is always a critical goal of cancer therapy. However, apoptosis, the best-known programmed cell death, is generally non-immunogenic and fails to trigger strong immune responses around the dying tumor cells. Our previous work published on Cancer Discovery has established the essential role of pyroptosis, a new type of ICD, on the efficacy of targeted therapy against melanoma via shaping the immune responses in tumor microenvironment in vivo. Now we have strong interest in how tumor cells suppress or avert pyroptosis or other types of ICD during treatment. New insights into these mechanisms will contribute to designing better therapy combinations that can deliver durable responses to patients.
- Discover the vulnerability of cancer. Since cancer research has generated 'big data', nowadays, in-silico analysis is indispensable to identify association and causality in big data and also to narrow down candidates for further experimental works. We have ongoing projects collaborated with two biostatisticians, Dr. Quan Long and Dr. Qingrun Zhang at the University of Calgary, to identify the vulnerable targets of tumors with or without treatment. This long-term collaboration has already resulted in a bioinformatic manuscript in revision by Science Advances. Further validations in the bench will provide novel therapeutic targets against various types of cancer.