Research

Overview:

The Computational Systems Biology Laboratory at USC develops mechanistic models of biological processes and utilizes the models to:
  • gain insight into the dynamics and regulation of biological systems
  • synthesize and interpret experimental and clinical observations
  • provide a quantitative framework to test biological hypotheses
  • support the development of novel therapeutics for pathological conditions
We perform experimental studies to obtain quantitative measurements needed to construct computational models that increase our understanding of specific biological processes. We also collaborate closely with experimental and clinical researchers. These fruitful collaborations enable experimental testing of the model predictions.

Current projects:

The main projects in the CSBL are focused on applying computational modeling to study angiogenesis, metabolism, and immunotherapy. Current projects study how these processes are exploited in cancer. The biochemical networks that regulate these processes involve numerous cell types, molecular species, and signaling pathways, and the dynamics occur on multiple timescales. Therefore, a systems biology approach, including experiment-based computational modeling, is required to understand these complex processes and their interconnectedness in cancer. Models can simulate biological processes under pathological conditions and predict interventions that restore normal physiology. Additionally, the models can identify which tumors will respond favorably to a particular therapy, aiding in the development and optimization of effective therapeutics.

Specific projects are described below.

Model of pro- and anti-angiogenic factors
Computational modeling is needed to understand the complexity and interconnected nature of the angiogenesis signaling pathways and predict the effect of anti-angiogenic strategies. A quantitative understanding of the relative levels of angiogenic factors under pathological conditions would aid in the development of therapeutic agents that target these factors. Thus, the long-term goal of this project is to investigate the angiogenic balance in cancer and identify effective therapies that target promoters and inhibitors of angiogenesis. Funded by the NSF CAREER Award (PI: Finley)

Model of metabolic phenotypes in cancer
Quantitative, dynamic models of the metabolic phenotypes observed in cancer can be used to develop therapies that inhibit tumor metabolism. The development of  an experiment-based, validated computational model of metabolism in various cancer types will provide a more in-depth understanding of the dynamics of altered tumor metabolism, which drives cancer progression. Our long-term goal is to understand the cellular metabolism of tumors and support the development of novel cancer therapies that inhibit aberrant tumor metabolism. Funded by the Rose Hills Research Fellowship and USC Provost's Office (PI: Finley)

Integrative kinetic model of tumor angiogenesis and metabolism
Although it is clear that tumor angiogenesis and glucose metabolism are interconnected, the mechanistic details of crosstalk between the two processes are unknown. Importantly, the functional impact of this crosstalk on cancer therapeutics has not been fully investigated. Therefore, the goal of this project is to address gaps in knowledge regarding the connection between metabolism and angiogenesis and identify novel targets for therapeutic intervention.

Systems biology approach to understand and design CAR immunotherapy
Chimeric antigen receptors (CARs) are engineered artificial receptors that, when expressed in T lymphocytes, enable the cells to recognize antigens secreted by tumor cells and mediate killing to eradicate the cancer. More studies are needed to make the CAR-engineered T cells a safe and reliable treatment modality that can benefit a broader population of patients and treat multiple cancer types. However, the development of CAR-based therapy is currently achieved through experimental “trial and error” approaches, and there is no quantitative framework that can guide the rational design of CARs. The goal of this project is to use computational systems biology tools to identify design principles of CAR-engineered T cells that enable robust and specific T cell activation. Funded by the NIH NRSA F31 Predoctoral Fellowship to Jennifer Rohrs (Co-Sponsor: Finley)

Additional Projects:

Our research group is collaborating with experimental and clinical researchers on projects.
  • Signaling pathways that regulate muscle mass This is a collaboration with E. Todd Schroeder, in the Division of Biokinesiology and Physical Therapy. We are studying the effects of exercise training, protein supplementation on muscle wasting in prostate cancer patients.
  • Computational study of pediatric multiple organ dysfunction syndrome We are using mathematical modeling to study the progression and severity of pediatric MODS.

WANT TO LEARN MORE?
PLEASE CONTACT US