The Sorger lab is interested in additional collaborations with corporate entities to:

• Analyze therapeutic effects of candidate drugs (both small molecule and biologics), perform combinatorial therapy in vitro and in silico, and develop a rational approach to polychemistry.
• Develop new protein assay technologies.
• Implement new infrastructure for imaging and activity assays.

Dr. Sorger uses activity-based proteomics with computational modeling to:

• Integrate genomics and proteomics with quantitative data on physiological responses, advanced imaging modalities, and new animal models to establish a systems biology approach to mammalian signaling.
   
• Analyze targeted and combination cancer therapies via novel methods for linking experiments and computation.
   
• Create comprehensive connectivity maps of biological circuits involved in inflammation and cancer.
   
• Enable construction of predictive cell-type,  specific models that reveal disease mechanisms and patient-specific variation to small-molecule and biologic drugs.
   
• Translate data into practical diagnostic tests and physiological-based biomarkers.
   
• Develop means to predict the therapeutic index of new drugs and thereby enable system pharmacology and accelerated drug discovery.

• Deriving molecular insights into the mechanism of action of small molecule drugs used to combat cancer and inflammation.
   
• Performing quantitative proteomics that reveal drug effects on cells.
   
• Connecting pathway data with predictive diagnostic responses to drug therapy, and in particular, molecular targeted drugs.
   
• Developing physiological-based biomarkers.
   
• Integrating multiple technologies and computational methods to generate data-driven computational modeling of a discrete set of cellular analytes that are perturbed by disease or drug exposure.
   
• Using advanced imaging assays and instrumentation.
   
• HT protein assays.
   
• Computational modeling.

Dr. Sorger’s laboratory integrates data-driven systems biology with computation and proteomics to generate “anatomical” profiles and quantitative molecular models of signaling involved in cell division, survival and death (apoptosis). By combining mathematics, high throughput measurement and mechanistic analysis of signaling networks, his laboratory teases apart the complex circuitry that converts extracellular signals, such as the pro-inflammatory cytokine tumor necrosis factor (TNF) into cellular responses. For example, Dr. Sorger has recently found that responses to TNF receptors are shaped by multi-step extra-cellular crosstalk via autocrine factors, such as TGF-α and IL-1. This finding hints at a close connection between inflammatory and oncogenic pathways and therapies, an emerging theme in his research.

Dr. Sorger has also performed important work on the mechanical and regulatory machinery that maintains chromosomal stability, focusing on the role of checkpoint and kinetochore proteins, p53 and APC. Determining the tumor-promoting potential of chromosomal instability in mouse models is an important aspect of this research. Dr. Sorger’s work is described in approximately 100 publications.
 

Biological Mechanisms and Pathways

• Autocrine cascade •
• Bioinformatics •
• Biological circuitry •
• Genomics •
• Inflammation •
• Oncology •
• Proteomics •
• Systems Biology
•  

Cancer

• Cancer •
• Oncology
•  

Disease Mechanisms

• Cancer •
• Inflammation •
• Patient-specific therapy •
• Personalized medicine
•  

Research Tools and Instrumentation

• Bioinformatics •
• Biomarker
•  

Therapeutic Discovery Tools and Assays

• Biomarker •
• Cancer •
• Combination index •
• Combination therapy •
• Combinatorial selectivity •
• Mechanism-based toxicity •
• Patient-specific therapy •
• Personalized medicine •
• Targeted therapy
•  

Therapeutics

• Combination therapy
•