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A Cancer Biomarker Screen for Drug Target Selection. Winter ‘13 Tommy Busch. Bioinformatics Drug T arget P rediction. Objective – To identify proteins that would make good targets for monoclonal antibody therapy for cancer

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Presentation Transcript
bioinformatics drug t arget p rediction
Bioinformatics Drug Target Prediction

Objective – To identify proteins that would make good targets for monoclonal antibody therapy for cancer

Method – Leverage gene expression, copy number, and clinical outcome data from the Cancer Genome Atlas

Rationale – Surface or secreted proteins associated with tumor metastasis have strong potential as pharmacological targets

selection pipeline
Selection Pipeline

Infer Protein

Activity Level

Differential

Analysis

Z-Score

results highlights
Results Highlights

Apoptosis

Angiogenesis

Developmental

Signaling

Inflammation

follow up investigation
Follow-up Investigation
  • Prioritize candidates based on phenotypes of genetic mutants and KO mice
  • Generate monoclonal antibodies for wet lab studies
  • Extend the selection pipeline to other cancers
recap
Recap

Problem

Can we pick tumor-specific drug targets? Yes

Strategy

Integrative bioinformatics analysis. CGA/GO/SPD

acknowledgments
Acknowledgments

PI’s

Dr. Philip Berman

Dr. Josh Stuart

Grad Students

Yulia Newton

Ted Goldstein