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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
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A Pipeline for Drug Target Identification and Validation

Eusebio Manchado1, Chun-Hao Huang1,2, Nilgun Tasdemir1,3

  • 1Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York 10065.

Cold Spring Harbor Symposia on Quantitative Biology
|January 7, 2017
PubMed

Insights

This study introduces an RNA interference (RNAi) pipeline for discovering cancer therapies. It uses optimized short-hairpin RNA (shRNA) and inducible RNAi with mouse models for effective in vivo target validation.

Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Tumor profiling generates vast genomic data, driving new cancer therapy development.
  • Targeting oncogenic lesions shows success but faces limitations in direct inhibition efficacy and transient benefits.
  • Functional genomics identifies cancer vulnerabilities, but in vivo target validation requires assessing tumor growth impact and toxicity.

Purpose of the Study:

  • To present an RNA interference (RNAi) pipeline for cancer target discovery and validation.
  • To detail the use of optimized short-hairpin RNA (shRNA) tools for negative selection screens.
  • To highlight an inducible RNAi platform combined with embryonic stem cell (ESC)-based genetically engineered mouse models (GEMMs) for in vivo validation.

Main Methods:

  • Development of an RNA interference (RNAi) pipeline for cancer target discovery.
  • Utilization of optimized short-hairpin RNA (shRNA) tools for negative selection screens.
  • Implementation of an inducible RNAi platform integrated with ESC-based GEMMs for in vivo target validation.

Main Results:

  • The pipeline facilitates deep in vivo target validation.
  • Optimized shRNA tools enable effective negative selection screens.
  • The inducible RNAi platform combined with GEMMs allows comprehensive assessment of target inhibition in vivo.

Conclusions:

  • The described RNAi pipeline offers a robust approach for cancer target discovery.
  • This method enables thorough in vivo validation of potential cancer targets.
  • The integrated system aids in identifying effective and safe cancer therapies by assessing both efficacy and toxicity.

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