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Assessing Cellular Target Engagement by SHP2 PTPN11 Phosphatase Inhibitors
Published on: July 17, 2020
A novel pipeline for prioritizing cancer type-specific therapeutic vulnerabilities using DepMap identifies PAK2 as a
Malay K Sannigrahi1, Austin C Cao1, Pavithra Rajagopalan1
1Department of Otorhinolaryngology-Head and Neck Surgery, University of Pennsylvania, Philadelphia, PA, USA.
Abstract:
There is limited guidance on exploiting the genome-wide loss-of-function CRISPR screens in cancer Dependency Map (DepMap) to identify new targets for individual cancer types. This study integrated multiple tools to filter these data in order to seek new therapeutic targets specific to head and neck squamous cell carcinoma (HNSCC). The resulting pipeline prioritized 143 targetable dependencies that represented both well-studied targets and emerging target classes like mitochondrial carriers and RNA-binding proteins. In total, 14 targets had clinical inhibitors used for other cancers or nonmalignant diseases that hold near-term potential to repurpose for HNSCC therapy. Comparing inhibitor response data that were publicly available for 13 prioritized targets between the cell lines with high vs. low dependency on each target uncovered novel therapeutic potential for the PAK2 serine/threonine kinase. PAK2 gene dependency was found to be associated with wild-type p53, low PAK2 mRNA, and diploid status of the 3q amplicon containing PAK2. These findings establish a generalizable pipeline to prioritize clinically relevant targets for individual cancer types using DepMap. Its application to HNSCC highlights novel relevance for PAK2 inhibition and identifies biomarkers of PAK2 inhibitor response.
Insights
This study presents a new pipeline to find cancer drug targets using CRISPR screens from the Dependency Map (DepMap). For head and neck squamous cell carcinoma (HNSCC), it identified PAK2 as a promising therapeutic target.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Genome-wide loss-of-function CRISPR screens in the cancer Dependency Map (DepMap) offer potential for identifying novel cancer targets.
- Limited guidance exists for effectively exploiting these screens for specific cancer types.
Purpose of the Study:
- To develop and apply a computational pipeline to prioritize therapeutically relevant targets in head and neck squamous cell carcinoma (HNSCC) using DepMap data.
- To identify actionable therapeutic targets and potential drug repurposing opportunities for HNSCC.
Main Methods:
- Integrated multiple computational tools to filter and prioritize genes from genome-wide CRISPR screens.
- Applied the pipeline to DepMap data for head and neck squamous cell carcinoma (HNSCC).
- Analyzed inhibitor response data to validate prioritized targets and identify biomarkers.
Main Results:
- Prioritized 143 targetable dependencies in HNSCC, including known and novel target classes.
- Identified 14 targets with existing clinical inhibitors suitable for repurposing in HNSCC.
- Uncovered PAK2 (serine/threonine kinase) as a novel therapeutic target, with dependency linked to wild-type p53, low PAK2 mRNA, and 3q amplicon diploid status.
Conclusions:
- Established a generalizable pipeline for prioritizing cancer-specific therapeutic targets from DepMap data.
- Highlighted PAK2 inhibition as a promising strategy for HNSCC treatment.
- Identified biomarkers predictive of PAK2 inhibitor response in HNSCC.
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