Whole genome CRISPR KO screening enables you to discover the genes that alter response to your compound.

Sub-groups of the patient population may carry mutations in specific gene(s) that affect the response of that individual to a therapeutic. By individually knocking out each of ~19,000 genes, you can identify the genes that alter resistance or sensitivity to your compound.

Horizon has optimized 35+ cell lines for the standard CRISPR KO screen offering called ResponderSCREEN.

Choose 1, 2 or 4 cell lines from our pre-optimized panel, provide us with your compound and you will receive a list of genes that are important for your drug activity.

Apply the data for patient stratification to:

  • Maximize the success of your drug development program
  • Reduce time to drug approval with improved trial design
  • Improve patient outcomes

Request more information


  • 1, 2 or 4 cell lines from Horizon’s list of 35+ pre-optimized cell lines
  • CRISPR KO screen using Horizon’s whole genome sgRNA library (~19,000 genes)
  • +/- one compound treatment (Client defined concentration)*
  • Comprehensive bioinformatics analysis
  • Average turnaround time: 12-18 weeks
  • Deliverables:
    • A list of genes of which disruption alter response to the compound of interest
    • A final report containing experimental design, all raw & analysed data and conclusions of the study

*Compound dosage selection available upon request

CRISPR screening workflow

CRISPR screening

Horizon has licensed the use and commercialization of CRISPR-Cas9 technology from The Broad Institute, ERS Genomics and Harvard University.

Case Study

Whole genome CRISPR KO resistance screen in A375 melanoma cells

Purpose: A proof of concept study to identify resistance factors against a BRAF kinase inhibitor Vemurafenib (PLX-4032) in A375 melanoma cells that carry a BRAF V600E gain-of-function mutation.


  • GeCKO v2 knockout library: 6 sgRNAs against 19,050 genes (Sanjana et al., 2014)
  • Pooled-based approach: lentivirus transduction of the library into cells with antibiotic selection
  • Treatment of the edited cell population with Vemurafenib for 14 days
  • Cell pellet collection and sample preparation
  • Next-generation sequencing and data analysis using an adapted MAGeCK workflow


  • Highest ranking genes were MED12, NF1, CUL3, NF2, TADA2B and TADA1, which are known to  confer resistance to Vemurafenib.
  • Additional hits include members of the STAGA histone acetyl transferase complex (TAFL5/PAF65b) and the Mediator complex (MED23).

 Figure 1. Ranking of the hits of the screen by
MAGeCK algorithm 

Download the complete application note

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