Active Cancer Genetics & Molecular Biology

Establishment of an industrial base- and prime-editing platform for the identification of cancer drug resistance mechanisms and targets.

In plain English

AI plain-English summary

Cancer drug resistance causes 80 to 90 percent of cancer-related deaths, yet current methods only detect it after it has already spread through patient populations. BaseRx, the company behind this project, is building a platform that uses advanced genome editing tools—specifically base editing and prime editing—to find the single-letter DNA changes that make tumours stop responding to drugs. Existing CRISPR screens can knock out genes, but they cannot mimic the precise point mutations that drive resistance in real patients. This platform aims to recreate that genetic diversity in the lab, letting researchers see which variants matter before they become a clinical problem. If the platform works, it could shift how drug resistance is studied: from reactive observation to proactive identification. Pharmaceutical companies might use it to test new drugs against a library of resistance mutations early in development, potentially flagging weak points before a drug reaches clinical trials. The impact would be felt in the drug development pipeline and in clinical decision-making, not in a patient’s daily life directly. This is applied biotechnology—it aims to make a specific industrial process faster and more predictive, not to produce an immediate consumer product.

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Cancer drug resistance is responsible for 80-90% of cancer-related deaths, making it a significant barrier to effective treatment (Mansoori,2017). Existing methods for characterising acquired resistance mechanisms are slow and reactive, identifying drug resistance only after it has occurred at scale in the clinic (Vasan et al.,2019). While CRISPR-Cas9 screening is effective for gene knockout studies, it lacks the precision to assess single-nucleotide changes, which are key drivers of cancer drug resistance. BaseRx is applying state of the art genome editing tools to prospectively identify single nucleotide variants driving resistance to cancer drugs thereby recapitulating the genetic diversity and tumour evolution observed across cancer patient populations in the laboratory and providing a platform for directly interpreting how variants affect response to therapy.

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Related Research

Grants with similar aims, by meaning.

CRISPR Screen Multiplexing for Uncharacterised Region Function (SMURF)
Whole Genome Sequence-guided targeting of colorectal and oesophageal cancers
Establishing the Genetic Landscape of Therapy Resistance in Lung Cancer with Gene Editing.
CRISPR in the Wild: demonstrating model-driven epigenome editing in cancer
Harnessing transposons for drug resistance gene discovery in cancer.

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