Active Cancer Heart, Stroke & Blood

KAT2A PROTACs targetting the differentiation of blasts and leukemic stem cells for the treatment of Acute Myeloid Leukaemia

In plain English

AI plain-English summary

A new class of drug molecules co-opts the cell’s own waste-disposal machinery to destroy a protein that helps acute myeloid leukaemia (AML) evade the immune system. More than 70% of AML patients over 65 die within a year of diagnosis, and fewer than 15% survive five years. Current chemotherapy is often too toxic for this age group and fails to eliminate the leukaemic stem cells that drive relapse. The target protein, KAT2A, blocks the body from recognising and destroying AML cells. The Cardiff team has developed three advanced molecules—called PROTACs—that tag KAT2A for removal by the cell’s natural degradation system, an approach that was not feasible five years ago. If these molecules succeed in regulatory studies, they could become a well-tolerated therapy for all AML patients, including the elderly. The same PROTAC technology could later be adapted to target other cancer-driving proteins, offering a generalisable platform for less toxic cancer treatments. The current project will determine the optimal dose and select the best molecule for clinical trials, building the data package needed to attract commercial investment.

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Acute Myeloid Leukaemia (AML) is a form of cancer that starts in the bone marrow and moves into the blood. The loss of blood cells to fight infection and to mediate blood clotting frequently leads to sepsis or significant hemorrhage. This cancer is most common in the older population (over 65 years) and is difficult to treat. Current therapies are relatively crude chemotherapeutic "sledgehammers" and are not widely effective and/or are poorly tolerated, particularly by the elderly. This leads to over 70% of patients over 65 years old dying within the first year of diagnosis and fewer than 15% living beyond year 5. The Medicines Discovery Institute at Cardiff University has developed a novel therapeutic agent which can revolutionise treatment of this disease and treat all AML patients, with the potential to be well tolerated in the vulnerable elderly population. We will do this by targeting a specific protein in the body, known as KAT2A, which plays a key role in blocking the body from recognising and destroying the cancer cells. Our approach has exploited a novel technology that allows us to harness the body's own molecular waste disposal systems within the cell to remove this target protein. This solution was unimaginable 5 years ago, but now presents us with the opportunity to advance a technology solution that could be widely used and would be less toxic than current treatments. Our project has many years of discovery effort behind it, and has completed an extensive campaign of optimisation and characterisation to identify three advanced molecules which have the potential to progress into clinical trials. Now, we need to further study these molecules to complete the data package that is required by regulatory agencies and to select the best of these molecules as the potential new therapy. These studies will establish the best dose to use for our novel molecules and inform us on how best to use these molecules to help patients. These experiments significantly enhance the potential for onward investment by groups focused on the development of new cancer treatments for this patient population.

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Researchers

Joanna Zabkiewicz (Co-Investigator)John Atack (Co-Investigator)Simon Ward (Principal Investigator)Steven Knapper (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Developing Novel Bispecific Antibody-Drug Conjugates to Treat Leukaemia
Synthesis of PROTAC-Antibody Conjugate for Application in Acute Myeloid Leukemia Therapy
Using novel combination therapies to target acute myeloid leukaemia (AML)
Finding therapeutic targets in FLT3-ITD AML using a systems biology approach
Clinical validation of a revolutionary multi-analyte companion diagnostic platform technology and treatment algorithm for precision medicine

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Research Grant

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