Children’s Hospital of Philadelphia and Penn Medicine Launch First CRISPR-Based Platform to Pinpoint Drivers of Acute Myeloid Leukemia in Patient Cells

New Toolkit Allows Researchers to Test Potential Cancer Targets Directly in Patient-Leukemia Cells

Excerpt from the Press Release:

PHILADELPHIA, Feb. 26, 2026 /PRNewswire/ — A new CRISPR-based tool that is directly used on patients’ cancer cells can identify genes and regulatory elements driving acute myeloid leukemia (AML), an aggressive blood cancer affecting the bone marrow and blood. This first-of-its-kind approach reveals how individual patient cells respond to genetic changes and makes it easier to identify drug targets and understand why some cancers stop responding to treatment. The findings were published today in Molecular Cell, by researchers from Children’s Hospital of Philadelphia (CHOP) and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine).

CRISPR genome-editing tools allow researchers to quickly test hundreds of genes at the same time to determine which ones are important for cancer growth and survival. These genetic toolkits have enabled the discovery and validation of new cancer drug targets. Until now, this approach has mostly been used in preclinical models or in long-established cancer cell lines grown in labs. These models do not fully represent the genetic diversity seen in patients. Researchers sought to apply CRISPR tools on heterogeneous tumor samples from patients to better understand which genetic elements cancer cells depend on and how they would respond to treatment.

AML accounts for about one in three leukemias in adults and is the second most common blood cancer in children in the U.S. While chemotherapy puts many patients with AML into remission, for those whose cancer does not respond to treatment or who experience relapse, treatment can be challenging, often due to certain gene or chromosome changes in the leukemia cells. This research aims to address that challenge. Because the new tool works on patient samples, the researchers hope it could one day be used not just as a research tool, but in the clinical setting to better prioritize treatment options based on each patient’s cancer’s unique biology.

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