Scientist Explores Gene to Increase Survival Rate of Patients with High-Risk Leukemia

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Chris Porter, MD


Project: Functional Genomic Screening to Identify Novel Targets for IKZF Mutated ALL

  • Chris Porter, MD
  • University of Colorado
  • Children’s Hospital of Denver

With an overall survival rate of about 90%, most leukemia patients receive a standardized treatment that has been proven successful. However, when a patient with leukemia relapses, his/her chances of survival decrease significantly. Mutations in the Ikaros gene (IKZF1) have been previously proven to lead to an increased risk of relapse and treatment failure.

Chris Porter, MD from the University of Colorado and Children’s Hospital of Denver splits his time seeing pediatric oncology patients and researching targeted therapies aimed at improving treatments for leukemia. His lab at the University of Colorado is focused on using functional genomic screening to identify novel therapeutic strategies for acute lymphoblastic leukemia (ALL). Oncogenes are proteins that, when mutated, initiate and maintain the cancerous state of a cell. Oncogene activation is damaging to the cell, though, and in order for the cell to survive, other genes and pathways must be altered to enable to cells to survive the oncogenic stress. This is called non-oncogene addiction. Determination of which non-oncogenes a given tumor is addicted to may lead to novel therapeutic approaches for that tumor. Dr. Porter hypothesizes that when the Ikaros gene is mutated, changes occur that allow cell survival, and he intends to determine what these changes are and how these cells resist chemotherapy. Dr. Porter hopes that this will lead to improved treatments for leukemia patients.

As the result of this project, Dr. Porter has made progress in the understanding and modeling of IKZF1-mutant ALL:

  • 1 clinically relevant model of IKZF1-mutant B-cell ALL developed
  • 1 genome-scale shRNA screen performed
  • 17 DNA damage response genes identified as potential therapeutic targets in IKZF1-mutant ALL

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