In vivo models of childhood leukemia for preclinical drug testing

Petra S Bachmann1, Richard B Lock

  • 1Children's Cancer Institute Australia for Medical Research, University of New South Wales, Sydney, Australia. rlock@ccia.unsw.edu.au

Current Drug Targets
|June 23, 2007
PubMed

Insights

Preclinical testing of novel anti-cancer drugs in animal models is crucial for prioritizing effective treatments for childhood acute leukemia. In vivo models, particularly human leukemia xenografts, are vital for evaluating new therapeutic agents.

Area of Science:

  • Hematology and Oncology
  • Translational Medicine
  • Pharmacology

Background:

  • The pipeline of new anti-cancer drugs for clinical trials outpaces the availability of pediatric acute leukemia patients for enrollment.
  • Effective preclinical testing is essential to identify and prioritize the most promising agents for childhood leukemia treatment.

Purpose of the Study:

  • To highlight the importance of preclinical testing for novel anti-cancer drugs in childhood acute leukemia.
  • To review the utility of established in vivo models for evaluating therapeutic efficacy.

Main Methods:

  • Review of historical and current in vivo models for leukemia research, including genetically engineered murine models.
  • Focus on human leukemia xenografts in immune-deficient murine hosts as a predominant preclinical testing platform.
  • Discussion of successful engraftment across various leukemia subtypes (ALL, AML, JMML, CML, CLL).

Main Results:

  • Human leukemia xenografts have demonstrated successful engraftment across a wide spectrum of acute and chronic leukemia subtypes in immune-deficient mice.
  • These models provide a viable system for the preclinical evaluation of novel therapeutic agents.

Conclusions:

  • In vivo preclinical testing is indispensable for identifying promising novel therapeutics for childhood acute leukemia.
  • Optimizing the use of these agents in combination with existing and new chemotherapeutics is facilitated by robust preclinical data.