Human tumor xenografts and mouse models of human tumors: re-discovering the models

Beverly A Teicher1

  • 1Genzyme Corporation, 49 New York Avenue, Framingham, MA 01701-9322, USA +1 508 271 2843 ; +1 508 620 1203 ; Beverly.Teicher@Genzyme.com.

Abstract

Insights

Human tumor xenografts and genetically engineered mouse (GEM) models are crucial for cancer drug discovery. Advances in technology improve these models, yet a broader range of models is needed to represent diverse human cancers.

Area of Science:

  • Oncology
  • Cancer Research
  • Drug Discovery

Background:

  • Human tumor xenografts and genetically engineered mouse (GEM) models are essential tools in cancer drug discovery.
  • Gene and protein expression technologies enhance understanding of cancer biology.
  • GEM models are increasingly utilized for evaluating immunotherapies.

Purpose of the Study:

  • To review the current status of human tumor xenografts, GEM models, and normal tissue assays in cancer drug discovery.
  • To highlight advancements and limitations in preclinical cancer modeling.

Main Methods:

  • Review of existing literature on human tumor xenografts and GEM models.
  • Discussion of technological advancements like gene/protein expression analysis and non-invasive imaging.
  • Evaluation of different implantation techniques (subcutaneous vs. orthotopic).

Main Results:

  • The Preclinical Pediatric Tumor Program features 47 well-characterized pediatric tumor xenografts.
  • Some studies indicate a lack of correlation between in vitro and in vivo characteristics of certain human tumor lines.
  • Orthotopic implantation is gaining favor over subcutaneous methods for better clinical relevance.
  • Recent GEM models incorporate multiple gene mutations for increased genetic instability.

Conclusions:

  • Cancer modeling using human tumor xenografts and GEMs is continuously evolving with new technologies.
  • Improved genetic engineering and imaging techniques enhance tumor modeling capabilities.
  • There is a significant need for more diverse preclinical models to cover the spectrum of human cancers.