PUBLICATION

Zebrafish as a Model for Cancer Self-Renewal

Authors
Ignatius, M.S., and Langenau, D.M.
ID
ZDB-PUB-091215-27
Date
2009
Source
Zebrafish   6(4): 377-387 (Journal)
Registered Authors
Ignatius, Myron, Langenau, David
Keywords
none
MeSH Terms
  • Animals
  • Disease Models, Animal
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Neoplasms/genetics
  • Neoplasms/immunology
  • Neoplasms/metabolism*
  • Neoplasms/pathology*
  • Neoplastic Stem Cells/immunology
  • Neoplastic Stem Cells/metabolism*
  • Neoplastic Stem Cells/pathology*
  • Zebrafish/genetics
  • Zebrafish/immunology
  • Zebrafish/metabolism*
PubMed
19954344 Full text @ Zebrafish
Abstract
Self-renewal is the process by which normal stem cells and cancer cells make more of themselves. In cancer, this process is ultimately responsible for the infinite replicative potential of malignant cells and is likely found in residual cell populations that evade conventional therapy. Two intrinsically opposing hypotheses have emerged to explain how self-renewal occurs in cancer. The cancer stem cell hypothesis states that self-renewal is confined to a discrete subpopulation of malignant cells, whereas the stochastic model suggests that all tumor cells have the potential to self-renew. Presently, the gold standard for measuring cancer self-renewal is limiting dilution cell transplantation into immune-matched or immune-deficient animals. From these experiments, tumor-initiating frequency can be calculated based on the number of animals that engraft disease following transplantation of various doses of tumor cells. Here, we describe how self-renewal assays are performed, summarize the current experimental models that support the cancer stem cell and stochastic models of cancer self-renewal, and enumerate how the zebrafish can be used to uncover important pathways in cancer self-renewal.
Genes / Markers
Figures
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Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping