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Related Experiment Videos

Transgenic oncogene mice. Tumor phenotype predicts genotype.

R D Cardiff1, E Sinn, W Muller

  • 1Department of Pathology, School of Medicine, University of California, Davis 95616.

The American Journal of Pathology
|September 1, 1991
PubMed
Summary

Oncogenes like ras, myc, and neu significantly influence mammary tumor characteristics in mice. Tumor cell appearance can predict the specific oncogene driving cancer growth, aiding in understanding disease progression.

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Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Oncogenes are key drivers of cancer development.
  • Understanding the relationship between oncogenes and tumor morphology is crucial for cancer research.
  • Existing classification systems may not fully capture the diversity of oncogene-induced tumors.

Purpose of the Study:

  • To investigate the influence of specific oncogenes (ras, myc, neu) on mammary tumor phenotype in transgenic mice.
  • To determine if tumor morphology can serve as a predictive marker for oncogene presence.
  • To explore how combinations of oncogenes affect tumor development and progression.

Main Methods:

  • Analysis of 607 mammary tumors from 407 transgenic mice harboring ras, myc, and/or neu oncogenes.
  • Classification of non-standard tumor phenotypes into eosinophilic small cell (SC), basophilic large cell (LC), and pale intermediate cell (IC).

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  • Statistical analysis to determine the specificity and sensitivity of phenotype-oncogene associations.

    • Main Results:

    • A high percentage (91%) of tumors exhibited non-standard phenotypes.
    • Specific associations were found: SC tumors with ras, LC tumors with myc, and IC tumors with neu (specificity > 0.90).
    • Combinations of oncogenes altered tumor types and incidence, with myc/ras or myc/neu accelerating tumorigenesis and ras/neu decreasing incidence.

    Conclusions:

    • Mammary tumor phenotype is a reliable predictor of the underlying oncogene.
    • Oncogene combinations significantly impact tumor progression and natural history.
    • This provides a basis for predicting disease trajectory based on tumor characteristics.