Using the RCAS-TVA system to model human cancer in mice

Leanne G Ahronian1, Brian C Lewis1

  • 1Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, Massachusetts 01605.

Insights

The RCAS-TVA system enables targeted gene delivery in mice for cancer modeling. This avian sarcoma leukosis virus subgroup A (ASLV-A) based system allows precise study of tumor development by infecting cells expressing the tumor virus A (TVA) receptor.

Area of Science:

  • * Molecular Biology
  • * Virology
  • * Cancer Research

Background:

  • * Avian sarcoma leukosis virus subgroup A (ASLV-A) requires the tumor virus A (TVA) receptor for cell infection.
  • * Mammalian cells typically lack TVA, conferring resistance to ASLV-A.
  • * Transgenic expression of TVA in mice creates target cells susceptible to ASLV-A-based vectors.

Purpose of the Study:

  • * To introduce and detail the RCAS-TVA gene delivery system for modeling human cancers in mice.
  • * To highlight the system's utility in studying oncogenesis and gene function in specific cell types.
  • * To compare the advantages of RCAS-TVA over traditional transgenic and knockout mouse models.

Main Methods:

  • * Engineering mice to express the TVA receptor in specific cell types or tissues.
  • * Utilizing ASLV-A-based RCAS viruses for gene delivery (cDNAs, shRNAs, miRNAs) to TVA-expressing cells.
  • * Comparing tumor development outcomes in RCAS-TVA models versus conventional genetic models.

Main Results:

  • * The RCAS-TVA system effectively models human tumors like pancreatic, ovarian, breast cancers, gliomas, and melanomas.
  • * Postnatal, low-efficiency virus delivery mimics sporadic gene expression in developing tumors.
  • * Enables comparative studies of oncogenes and tumor suppressor genes in a single transgenic line.
  • * Facilitates combination studies with other mouse models to investigate cooperating genetic events.

Conclusions:

  • * The RCAS-TVA system is a versatile and powerful tool for preclinical cancer research and modeling.
  • * It offers advantages in mimicking tumor development and studying genetic interactions compared to traditional methods.
  • * This system facilitates the investigation of gene function and oncogenesis in a targeted and adaptable manner.