Genetically Engineered Mouse Model Development
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Genetically Engineered Mouse Model Development

Genetically engineered mouse models (GEMM) of ovarian cancer effectively replicate the biological features and pathological processes of human ovarian cancer through precise gene editing. Alfa Cytology, with its dedicated team of researchers, is fully committed to advancing the research and development of these invaluable GEMM.

Introduction to Genetically Engineered Mouse Model

The GEMM of ovarian cancer is a sophisticated experimental animal model created using advanced gene editing technology to precisely mimic the biological features and pathological processes of human ovarian cancer. These models are typically genetically modified with specific alterations in key genes associated with ovarian cancer, such as KRAS, PIK3CA, and TP53, among others. Such genetic modifications enable the mice to naturally develop ovarian tumors in vivo, closely resembling the human disease.

Different strategies to manipulate the mouse genome.Fig.1 Different strategies to manipulate the mouse genome. (BISWAS K, et al., 2023)

Technologies for Developing Genetically Engineered Mouse Models

  • Transgenic Technology: Transgenic technology enables the introduction of exogenous genes (such as oncogenes or their mutants) into mouse fertilized eggs or embryonic stem cells.
  • Knockout Technology: Gene knockout technology uses homologous recombination or gene editing tools like CRISPR/Cas9 to delete a gene or part of its sequence in mice.
  • Embryonic Stem Cell Technology: By introducing exogenous genes into embryonic stem cells and exploiting the totipotency of these cells, researchers can generate chimeric or transgenic mice.

Our Services

Alfa Cytology is committed to the research and development of genetically engineered mouse models of ovarian cancer to advance this field. We use advanced gene editing technologies to create efficient experimental models, offering researchers robust tools to investigate the pathogenesis and pathology of ovarian cancer.

Workflow of Genetically Engineered Mouse Model Development

Gene Editing and Model Construction

Using gene editing techniques such as CRISPR, specific genes were targeted to create mouse models of ovarian cancer. These models were designed to accurately reflect the genetic background of human ovarian cancer.

Phenotypic Evaluation of the Model

A systematic phenotypic analysis was conducted on the constructed mouse models. This included assessing tumor growth rates, metastatic potential, and biomarker expression to verify the validity and stability of the models.

Pharmacodynamics Evaluation

GEMM of ovarian cancer can monitor tumor growth, metastasis, and survival post-drug administration. They also help analyze drug effects on the tumor microenvironment and immune system, and provide insights into drug mechanisms via histology and biomarker detection.

Genetically Engineered Mouse Model of Ovarian Cancer

Genetically engineered mouse models of ovarian cancer primarily encompass the following types:

Knockout Mice: Our research team generated these models by knocking out specific genes associated with ovarian cancer. In this way, we can study the role of these genes in tumorigenesis.

  • TP53
  • BRCA1 / BRCA2
  • PTEN
  • KRAS
  • PIK3CA
  • GATA3

Transgenic Mice: Oncogenes can be introduced into the mouse genome to induce ovarian cancer formation. This facilitates the study of tumor development and metastasis.

  • KRAS
  • c-Myc
  • BRCA1 / BRCA2
  • TP53
  • More

Alfa Cytology has garnered extensive experience over many years in researching genetically engineered mouse models of ovarian cancer. Leveraging advanced gene editing technologies, our expert team has successfully developed a variety of mouse models to support diverse research projects. Should you have any questions about our services or require additional information, please do not hesitate to contact us.

Reference

  1. BISWAS K, MOHAMMED A, SHARAN S K, et al. Genetically engineered mouse models for hereditary cancer syndromes [J]. Cancer Sci, 2023, 114(5): 1800-15.

! For research use only.