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DOI 10.1002/ame2.12568

Медицинская библиотека · Animal models and experimental medicine · 2025

System genetic analysis of intestinal cancer and periodontitis development as influenced by aging and diabesity using Collaborative Cross mice.

Lone Iqbal M, Zohud Osayd, Midlej Kareem, Brenner Charles, Iraqi Fuad A

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Аннотация

It is increasingly recognized that young, chow-fed inbred mice poorly model the complexity of human carcinogenesis. In humans, age and adiposity are major risk factors for malignancies, but most genetically engineered mouse models (GEMM) induce carcinogenesis too rapidly to study these influences. Standard strains, such as C57BL/6, commonly used in GEMMs, further limit the exploration of aging and metabolic health effects. A similar challenge arises in modeling periodontitis, a disease influenced by aging, diabesity, and genetic architecture. We propose using diverse mouse populations with hybrid vigor, such as the Collaborative Cross (CC) × ApcMin hybrid, to slow disease progression and better model human colorectal cancer (CRC) and comorbidities. This perspective highlights the advantages of this model, where delayed carcinogenesis reveals interactions with aging and adiposity. Unlike ApcMin mice, which develop cancer rapidly, CC × ApcMin hybrids recapitulate human-like progression. This facilitates the identification of modifier loci affecting inflammation, diet susceptibility, organ size, and polyposis distribution. The CC × ApcMin model offers a transformative platform for studying CRC as a disease of adulthood, reflecting its complex interplay with aging and comorbidities. The insights gained from this approach will enhance early detection, management, and treatment strategies for CRC and related conditions.

Для цитирования: Lone Iqbal M, Zohud Osayd, Midlej Kareem, Brenner Charles, Iraqi Fuad A. System genetic analysis of intestinal cancer and periodontitis development as influenced by aging and diabesity using Collaborative Cross mice.. Animal models and experimental medicine. 2025. DOI: 10.1002/ame2.12568.

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