Optimization of a mouse model of pancreatic cancer to simulate the human phenotypes of metastasis and cachexia

Autor: Victoria Spadafora, Benjamin R. Pryce, Alexander Oles, Erin E. Talbert, Martin Romeo, Silvia Vaena, Stefano Berto, Michael C. Ostrowski, David J. Wang, Denis C. Guttridge
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Cancer, Vol 24, Iss 1, Pp 1-19 (2024)
Druh dokumentu: article
ISSN: 1471-2407
DOI: 10.1186/s12885-024-12104-0
Popis: Abstract Background Pancreatic ductal adenocarcinoma (PDAC) presents with a high mortality rate. Two important features of PDAC contribute to this poor outcome. The first is metastasis which occurs in ~ 80% of PDAC patients. The second is cachexia, which compromises treatment tolerance for patients and reduces their quality of life. Although various mouse models of PDAC exist, recapitulating both metastatic and cachectic features have been challenging. Methods Here, we optimize an orthotopic mouse model of PDAC by altering several conditions, including the subcloning of parental murine PDAC cells, implantation site, number of transplanted cells, and age of recipient mice. We perform spatial profiling to compare primary and metastatic immune microenvironments and RNA sequencing to gain insight into the mechanisms of muscle wasting in PDAC-induced cachexia, comparing non-metastatic to metastatic conditions. Results These modifications extend the time course of the disease and concurrently increase the rate of metastasis to approximately 70%. Furthermore, reliable cachexia endpoints are achieved in both PDAC mice with and without metastases, which is reminiscent of patients. We also find that cachectic muscles from PDAC mice with metastasis exhibit a similar transcriptional profile to muscles derived from mice and patients without metastasis. Conclusion Together, this model is likely to be advantageous in both advancing our understanding of the mechanism of PDAC cachexia, as well as in the evaluation of novel therapeutics.
Databáze: Directory of Open Access Journals
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