On May 25, 2021 At the annual meeting of the American Association for Cancer Research (AACR) (Free AACR Whitepaper) (AACR 2021: April 10 – 15 th and May 17-21 st) scientists from Cellaria Inc. (Wakefield, MA, USA), a scientific innovator with breakthrough tools for cancer research, reported that it will present new work demonstrating the value of patient-specific cancer models in studies of metastasis, and the associated development of drug resistance (Press release, Cellaria, MAY 25, 2021, View Source [SID1234580535]). Cellaria offers models that accurately represent a diverse range of disease types, progression grades and genetic profiles. These enable researchers to study disease pathways and develop patient-specific therapies more effectively. The new research demonstrates the utility of patient-specific ovarian, breast and pancreatic cancer models in studies of the tumor microenvironment and the metastatic niche, illustrating their potential to improve the likelihood of success in clinical trials.
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Cellaria’s poster is entitled ‘Modeling the metastatic niche interactions between patient tumor and mesenchymal cells to identify drivers of chemotherapy drug resistance’. The process of metastasis involves cancer cells moving to and thriving in a foreign microenvironment. The Metastatic niche facilitates this process by performing functions such as anchorage, proliferation, and expansion. In this process, mesenchymal stem cells (MSC) sourced from adipose tissue were co-cultured in three-dimensional tumor spheroids to simulate the microenvironment of the metastatic niche. The resulting models were then tested with a broad range chemotherapeutic agent. The impact of different MSC seeding ratios on the resulting response curve was investigated.
The results show that chemotherapeutic response is dependent on MSC seeding ratio, but that even at low levels MSCs have an impact on the drug response of metastatic tumor spheroids. These effects are observed across the patient profile spectrum, with each cancer type. Though there is detectable variation, the strength of the effect is not homogeneous. Disease type, MSC ratio, and drug utilized all influence the observed results. A key conclusion from the work is that the models provide a reproducible, easily scaled tool for assessing the efficacy of chemotherapeutic drugs with respect to metastatic tumors, thereby supporting the development of more effective, precisely targeted therapies.