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Author Spotlight: Validating Cancer Therapy Responses with Desmoplastic Spheroid Models
Published on: September 27, 2024
Biomaterial substrate-derived compact cellular spheroids mimicking the behavior of pancreatic cancer and
Chui-Wei Wong1, Hao-Wei Han1, Yu-Wen Tien2
1Institute of Polymer Science and Engineering, National Taiwan University, Taipei, Taiwan.
Abstract:
Pancreatic stromal cells especially pancreatic stellate cells (PSCs) play a critical role in the progression of human pancreatic ductal adenocarcinoma (PDAC). However, the exact interaction between cancer cells and PSCs remains to be elucidated in order to develop more effective therapeutic approaches to treat PDAC. The microenvironment of PDAC shows higher hyaluronan (HA) levels, which is associated with poor prognosis of PDAC patients. In the current study, an efficient three-dimensional tumor spheroid model for PDAC was established. The pancreatic cancer cells and PSCs were co-cultured on hyaluronan grafted chitosan (CS-HA) coated plates to generate 3D tumor-like co-spheroids. The pancreatic cancer cells and PSCs (1:9 ratio) co-cultured on CS-HA coated plates were assembled into tumor-like co-spheroids with 3D core-shell structure in 48 h. These spheroids displayed potent in vitro tumorigenicity such as up-regulated expression of stemness and migration markers. The migration rate of cancer cells in spheroids (from 1:9 cell ratio) was much faster (3.2-fold) than that of cancer cells alone. Meanwhile, this unique co-spheroidal cancer cell structure with the outer wrap of PSCs contributed to the chemo-resistance of pancreatic cancer cells to gemcitabine as well as sensitivity to the combined gemcitabine and Abraxane treatment in vitro. The metastatic nature of the spheroids was confirmed by the zebrafish xenograft model in vivo. The compact and dynamic pancreatic cancer-PSC co-spheroids generated by the unique 3D co-culture platform on CS-HA biomaterials can mimic the PSC-constituting microenvironment of PDAC and demonstrate the chemo-resistant, invasive, and metastatic phenotypes. They have potential applications in personalized and high-throughput drug screening.
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