Pancreatic cancer (PC) is a serious cancer with a large unmet need and a lower survival rate compared to other cancers. In order to understand the unique biology of PC and to facilitate research on new therapeutic targets, bioengineering techniques are increasingly applied to the design and construction of patient-specific models. Alfa Oncology is dedicated to helping researchers and professionals get insight into PC in an efficient, cost-effective, and effective manner. We are now offering in vitro preclinical models of PC, including 2D cell lines and 3D spheroids.
Fig. 1 Schematic of the tumor microenvironment of pancreatic cancer. (Tomás-Bort, Elena, et al., 2020)
The service offering at Alfa Oncology
Newly established PC cell lines may provide sufficient models for studying the broader biological and molecular features of PC. We have established cell culture-based methods for tumor cell isolation and expansion for further molecular and functional testing, including in vitro 2D and 3D culture systems.
2D cell line establishment, characterization, and application
PC cell lines are characterized by specific mutations, including KRAS, p53, p16, and SMAD4, and can be derived from different sites in patient and murine tumors. Compared to other models, 2D cell culture is the simplest, fastest,and most economical form to study metastasis and invasion. In addition, 2D cell culture can be applied to mimic the signals from the tumor microenvironment (TME) tumor by co-culturing cancer cells with stromal cells. We offer PC cell line establishment and characterization services to help researchers and professionals to confirm therapeutic efficacy or identify additional options. Our pancreatic ductal adenocarcinoma (PDAC) cell lines can greatly assist in screening for genes that promote PDAC migration and survival as well as chemo- or radio-resistance in the preclinical setting.
|Available PC cell lines at Alfa Oncology|
3D cell culture is an innovative approach that bridges the gap between traditional 2D cell culture and animal models, enabling more accurate replication of tumor invasion. 3D spheroids have proven useful in cancer cell research, particularly for modeling TME components and testing new therapeutic approaches for TME targeting. Our capabilities can provide relatively stable 3D PC tumor-tissue invasion models for high-throughput (HT) phenotypic drug screening. For example, we can provide pancreatic stellate cell (PSC)/PDAC spheroids that are based on a modified hanging drop method incorporating methylcellulose. As a major source of stromal fibrosis, PSCs interact closely with cancer cells to produce a supportive environment that promotes local and remote tumor development. Co-culture of PDAC cells with PSCs leads to a desmoplastic response and the formation of tumor-like cell morphology and histology, offering useful tools for screening cancer and stroma targeting drugs. The model is highly reproducible and consistent, allowing for validation steps prior to animal testing and reducing the number of animals required.
|Available PC Spheroids model techniques and applications|
|Modified hanging drop||PC stroma interaction analysis and HT automated drug screening assays|
|Co-culture (CS-HA coated plates)||PC cellular interaction, migration, and drug resistance|
|Co-culture (type I collagen)||PC stroma-mediated cell motility and drug resistance|
Alfa Oncology is a leading global life sciences company. We have an in-depth understanding of PC cells and other components. Here, we are dedicated to offering different preclinical cell models for PC research and the development of successful therapeutic regimens. If you are interested in our services, please feel free to contact us. We will provide a professional, competitively priced solution that fits your needs.
- Miquel, Maria, Shuman Zhang, and Christian Pilarsky. "Pre-clinical Models of Metastasis in Pancreatic Cancer." Frontiers in cell and developmental biology (2021): 2825.
- Tomás-Bort, Elena, et al. "3D approaches to model the tumor microenvironment of pancreatic cancer." Theranostics 10.11 (2020): 5074.