Using 3D co culture models to study Ovarian cancer metastasis and pathophysiology
Poster Number
15
Format
Oral Presentation
Faculty Mentor Name
Maria F. Gencoglu
Faculty Mentor Department
Bioengineering
Abstract/Artist Statement
Ovarian cancer (OvCa) is the second most common gynecologic malignancy, although it is currently taking more lives compared to any other form of cancer infiltrating the reproductive system. Most patients are diagnosed at late stages due to the rapid metastasis of OvCa tumors and the lack of understanding regarding the complete pathophysiology of OvCa. Current medical care focuses on cytoreduction, followed by platinum and taxane-based chemotherapy, which takes an aggressive toll on patients. These extreme medical lengths do not guarantee a cure for OvCa patients, considering about 70% of them relapse, and this period up to relapse varies between a few months to up to five years, hence the unpredictability of OvCa (Ushijima 2009).
Three dimensional co culture models have become more prevalent over the past decade for in vitro disease modeling, and current research highlights certain useful properties of these models that can be applied to OvCa metastasis modeling. Co culture models can provide insight into biological responses of tumors, including drug resistance, cell-to-cell interactions, and metastasis (Gencoglu 2018). Using a co culture model to study the pathophysiology of OvCa requires mimicking the tumor’s microenvironment using natural biomaterials and OvCa cell lines. This implementation sets the stage for an increased reliability on three dimensional modeling, which can be ultimately translated into computer based models and simulations used to aid treatment decisions for patients. Co culture models can be used to study the mechanism through which OvCa metastasizes, as well as potentially help identify certain biomarkers associated with OvCa. This has the potential to facilitate early detection of OvCa, as well as increase treatment possibilities for patients who may not have favorable reactions to current treatments. Ultimately, using co culture models can result in a greater understanding of OvCa pathophysiology while improving medical treatment for OvCa cancer patients.
Location
University of the Pacific, 3601 Pacific Ave., Stockton, CA 95211
Start Date
24-4-2021 1:00 PM
End Date
24-4-2021 2:15 PM
Using 3D co culture models to study Ovarian cancer metastasis and pathophysiology
University of the Pacific, 3601 Pacific Ave., Stockton, CA 95211
Ovarian cancer (OvCa) is the second most common gynecologic malignancy, although it is currently taking more lives compared to any other form of cancer infiltrating the reproductive system. Most patients are diagnosed at late stages due to the rapid metastasis of OvCa tumors and the lack of understanding regarding the complete pathophysiology of OvCa. Current medical care focuses on cytoreduction, followed by platinum and taxane-based chemotherapy, which takes an aggressive toll on patients. These extreme medical lengths do not guarantee a cure for OvCa patients, considering about 70% of them relapse, and this period up to relapse varies between a few months to up to five years, hence the unpredictability of OvCa (Ushijima 2009).
Three dimensional co culture models have become more prevalent over the past decade for in vitro disease modeling, and current research highlights certain useful properties of these models that can be applied to OvCa metastasis modeling. Co culture models can provide insight into biological responses of tumors, including drug resistance, cell-to-cell interactions, and metastasis (Gencoglu 2018). Using a co culture model to study the pathophysiology of OvCa requires mimicking the tumor’s microenvironment using natural biomaterials and OvCa cell lines. This implementation sets the stage for an increased reliability on three dimensional modeling, which can be ultimately translated into computer based models and simulations used to aid treatment decisions for patients. Co culture models can be used to study the mechanism through which OvCa metastasizes, as well as potentially help identify certain biomarkers associated with OvCa. This has the potential to facilitate early detection of OvCa, as well as increase treatment possibilities for patients who may not have favorable reactions to current treatments. Ultimately, using co culture models can result in a greater understanding of OvCa pathophysiology while improving medical treatment for OvCa cancer patients.