Engineering high throughput screening platforms of cervical cancer

Abstract

Cervical cancer is the second leading cause of cancer‐related death in women under 40 and is one of the few cancers to have an increased incidence rate and decreased survival rate over the last 10 years. One in five patients will have recurrent and/or distant metastatic disease and these patients face a 5‐year survival rate of less than 17%. Thus, there is a pressing need to develop new anticancer therapeutics for this underserved patient population. However, the development of new anticancer drugs remains a challenge, as only 7% of novel anticancer drugs are approved for clinical use. To facilitate identification of novel and effective anticancer drugs for cervical cancer, we developed a multilayer multicellular platform of human cervical cancer cell lines and primary human microvascular endothelial cells that interfaces with high throughput drug screening methods to evaluate the anti‐metastatic and anti‐angiogenic drug efficacy simultaneously. Through the use of design of experiments statistical optimization, we identified the specific concentrations of collagen I, fibrinogen, fibronectin, GelMA, and PEGDA in each hydrogel layer that maximized both cervical cancer invasion and endothelial microvessel length. We then validated the optimized platform and assessed its viscoelastic properties. Finally, using this optimized platform, we conducted a targeted drug screen of four clinically relevant drugs on two cervical cancer cell lines. Overall, this work provides a valuable platform that can be used to screen large compound libraries for mechanistic studies, drug discovery, and precision oncology for cervical cancer patients.

Engineering a three-dimensional multilayer multicellular model of endometrial cancer for high throughput drug screening and novel treatment methods

“…We developed a unique multilayer multicellular model designed to replicate the complex Specifically, the bottom hydrogel layer was developed using a blend of Col I, fibrinogen, and synthetic polymers-GelMA or PEGDA. Echoing our previous findings, 19 we found that varying Col I and fibrinogen concentrations within the range of 0.5 to 2.5 mg/mL significantly influenced microvessel formation and cancer invasion. Specifically, 1.91 mg/mL Col I and 0.6 mg/mL fibrinogen maximized microvessel length and endometrial cancer invasion, demonstrating significant interactions with each other.…”

Development of a 3Din vitrohuman-sized model of cervical dysplasia to evaluate the delivery of ethyl cellulose-ethanol injection for the treatment of cervical dysplasia ablation

“…(28) However, the GelMA hydrogel has enough flexibility in its mechanical properties that allows the incorporation of more ECM components to approximate the human cervix better, a focus of future work. (20,29) We also showed that the GelMA-hydrogel model had high cell viability and promoted cell growth over 48 hours. GelMA has proven to have good transport of nutrients and oxygen that enables cell response over time.…”

“…In a prior study, we successfully demonstrated that using gelatin methacrylate (GelMA) as the main component in a 3D in vitro model allowed phenotypic cell responses that captured the histology of the tumor microenvironment. (20) Notably, GelMA at 8.7% w/v was observed to support cervical cancer progression. (20) Despite its success in modeling cervical cancer, our 3D model reflected characteristics of metastatic cancer and is therefore unsuitable for studying cervical dysplasia.…”

“…(20) Notably, GelMA at 8.7% w/v was observed to support cervical cancer progression. (20) Despite its success in modeling cervical cancer, our 3D model reflected characteristics of metastatic cancer and is therefore unsuitable for studying cervical dysplasia. Additionally, the model’s construction in a 96-well plate restricted its size, rendering it ill-suited for testing treatments such as the EC-ethanol injection.…”

Statistical optimization of hydrazone-crosslinked hyaluronic acid hydrogels for protein delivery

“…We and others have used DoE to predict responses of hydrogels and cells within hydrogels in systems with multiple input variables. 8,[11][12][13][14] This approach can be widely used in regenerative medicine applications such as scaffold design, cell culture optimization, and the development of in vitro model systems, accelerating the timeframe in which new platforms can be optimized. [15][16][17] In this study, we were specifically interested in tuning the properties of hyaluronic acid hydrogels formed via hydrazone crosslinking.…”