(604f) Development of a Novel Synthetic Peptide Based 3D Model of Ovarian Cancer – Towards Structurally Customised in Vitro models

INTRODUCTION: Termed as the ‘silent killer’, epithelial ovarian cancer (EOC) earns its nickname due to its high mortality rate, with 5-year survival rates of only 46%, 46.5% and 38% in the UK, USA & Europe respectively (www.cancerresearchuk.org, www.ocrahope.org). EOC has the highest death rate amongst all gynaecological cancers worldwide [1]. This is primarily attributed to the asymptotic nature of the disease which leads to late diagnosis, the development of extensive chemotherapy resistant tumours, high recurrence rates along with the lack of a mechanistic understanding of the EOC pathogenesis and metastasis. The poor prognosis also increases its economic burden. According to recently published reports the economic burden of EOC in the USA is close to $5.8billion/year (www.progressreport.cancer.gov), while in the UK as per the NHS, it’s about £0.35 billion/year for EOC diagnosed at Stages III & IV. Hence, society, researchers and the clinical community are in dire need for a more in-depth study of the EOC microenvironment, to design better patient specific treatments and to advance current therapeutic methods. A proper mechanistic understanding of the EOC pathology and metastasis requires the development of a robust experimental model of EOC and its interaction with the surrounding microenvironment in vivo. Animal models and 2D in vitro models, which are widely used for such studies involve several limitations including the over simplistic nature of 2D models and the expensive, time consuming nature of animal models. Hence, recently, researchers have focussed on the development of 3D in vitro models of ovarian cancer in the form of spheroids or in hydrogels [2,3]. However, most of these models are of relatively short term viability (maximum 7 days) and lack the ability for growth surface customisation to mimic cancers of different stiffness.

The aim of our current work is to assess and develop a customised versatile 3D model of ovarian cancer based on synthetic peptide hydrogels and to assess the feasibility of the model for therapeutic assessment.

METHODS: Peptide based hydrogels (Manchester BioGel, UK) of different stiffness and charge were prepared as per the manufacturer’s instructions and seeded with A2780 ovarian cancer cell lines. The 3D cultures were maintained and monitored for an extended period of time (3- 4 weeks). Feasibility of using this model for assessment of chemotherapeutic agent (Cisplatin) was also carried out. Various in situ assays for monitoring the cell viability, spatial organisation and ECM production were performed. More specifically, immunofluorescent assays and subsequent imaging with CLSM and SEM were carried out at specific time points for all stiffness levels under consideration.

RESULTS: We have successfully established a synthetic hydrogel based 3D model of primary ovarian cancer. In situ analysis of cell growth, morphology and viability suggested that the stiffness and charge of the hydrogels affected the growth and morphology of ovarian cancer cells. Specific ECM proteins or peptide motives, i.e., collagen I, RGD were found to be beneficial for ovarian cancer cells. The hydrogel based long term model of ovarian cancer could also be used for assessment of chemotherapeutic treatment in vitro.

CONCLUSIONS: Our data show the feasibility of using custom designed synthetic pepti-gels for long term culture of EOC. The stiffness and charge of the hydrogel is shown to affect the cell growth and morphology. Our model can be used as a rapid tool for personalised treatment screening of ovarian cancer.

ACKNOWLEDGMENT: The project is supported financially by the 3DBioNet (UKRI). Further financial support has been received from the Department of Chemical and Process Engineering t - University of Surrey, an Impact Acceleration Grant (IAA-KN9149C) from University of Surrey, an IAA–EPSRC Grant (RN0281J) and the Royal Society. E.V. is thankful to the Royal Academy of Engineering for an industrial Fellowship.

REFERENCE:

[1] Ahmed, N. & Stenvers, K. Frontiers in oncology 3, 256 (2013).

[2] Avraham-Chakim, L. et al. PloS one 8, e60965 (2013).

[3] Yang, Z. & Zhao, X. International journal of nanomedicine 6, 303 (2011).