Assessing the tumour microenvironment and treatment response in endometrial cancer patient derived explants

About the Project

Project:

Endometrial cancer is the most common gynaecological malignancy in many countries and although it is typically associated with a good long-term outcome the prognosis of metastatic endometrial cancer (EC) is very poor. The complete response rate of advanced/recurrent EC to the current standard of care chemotherapy (carboplatin/paclitaxel) is low, and there are limited new therapies successfully approved for EC. A reason for this is that current pre-clinical studies fail to replicate intra-tumour genetic and microenvironmental heterogeneity and tumour-stromal interactions, therefore are not predictive of patient outcomes. We have developed of a novel Endometrial Cancer patient derived explant (PDE) platform which maintains viability across both tumour and stroma for up to 48 hours in culture across all subtypes of endometrial cancer and have reported evidence of differential drug response following culture with cytotoxic agents to provide proof of concept for use of this platform for drug response studies1. This PDE model truly captures tumour heterogeneity and preserves a personalised tumour microenvironment reflective of in-vivo conditions therefore representing a powerful platform for pre-clinical modelling, drug response studies and personalized medicine in endometrial cancer2.

This project will explore changes in thetumour microenvironment, includingimmune landscape, of endometrial cancer (EC) in response to treatment. This will involve analysis of patient derived explants from patients with different EC histological subtypes that have undergone treatment with standard of care chemotherapy and immunotherapy aiming to identify mechanisms of drug resistance and molecular markers of response.

Training Opportunities:

The studentship offers training in state-of-the-art patient derived cancer explant technology based out the Explant Facility. Training will also be provided for histology, immunohistochemistry, multiplexed immunofluorescence, digital pathology, AI driven image analysis, bioinformatics and statistics.

Outputs:

Conference presentations, posters, publications.

Apply at:

https://le.ac.uk/study/research-degrees/research-subjects/cancer-studies

PhD entry requirements:https://le.ac.uk/study/research-degrees/entry-reqs

Supervisor contact details:

Dr Esther Moss, em321@le.ac.uk

Dr Gareth Miles, gjm14@leicester.ac.uk

References

1. Collins A, Miles GJ, Powley IR, et al. Development of a patient-derived explant model for prediction of drug responses in endometrial cancer. Gynecol Oncol. Feb 2021;160(2):557-567. doi:10.1016/j.ygyno.2020.11.033

2. Collins A, Miles GJ, Wood J, MacFarlane M, Pritchard C, Moss E. Patient-derived explants, xenografts and organoids: 3-dimensional patient-relevant pre-clinical models in endometrial cancer. Gynecol Oncol. Jan 2020;156(1):251-259. doi:10.1016/j.ygyno.2019.11.020