Establishing novel patient-like models of Ewing sarcoma to explore response to radiotherapy-drug combinations

Background: 40-50% of Ewing sarcoma patients progress on initial treatment or recur after primary treatment. Around 85% of patients have metastatic disease at recurrence and ≤15% of patients survive recurrent disease. There is a pressing need for new therapeutic approaches. Many targeted drugs have been trialled at relapse.

Most are ineffective.

Multi-targeted tyrosine kinase inhibitors (mTKIs) have shown better results than any other drugs so far, as single agents. Immunotherapy has also been investigated, with limited success.

Ewing sarcomas are immunologically “cold”; therefore activating effector T-cell responses is likely to improve anti-tumour immunity in these patients.

A rational way to achieve this is by combining radiotherapy (RT) with therapies that modulate immune contexture e.g. mTKIs.

In clinical practice, RT is frequently used at recurrence, and improving the efficacy of RT could yield significant impact on overall outcome.

We hypothesise: RT-mTKIs combination therapy is a rational new treatment for Ewing sarcoma that will synergistically modulate the immune contexture toward anti-tumour responses. To test this hypothesis we need appropriate pre-clinical models.

We have access to recently generated, fully annotated Ewing PDX cell lines, which remain faithful to original patient phenotype in xenografts. However, these PDX models have never been used to explore RT response.

Aims and methods: 1) Generate orthotopic (intra-femoral) PDX models of Ewing sarcoma and establish their responsiveness to radiotherapy 2) Explore novel drug-RT combinations in vitro, focussing on mTKIs 3) Evaluate the antigen landscape following drug-RT treatment, using immunopeptidomics Although PDX-orthotopic mouse models are gold standard to recapitulate therapeutic responses of patients, they come with a major caveat - you cannot evaluate adaptive immune responses, as the mice are immune-compromised.

Therefore, it is essential we employ a complementary approach to ascertain the potential effect of combinations on the adaptive immune system.

This can be achieved using immunopeptidomics, which allows us to interrogate the antigenic landscape of the tumour cells, from which T-cell responses can be predicted.

This approach has already been used successfully by the Oxford team to infer novel combinatorial treatment strategies with RT, highlighting the translational relevance of this approach.

How the results will be used: complementary data from Manchester and Oxford will generate the most patient-like models of Ewing sarcoma to date and provide a holistic picture of their tumour biology and immune landscape.

Using these patient-like models to evaluate drug-RT combinations significantly increases the likelihood our findings will translate to patients.