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Get Free Access340 Background: Prostate cancer is frequently cured with high-dose rate brachytherapy as a front-line treatment. However, a significant number unfortunately develop intrinsic resistance. Although considered to be an immune-excluded tissue, immune responses are implicated in driving tumour-eradication in prostate cancer. This has not been proven, and yet is used as the rationale for numerous clinical trials combining radiation and immunotherapies. We hypothesise that there is a predictable but differential relationship between radiation and the immune responses in prostate cancer that could be used to fulfil a clinical need - identifying patients that would benefit from immune intervention in conjunction with radiation. Methods: We present here the results of comprehensive immunological profiling of a cohort of world-unique pre- and post-radiation tissues from 24 patients (RadBank cohort). These were assessed using pathological classification, tissue segmentation (cancer/surrounding stroma), multiplex IHC, gene expression profiling, T-cell receptor sequencing, and spatial computational analysis. Results: Our data resolved three classes of prostate cancer tissue based on immune infiltrate level, immune-activation and -checkpoint gene signatures, spatial clustering and T cell clone sequencing: We have begun to resolve clear patient and clinical classifiers based on immune responses to radiation, and identified patients groups likely to benefit from immune therapy alongside radiation. Conclusions: Importantly, these classifications are associated with baseline gene expression profiles that may be used for pre-clinical stratification and more sophisticated treatment paradigms.
Scott Williams, Simon P. Keam, Heloise M. Halse, Thu Quynh Nguyen, Catherine Mitchell, Franco Caramia, David J. Byrne, Sue Haupt, Georgina L. Ryland, Phillip K. Darcy, Shahneen Sandhu, Piers Blombery, Ygal Haupt, Paul J. Neeson (2020). Predicting radiation-induced immune trafficking and activation in localized prostate cancer.. , 38(6_suppl), DOI: https://doi.org/10.1200/jco.2020.38.6_suppl.340.
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Type
Article
Year
2020
Authors
14
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1200/jco.2020.38.6_suppl.340
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