Work

41P Total tumor burden and radiomics to evaluate response in dose escalation studies: Roginolisib (IOA-244), a highly selective PI3Kδ inhibitor in metastatic uveal melanoma patients

Year: 2024

Type: article

Abstract: tumour types (melanoma, renal cell carcinoma, bladder cancer and triple-negative breast cancer), where predicting treatment outcomes and toxicities remains an unmet need.Results: We have access to longitudinal samples of >3,000 patients across 10 reported studies.Through partner NHS sites, we aim to prospectively collect and profile samples (blood, stool and tumour) from w3,000 patients over 3 years.A tiered approach will implement workflows for high-volume biomarker discovery (Tier 1).Indepth profiling (Tiers 2&3) will further characterize tumours using peripheral immune profiling including high-dimensional flow cytometry, liquid biopsy (cfDNA, immune methylation profiling), spatial tissue image-profiling and molecular profiling (WES, bulk&long-read RNAseq, TCR&BCRseq).For selected patients, we will apply Representative Sequencing (RepSeq), to overcome sampling bias in solid tumours and conduct drug-sensitivity screening through patient-derived tumour fragments.Conclusions: Machine learning will be applied to derive uni-and multi-modal biomarkers of response and toxicity, and the master databases will be available for ongoing academic and industry research.

Source: Immuno-Oncology Technology

DOI: 10.1016/j.iotech.2024.101001