Dataset used to generate figures 2-6 in the manuscript titled: "Ex vivo drug screening and clustering of bladder cancers for pre-clinical treatment prediction."

This is the processed data used to generate the images in the paper titled "Ex vivo drug screening and clustering of bladder cancers for pre-clinical treatment prediction"It contains both drug screening data and genetic sequencing data from bladder cancer patients. The paper investigates drug sensitivity's or resistance to 15 anti cancer therapies directly on patient derived cell cultures. Sequencing data is in the for of MAF files and the drug screen is in CSV format.Figure 2Maf_Files.mafCancer Drivers_Updated July 2023.csvModified Z Score_columns.csvsample summary of mutationsTumour .csv characteristics_UPDATED 100523.csvFigure 3clusters of drug to annotate pheatmap.csvclusters of tumours to annotate pheatmap.csvFigure 3C - Tumour characteristics_UPDATED 100523.csvFigure 3C - Tumour characteristics_UPDATED 100523.csvFigure 4CIS RES group tumour clusters.csvCIS RES group tumour clusters.csvMatrix for heatmap_modified Z_updated for mTOR with Z SCORE_without inactive_CIS RES ONLY.csvTumour characteristics_UPDATED 100523_without LN.csvFigure 5Res EVP sample summary.csvres_cohort_variants.csvSens EVP sample summary.csvsens_cohort_variants.csvFigure 6Modified Z Score_columns.csvThe RAW data that support the findings of this study are available from the corresponding author upon reasonable request.Ethical Approval:South West - Frenchay Research Ethics Committee (REC): 20/SW/0193;South Yorkshire REC 10/H1310/73)AbstractBackgroundBladder cancer (BC) is the tenth most common cancer and ninth leading cause of cancer death worldwide. BC has high rates of treatment-failure, so alternate approaches are needed to personalise treatments to individual patients in order to improve outcomes from this disease. One method which could provide actionable results to influence clinical decisions on alternative treatments is Ex vivo drug screening.MethodologyWe explored the feasibility of using ex vivo drug screening directly on patient tumour tissue from transurethral resection of the bladder tumours (TURBT) and cystectomies. We screened 38 BC patients investigating drug sensitivities to 15 agents including standard of care treatments and some more exploratory compounds. In addition, we investigated ex vivo sensitivity and resistance over the 15 compounds and annotated common mutational profiles. We saw high methodological success (41/54 samples, 75.9%), in clinically useful timeframes (4 days), and identified distinct drug and tumour clusters.ResultsHere we show drug resistance was associated with aggressive clinical features, mutation burden and differed with individual gene mutations. Cross resistance between agents was common. Cisplatin-resistant tumours differed by mutational profiles and included those with multi-drug resistance and those sensitive to alternate agents. Observed clinical responses matched our ex vivo response (5/6 patients, 83.3%). Proliferative responses were observed to some receptor tyrosine kinase inhibitors, cautioning their un-selected widespread use.ConclusionsEx vivo drug screening identified drug clusters of patients’ tumours who could potentially respond to standard of care and alternative therapies. Our approach offers a platform to potentially individualise treatments, especially in drug-resistant tumours