Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA; Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA.
Eur Urol. 2024 Nov;86(5):434-444. doi: 10.1016/j.eururo.2024.05.026. Epub 2024 Aug 17.
Predicting response to therapy for each patient's tumor is critical to improving long-term outcomes for muscle-invasive bladder cancer. This study aims to establish ex vivo bladder cancer patient-derived organoid (PDO) models that are representative of patients' tumors and determine the potential efficacy of standard of care and curated experimental therapies.
Tumor material was collected prospectively from consented bladder cancer patients to generate short-term PDO models, which were screened against a panel of clinically relevant drugs in ex vivo three-dimensional culture. Multiomic profiling was utilized to validate the PDO models, establish the molecular characteristics of each tumor, and identify potential biomarkers of drug response. Gene expression (GEX) patterns between paired primary tissue and PDO samples were assessed using Spearman's rank correlation coefficients. Molecular correlates of therapy response were identified using Pearson correlation coefficients and Kruskal-Wallis tests with Dunn's post hoc pairwise comparison testing.
A total of 106 tumors were collected from 97 patients, with 65 samples yielding sufficient material for complete multiomic molecular characterization and PDO screening with six to 32 drugs/combinations. Short-term PDOs faithfully represent the tumor molecular characteristics, maintain diverse cell types, and avoid shifts in GEX-based subtyping that accompany long-term PDO cultures. Utilizing an integrative approach, novel correlations between ex vivo drug responses and genomic alterations, GEX, and protein expression were identified, including a multiomic signature of gemcitabine response. The positive predictive value of ex vivo drug responses and the novel multiomic gemcitabine response signature need to be validated in future studies.
Short-term PDO cultures retain the molecular characteristics of tumor tissue and avoid shifts in expression-based subtyping that have plagued long-term cultures. Integration of multiomic profiling and ex vivo drug screening data identifies potential predictive biomarkers, including a novel signature of gemcitabine response.
Better models are needed to predict patient response to therapy in bladder cancer. We developed a platform that uses short-term culture to best mimic each patient's tumor and assess potential sensitivity to therapeutics.
预测每位患者肿瘤的治疗反应对于提高肌层浸润性膀胱癌的长期预后至关重要。本研究旨在建立能够代表患者肿瘤的离体膀胱癌患者来源类器官(PDO)模型,并确定标准治疗和精选实验性治疗的潜在疗效。
前瞻性地从同意的膀胱癌患者收集肿瘤组织以生成短期 PDO 模型,并在离体三维培养中对其进行临床相关药物的筛选。多组学分析用于验证 PDO 模型,确定每个肿瘤的分子特征,并确定潜在的药物反应生物标志物。使用 Spearman 等级相关系数评估配对的原发组织和 PDO 样本之间的基因表达(GEX)模式。使用 Pearson 相关系数和 Kruskal-Wallis 检验识别与治疗反应相关的分子,并使用 Dunn 事后两两比较检验进行比较。
从 97 名患者中收集了 106 个肿瘤,其中 65 个样本提供了足够的材料用于进行全面的多组学分子特征分析和 PDO 筛选,涉及 6 到 32 种药物/组合。短期 PDO 能够忠实反映肿瘤的分子特征,保留多种细胞类型,并避免与长期 PDO 培养相关的 GEX 为基础的亚分型转变。利用综合方法,确定了体外药物反应与基因组改变、GEX 和蛋白质表达之间的新相关性,包括吉西他滨反应的多组学特征。需要在未来的研究中验证体外药物反应的阳性预测值和新的多组学吉西他滨反应特征。
短期 PDO 培养保留了肿瘤组织的分子特征,并避免了长期培养中以表达为基础的亚分型转变。多组学分析和体外药物筛选数据的整合确定了潜在的预测生物标志物,包括吉西他滨反应的新特征。
膀胱癌需要更好的模型来预测患者对治疗的反应。我们开发了一种平台,使用短期培养来最好地模拟每位患者的肿瘤,并评估对治疗的潜在敏感性。