Integrative molecular dissection of acquired resistance to PD1/PD-L1 blockade in localized and metastatic urothelial carcinoma

转移性尿路上皮癌(MUC)一般无法治愈，存活率不高 以顺铂为基础的一线化疗和铂后PD1/L1抑制剂治疗所提供的益处。最优 PD1/L1抑制剂治疗进展性MUC有必要用新的药物治疗 (enfortomab vedotin，erdafitinib)提供适度的增量益处和毒性。有限的数据 存在对PD1/L1抑制剂系统治疗后获得的肿瘤的分析，这是必要的，以确定 既有反应又有阻力的原因。事实上，对PD1/L1抑制剂后UC肿瘤的多平台分析 还没有报道过。这项研究的首要假设是肿瘤、免疫和间质 微环境因素决定对PD-1/L1治疗MUC的抵抗力，以及整合的整体 而对治疗后肿瘤的单细胞分子解剖将揭示这些特征。我们建议 创新且具有潜在变革性的多平台纵向获得的批量和/或单电池(Sc) 肌肉浸润性膀胱癌PD1/L1抑制剂治疗前后肿瘤组织及血浆分析 和MUC发表关于肿瘤生物学和耐药性的深刻见解，以及可用于 开发新的治疗方法。我们将对两个不同的队列进行详细的多平台分析，总计 170例患者：1)PD1/L1抑制剂暴露前后的肿瘤组织或未经处理的对照组 (n=130)和2)血浆无细胞(Cf)-DNA在PD1/L1抑制剂作用前后或未经处理 对照组(n=40)。全外显子组测序、RNA-SEQ和正交多参数IHC用于免疫 基线经尿道膀胱肿瘤电切术(TURBT)石蜡包埋标记物 包埋(FFPE)标本和治疗后肿瘤。纳入的患者来自评估一项 PD1/L1抑制剂(n=70)，作为MIBC的RC之前的新辅助治疗，或接受PD1/L1抑制剂治疗 MUC(n=50)和对照组未治疗和暂时分离的无介入治疗的FFPE系列瘤 10例。对PD1/L1后MUC肿瘤(n=20)的子集进行scRNAseq以分析肿瘤、间质和 免疫细胞。使用获得的质控血浆cfdna进行WES免疫基因组分析。 PD1/L1抑制剂治疗前后及未治疗对照组(n=40)。的功能相关性 通过检查功能免疫来研究特定的基因组变化和由此预测的新抗原 和基质读数，这将揭示关于基因组改变的免疫原性的见解，这些改变可以 然后为治疗进展提供基础。我们将开发一种新的集成模型，使用Depth 学习架构来解释分子肿瘤、间质和免疫的静止快照 配置文件，以及临床数据的基于时间的轨迹，以计算聚合不同的数据类型。 综上所述，这项创新的研究有望提供关于UC决定因素的发现 随着PD1/L1抑制剂的进展，这是一种具有大量未得到满足的需求的不治之症。

Project Summary/Abstract Metastatic urothelial carcinoma (mUC) is generally incurable with modest survival benefit provided by first-line cisplatin-based chemotherapy and post-platinum PD1/L1 inhibitor therapy. Optimal therapy for progressive mUC following PD1/L1 inhibitors is necessary with new agents for this setting (enfortumab vedotin, erdafitinib) providing modest incremental benefits coupled with toxicities. Limited data exist for analysis of tumor acquired after PD1/L1 inhibitor systemic therapy, which is necessary to determine causes of both response and resistance. Indeed, multiplatform analyses of post-PD1/L1 inhibitor UC tumor have not been reported. The overarching hypothesis of this study is that tumor, immune and stromal microenvironmental factors determine resistance to PD-1/L1 therapy mUC, and that integrated bulk and single cell molecular dissection of post-treatment tumors will reveal these features. We propose innovative and potentially transformative multiplatform longitudinally obtained bulk and/or single cell (sc) analysis of pre and post PD1/L1 inhibitor tumor tissue and plasma from muscle invasive bladder cancer (MIBC) and mUC to shed deep insights regarding tumor biology and resistance and information that can be used to develop new therapies. We will perform detailed multiplatform analyses on 2 separate cohorts totaling 170 patients: 1) tumor tissue obtained before and after PD1/L1 inhibitor exposure or untreated controls (n=130) and 2) plasma cell-free (cf)-DNA obtained before and after PD1/L1 inhibitor exposure or untreated controls (n=40). Whole exome sequencing (WES), RNA-Seq and orthogonal multiparametric IHC for immune markers is performed of baseline transurethral resection of bladder tumor (TURBT) formalin fixed paraffin embedded (FFPE) specimens and post-therapy tumors. Patients included are from trials that evaluated a PD1/L1 inhibitor (n=70) as neoadjuvant therapy preceding RC for MIBC, or who received a PD1/L1 inhibitor for mUC (n=50) and control untreated and temporally separated serial FFPE tumors without intervening therapy (n=10). scRNAseq is performed on a subset of post-PD1/L1 mUC tumors (n=20) to analyze tumor, stromal and immune cells. WES is performed for immunogenomic analyses using quality-controlled plasma cfDNA obtained before and after PD1/L1 inhibitor therapy or control untreated patients (n=40). The functional relevance of specific genomic alterations and resultant predicted neoantigens is studied by examining functional immune and stromal readouts, which will shed insights regarding the immunogenicity of genomic alterations that can then provide the foundation for therapeutic advances. We will develop a novel integrated model using deep learning architecture to account for the stationary snapshot of the molecular tumor, stromal and immune profiles, and the time-based trajectory of clinical data to computationally aggregate heterogeneous data types. To summarize, this innovative study is expected to provide discoveries regarding determinants of UC progression following PD1/L1 inhibitors, an incurable disease setting with substantial unmet needs.