Dissecting myeloid cell-mediated resistance to immune checkpoint blockade in bladder cancer

剖析膀胱癌中骨髓细胞介导的免疫检查点阻断抵抗

• 批准号: 10380068
• 负责人: Nina Bhardwaj
• 金额: $ 68.93万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10380068
• 关键词: Atlases; Automobile Driving; Binding; Biological Markers; Biometry; Bladder Neoplasm; Blood; Cell Communication; Cells; Clinical; Clinical Trials; Computational Biology; Coupled; Data; Event; Fibroblasts; Future; Genes; Genomics; Goals; Immune; Immunologist; Immunology; Immunosuppression; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Maps; Mediating; Medical Oncology; Modeling; Molecular; Mutation; Myelogenous; Myeloid Cells; Natural Killer Cells; Oncologist; Outcome; Patients; Population; Positioning Attribute; Research Personnel; Resistance; Resolution; Resources; Role; Specimen; T-Lymphocyte; Translational Research; Tumor Tissue; Urine; Urologist; Urology; anti-PD-1/PD-L1; anti-PD-L1 antibodies; biomarker discovery; cancer type; checkpoint inhibition; clinically relevant; cohort; experience; genetic signature; immune checkpoint blockade; macrophage; monocyte; multidisciplinary; muscle invasive bladder cancer; new therapeutic target; novel marker; patient subsets; predictive marker; response; single-cell RNA sequencing; therapeutic target; transcriptomics; tumor

Immune checkpoint inhibition (CPI) with anti-PD-1/PD-L1 antibodies has changed the treatment landscape for several types of cancers including bladder cancer. In patients with advanced bladder cancer, CPI can induce unprecedented durable responses. However, only a subset of patients responds to such treatment necessitating a better understanding of mechanisms of primary resistance to facilitate the identification of predictive biomarkers and rational combination approaches. We used an integrative approach to identify biomarkers in a large clinical trial cohort of patients with metastatic bladder cancer that are independently associated with response/resistance to CPI beyond tumor mutational burden (TMB) alone. We identified three key gene modules derived from pre-treatment tumor transcriptomic data: a “good immune” module associated with response to CPI, a stromal module associated with resistance to CPI, and a “bad immune” module also associated with resistance to CPI, but that appears to mediate the negative impact of the stromal module upon outcomes with CPI. Using single cell RNA sequencing data generated from fresh bladder cancer specimens to dissect the cellular components and molecular interactions responsible for expression of these 3 gene modules, we determined that the “good immune” module emanates largely from T- cells and NK cells, the stromal module emanates from cancer-associated fibroblasts (CAFs), and the “bad immune” module emanates predominantly from monocytes-macrophages (MΦ). We hypothesize that myeloid cells drive primary resistance to CPI in bladder cancer. We further hypothesize that comprehensive cellular and molecular maps of bladder cancer will facilitate identification of precise monocyte-MΦ subpopulations, and CAF-myeloid-T-cell interactions, that can be leveraged to define novel biomarkers and therapeutic targets. With access to a unique set of clinical trial cohorts that will provide tumor tissue, blood and urine specimens as well as outcome data to CPI, we are uniquely positioned to: (Aim 1) Dissect gene modules associated with response/resistance to CPI using high resolution maps of the cellular and molecular landscape of muscle-invasive bladder cancer; Aim 2: Define the role of “bad immune” module genes in governing monocyte-MΦ-mediated immune suppression; Aim 3: Refine and validate a monocyte-MΦ-related gene signature as a biomarker of CPI resistance in clinical trial cohorts. This proposal comprises an integrated network of multi-disciplinary collaborative investigators (GU oncologists, urologists, immunologists and bioinformaticians) to accelerate translational research and maximize future clinical benefits. These efforts will lead to the discovery of biomarkers, and potential therapeutic targets, to extend the benefits of CPI beyond the 15-20% of patients with advanced bladder cancer that respond to treatment.

具有抗PD-1/PD-L1抗体的免疫检查点抑制（CPI）已改变了处理 包括膀胱癌在内的几种类型的癌症的景观。在晚期膀胱癌的患者中 CPI可以诱导前所未有的耐用响应。但是，只有一部分患者对此做出反应 理解对主要抵抗机制的更好理解以促进的必要治疗 预测生物标志物和理性组合方法的识别。我们使用了综合方法 在大型临床试验中鉴定生物标志物，由转移性膀胱癌患者组成 仅与肿瘤突变伯嫩（TMB）之外的CPI反应/抗性独立相关。我们 鉴定出从预处理肿瘤转录组数据中得出的三个关键基因模块：一种“良好的免疫” 与对CPI的响应相关的模块，CPI是与CPI抗性相关的基质模块，并且“不良 免疫”模块也与对CPI的抗性有关，但这似乎介导 CPI结果的基质模块。使用新鲜产生的单细胞RNA测序数据 膀胱癌标本剖析细胞成分和负责的分子相互作用 这3个基因模块的表达，我们确定“良好的免疫”模块在很大程度上源自T- 细胞和NK细胞，基质模块是由癌症相关的成纤维细胞（CAF）和“不良的 免疫”模块主要来自单核细胞巨噬细胞（Mφ）。我们假设髓样 细胞在膀胱癌中对CPI的主要耐药性。我们进一步假设该全面的细胞 膀胱癌的分子图将促进精确单核细胞亚群的鉴定，并有助于鉴定 CAF-乳细胞T细胞相互作用，可以利用以定义新型的生物标志物和治疗靶标。 可以使用一组独特的临床试验队列，这些临床试验队列将提供肿瘤组织，血液和尿液 标本以及对CPI的结果数据，我们唯一地定位于：（AIM 1）剖析基因模块 使用细胞和分子景观的高分辨率图与对CPI的响应/抗性有关 肌肉侵入性膀胱癌；目标2：定义“不良免疫”模块基因在管理中的作用 单核细胞M介导的免疫抑制； AIM 3：完善并验证单核细胞Mφ相关基因 签名作为临床试验队列中CPI抗性的生物标志物。 该提案包括一个综合的多学科合作调查员（GU）网络 肿瘤学家，泌尿科医生，免疫学家和生物信息学家加速转化研究和 最大化未来的临床益处。这些努力将导致发现生物标志物和潜力 治疗靶标，以将CPI的益处扩大到15-20％的晚期膀胱癌患者之外 对治疗的反应。