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.

使用抗 PD-1/PD-L1 抗体进行免疫检查点抑制 (CPI) 改变了治疗方法 包括膀胱癌在内的多种癌症的景观。在晚期膀胱癌患者中， CPI 可以引发前所未有的持久反应。然而，只有一小部分患者对这种反应有反应 治疗需要更好地了解原发耐药机制，以促进 预测生物标志物的识别和合理的组合方法。我们采用了综合方法 在转移性膀胱癌患者的大型临床试验队列中鉴定生物标志物 除了肿瘤突变负荷（TMB）之外，与对 CPI 的反应/耐药独立相关。我们 确定了来自治疗前肿瘤转录组数据的三个关键基因模块：“良好的免疫” 与 CPI 反应相关的模块、与 CPI 抵抗相关的基质模块以及“坏”模块 免疫”模块也与抵抗 CPI 相关，但这似乎可以调节 CPI 的负面影响 基质模块根据 CPI 的结果。使用新鲜的单细胞 RNA 测序数据 膀胱癌标本来剖析负责的细胞成分和分子相互作用 通过对这 3 个基因模块的表达进行分析，我们确定“良好的免疫”模块主要来自 T- 细胞和 NK 细胞，基质模块源自癌症相关成纤维细胞 (CAF)，而“坏细胞” “免疫”模块主要源自单核细胞-巨噬细胞 (MΦ)。我们假设骨髓细胞 细胞驱动膀胱癌对 CP​​I 的初级抵抗。我们进一步假设综合细胞 膀胱癌的分子图谱将有助于精确识别单核细胞-MΦ亚群，以及 CAF-骨髓-T 细胞相互作用，可用于定义新的生物标志物和治疗靶点。 可以获得一组独特的临床试验队列，这些队列将提供肿瘤组织、血液和尿液 样本以及 CPI 结果数据，我们具有独特的定位：（目标 1）剖析基因模块 使用细胞和分子景观的高分辨率图与 CPI 的反应/抵抗相关 肌层浸润性膀胱癌；目标 2：定义“不良免疫”模块基因在调控中的作用 单核细胞-MΦ介导的免疫抑制；目标 3：精炼和验证单核细胞 MΦ 相关基因 签名作为临床试验队列中 CPI 抵抗的生物标志物。 该提案包括一个多学科协作研究人员的综合网络（GU 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 最大限度地提高未来的临床效益。这些努力将导致生物标志物的发现，以及潜在的 治疗目标，将 CPI 的益处扩大到 15-20% 的晚期膀胱癌患者 对治疗有反应。