Integrating targeted and immunotherapy to treat genetically heterogeneous cancers

整合靶向治疗和免疫治疗来治疗遗传异质性癌症

• 批准号: 9767561
• 负责人: ALLAN BALMAIN
• 金额: $ 98.01万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-17 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9767561
• 关键词: Address; Advanced Malignant Neoplasm; Antibodies; Antigen Presentation; Antigens; Antineoplastic Agents; CRISPR screen; Cancer Model; Candidate Disease Gene; Categories; Cells; Clinical; Clinical Trials; Collection; Competence; DNA Damage; Databases; Diagnostic; Disease; Drug Combinations; Drug Targeting; Effector Cell; Gene Expression; Genes; Genetic; Goals; Grant; Human; Immune; Immune response; Immune system; Immunologics; Immunooncology; Immunophenotyping; Immunotherapy; Infiltration; Laboratories; Lead; Malignant Neoplasms; Measures; Metabolic stress; Modeling; Mus; Mutation; Myeloid Cells; Network-based; Neuroblastoma; Pathway Analysis; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacology; Phase; Point Mutation; Predisposition; Proteomics; Reagent; Squamous cell carcinoma; T cell response; T-Cell Activation; T-Lymphocyte; Testing; Tumor Cell Line; Tumor-infiltrating immune cells; cancer immunotherapy; cancer therapy; data mining; druggable target; high throughput screening; immune checkpoint blockade; immunoregulation; improved; inhibitor/antagonist; innovation; monocyte; mouse model; neoplastic cell; novel; pre-clinical; response; screening; small molecule; transcriptome sequencing; treatment response; tumor; tumor microenvironment

Identification of cancer drug targets using high throughput screens of tumor cell lines has led to a number of agents presently in clinical trials. In addition, recent advances in drugs that attack immune cells within tumors, such as αCTLA4 and αPD-1, have highlighted the importance of immune modulation as a strategy for cancer therapy. The next phase of cancer drug target discovery will seek to integrate these strategies to identify combinations of drugs that most efficiently target both tumor cells and the immune components in advanced cancers. The goal of this proposal is to identify and validate these combinations using large-scale data mining and mouse pre-clinical cancer models that mimic the major genetic features of human cancer. This proposal addresses both mechanisms of immune escape by a) finding genetic targets that may enhance tumor mutation load, and b) carrying out high throughout screens in T cells or myeloid cells for targets that promote immune cell infiltration. We will exploit unique mouse models that mirror major genetic categories of human cancer – high vs low mutation load, and strong vs weak immune infiltrate. Applying single-cell RNAseq and mass cytometric proteomic analyses, cutting edge immune composition databases and novel computational network approaches to cancer target discovery using existing large databases, we propose to identify vulnerabilities addressed by combining small molecule drugs with immunotherapy. We will make immunologically “cold” tumors, that do not engage the immune system, into “hot” tumors that present more or stronger antigens, or that encourage infiltration by immune effector cells. To achieve this goal, we propose three highly innovative aims centered on perturbation of specific targets: first by a CRISP/Cas9 screen in immune cells of the tumor microenvironment, second through increasing antigen load in tumors to optimize immune recognition and finally through a network-based identification of tumor-expressed targets that may confer susceptibility to existing immune-oncology therapies. This represents a true `network' of our collective expertise as well as a measured collection of candidate and screening approaches. AIM 1 –We will perform CRISPR screens in monocytes and T-cells to identify genes associated with tumor entry and function in two distinct tumor types. AIM 2– We will use genetic or pharmacological perturbation of newly generated candidate genes involved in metabolic stress and ROS-induced DNA damage to increase mutation load and antigen abundance in a tumor- specific manner, leading to improved responses to immunotherapy. AIM 3 – We will exploit gene expression networks to identify druggable targets and pathways that augment immune responses. This proposal identifies pathways and perturbants for accelerating immunotherapies.

使用肿瘤细胞系的高通量筛选来鉴定癌症药物靶点已经导致了许多癌症治疗的进展。 目前在临床试验中的药物。此外，攻击肿瘤内免疫细胞的药物的最新进展， 如α CTLA 4和αPD-1，强调了免疫调节作为癌症治疗策略的重要性。 疗法癌症药物靶点发现的下一阶段将寻求整合这些策略， 最有效地靶向肿瘤细胞和免疫成分的药物组合， 癌的本提案的目标是使用大规模数据挖掘来识别和验证这些组合 以及模拟人类癌症主要遗传特征的小鼠临床前癌症模型。这项建议 通过a）发现可能增强肿瘤突变的遗传靶点来解决免疫逃逸的两种机制 负载，和B）在T细胞或骨髓细胞中进行高通量筛选，以寻找促进免疫应答的靶， 细胞浸润我们将利用独特的小鼠模型，反映人类癌症的主要遗传类别- 高与低突变负荷，以及强与弱免疫浸润。应用单细胞RNAseq和mass 细胞计量蛋白质组学分析、尖端免疫组成数据库和新型计算网络 癌症目标发现的方法，使用现有的大型数据库，我们建议识别漏洞 通过将小分子药物与免疫疗法相结合来解决。我们将使免疫学上的“冷” 肿瘤，不参与免疫系统，成为“热”肿瘤，提出更多或更强的抗原，或 促进免疫效应细胞的浸润。为了实现这一目标，我们提出了三个高度创新的 目标集中在特定靶点的扰动：首先通过肿瘤免疫细胞中的CRISP/Cas9筛选 微环境，其次通过增加肿瘤中的抗原负荷来优化免疫识别， 最后，通过基于网络的肿瘤表达靶点的鉴定， 现有的免疫肿瘤疗法。这是我们集体专门知识的真正“网络”， 候选人和筛选方法的测量收集。 目的1 -我们将在单核细胞和T细胞中进行CRISPR筛选，以识别与肿瘤相关的基因 在两种不同的肿瘤类型中的进入和功能。 目的2-我们将使用新生成的候选基因的遗传或药理学干扰来参与 代谢应激和ROS诱导的DNA损伤增加肿瘤中的突变负荷和抗原丰度- 特异性方式，导致对免疫疗法的反应改善。 目的3 -我们将利用基因表达网络来确定可药用的目标和途径， 免疫反应。 该提案确定了加速免疫治疗的途径和干扰物。