Project 3: Impact of tumor genetics on PDAC immunobiology and responses to macrophage-targeted immunotherapy

项目 3：肿瘤遗传学对 PDAC 免疫生物学的影响以及对巨噬细胞靶向免疫治疗的反应

• 批准号: 10704089
• 负责人: EDGAR G. ENGLEMAN
• 金额: $ 42.16万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10704089
• 关键词: Affect; Agonist; Antibodies; Antigen-Presenting Cells; Automobile Driving; Base Composition; Biological Assay; CDKN2A gene; Cell Line; Cells; Complement; DNA Sequence Alteration; Data; Development; Disease Progression; Duct (organ) structure; Ductal Epithelial Cell; Environment; Enzyme-Linked Immunosorbent Assay; Exhibits; Frequencies; Genetic; Genetically Engineered Mouse; Genomics; Genotype; Goals; Granulocyte-Macrophage Colony-Stimulating Factor; Growth; Human; Immune; Immune response; Immune system; Immunobiology; Immunologics; Immunotherapy; KRAS2 gene; Lesion; Ligands; MADH4 gene; Macrophage; Malignant Neoplasms; Malignant neoplasm of pancreas; Mediating; Methods; Modeling; Molecular; Mus; Mutation; Organism; Pancreatic Ductal Adenocarcinoma; Pancreatic duct; Pattern recognition receptor; Property; Quantitative Reverse Transcriptase PCR; Resistance; Role; Shapes; Signal Pathway; Specimen; System; T-Cell Activation; T-Lymphocyte; TP53 gene; Testing; Therapeutic; Transplantation; Treatment Efficacy; Tumor Promotion; Tumor-Derived; Tumor-associated macrophages; Tumor-infiltrating immune cells; Variant; Work; analytical tool; antitumor effect; cancer cell; cell type; cytokine; driver mutation; effective therapy; exome sequencing; high dimensionality; immune cell infiltrate; immune checkpoint blockade; immune function; immunoregulation; improved; molecular subtypes; mouse dectin-2; mouse model; mutational status; neoplastic cell; neutralizing antibody; pancreatic ductal adenocarcinoma model; patient population; pharmacologic; programs; receptor; recruit; response; single-cell RNA sequencing; targeted treatment; therapy resistant; transplant model; treatment response; tumor; tumor growth; tumor microenvironment

ABSTRACT (Project 3) Pancreatic ductal adenocarcinoma (PDAC), an aggressive malignancy that is poorly responsive to treatment, is characterized by a prominent infiltration of immune cells. In particular, macrophages are abundant within the tumor microenvironment (TME) in PDAC and contribute to disease progression and treatment resistance. However, the factors affecting the recruitment and distribution of immune cells, including macrophages, in PDAC remain largely unknown. Recently, our collaborators in Project 1 found that tumors differing in their Trp53 status exhibited different immune profiles. Our collaborators further observed that the cell type of origin (acinar or ductal) influenced the tumor molecular subtype (classical or basal-like), which is also known to be shaped by the immune composition of the tumor. We postulate that somatic alterations in cancer cells, the cell type of origin, and tumor molecular subtype influence the immune landscape within the TME and throughout the host during PDAC progression. To test this hypothesis, we will determine immune cell frequency, distribution, and function in the TME and throughout the host using high-dimensional analytical tools (CODEX and CyTOF) on genetically engineered mouse models (GEMMs) of PDAC that vary in their driver mutations and cell type of origin (developed by Project 1). Additionally, we will use molecular methods to identify immunomodulatory factors regulating immune cell recruitment in the context of different genetic mutations and cell type of origin, and we will use genetic, pharmacological, and neutralizing antibody-based approaches to confirm the functional effects of these factors in driving PDAC progression. Importantly, we will validate findings from these studies in human PDAC specimens and in cell lines derived from human pancreatic ductal cells. Finally, we recently found that the pattern recognition receptor, Dectin-2, is expressed on tumor- associated macrophages (TAMs) in an aggressive, transplantable model of PDAC. Notably, administration of natural Dectin-2 ligands induces sustained PDAC regression in a T-cell dependent manner by reprogramming immunosuppressive TAMs into immunostimulatory antigen-presenting cells (APCs). We hypothesize that PDAC can be effectively treated by reprogramming Dectin-2+ TAMs into immunostimulatory APCs. We will treat autochthonous tumors arising in the GEMMs developed by Project 1 with Dectin-2 ligands to test this hypothesis. Furthermore, to identify mechanisms by which Dectin-2 stimulation is therapeutically efficacious, we will use CODEX and CyTOF to observe changes to the immune landscape occurring within the TME and throughout the host upon treatment. Molecular approaches will be used to identify immunomodulatory factors responsible for mediating therapeutic efficacy. Together, these studies will improve our understanding of how the immune system is altered during PDAC development in the context of variation in genetic mutations, cell type of origin, and molecular subtype, and in response to TAM reprogramming.

摘要(项目3) 胰腺导管腺癌(PDAC)是一种对治疗反应不佳的侵袭性恶性肿瘤， 以免疫细胞的显著渗透为特征。特别是，巨噬细胞在脑内大量存在。 肿瘤微环境(TME)在PDAC，并有助于疾病的进展和治疗耐药。 然而，影响包括巨噬细胞在内的免疫细胞在体内招募和分布的因素 PDAC在很大程度上仍不为人所知。最近，我们在项目1中的合作者发现，肿瘤在他们的 TrP53状态表现出不同的免疫特征。我们的合作者进一步观察到起源的细胞类型 (腺泡或导管)影响肿瘤分子亚型(经典或基底样)，这也是已知的 由肿瘤的免疫成分决定。我们假设癌细胞的体细胞变化，即细胞 起源类型和肿瘤分子亚型影响TME内和整个TME的免疫格局 在PDAC进展过程中的宿主。为了验证这一假设，我们将确定免疫细胞频率， 使用高维分析工具(CODEX)在TME和整个宿主中的分布和功能 和CyTOF)在驱动突变不同的PDAC基因工程小鼠模型(GEMM)上 和来源的细胞类型(由项目1开发)。此外，我们将使用分子方法来鉴定 免疫调节因子在不同基因突变和不同背景下调节免疫细胞募集 细胞类型的起源，我们将使用基于遗传、药物和中和抗体的方法来 确认这些因素在推动PDAC进展中的功能作用。重要的是，我们将验证 这些研究在人PDAC标本和人胰腺导管来源的细胞系中的发现 细胞。最后，我们最近发现，模式识别受体Dectin-2在肿瘤上表达。 相关巨噬细胞(TAM)在侵袭性的，可移植的PDAC模型中。值得注意的是，管理 天然Dectin-2配体通过重编程诱导T细胞依赖的持续性PDAC回归 免疫抑制TAMs转化为免疫刺激性抗原提呈细胞(APC)。我们假设 通过将Dectin-2+TAMs重新编程为免疫刺激的APC，可以有效地治疗PDAC。我们会 用Dectin-2配体治疗由项目1开发的GEMM中出现的本土肿瘤以测试这一点 假设。此外，为了确定Dectin-2刺激具有治疗效果的机制， 我们将使用CODEX和CyTOF来观察TME内发生的免疫格局的变化 经治疗后遍及宿主。将使用分子方法来识别免疫调节因子 负责调停治疗效果。总而言之，这些研究将提高我们对 在PDAC发育过程中，免疫系统在遗传突变、细胞变异的背景下发生变化 起源类型，以及分子亚型，并响应的重新编程。