Spatial functional genomics to identify regulators of the tumor microenvironment and cancer immunity

空间功能基因组学识别肿瘤微环境和癌症免疫的调节因子

• 批准号: 10720979
• 负责人: Brian D Brown
• 金额: $ 103.23万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-19 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10720979
• 关键词: Affect; Antibodies; Architecture; CD8-Positive T-Lymphocytes; CRISPR screen; Cancer Biology; Candidate Disease Gene; Categories; Cell Communication; Cell Cycle; Cell Death; Cell Fraction; Cell membrane; Cells; Clustered Regularly Interspaced Short Palindromic Repeats; Collagen; Collection; Complementary DNA; Computer Analysis; Data; Development; Drug Targeting; Environment; Fibroblasts; Gene Expression; Genes; Genomics; Goals; Growth; Head Cancer; Immune; Immunity; Immunocompetent; Immunologic Surveillance; Immunotherapy; In Situ; Infiltration; Invaded; Knock-out; Knowledge; Ligands; Machine Learning; Macrophage; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of ovary; Malignant neoplasm of pancreas; Maps; Measures; Mediating; Modeling; Morphology; Mutate; Mutation; Neck Cancer; Neoplasm Metastasis; Non-Small-Cell Lung Carcinoma; Oncogenes; Outcome Study; Ovarian Serous Adenocarcinoma; Pancreatic Adenocarcinoma; Pancreatic Ductal Adenocarcinoma; Patients; Pharmaceutical Preparations; Phenotype; Positioning Attribute; Process; Publishing; Resistance; Resolution; Role; Selection for Treatments; Serous; Solid Neoplasm; T cell therapy; Testing; The Cancer Genome Atlas; Tumor Biology; Tumor Immunity; Tumor-Associated Process; antiangiogenesis therapy; cancer cell; cancer imaging; cancer therapy; candidate identification; cell stroma; chemokine; cohort; cytokine; extracellular; fitness; functional genomics; gene function; genomic platform; immune checkpoint blockade; immunosuppressed; improved; in vivo; innovation; insight; malignant breast neoplasm; mouse model; mouth squamous cell carcinoma; multiplexed imaging; novel therapeutic intervention; overexpression; personalized medicine; predicting response; preservation; recruit; refractory cancer; response; therapy resistant; transcriptomics; treatment response; tumor; tumor behavior; tumor growth; tumor microenvironment

PROJECT SUMMARY Tumor growth and response to therapy, particularly immunotherapy, are all highly dependent on the tumor microenvironment (TME): the collection of cells and extracellular factors (cytokines, chemokines, collagens, etc.) that form around cancer cells. This is evident from the major impact drugs targeting TME components can have on cancers, including immune checkpoint blockade (ICB). Though there is a relatively good understanding of key genes regulating cancer cell intrinsic processes, such as cell cycle, there is less known about genes controlling the extrinsic environment that protects cancer cells from immunity and aids growth. The objective of this project is to determine the genes controlling tumor composition and facilitating tumor growth and resistance to immunity & immunotherapy, with the goal of identifying vulnerability factors that can be targeted to enhance tumor immunity and improve cancer treatment. The overarching hypothesis, which forms the rationale for this U01, is that malignant cells turn on or off genes, including intrinsically operating genes, through mutations and selective gene expression, that act extrinsically to recruit, position, & polarize immune & stroma cells into a state that subverts immunity & facilitates tumor growth1, 2. To reach our objective, we will employ a first-of-its-kind spatial functional genomics platform, called Perturb-map, which permits extensive phenotypic analysis of dozens of single or multiple gene perturbations in a tumor at single cell resolution and with spatial architecture preserved. With Perturb-map, CRISPR knockout (KO) or cDNA overexpression (OE) screens are resolved by multiplex imaging & spatial transcriptomics (ST), and this allows study of entire classes of genes (e.g. secreted factors) and phenotypes (e.g. TME composition) not feasible with existing screens. We will use Perturb-map to determine the role of 100s of genes in controlling many critical tumor processes, including tumor: (i) growth, (ii) morphology, (iii) metastasis, (iv) cell-cell interactions, (v) subclonal interactions, (vi) immune/stroma recruitment & polarization, (vii) resistance to immunotherapy & other treatments. The breadth & depth of analysis of each gene will be achieved at a scale and efficiency not previously feasible. We will focus on 3 broad categories of genes, identified through analysis of TCGA, ICB-treated cohorts, single cell-omics, and other patient data, including: commonly mutated cancer genes in solid tumors (Aim 1), genes correlating with resistance or response to ICB immunotherapy (Aim 2), and cancer cell-derived ligands and secreted molecules (Aim 3). Studies will be carried out in immunocompetent, orthotopic models of non-small cell lung carcinoma, high grade serous ovarian carcinoma, pancreatic adenocarcinoma, and oral squamous cell carcinoma. The study outcome will determine the roles of 100s of genes in many processes critical to unimpeded cancer growth, including identifying genes shielding cancers from immunity. In doing so, they will generate insights into mechanisms of aggressive tumor behavior and treatment resistance that will help to improve and personalize treatment selection and drive the immediate next steps towards the development of novel therapeutic strategies.

项目摘要 肿瘤生长和对治疗的反应，特别是免疫治疗，都高度依赖于肿瘤。 微环境（TME）：细胞和细胞外因子（细胞因子、趋化因子、胶原蛋白等）的集合。 癌细胞周围形成的这从靶向TME组分的药物可能产生的主要影响中可以看出 包括免疫检查点阻断（ICB）。尽管人们对 调节癌细胞内在过程的关键基因，如细胞周期，对基因的了解较少 控制外部环境，保护癌细胞免受免疫和艾滋病的增长。 本项目的目的是确定控制肿瘤成分和促进肿瘤发生的基因。 生长和抵抗免疫和免疫疗法，目的是确定脆弱性因素， 靶向增强肿瘤免疫力，改善癌症治疗。最重要的假设， 形成了这个U 01的基本原理，是恶性细胞打开或关闭基因，包括内在操作基因， 通过突变和选择性的基因表达，这些基因在招募、定位、免疫和 基质细胞进入破坏免疫和促进肿瘤生长的状态1，2。为了达到我们的目标，我们将 采用了第一个空间功能基因组学平台，称为扰动图，它允许广泛的 在单细胞分辨率下对肿瘤中的数十个单个或多个基因扰动进行表型分析， 空间结构得以保留。使用Perturb-map、CRISPR敲除（KO）或cDNA过表达（OE） 多重成像和空间转录组学（ST）可以解决屏幕，这使得整个类的研究成为可能 基因（例如分泌因子）和表型（例如TME组成）的筛选在现有筛选中不可行。 我们将使用微扰图来确定100多个基因在控制许多关键肿瘤过程中的作用， 包括肿瘤：（i）生长，（ii）形态，（iii）转移，（iv）细胞-细胞相互作用，（v）亚克隆相互作用， (vi)免疫/基质募集和极化，（vii）对免疫疗法和其他治疗的抗性。广度 对每个基因的分析深度将以以前不可行的规模和效率实现。我们将重点 3大类基因，通过TCGA分析，ICB治疗组，单细胞组学， 其他患者数据，包括：实体瘤中常见的突变癌症基因（Aim 1），与 对ICB免疫疗法的抗性或应答（Aim 2），以及癌细胞衍生的配体和分泌的分子 (Aim 3）。研究将在非小细胞肺癌的免疫活性原位模型中进行， 高级别浆液性卵巢癌、胰腺癌和口腔鳞状细胞癌。 研究结果将确定100多个基因在对癌症畅通至关重要的许多过程中的作用 生长，包括识别保护癌症免受免疫的基因。在这样做的过程中，他们将深入了解 侵袭性肿瘤行为和治疗抗性的机制，这将有助于改善和个性化 治疗选择，并推动下一步的新的治疗策略的发展。