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

项目总结 肿瘤的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。 在癌细胞周围形成。从针对TME成分的药物可能产生的主要影响可以明显看出这一点 癌症，包括免疫检查点阻断(ICB)。尽管有相对较好的理解 调控癌细胞内在过程的关键基因，如细胞周期，目前还知之甚少 控制保护癌细胞免受免疫和帮助生长的外部环境。 这个项目的目标是确定控制肿瘤成分和促进肿瘤发生的基因。 生长和对免疫和免疫疗法的抵抗力，目的是确定可以 有针对性地增强肿瘤免疫力，改善癌症治疗。最重要的假设是， 形成这种U01的基本原理是，恶性细胞开启或关闭基因，包括内在操作基因， 通过突变和选择性的基因表达，这些外在的作用可以招募、定位和极化免疫和 基质细胞进入一种颠覆免疫并促进肿瘤生长的状态1，2。为了达到我们的目标，我们将 采用首创的空间功能基因组学平台，称为扰动地图，它允许广泛的 肿瘤中数十个单基因或多基因扰动的单细胞分辨率和表型分析 保留了空间建筑。带有扰动MAP、CRISPR基因敲除(KO)或基因过表达(OE) 屏幕通过多路成像和空间转录学(ST)进行解析，这允许对整个班级进行研究 基因(如分泌因子)和表型(如TME组成)在现有筛查中不可行。 我们将使用扰动图谱来确定100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)对免疫治疗和其他治疗的抵抗力。广度 对每个基因的深度分析将以以前不可能实现的规模和效率实现。我们将专注于 通过分析TCGA、ICB处理的队列、单细胞组学和 其他患者数据，包括：实体肿瘤中常见的突变癌症基因(目标1)，与 对ICB免疫治疗的抵抗或反应(目标2)，以及癌细胞衍生的配体和分泌分子 (目标3)。研究将在免疫活性的原位非小细胞肺癌模型中进行， 高级别浆液性卵巢癌、胰腺癌和口腔鳞癌。 研究结果将确定100个基因在许多对癌症畅通至关重要的过程中的作用 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，他们将产生对 有助于改善和个性化的侵袭性肿瘤行为和治疗阻力的机制 选择治疗方法，并推动立即采取下一步措施，开发新的治疗策略。

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.