Spatially resolved, single cell biomarkers of B cell lymphoma

B 细胞淋巴瘤的空间分辨单细胞生物标志物

• 批准号: 10522993
• 负责人: Akil Merchant
• 金额: $ 61.62万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10522993
• 关键词: Address; Adoption; Adult; Algorithms; Archives; B-Cell Lymphomas; B-Lymphocytes; Biological Markers; Biological Models; Cells; Chemoresistance; Childhood; Classification; Clinical; Cytometry; Development; Elements; Ensure; Gene Expression; Genetic; Goals; Histologic; Histology; Human; Human Herpesvirus 4; Image; Image Analysis; Immune; Immune Targeting; Immune checkpoint inhibitor; Immunohistochemistry; Immunophenotyping; Immunotherapy; In Vitro; International Prognostic Index; Link; Lymphoma; Malignant Neoplasms; Mediating; Methods; Modeling; Molecular; Molecular Profiling; Mus; Nature; Non-Hodgkin' s Lymphoma; Non-Malignant; Oncogenic; Outcome; PD-1/PD-L1; Pathologist; Patient-Focused Outcomes; Patients; Phenotype; Preclinical Testing; Prognostic Marker; Publishing; Research; Resistance; Resolution; Resources; Role; Sample Size; Sampling; Structure; Subgroup; Systems Biology; Testing; Tissues; Training; Tumor Markers; Validation; Work; base; cancer cell; cancer type; candidate marker; cohort; digital imaging; in vitro Model; in vivo Model; insight; large cell Diffuse non-Hodgkin' s lymphoma; next generation; novel; novel strategies; phenotypic biomarker; pre-clinical; predictive marker; prognostic; programmed cell death ligand 1; protein biomarkers; response; single cell analysis; standard care; survival prediction; targeted agent; targeted cancer therapy; targeted treatment; tumor; tumor growth; tumor-immune system interactions

Project Summary/Abstract Diffuse Large B-Cell Lymphoma (DLBCL) is the most common form of Non-Hodgkin Lymphoma (NHL). DLBCL tumors are highly heterogeneous and molecular profiling has revealed up to six distinct prognostically relevant sub-groups, however these classifications are primarily based on profiles of the malignant cells. Non-malignant cells in the tumor immune microenvironment (TME) can be powerful modulators of tumor growth and can be targeted for cancer therapy, yet biomarkers that include TME elements have not been developed. We hypothesize that successful development of next generation immune targeting therapies for lymphoma will require spatially resolved, highly multiplexed single cell based biomarkers of TME composition and structure. In this study we propose to perform imaging mass cytometry analysis (IMC) on over 2000 cases of aggressive B cell lymphoma with the following aims: Specific Aim 1: Validate spatially-derived protein biomarkers of DLBCL outcomes (n-830 patients). Specific Aim 2: Analyze the single cell topology of histologically diverse aggressive B cell lymphomas (n=1380) to identify shared TME based biomarkers across all aggressive B cell lymphoma. Specific Aim 3: Determine which TME elements modulate chemoresistance and mediate response to immune therapies in lymphoma through in vitro model systems. In the first two Aims, we will apply our novel abundance weighted score (M-score), developed specifically for IMC analysis, to validate candidate biomarkers (such as PD-L1+/CCR4+/TIM-3+) and identify new biomarkers. We will also apply our single cell spatial clustering algorithm, Regions of Immune Cell Organization (RICO), to identify tumor-immune spatial clusters that are associated with clinical outcome. The spatial resolved, single cell, highly multiplexed, digital image analysis proposed here will have clinical impact for the ~80,000 new US cases of NHL. Specific Aim 1 will validate and discover protein biomarkers in a image format familiar to pathologists allowing for seamless clinical adoption, Specific Aim 2 will refine methods for spatial systems biology applied to challenging lymphoma types, and Specific Aim 3 will allow pre-clinical validation of prognostic and predictive biomarkers.

项目总结/摘要 弥漫性大B细胞淋巴瘤（DLBCL）是非霍奇金淋巴瘤（NHL）最常见的形式。DLBCL 肿瘤是高度异质性的，并且分子谱分析已经揭示了多达六种不同的肿瘤相关性。 亚组，然而这些分类主要基于恶性细胞的特征。非恶性 肿瘤免疫微环境（TME）中的细胞可以是肿瘤生长的强大调节剂， 尽管TME元件被靶向用于癌症治疗，但尚未开发出包括TME元件的生物标志物。我们 假设成功开发下一代淋巴瘤免疫靶向疗法 将需要TME组成的空间分辨的、高度多重的基于单细胞的生物标志物， 结构在这项研究中，我们建议对2000多例乳腺癌患者进行成像质谱细胞术分析（IMC）。 侵袭性B细胞淋巴瘤，目的如下：具体目的1：空间来源的蛋白质生物标志物 DLBCL结局（n-830例患者）。具体目标2：分析组织学多样性的单细胞拓扑结构 侵袭性B细胞淋巴瘤（n=1380），以鉴定所有侵袭性B细胞淋巴瘤中共有的基于TME的生物标志物。 淋巴瘤具体目标3：确定哪些TME元件调节化学抗性并介导反应 淋巴瘤的免疫治疗。在前两个目标中，我们将应用我们的小说 丰度加权评分（M评分），专门为IMC分析开发，以验证候选生物标志物 (such作为PD-L1+/CCR 4 +/TIM-3+），并鉴定新的生物标志物。我们还将应用我们的单细胞空间 一种识别肿瘤免疫空间簇的聚类算法，免疫细胞组织区域（RICO） 与临床结果相关的因素。空间分辨，单细胞，高度复用，数字图像 本文提出的分析将对美国约80，000例NHL新发病例产生临床影响。具体目标1将确认 并以病理学家熟悉的图像格式发现蛋白质生物标志物， 通过，具体目标2将完善应用于挑战性淋巴瘤的空间系统生物学方法 类型和特定目标3将允许预后和预测生物标志物的临床前验证。