Characterizing the immune and metabolic profiles of cutaneous T-cell lymphoma in formalin-fixed paraffin-embedded skin tissue samples

表征福尔马林固定石蜡包埋皮肤组织样本中皮肤 T 细胞淋巴瘤的免疫和代谢特征

• 批准号: 10058252
• 负责人: Darci Phillips
• 金额: $ 3.86万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10058252
• 关键词: Address; Antibodies; Benign; Blood; Cell Communication; Cell Line; Cell physiology; Cells; Clinical; Complex; Coupled; Cutaneous T-cell lymphoma; Data; Data Set; Dendritic Cells; Detection; Diagnosis; Diagnostic; Disease; Early Diagnosis; Energy Metabolism; Formalin; Glucose; Glycolysis; Goals; Growth Factor; Heterogeneity; Histologic; Image; Immune; Immune mediated destruction; Immunity; Immunohistochemistry; Immunomodulators; Individual; Light; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Metabolic; Metabolism; Metals; Molecular; Morphology; Multiparametric Analysis; Multiplexed Ion Beam Imaging; Non-Malignant; Outcome; Paraffin Embedding; Pathogenesis; Patients; Phenotype; Play; Prognostic Marker; Regulatory T-Lymphocyte; Reporting; Research; Resolution; Role; Sampling; Sirolimus; Skin; Skin Tissue; Slide; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Spectrometry, Mass, Secondary Ion; Systemic Therapy; T-Lymphocyte; Techniques; Technology; Therapeutic; Tissue Embedding; Tissue Sample; Treatment outcome; Tumor Suppression; Work; antibody conjugate; diagnostic biomarker; effector T cell; fatty acid oxidation; improved; innovation; insight; mTOR Inhibitor; machine learning algorithm; macrophage; metabolic profile; metabolomics; molecular diagnostics; nanometer resolution; neoplastic cell; new technology; prognostic; protein expression; skin lesion; therapeutic biomarker; therapeutic target; treatment response; treatment strategy; tumor; tumor microenvironment; Address; Antibodies; Benign; Blood; Cell Communication; Cell Line; Cell physiology; Cells; Clinical; Complex; Coupled; Cutaneous T-cell lymphoma; Data; Data Set; Dendritic Cells; Detection; Diagnosis; Diagnostic; Disease; Early Diagnosis; Energy Metabolism; Formalin; Glucose; Glycolysis; Goals; Growth Factor; Heterogeneity; Histologic; Image; Immune; Immune mediated destruction; Immunity; Immunohistochemistry; Immunomodulators; Individual; Light; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Metabolic; Metabolism; Metals; Molecular; Morphology; Multiparametric Analysis; Multiplexed Ion Beam Imaging; Non-Malignant; Outcome; Paraffin Embedding; Pathogenesis; Patients; Phenotype; Play; Prognostic Marker; Regulatory T-Lymphocyte; Reporting; Research; Resolution; Role; Sampling; Sirolimus; Skin; Skin Tissue; Slide; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Spectrometry, Mass, Secondary Ion; Systemic Therapy; T-Lymphocyte; Techniques; Technology; Therapeutic; Tissue Embedding; Tissue Sample; Treatment outcome; Tumor Suppression; Work; antibody conjugate; diagnostic biomarker; effector T cell; fatty acid oxidation; improved; innovation; insight; mTOR Inhibitor; machine learning algorithm; macrophage; metabolic profile; metabolomics; molecular diagnostics; nanometer resolution; neoplastic cell; new technology; prognostic; protein expression; skin lesion; therapeutic biomarker; therapeutic target; treatment response; treatment strategy; tumor; tumor microenvironment

PROJECT SUMMARY/ABSTRACT Cutaneous T-cell lymphoma (CTCL) is a rare, but potentially devastating malignancy of the skin. Early detection of CTCL is associated with positive clinical outcomes, but diagnosis is often complicated by the heterogeneous clinical and histological presentation. Additionally, systemic therapies remain sub- optimal for CTCL, highlighting the need for new treatment strategies. To date, most studies have been performed on blood from CTCL patients, which has revealed a complex interplay between host immunity, malignant T-cells and the tumor microenvironment. However, the molecular mechanisms that govern disease pathogenesis, especially in the skin, remain largely undefined. The goal of the proposed research is to use new technologies that allow for multi-parametric, high- resolution analyses in formalin-fixed paraffin-embedded (FFPE) skin tissue samples to define the immune and metabolic profiles of CTCL at different stages of disease. The first technology is Multiplexed Ion Beam Imaging (MIBI), which uses secondary ion mass spectrometry to visualize up to 100 metal conjugated antibodies simultaneously at nanometer resolution in FFPE tissue sections. Specifically, Aim I will use MIBI to define the heterogeneity and plasticity of cells that exist at the CTCL tumor-host interface, to improve the precision with which CTCL is diagnosed and treated. The second technology is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which can detect thousands of metabolites in FFPE tissue sections. Specifically, Aim II will use MALDI-MSI to determine the reflective metabolic activity of the CTCL microenvironment, thereby adding functional insight to disease pathogenesis and revealing potential metabolically active therapeutic targets. Overall, these studies will characterize the molecular heterogeneity and functional complexity of CTCL, which will shed light on how this disease evades immune destruction and reprograms energy- metabolism. As such, this work promises to improve the detection, treatment and clinical outcomes for CTCL.

项目摘要/摘要 皮肤T细胞淋巴瘤（CTCL）是皮肤的罕见但可能具有毁灭性的恶性肿瘤。 CTCL的早期检测与阳性临床结果有关，但诊断通常很复杂 由异质临床和组织学表现。此外，全身疗法仍然是 CTCL的最佳选择，强调了对新治疗策略的需求。迄今为止，大多数研究已经 在CTCL患者的血液上进行的，这表明宿主免疫之间存在复杂的相互作用， 恶性T细胞和肿瘤微环境。但是，控制的分子机制 疾病的发病机理，尤其是在皮肤中，在很大程度上仍然不确定。 拟议的研究的目的是使用允许多参数，高级技术的新技术 在福尔马林固定石蜡包裹（FFPE）皮肤组织样品中进行分辨率分析以定义免疫 在疾病的不同阶段，CTCL的代谢谱。第一个技术是多路复用的离子束 成像（MIBI），它使用二级离子质谱法可视化多达100个金属共轭 FFPE组织切片中纳米分辨率同时抗体。具体来说，目标我将使用 MIBI定义CTCL肿瘤宿主界面上存在的细胞的异质性和可塑性， 提高CTCL诊断和处理的精度。第二种技术是矩阵辅助的 激光解吸/电离质谱成像（MALDI-MSI），可以检测数千个 FFPE组织切片中的代谢产物。具体而言，AIM II将使用MALDI-MSI来确定反思性 CTCL微环境的代谢活性，从而为疾病增加了功能洞察力 发病机理并揭示潜在的代谢活性治疗靶标。 总体而言，这些研究将表征分子异质性和功能复杂性 CTCL将阐明这种疾病如何逃避免疫破坏并重新编程。 代谢。因此，这项工作有望改善检测，治疗和临床结果 CTCL。