Suppr超能文献

通过 CODEX 组织成像技术对肿瘤微环境中的免疫调节蛋白进行高度多重表型分析。

Highly Multiplexed Phenotyping of Immunoregulatory Proteins in the Tumor Microenvironment by CODEX Tissue Imaging.

机构信息

Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States.

Department of Dermatology, Stanford University School of Medicine, Stanford, CA, United States.

出版信息

Front Immunol. 2021 May 19;12:687673. doi: 10.3389/fimmu.2021.687673. eCollection 2021.

Abstract

Immunotherapies are revolutionizing cancer treatment by boosting the natural ability of the immune system. In addition to antibodies against traditional checkpoint molecules or their ligands (i.e., CTLA-4, PD-1, and PD-L1), therapies targeting molecules such as ICOS, IDO-1, LAG-3, OX40, TIM-3, and VISTA are currently in clinical trials. To better inform clinical care and the design of therapeutic combination strategies, the co-expression of immunoregulatory proteins on individual immune cells within the tumor microenvironment must be robustly characterized. Highly multiplexed tissue imaging platforms, such as CO-Detection by indEXing (CODEX), are primed to meet this need by enabling >50 markers to be simultaneously analyzed in single-cells on formalin-fixed paraffin-embedded (FFPE) tissue sections. Assembly and validation of antibody panels is particularly challenging, with respect to the specificity of antigen detection and robustness of signal over background. Herein, we report the design, development, optimization, and application of a 56-marker CODEX antibody panel to eight cutaneous T cell lymphoma (CTCL) patient samples. This panel is comprised of structural, tumor, and immune cell markers, including eight immunoregulatory proteins that are approved or currently undergoing clinical trials as immunotherapy targets. Here we provide a resource to enable extensive high-dimensional, spatially resolved characterization of the tissue microenvironment across tumor types and imaging modalities. This framework provides researchers with a readily applicable blueprint to study tumor immunology, tissue architecture, and enable mechanistic insights into immunotherapeutic targets.

摘要

免疫疗法通过增强免疫系统的自然能力,正在彻底改变癌症治疗。除了针对传统检查点分子或其配体(即 CTLA-4、PD-1 和 PD-L1)的抗体外,目前还在临床试验中针对 ICOS、IDO-1、LAG-3、OX40、TIM-3 和 VISTA 等分子的疗法。为了更好地为临床护理提供信息,并设计治疗联合策略,必须对肿瘤微环境中单个免疫细胞上的免疫调节蛋白的共表达进行强有力的特征描述。高度多重化的组织成像平台,如通过索引的共检测(CODEX),通过能够在福尔马林固定石蜡包埋(FFPE)组织切片上的单个细胞中同时分析>50 个标记物,从而满足这一需求。抗体面板的组装和验证特别具有挑战性,涉及抗原检测的特异性和信号相对于背景的稳健性。在此,我们报告了一个由 56 个标记物组成的 CODEX 抗体面板的设计、开发、优化和在 8 个皮肤 T 细胞淋巴瘤(CTCL)患者样本中的应用。该面板由结构、肿瘤和免疫细胞标记物组成,包括 8 种免疫调节蛋白,它们是作为免疫治疗靶点获得批准或正在进行临床试验的。在这里,我们提供了一种资源,能够广泛地对肿瘤类型和成像方式的组织微环境进行高维、空间分辨的特征描述。该框架为研究人员提供了一个易于应用的蓝图,用于研究肿瘤免疫学、组织架构,并为免疫治疗靶点提供机制见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d3b/8170307/6cd5e2705a89/fimmu-12-687673-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验