Khalfaoui Latifa, Moore Raymond M, Villasboas Jose C, Whitaker Kaitlyn R, Novotny Brenna C, Thompson Michael A, Pabelick Christina M, Prakash Y S
Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 4-184 W Jos SMH, 200 First St SW, Rochester, Minnesota, 55905, USA.
Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
Respir Res. 2025 Jul 2;26(1):232. doi: 10.1186/s12931-025-03315-5.
Chronic respiratory diseases such as asthma and COPD involve interactions between multiple resident and immune cell types within bronchial airways, resulting in structural and functional changes. Thus cellular heterogeneity, arrangements and associated neighborhoods as well as interactions between cells and matrices represent intriguing yet challenging areas of study. Spatial phenotypic profiling facilitates exploration of these issues of the cellular microenvironment and identification of context-dependent cell-cell interactions. Utilizing spatial phenotyping, we interrogated the features and cellular landscape of lungs from non-asthmatics, asthmatics, and COPD in FFPE samples by developing a 10-plex antibody panel for the Akoya PhenoCycler-Fusion system, focused on immune cells (CD45, CD3, CD4, CD8), proliferative cells (Ki67, PCNA), angiogenesis (CD34), epithelium (E-cadherin), smooth muscle (SMA) and extracellular matrix (collagen). We performed cell segmentation on multiplex immunofluorescence images and quantified marker intensity in each cell. Phenotypes were manually identified after normalization, integration, and clustering cells across samples. The composition, cell profiling, and distribution varied significantly between asthmatics and COPD compared to non-asthmatics emphasizing disease heterogeneity. Spatially agnostic analysis revealed that the matrix cluster was more abundant in COPD compared to non-asthmatics and asthmatics, consistent with a greater role for fibrosis. However, asthmatic patients had a higher proportion of unclassified and CD8 + clusters highlighting immune responses. Co-localization analysis showed near random distribution in non-asthmatics. But strong spatial interaction between T cells and other immune or matrix cells in asthma, and a higher avoidance of smooth muscle and immune cells, and of proliferative markers in both asthmatic and COPD. Niche analysis demonstrated different recurrent cell-cell interactions in asthmatic and COPD cohorts. In COPD, the matrix cell-enriched niche was more abundant, while in asthmatics, the unclassified cell-enriched niche was more prevalent compared to non-asthmatics. These findings provide insights into differential spatial organization of cells and tissues in asthma and COPD, with immune and epithelial mechanisms suggesting active inflammation and remodeling in asthma, but fibrotic processes in COPD, and potential role for vascular processes in both conditions.
哮喘和慢性阻塞性肺疾病（COPD）等慢性呼吸道疾病涉及支气管气道内多种固有细胞和免疫细胞类型之间的相互作用，导致结构和功能发生变化。因此，细胞异质性、排列方式、相关邻域以及细胞与基质之间的相互作用代表了有趣但具有挑战性的研究领域。空间表型分析有助于探索细胞微环境的这些问题，并识别依赖于背景的细胞间相互作用。利用空间表型分析，我们通过为Akoya PhenoCycler-Fusion系统开发一个10重抗体组合，聚焦于免疫细胞（CD45、CD3、CD4、CD8）、增殖细胞（Ki67、PCNA）、血管生成（CD３４）、上皮细胞（E-钙黏蛋白）、平滑肌（SMA）和细胞外基质（胶原蛋白），研究了FFPE样本中来自非哮喘患者、哮喘患者和COPD患者肺部的特征和细胞景观。我们对多重免疫荧光图像进行细胞分割，并对每个细胞中的标志物强度进行定量。在对样本进行归一化、整合和细胞聚类后，手动识别表型。与非哮喘患者相比，哮喘患者和COPD患者之间的组成、细胞图谱和分布存在显著差异，强调了疾病的异质性。不考虑空间因素的分析显示，与非哮喘患者和哮喘患者相比，COPD患者中的基质簇更为丰富，这与纤维化的更大作用一致。然而，哮喘患者中未分类和CD8 +簇的比例更高，突出了免疫反应。共定位分析显示在非哮喘患者中分布近乎随机。但在哮喘中T细胞与其他免疫或基质细胞之间存在强烈的空间相互作用，并且在哮喘和COPD中平滑肌和免疫细胞以及增殖标志物的回避程度更高。生态位分析表明哮喘和COPD队列中存在不同的反复细胞间相互作用。在COPD中，富含基质细胞的生态位更为丰富，而在哮喘患者中，与非哮喘患者相比，富含未分类细胞的生态位更为普遍。这些发现为哮喘和COPD中细胞和组织的差异空间组织提供了见解，免疫和上皮机制表明哮喘中存在活跃的炎症和重塑，但COPD中存在纤维化过程，并且在这两种情况下血管过程都具有潜在作用。
