Neighborhood clustering analysis to define epithelial–stromal interface for tumor infiltrating lymphocyte evaluation

Q2 Medicine
Tony Yeung , Yi Zhang , Qianghua Zhou , Richard Burack
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引用次数: 0

Abstract

Evaluation of tumor infiltrating lymphocytes as recommended by current guidelines is largely based on stromal regions within the tumor. In the context of epithelial malignancies, the epithelial region and the epithelial–stromal interface are not assessed, because of technical difficulties in manually discerning lymphocytes when admixed with epithelial tumor cells. The inability to quantify immune cells in epithelial-associated areas may negatively impact evaluation of patient response to immune checkpoint therapies. Innovative spatial analysis techniques have emerged that can directly address challenges associated with quantification of lymphocytes in specialized regions like the interface. In this study, we apply supervised neighborhood clustering analysis (via an open-source application CytoMAP) to assess the spatial distribution of CD8+ T cells, CD8+ TIM3+ (T cell immunoglobulin and mucin-domain containing-3) exhausted T cells, and TIM3+ CD8- macrophages on a gynecological tumor microarray. Neighborhood clustering analysis is adept at objectively mapping the epithelial–stromal interface alongside the epithelial and stromal region of each tumor under a three-compartment model. When tumors are partitioned by the conventional two-compartment model (epithelial and stromal region only), the highest density of total CD8+ T cells is found in the stromal region in a slight majority of tumors. In contrast, the interface region surpasses both the epithelial and stromal region in holding the highest density of CD8+ T cells when this unique region is incorporated into the three-compartment model. Further subset analysis shows higher proportion of CD8+ TIM3+ exhausted T cells within the interface and epithelial region, as compared to CD8+ TIM3- T cells which span from the stroma to the interface. These results highlight the utility of implementing quantitative spatial technique and immune subset analysis in the assessment of tumor infiltrating lymphocytes, and underscore the potential significance of the under-reported tumor epithelial–stromal interface.
邻域聚类分析定义肿瘤浸润淋巴细胞评价的上皮-基质界面
目前指南中推荐的肿瘤浸润淋巴细胞的评估主要基于肿瘤内的基质区域。在上皮恶性肿瘤的背景下,由于人工识别淋巴细胞与上皮肿瘤细胞混合在一起的技术困难,因此不评估上皮区域和上皮-基质界面。无法量化上皮相关区域的免疫细胞可能会对评估患者对免疫检查点疗法的反应产生负面影响。创新的空间分析技术已经出现,可以直接解决与特定区域(如界面)淋巴细胞定量相关的挑战。在这项研究中,我们应用监督邻域聚类分析(通过开源应用程序CytoMAP)来评估CD8+ T细胞,CD8+ TIM3+ (T细胞免疫球蛋白和粘蛋白结构域-3)耗尽T细胞和TIM3+ CD8-巨噬细胞在妇科肿瘤微阵列上的空间分布。邻域聚类分析擅长于在三室模型下客观地绘制上皮-基质界面以及每个肿瘤的上皮和基质区域。当用传统的双室模型(仅上皮和间质区)对肿瘤进行分割时,在绝大多数肿瘤中,CD8+ T细胞总密度最高的是间质区。相比之下,当这个独特的区域被纳入三室模型时,界面区域在容纳CD8+ T细胞密度方面超过了上皮和基质区域。进一步的亚群分析显示,与从基质到界面的CD8+ TIM3- T细胞相比,CD8+ TIM3- T细胞在界面和上皮区域内的比例更高。这些结果强调了实施定量空间技术和免疫亚群分析在评估肿瘤浸润淋巴细胞中的效用,并强调了未被报道的肿瘤上皮-基质界面的潜在意义。
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来源期刊
Journal of Pathology Informatics
Journal of Pathology Informatics Medicine-Pathology and Forensic Medicine
CiteScore
3.70
自引率
0.00%
发文量
2
审稿时长
18 weeks
期刊介绍: The Journal of Pathology Informatics (JPI) is an open access peer-reviewed journal dedicated to the advancement of pathology informatics. This is the official journal of the Association for Pathology Informatics (API). The journal aims to publish broadly about pathology informatics and freely disseminate all articles worldwide. This journal is of interest to pathologists, informaticians, academics, researchers, health IT specialists, information officers, IT staff, vendors, and anyone with an interest in informatics. We encourage submissions from anyone with an interest in the field of pathology informatics. We publish all types of papers related to pathology informatics including original research articles, technical notes, reviews, viewpoints, commentaries, editorials, symposia, meeting abstracts, book reviews, and correspondence to the editors. All submissions are subject to rigorous peer review by the well-regarded editorial board and by expert referees in appropriate specialties.
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