利用高阶色原复用技术对前列腺肿瘤微环境进行数字化分析

Rahul Rajendran, Rachel C. Beck, Morteza M. Waskasi, Brian D. Kelly, Daniel R. Bauer
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引用次数: 0

摘要

随着我们对肿瘤微环境了解的加深,病理领域越来越多地利用多分析物诊断分析来了解肿瘤生长的重要特征。在临床环境中,明场显色法代表了金标准,并作为一线诊断方法发展了显著的信任。然而,传统的明场测试仅限于低阶分析,是视觉询问。我们开发了一种混合的明场显色多路复用方法,克服了这些限制,实现了高阶多路复用分析。然而,如何兼容高阶明场复用图像与先进的分析算法还没有得到广泛的评估。在本研究中,我们通过开发一种新的6标记前列腺癌检测来解决这一空白,该检测针对肿瘤微环境的各个方面,如前列腺特异性生物标志物(PSMA和p504s)、免疫生物标志物(CD8和PD-L1)、预后生物标志物(Ki-67)以及辅助诊断生物标志物(基底细胞混合物),并将该检测应用于143种不同分级的腺癌前列腺组织。然后在我们的光谱多路复用成像平台上对组织进行成像,并挖掘与癌症存在和疾病等级相关的蛋白质组学和空间特征。提取的特征用于训练UMAP模型,该模型区分健康组织和癌组织的准确率为89%,并根据癌症等级识别细胞簇。为了进行空间分析,计算了所有生物标志物的细胞间距离,并研究了健康组织和腺癌组织之间的差异。我们报道p504s阳性细胞与腺癌组织中表达PD-L1、CD8、Ki-67和基底细胞的细胞至少接近健康对照组织的2倍。这些发现为理解前列腺肿瘤微环境的指纹图谱提供了有力的见解,并表明高阶显色复用与数字分析是兼容的。因此,提出的显色多路复用系统结合了明场分析的临床适用性和高阶多路复用的新兴诊断能力,以数字病理友好的形式,非常适合用于转化研究,以更好地了解肿瘤的发展和生长机制。
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Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing

As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.

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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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