B006:基于数字空间剖面的无偏组织采样网格组织剖面策略

S. Church, Chris Merritt, Giang T Ong, A. White, Kristi Zevin, S. Warren, J. Beechem
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引用次数: 0

摘要

对组织内蛋白质和rna的空间分布和丰度进行表征,可以深入了解生物系统。从临床样品中同时检测多个靶点的能力提高了发现的潜力,但事实证明,对于福尔马林固定石蜡包埋(FFPE)组织来说,这是一个挑战。NanoString Technologies®开发了数字空间分析(DSP)平台,可以使用非破坏性协议对FFPE组织中的蛋白质或RNA进行高度多路分析。该技术可用于量化用户定义感兴趣区域(ROI)内目标的丰度,使用各种掩蔽策略来选择和定义这些区域,包括几何、表型或基于组织内某些标记的表达自动生成的掩蔽。目前的技术能够分析几十个目标,并且未来的迭代能够同时分析数百或数千个目标。控制ROI的大小、形状和特征定义了所生成信息的异构性和粒度。迄今为止,对DSP的研究主要集中在以非系统的方式分析感兴趣的区域。然而,以网格方式对组织进行分析,可以在整个组织切片或较小的组织区域内对蛋白质表达进行均匀采样,从而实现无偏见的评估,这可能有助于生物标志物的发现。本研究利用DSP和网格ROI选择策略来分析正常和肿瘤组织中的蛋白质分布。来自扁桃体或结直肠肿瘤的FFPE组织通过可光切割的连接剂和多达3个荧光抗体结合到独特的DNA寡核苷酸上,用44 plex的抗体鸡尾酒染色。用荧光抗体收集组织的视觉图像,然后用紫外线照射感兴趣的选定区域以释放寡核苷酸用于收集。对roi进行连续分析,然后在标准NanoString分析中定量捕获寡核苷酸。在本研究中,扁桃体和结直肠癌(CRC)组织在DSP平台上使用网格化ROI选择策略进行分析,通过低分辨率采样或通过高分辨率采样从组织内的特定区域收集整个组织切片的蛋白质谱。组织的低分辨率采样提供了蛋白质分布在扁桃体或结直肠癌部分的估计。它进一步能够识别肿瘤内的兴趣区域,适合用高分辨率方法进行更深入的分析。通过观察蛋白质的分布,更高分辨率的分析可以在分子水平上重建组织形态。生发中心和淋巴结内t细胞区不同的蛋白质谱。此外,我们看到不同淋巴结之间蛋白质表达的变化可能有助于不同的生物功能。同样,在结直肠癌组织中,我们发现蛋白质谱在肿瘤和肿瘤微环境之间具有独特的分布。例如,免疫细胞类型标记物的表达高度定位,特别是在组织的离散区域而不是分布在整个肿瘤微环境中,以及已知参与肿瘤生长/进展的途径的强表达分布在组织的肿瘤丰富区域。此外,免疫检查点分子(如PD-L1和TIM3)似乎在主要为肿瘤的组织区域表达。这是否代表免疫细胞的肿瘤浸润或检查点分子的异常表达仍有待确定。这些结果表明,使用NanoString DSP平台,网格化ROI选择策略可以以无偏的方式对组织进行深度分析,从而询问FFPE组织内的免疫生物学。引文格式:Sarah Church, Chris Merritt, Giang Ong, Andrew White, Kristi Zevin, Sarah Warren, Joseph M. Beechem。基于数字空间剖面的无偏组织采样网格组织剖面策略[摘要]。第四届CRI-CIMT-EATI-AACR国际癌症免疫治疗会议:将科学转化为生存;2018年9月30日至10月3日;纽约,纽约。费城(PA): AACR;癌症免疫学杂志,2019;7(2增刊):摘要nr B006。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abstract B006: Gridded tissue profiling strategy with digital spatial profiling for unbiased tissue sampling
Characterization of the spatial distribution and abundance of protein and RNAs within a tissue enables deep understanding of biologic systems. The ability to interrogate multiple targets simultaneously from clinical samples enhances the potential for discovery, but has proven to be challenging for formalin fixed paraffin embedded (FFPE) tissue. NanoString Technologies® has developed the Digital Spatial Profiling (DSP) platform to enable highly multiplexed profiling of protein or RNA from FFPE tissue using a non-destructive protocol. This technology can be used to quantify the abundance of targets within user-defined regions of interest (ROI) using a variety of masking strategies to select and define those regions, including geometric, phenotypic, or automatically generated masks based on expression of certain markers within the tissue. The current technology is capable of profiling dozens of targets, and future iterations could enable hundreds or thousands of targets to be profiled simultaneously. Controlling ROI size, shape, and features defines the heterogeneity and granularity of the information generated. To date, studies on the DSP have largely focused on profiling regions of interest in a nonsystematic way. However, profiling a tissue in a gridded fashion enables a uniform sampling of protein expression either across a whole tissue section or within a smaller area of the tissue to enable nonbiased evaluation, which may aid in biomarker discovery. This study utilizes DSP and a gridded ROI selection strategy to profile protein distribution within normal and tumor tissue. FFPE tissue from tonsil or colorectal tumors are stained with a 44-plex cocktail of antibodies conjugated to unique DNA oligos via a photocleavable linker and up to 3 fluorescent antibodies. Visual images of the tissue are collected with the fluorescent antibodies, and selected regions of interest are subsequently illuminated with UV light to release the oligos for collection. ROIs are profiled serially and captured oligos are then quantitated in the standard NanoString assay. In this study, tonsil and colorectal cancer (CRC) tissue is profiled on the DSP platform using a gridded ROI selection strategy to collect protein profiles from an entire tissue section either via low-resolution sampling or from specific regions within the tissue via high-resolution sampling. Low-resolution sampling of the tissue provides an estimate of the protein distribution across a section of tonsil or CRC. It further enables identification of regions of interest within the tumor suitable for deeper profiling with the high-resolution approach. The higher resolution profiling enables reconstruction of the tissue morphology at the molecular level by looking solely at the distribution of proteins. A distinct protein profiles for the germinal centers and T-cell zones within lymph nodes. Furthermore, we see variations emerges of protein expression between different lymph nodes that may contribute to different biologic functionality. Similarly, in CRC tissue, we see protein profiles that distribute uniquely between the tumor and the tumor microenvironment. For example, there is highly localized expression of immune cell type markers in particular, discrete regions of the tissue rather than distributed throughout the tumor microenvironment, and strong expression of pathways know to be involved in tumor growth/progression distributed to tumor-rich region of the tissue. Furthermore, there appears to be expression of select immune checkpoint molecules (e.g., PD-L1 and TIM3) in regions of the tissue that are predominantly tumor. Whether this represents tumor infiltration by immune cells or aberrant expression of the checkpoint molecules remains to be determined. These results demonstrate the utility of a gridded ROI selection strategy for deep profiling of tissue in an unbiased way to interrogate the immune biology within FFPE tissue using the NanoString DSP platform. Citation Format: Sarah Church, Chris Merritt, Giang Ong, Andrew White, Kristi Zevin, Sarah Warren, Joseph M. Beechem. Gridded tissue profiling strategy with digital spatial profiling for unbiased tissue sampling [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B006.
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