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源自存档头颈部鳞状细胞癌样本的肿瘤和基质激光显微切割富集后的dia-PASEF蛋白质组学

dia-PASEF Proteomics of Tumor and Stroma LMD Enriched from Archived HNSCC Samples.

作者信息

Panigrahi Aswini, Hunt Allison L, Assis Diego, Willetts Matthew, Kallakury Bhaskar V, Davidson Bruce, Conrads Thomas P, Goldman Radoslav

机构信息

Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20057, USA.

Women's Health Integrated Research Center, Women's Service Line, Inova Health System, Annandale, VA 22003, USA.

出版信息

bioRxiv. 2024 Aug 10:2024.08.09.607341. doi: 10.1101/2024.08.09.607341.

Abstract

We employed laser microdissection to selectively harvest tumor cells and stroma from the microenvironment of formalin-fixed, paraffin-embedded head and neck squamous cell carcinoma (HNSCC) tissues. The captured HNSCC tissue fractions were analyzed by quantitative mass spectrometry-based proteomics using a data independent analysis approach. In paired samples, we achieved excellent proteome coverage having quantified 6,668 proteins with a median quantitative coefficient of variation under 10%. We observed significant differences in relevant functional pathways between the spatially resolved tumor and stroma regions. Our results identified extracellular matrix (ECM) as a major component enriched in the stroma, including many cancer associated fibroblast signature proteins in this compartment. We demonstrate the potential for comparative deep proteome analysis from very low starting input in a scalable format that is useful to decipher the alterations in tumor and the stromal microenvironment. Correlating such results with clinical features or disease progression will likely enable identification of novel targets for disease classification and interventions.

摘要

我们采用激光显微切割技术,从福尔马林固定、石蜡包埋的头颈部鳞状细胞癌(HNSCC)组织微环境中选择性地获取肿瘤细胞和基质。利用数据独立分析方法,通过基于定量质谱的蛋白质组学对捕获的HNSCC组织部分进行分析。在配对样本中,我们实现了出色的蛋白质组覆盖,定量了6668种蛋白质,定量变异系数中位数低于10%。我们观察到在空间分辨的肿瘤和基质区域之间,相关功能通路存在显著差异。我们的结果确定细胞外基质(ECM)是基质中富集的主要成分,包括该区域许多癌症相关成纤维细胞特征蛋白。我们展示了以可扩展的形式从极低起始输入进行比较深度蛋白质组分析的潜力,这有助于解读肿瘤和基质微环境中的变化。将这些结果与临床特征或疾病进展相关联,可能会有助于识别疾病分类和干预的新靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad5e/11326218/bcab8b60acbb/nihpp-2024.08.09.607341v1-f0001.jpg

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