Suppr超能文献

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物的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, Ahn Jaeil, Conrads Thomas P, Goldman Radoslav

机构信息

Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia 20057, United States.

Women's Health Integrated Research Center, Women's Service Line, Inova Health System, Annandale, Virginia 22003, United States.

出版信息

ACS Omega. 2025 Mar 25;10(13):13296-13302. doi: 10.1021/acsomega.4c11051. eCollection 2025 Apr 8.

Abstract

We employed laser microdissection to selectively harvest histology-resolved tumors and stroma from formalin-fixed, paraffin-embedded head and neck squamous cell carcinoma (HNSCC) tissues. Peptide digests from the LMD-enriched HNSCC tissue were analyzed by quantitative mass-spectrometry-based proteomics using a data independent analysis approach. In paired samples, excellent proteome coverage was achieved, having quantified 6668 proteins with a median quantitative coefficient of variation under 10%. Significant differences in relevant functional pathways between the tumor and the stroma regions were observed. Extracellular matrix (ECM) was identified 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 a very low starting input in a scalable format. Correlating such results with clinical features or disease progression will likely enable the 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)组织中选择性地获取组织学分辨的肿瘤和基质。使用数据独立分析方法,通过基于定量质谱的蛋白质组学对激光显微切割富集的HNSCC组织的肽段消化物进行分析。在配对样本中,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%。观察到肿瘤和基质区域之间相关功能途径的显著差异。细胞外基质(ECM)被确定为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形式从极低起始输入进行比较深度蛋白质组分析的潜力。将这些结果与临床特征或疾病进展相关联,可能有助于识别疾病分类和干预的新靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0de/11983184/c82b4ed14c79/ao4c11051_0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验