five

Systematic Evaluation of the Impact of Storage Time on Label-Free Proteomics of Colorectal Adenocarcinoma Formalin-Fixed Paraffin-Embedded Tissues

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Systematic_Evaluation_of_the_Impact_of_Storage_Time_on_Label-Free_Proteomics_of_Colorectal_Adenocarcinoma_Formalin-Fixed_Paraffin-Embedded_Tissues/31801865
下载链接
链接失效反馈
官方服务:
资源简介:
Mass spectrometry (MS)-based proteomics has empowered comprehensive protein profiling of biological specimens. However, formalin-fixed paraffin-embedded (FFPE) tissuescritical resources for clinical biomarker discovery-remain underexplored in the setting of long-term storage (>15 years). Herein, we systematically evaluated the impact of storage time on proteomic analyses of 80 colorectal adenocarcinoma (CRC) FFPE samples, which were stratified by two key variables: storage time (>15 years vs <1 year) and tissue type (tumor vs adjacent normal tissue). We adopted a standardized protein extraction strategy, and subsequent proteomic profiling was performed via data-dependent acquisition and data-independent acquisition MS workflows. Our results demonstrated that FFPE tissue storage time impacts protein extraction efficiency, peptide yields, PTM identification, and protein quantification. The impacts were more pronounced on the peptide level. However, the biological enrichments (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis) from the global proteome profile and from differentially expressed proteins in CRC tissues were independent of archival time. Five clinically relevant biomarkers of CRC were further validated via immunohistochemistry. Collectively, our findings confirm that FFPE tissues retain stability for proteomic analyses even following >15 years of storage, thereby providing critical insights for leveraging archival FFPE biobanks to advance clinical proteomics and archival pathology research.
创建时间:
2026-03-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作