Assessing Long-Term Stored Tissues for Multi-Omics Data Quality and Proteogenomics Suitability
收藏NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Assessing_Long-Term_Stored_Tissues_for_Multi-Omics_Data_Quality_and_Proteogenomics_Suitability/29877614
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资源简介:
As research into cancer biology progresses, multiomics
analyses
have become essential for unraveling its molecular complexities. However,
sample availability remains a challenge due to factors such as collection
procedures and long-term storage effects. Archived samples present
an opportunity to expand multiomics studies, but concerns persist
regarding storage duration’s impact on data reliability. This
study examines the genomic, transcriptomic, and proteomic profiles
of samples stored for over a decade. Transcriptomic analysis revealed
a decline in read counts for protein-coding genes but preserved core
gene expression patterns. Proteomic measurements remained stable,
with minimal changes in post-translational modifications. While phosphorylation
and acetylation rates were largely unaffected, a slight increase in
modification frequencies was observed. Housekeeping genes and proteins
exhibited consistent expression across samples, yet proteomic differences
between the tumor and normal tissues were distinct. Despite technical
variations in transcriptomic data, essential transcription factors
and kinases retained functionality. These findings underscore the
viability of archived samples for multiomics research, enabling broader
investigations into cancer biology and providing insights into molecular
mechanisms. By leveraging archived specimens, researchers can overcome
sample limitations and advance precision oncology efforts, ultimately
deepening our understanding of cancer at the systems level.
创建时间:
2025-08-10



