ArticleiScience2026
A data-driven pan-cancer proteogenomic analysis reveals the characteristics of human cancer protein expression.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Proprotein convertase activity regulates cumulus-oocyte-complex matrix integrity and cumulus cell migration during ovulation via a GDF9-dependent mechanism.bioRxiv : the preprint server for biology · 2026Article
- Review
- The tumor microenvironment of medulloblastoma: from emerging biological insights to novel therapeutic targeting.Frontiers in oncology · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomics and epigenomics outline potential cellular changes, while proteomics reflects actual molecular events. To systematically bridge the molecular hierarchies and validate their functional interplay, we established the most comprehensive pan-cancer paired multi-omics resource to date, systematically integrating proteomic, transcriptomic, and genomic data from both tumor and adjacent normal tissues spanning 15 cancer types (2,555 tumor samples), thereby enabling a robust cross-omics exploration. Analysis revealed that tumor tissues exhibit higher correlation between transcriptomic and proteomic expression levels compared to normal tissues. Key tumor development pathways exhibited strong mRNA-protein correlations. Genes with high mRNA-protein correlation and high expression were associated with lower survival rates, highlighting potential therapeutic targets. We developed a comprehensive tool, the CPGTA R package, based on reintegrated datasets that facilitates multi-omics data integration and reanalysis. Our research enhances cancer molecular characterization while providing insights into mechanisms underlying cancer progression and treatment resistance.
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Registered trials
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