PEN

PEN integrates paired proteomic, phosphoproteomic, transcriptomic, and genomic data from 145 human cancer cell lines to enable proteogenomic analyses that link DNA, mRNA, protein abundance, phosphorylation-site variations, and novel peptide expression in cancer.

Key Features:

• Extensive dataset: Contains proteomic and phosphoproteomic data covering over 4 million peptides and more than 13,000 proteins, and reports 7,138 phosphorylation site–associated genomic variations aggregated from 117 studies across 12 cancer types.
• Paired multi-omics integration: Integrates genetic, transcriptomic, and proteomic measurements from the same cell lines to support direct comparisons among DNA, mRNA, and protein levels.
• CNA and expression associations: Enables genome-wide analyses of somatic copy number alterations (CNA) and their cis/trans associations with mRNA and protein expression levels.
• Variant and PTM characterization: Supports analysis of single amino acid variations in coding genes, post-translational modification site variations, and peptide expressions derived from noncoding regions and fusion genes.
• mRNA–protein correlation and novel peptide landscape: Provides data for quantitative assessment of mRNA–protein abundance correlations and the discovery and characterization of novel peptides.
• Functional annotation: Includes functional annotation of proteogenomic interactions to facilitate interpretation of molecular features relevant to cancer biology.

Scientific Applications:

• Proteogenomic characterization of cancer: Supports identification and interpretation of molecular alterations across DNA, RNA, protein, and phosphorylation layers in cancer cell lines.
• Comparative multi-omics analyses: Enables quantitative comparisons of proteogenomic results across studies and cancer types to investigate oncogenic modulation.
• Variant and novel peptide discovery: Facilitates detection and analysis of single amino acid variations, PTM-associated genomic variations, and novel peptides from noncoding regions and fusion genes.
• Target and biomarker investigation: Provides integrated evidence for exploring molecular features relevant to therapeutic targeting and biomarker development in cancer.

Methodology:

Consolidates DNA, RNA, and protein characterization data from public studies of human cancer cell lines and integrates somatic copy number alterations, transcriptomic differences, peptide expressions, phosphorylation-site–associated variations, and single amino acid variations into a unified dataset.