A curated resource for phosphosite-specific signature analysis


  • K. Krug
  • P. Mertins
  • B. Zhang
  • P. Hornbeck
  • R. Raju
  • R. Ahmad
  • M. Szucs
  • F. Mundt
  • D. Forestier
  • J. Jane-Valbuena
  • H. Keshishian
  • M.A. Gillette
  • P. Tamayo
  • J.P. Mesirov
  • J.D. Jaffe
  • S.A. Carr
  • D.R. Mani


  • Molecular & Cellular Proteomics


  • Mol Cell Proteomics 18 (3): 576-593


  • Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM datasets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level due to the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTM Signature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized dataset of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared to gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at