Proteome-wide tyrosine phosphorylation analysis reveals dysregulated signaling pathways in ovarian tumors

  • Guang Song
  • , Li Chen
  • , Bai Zhang
  • , Qifeng Song
  • , Yu Yu
  • , Cedric Moore
  • , Tian Li Wang
  • , Ie Ming Shih
  • , Hui Zhang
  • , Daniel W. Chan
  • , Zhen Zhang*
  • , Heng Zhu
  • *Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

21 Scopus citations

Abstract

The recent accomplishment of comprehensive proteogenomic analysis of high-grade serous ovarian carcinoma (HGSOC) tissues reveals cancer associated molecular alterations were not limited to variations among DNA, and mRNA/protein expression, but are a result of complex reprogramming of signaling pathways/networks mediated by the protein and post-translational modification (PTM) interactomes. A systematic, multiplexed approach interrogating enzyme-substrate relationships in the context of PTMs is fundamental in understanding the dynamics of these pathways, regulation of cellular processes, and their roles in disease processes. Here, as part of Clinical Proteomic Tumor Analysis Consortium (CPTAC) project, we established a multiplexed PTM assay (tyrosine phosphorylation, and lysine acetylation, ubiquitylation and SUMOylation) method to identify protein probes’ PTMs on the human proteome array. Further, we focused on the tyrosine phosphorylation and identified 19 kinases are potentially responsible for the dysregulated signaling pathways observed in HGSOC. Additionally, elevated kinase activity was observed when 14 ovarian cancer cell lines or tumor tissues were subjected to test the autophosphorylation status of PTK2 (pY397) and PTK2B (pY402) as a proxy for kinase activity. Taken together, this report demonstrates that PTM signatures based on lysate reactions on human proteome array is a powerful, unbiased approach to identify dysregulated PTM pathways in tumors.

Original languageEnglish
Pages (from-to)448-460
Number of pages13
JournalMolecular and Cellular Proteomics
Volume18
Issue number3
DOIs
StatePublished - 03 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Song et al.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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