Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells

Area of Science:

• Oncology
• Biochemistry
• Bioinformatics

Background:

• Cellular signaling, particularly phosphorylation by protein kinases, is frequently deregulated in cancer, making kinases critical targets for research and therapy.
• Despite extensive investigation, a complete understanding of kinase dysfunction in oncogenesis remains elusive.
• Mass-spectrometry (MS)-based phosphoproteomics offers a powerful approach to study phosphorylation, identifying thousands of phosphopeptides and indirectly reflecting protein kinase activity.

Purpose of the Study:

• To discuss computational methods for predicting kinase activity scores from MS-based phosphoproteomics data.
• To review existing databases of kinase-substrate relationships and bioinformatic tools for novel kinase target discovery.
• To introduce and illustrate methods for inferring kinase activities, including a detailed protocol for Kinase Substrate Enrichment Analysis (KSEA).

Main Methods:

• Explanation of phosphoproteomics data acquisition from a computational analysis perspective.
• Review of databases for experimentally verified kinase-substrate relationships.
• Introduction of computational tools and methods, including KSEA, to infer kinase activity from phosphoproteomics data and kinase-substrate relationships.

Main Results:

• The chapter details computational approaches to derive kinase activity insights from phosphoproteomics data.
• It highlights the utility of KSEA, implemented in the open-source Kinase Activity Toolbox (kinact).
• The presented methods facilitate the discovery of novel kinase targets and understanding of kinase roles in cancer.

Conclusions:

• Computational analysis of phosphoproteomics data provides valuable insights into protein kinase activity in cancer.
• Tools like KSEA, integrated into the kinact toolbox, enable robust prediction of kinase activity scores.
• This approach aids in advancing cancer research by elucidating kinase dysfunction and identifying potential therapeutic strategies.