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Updated: Jun 19, 2026
07:42
Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
Proteomics, pathway array and signaling network-based medicine in cancer
David Y Zhang1, Fei Ye, Ling Gao
1Department of Pathology, Mount Sinai School of Medicine, New York, NY, USA. david.zhang@mssm.edu.
Cell Division
|October 30, 2009
Summary
Identifying cancer
Area of Science:
- Oncology
- Bioinformatics
- Molecular Biology
Background:
- Cancer arises from disrupted cellular signaling networks due to genetic and epigenetic changes.
- Understanding these molecular alterations is key to cancer mechanism and personalized medicine.
- Technological advancements enable global assessment of genetic, epigenetic, and proteomic changes in cancer.
Purpose of the Study:
- To review and compare Pathway Array analysis with other proteomic methods for cancer signaling network analysis.
- To highlight the utility of signaling network signatures as cancer biomarkers for diagnosis, prognosis, and therapy.
- To emphasize the growing role of bioinformatics in constructing complex signaling networks for clinical applications.
Main Methods:
- Review of existing literature on proteomic approaches for cancer signaling network analysis.
- Comparison of Pathway Array analysis with other proteomic techniques.
- Discussion of bioinformatics tools for network construction and analysis.
Main Results:
- Pathway Array analysis offers a valuable approach for studying cancer protein networks.
- Signaling network signatures can serve as effective biomarkers for cancer diagnosis, prognosis, and therapeutic targeting.
- Bioinformatics facilitates the construction of intricate signaling networks essential for future personalized medicine.
Conclusions:
- Pathway Array analysis is a powerful tool for dissecting cancer signaling pathways.
- Network-based signatures hold significant promise for advancing personalized cancer care.
- The integration of bioinformatics and network analysis is crucial for future cancer research and treatment.
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