Related Experiment Video
Updated: Nov 21, 2025

Identification of Kinase-substrate Pairs Using High Throughput Screening
Published on: August 29, 2015
Kinase-substrate Edge Biomarkers Provide a More Accurate Prognostic Prediction in ER-negative Breast Cancer
Yidi Sun1, Chen Li2, Shichao Pang3
1CAS Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Shanghai 200031, China.
Abstract:
The estrogen receptor (ER)-negative breast cancer subtype is aggressive with few treatment options available. To identify specific prognostic factors for ER-negative breast cancer, this study included 705,729 and 1034 breast invasive cancer patients from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. To identify key differential kinase-substrate node and edge biomarkers between ER-negative and ER-positive breast cancer patients, we adopted a network-based method using correlation coefficients between molecular pairs in the kinase regulatory network. Integrated analysis of the clinical and molecular data revealed the significant prognostic power of kinase-substrate node and edge features for both subtypes of breast cancer. Two promising kinase-substrate edge features, CSNK1A1-NFATC3 and SRC-OCLN, were identified for more accurate prognostic prediction in ER-negative breast cancer patients.
Related Concept Videos
Transducer Mechanism: Enzyme-Linked Receptors
Major types that are helpful drug targets include:
Mitogens and the Cell Cycle
Targeted Cancer Therapies
There are several types of targeted therapies against...

