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Updated: Jun 7, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Gene Expression and Pathway Activation Biomarkers of Breast Cancer Sensitivity to Taxanes
Daniil Luppov1,2, Maxim Sorokin2,3,4, Marianna Zolotovskaya5,2
1Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia. luppov.dv@phystech.su.
Abstract:
Taxanes are one of the most widely used classes of breast cancer (BC) therapeutics. Despite the long history of clinical usage, the molecular mechanisms of their action and cancer resistance are still not fully understood. Here we aimed to identify gene expression and molecular pathway activation biomarkers of BC sensitivity to taxane drugs paclitaxel and docetaxel. We used to our knowledge the biggest collection of clinically annotated publicly available literature BC gene expression data (12 datasets, n = 1250) and the experimental clinical BC cohort (n = 12). Seven literature datasets were used for biomarker discovery (n = 914), and the remaining five literature plus one experimental datasets (n = 336) - for the validation. We totally found 34 genes and 29 molecular pathways which could strongly discriminate good and poor responders to taxane treatments. The biomarker genes and pathways were associated with molecular processes related to formation of mitotic spindle and centromeres, and with the spindle assembly mitotic checkpoint. Furthermore, we created gene expression and pathway activation signatures predicting BC response to taxanes. These signatures were tested on the validation BC cohort and demonstrated strong biomarker potential reflected by mean AUC values of 0.76 and 0.77, respectively, which outperforms previously reported analogs. Taken together, these findings can deepen our understanding of mechanism of action of taxanes and potentially improve personalization of treatment in BC.
Insights
Researchers identified gene expression and molecular pathway biomarkers to predict breast cancer (BC) response to taxane chemotherapy. These findings enhance understanding of taxane mechanisms and aid personalized BC treatment.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Taxanes are vital breast cancer (BC) therapeutics, but their mechanisms of action and resistance remain incompletely understood.
- Identifying reliable biomarkers for taxane response is crucial for optimizing BC treatment strategies.
Purpose of the Study:
- To discover gene expression and molecular pathway biomarkers predicting BC sensitivity to taxanes (paclitaxel and docetaxel).
- To develop and validate predictive signatures for BC response to taxane-based therapies.
Main Methods:
- Utilized a large collection of publicly available BC gene expression data (12 datasets, n=1250) for biomarker discovery and validation.
- Employed an experimental clinical BC cohort (n=12) for validation of discovered signatures.
- Identified 34 genes and 29 molecular pathways discriminating between good and poor responders to taxanes.
Main Results:
- Discovered biomarkers associated with mitotic spindle formation, centromeres, and spindle assembly checkpoint.
- Developed gene expression and pathway activation signatures with strong predictive potential.
- Validation cohort showed high performance (mean AUC 0.76-0.77), outperforming previous analogs.
Conclusions:
- The identified biomarkers and signatures offer a deeper understanding of taxane action in BC.
- These findings hold potential for improving personalized treatment strategies for breast cancer patients receiving taxanes.
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