Gene Signature Predicts Breast Cancer Outcome
Author Information
Author(s): Korkola James E, Blaveri Ekaterina, DeVries Sandy, Moore Dan H II, Hwang E Shelley, Chen Yunn-Yi, Estep Anne L H, Chew Karen L, Jensen Ronald H, Waldman Frederic M
Primary Institution: Comprehensive Cancer Center, University of California, San Francisco
Hypothesis
Can gene expression profiling predict outcomes in breast cancer patients?
Conclusion
A robust gene selection has identified a predictive gene set that may help in predicting outcomes for breast cancer patients.
Supporting Evidence
- The gene set correctly predicted outcomes in 62-65% of patients.
- The predictive gene set was validated in two independent data sets.
- The gene set was most effective in predicting outcomes for ER positive and node negative tumors.
Takeaway
Scientists studied breast cancer tumors to find a group of genes that can help predict how well patients will do after treatment.
Methodology
The study used expression microarrays to analyze 162 breast tumors and identified gene sets associated with disease-free survival.
Potential Biases
Potential bias due to sample selection and the inherent variability in gene expression across different tumor types.
Limitations
The predictive gene set may not be applicable to all breast cancer subtypes and requires further validation in diverse populations.
Participant Demographics
Included 140 invasive ductal tumors, 17 invasive lobular tumors, and other types, with varying ER status and nodal involvement.
Statistical Information
P-Value
p<0.00001
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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