3D Culture Model Predicts Breast Cancer Outcomes
Author Information
Author(s): Martin Katherine J., Patrick Denis R., Bissell Mina J., Fournier Marcia V.
Primary Institution: GlaxoSmithKline, Collegeville, Pennsylvania, United States of America
Hypothesis
The ability of a gene signature to demonstrate predictive power across different independent datasets supports the conclusion that it is composed of key, biologically relevant genes.
Conclusion
The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer.
Supporting Evidence
- The 3D-signature was validated across three independent datasets.
- At 10 years, the probability of positive outcome was significantly higher in the good-prognosis group compared to the poor-prognosis group.
- The 3D-signature was a strong independent factor in predicting breast cancer outcome.
Takeaway
Scientists found a special set of genes that can help predict how well breast cancer patients will do, using a lab model that mimics real breast tissue.
Methodology
The study used a 3D culture model of non-malignant human mammary epithelial cells to identify a gene signature that predicts breast cancer prognosis across three independent datasets.
Limitations
The smaller dataset of Sorlie may have had insufficient numbers of patients to achieve a significant result for the 3D signature in the multivariable analysis.
Participant Demographics
The study included breast cancer patients from three independent datasets with varying ER status.
Statistical Information
P-Value
p<0.0001
Confidence Interval
95% CI 3.0 to 12.2
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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