Copy Number Based Prognostic Model for Early-Stage Breast Cancer
Author Information
Author(s): Patricia A. Thompson, Abenaa M. Brewster, Kim-Anh Do, Veerabhadran Baladandayuthapani, Bradley M. Broom, Mary E. Edgerton, Karin M. Hahn, James L. Murray, Aysegul Sahin, Spyros Tsavachidis, Yuker Wang, Li Zhang, Gabriel N. Hortobagyi, Gordon B. Mills, Melissa L. Bondy
Primary Institution: MD Anderson Cancer Center, University of Texas
Hypothesis
Some chromosomal changes in breast cancer may influence metastatic potential independent of expression subtypes.
Conclusion
The study identifies a set of 19 copy number imbalances that can significantly improve the prediction of recurrence risk in early-stage breast cancer.
Supporting Evidence
- The 19-CNI model significantly outperformed clinical models in predicting recurrence.
- Specific CNIs were identified that correlate with higher recurrence risk.
- The model showed improved prognostication for ER–, HER2+, and luminal B tumors.
- Patients with high-risk CNI signatures had a significantly higher probability of recurrence.
Takeaway
Researchers found specific changes in the DNA of breast cancer tumors that can help predict if a patient is likely to have a recurrence of cancer.
Methodology
High-density molecular inversion probe arrays were used to determine copy number gains and losses in breast tumors, and a boosting strategy was applied to fit hazards models for recurrence.
Limitations
The study may be limited by the use of older samples and the approximation of tumor subtypes based on tumor markers.
Participant Demographics
{"age":{"mean":54.4,"standard_deviation":12.6},"race":{"White":715,"Black":125,"Hispanic":123,"Other":8}}
Statistical Information
P-Value
p<0.001
Confidence Interval
95% CI for C-Index ± 0.02
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website