Several studies have linked various molecular biomarkers, including DRGs, with breast cancer outcomes, but there is currently no accurate prediction signature for DRGs.
Dr. Zhijun Dai of Zhejiang University College of Medicine, in Hangzhou, China, and colleagues used data from the Cancer Genome Atlas and Gene Expression Omnibus databases to construct a DRG-based prognostic model to predict three- and five-year overall survival in women with breast cancer.
Multivariate Cox proportional-hazards regression analysis identified eight DRGs (MDC1, RPA3, MED17, DDB2, SFPQ, XRCC4, CYP19A1, and PARP3) that were incorporated into a total risk score, with higher scores representing worse prognosis.
The discriminative accuracy of the score (as assessed by area under the curve of the receiver-operating characteristic curve) was 70.8% for three-year survival and 70.4% for five-year survival, the researchers report in JAMA Network Open.
The risk score showed similar predictive accuracy in two external validation sets of women with breast cancer.
The risk score remained an independent predictor of overall survival after adjustment for clinicopathologic characteristics.
Gene Ontology analyses revealed that angiogenesis regulation pathways were the main enriched pathways in women with high risk scores. And the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed enrichment of three cancer-related pathways (hedgehog signaling, retinoic acid-inducible gene 1-like receptor signaling, and cytosolic DNA-sensing) in the high-risk group.
"The 8-DRG signature is an independent risk factor associated with breast cancer," the authors conclude. "We hope that it can be applied in clinical treatments or research studies as a potential prognostic biomarker of breast cancer."
The researchers report no conflicts of interest.
Dr. Dai did not respond to a request for comments.
By Reuters Staff
SOURCE: https://bit.ly/33zwmcO JAMA Network Open, online October 5, 2020.
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