medwireNews: A prognostic model based on eight DNA repair-related genes (DRGs) may help identify women with breast cancer who are at high risk for death, Chinese researchers report.
Zhijun Dai (Zhejiang University, Hangzhou) and colleagues hope that their model, which can divide patients into high- and low-risk categories, “can be applied in clinical treatments or research studies as a potential prognostic biomarker of [breast cancer].”
The researchers developed the model using The Cancer Genome Atlas tissue samples from 707 women with breast cancer and 112 healthy controls.
Transcriptome RNA sequencing initially identified 496 differentially expressed DRGs, of which 33 had prognostic value on univariate analysis. Of these, eight (MDC1, RPA3, MED17, DDB2, SFPQ, XRCC4, CYP19A1, and PARP3) were selected for the final model.
Dai and team note that the genes selected mainly involved vascular endothelial cell regulation pathways.
As reported in JAMA Network Open, the area under the receiver operating characteristic curve (AUC) was 0.708 for 3-year overall survival (OS) and 0.704 for 5-year OS.
Dai and team say these suggest “that the 8-gene signature had a good predictive accuracy.”
Indeed, the overall AUCs were greater than those for any individual gene in the model, which ranged from 0.367 to 0.685.
The findings were then validated in two cohorts from the Gene Expression Omnibus database.
In the first cohort (n=155, mean age 67 years), the AUCs for 3-year and 5-year OS were 0.717 and 0.772, respectively, while in the second cohort (n=122, mean age 58 years) they were 0.691 and 0.718, respectively.
Furthermore, multivariate analysis adjusted for factors associated with breast cancer survival revealed that the 8-DRG risk score was independently associated with outcome. Specifically, individuals classified as high risk had a significant 1.39-fold higher risk for death than those classified as low risk.
Dai and co-authors conclude: “Overall, from the perspective of clinical implications, our 8-DRG prognostic model gives reproducible and reliable results and, thus, can more accurately predict OS of patients with [breast cancer].”
They add that “large-scale multicenter cohorts are needed for external validation.”
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