The Prosigna 50-gene profile and responsiveness to adjuvant anthracycline-based chemotherapy in high-risk breast cancer patients.
Maj-Britt JensenAnne-Vibeke LænkholmEva BalslevWesley BuckinghamSean FerreeVesna GlavicicJeanette Dupont JensenAnn Søegaard KnoopHenning T MouridsenDorte NielsenTorsten O NielsenBent EjlertsenPublished in: NPJ breast cancer (2020)
The DBCG89D trial randomized high-risk early breast cancer patients to adjuvant CMF (cyclophosphamide, methotrexate and fluorouracil) or CEF (cyclophosphamide, epirubicin and fluorouracil). Prosigna assays were performed by researchers with no access to clinical data. Time to distant recurrence (DR) was the primary endpoint, time to recurrence (TR) and overall survival (OS) secondary. Among the 980 Danish patients enrolled, Prosigna results were obtained in 686. Continuous ROR score was associated with DR for CMF (adjusted hazard ratio (HR) 1.20, 95% CI 1.09-1.33), and for CEF (HR 1.04, 95% CI 0.92-1.18), P interaction = 0.06. DR was significantly longer in CEF compared to CMF treated patients with Her2-enriched tumors (HR 0.58, 95% CI 0.38-0.86), but not in patients with luminal tumors. Heterogeneity of treatment effect was significant for TR and OS. In this prospective-retrospective analysis, patients with Her2-enriched breast cancer derived substantial benefit from anthracycline chemotherapy whereas anthracyclines are not an essential component of chemotherapy for patients with luminal subtypes. The benefit of CEF vs. CMF correlated with increasing ROR Score.
Keyphrases
- high dose
- locally advanced
- editorial comment
- early stage
- free survival
- end stage renal disease
- phase iii
- low dose
- newly diagnosed
- ejection fraction
- phase ii
- clinical trial
- open label
- peritoneal dialysis
- prognostic factors
- study protocol
- lymph node
- rectal cancer
- dna methylation
- copy number
- single cell
- patient reported outcomes
- electronic health record
- radiation therapy
- young adults
- chemotherapy induced
- artificial intelligence
- transcription factor
- placebo controlled
- deep learning