TUESDAY, May 10 (HealthDay News) -- A genomic predictor combining estrogen receptor (ER) status with chemoresistance, chemosensitivity, and endocrine sensitivity may identify patients with newly diagnosed breast cancer with a high chance of survival following taxane and anthracycline chemotherapy, according to a study published in the May 11 issue of the Journal of the American Medical Association.
Christos Hatzis, Ph.D., from Nuvera Biosciences Inc. in Woburn, Mass., and colleagues developed and tested genomic predictors for taxane and anthracycline treatment in 310 newly diagnosed patients with invasive breast cancer. Predictive signatures stratified according to ER status were identified from gene expression microarrays for resistance and response to chemotherapy. Treatment sensitivity was then predicted by combining signatures for endocrine therapy sensitivity, chemoresistance, and chemosensitivity, and was independently validated by comparing with other reported genomic predictors in 198 patients.
The investigators found that, at an average follow-up of three years, 28 percent of patients in the validation cohort were predicted to be treatment sensitive and had a 56 percent probability of excellent pathologic response, a distant relapse-free survival (DRFS) of 92 percent, and an absolute risk reduction (ARR) of 18 percent. Survival was predicted in patients with ER-positive (30 percent predicted sensitive; DRFS, 97 percent; and ARR, 11 percent), and ER-negative (26 percent predicted sensitive; DRFS, 83 percent; and ARR, 26 percent) cancers, and was significant after adjusting for confounders. Other genomic predictors showed lower survival for patients predicted to respond to chemotherapy.
"The three-year DRFS of 92 percent for patients predicted to be treatment sensitive (negative predictive value) was higher than in the unselected cohort (79 percent), with a statistically significant ARR of 18 percent," the authors write.
Several of the study authors disclosed financial relationships with the pharmaceutical industry.
Abstract
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