Researchers have developed a novel predictive test that included genomic signatures that indicated chemoresistance, chemosensitivity and endocrine sensitivity may help predict likelihood of survival following chemotherapy in women diagnosed with breast cancer.
Identification of patients with high likelihood of survival following a standard chemotherapy regimen (and then endocrine therapy, if estrogen receptor [ER]-positive) would reaffirm a treatment decision regarding the use of chemotherapy. "Conversely, identification of those with significant risk of relapse despite standard chemotherapy could be used to advise participation in an appropriate clinical trial of potentially more effective treatment," according to background information in the article.
Christos Hatzis, Ph.D., of Nuvera Biosciences Inc., Woburn, Mass., and colleagues conducted a study, from June 2000 to March 2010, to develop a predictor of response and survival from chemotherapy for patients with invasive breast cancer. Patients were those with newly diagnosed ERBB2 (HER2 or HER2/neu)-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens (then endocrine therapy if estrogen receptor-positive). Different predictive signatures for resistance and response to preoperative chemotherapy were developed from gene expression microarrays (special type of testing) of newly diagnosed breast cancer (n = 310 patients). Breast cancer treatment sensitivity was predicted using the combination of signatures for sensitivity to endocrine therapy, chemoresistance, and chemosensitivity, with independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response.
The researchers found that the chemopredictive test algorithm had a positive predictive value (PPV) of 56 percent for prediction of pathologic response after excluding patients with predicted endocrine sensitivity. In 28 percent of patients predicted to be treatment sensitive, the 3-year distant relapse-free survival (DRFS) was 92 percent, and there was an absolute risk reduction (ARR) of 18 percent. Patients predicted to be treatment sensitive had a 5-fold reduction in the risk of distant relapse. "Overall, there was a significant association between predicted sensitivity to treatment and improved DRFS," the authors write.
Treatment sensitivity was predicted in 37 of 123 patients (30 percent) in the ER-positive phenotypic subgroup and in 19 of 74 (26 percent) in the ER-negative subgroup. In the ER-positive subgroup, these patients had a DRFS of 97 percent and a significant ARR of 11 percent at 3 years of follow-up. Patients with ER-negative cancer predicted to be treatment sensitive had significantly improved 3-year DRFS of 83 percent, an ARR of 26 percent and a positive predictive value for pathologic response of 83 percent.
The researchers note that other genomic predictors showed paradoxically worse survival for patients predicted to be responsive to chemotherapy.
"Any test based on predicted sensitivity, resistance, or both to guide the selection of a standard adjuvant treatment regimen should predict a high probability of survival for patients predicted to be treatment sensitive (negative predictive value, no relapse if predicted to be treatment sensitive) and a clinically meaningful survival difference between patients predicted to be treatment sensitive and insensitive (ARR) as well as improve on predictions using existing clinical-pathological information. The performance of our predictive test meets these criteria in an independent validation cohort," the authors write.
The researchers add that a predictive test with this performance could potentially assist medical decision-making as it could identify patients with stage II-III, ER-positive and ERBB2-negative breast cancer with excellent 3-year and 5-year DRFS (97 percent) following a standard adjuvant treatment.
The authors conclude that it is "imperative to continue to evaluate the predictive accuracy of this test in additional validation studies."