A Genomic Predictor of Response and Survival Following Taxane-Anthracycline Chemotherapy for Invasive Breast Cancer

Abstract

CONTEXT Accurate prediction of who will (or won’t) have high probability of survival benefit from standard treatments is fundamental for individualized cancer treatment strategies. OBJECTIVE To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer. DESIGN Development of different predictive signatures for resistance and response to neoadjuvant chemotherapy (stratified according to estrogen receptor (ER) status) from gene expression microarrays of newly diagnosed breast cancer (310 patients). Then prediction of breast cancer treatment-sensitivity using the combination of signatures for: 1) sensitivity to endocrine therapy, 2) chemo-resistance, and 3) chemo-sensitivity. Independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response. SETTING Prospective multicenter study to develop and test genomic predictors for neoadjuvant chemotherapy. PATIENTS Newly diagnosed HER2-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens then endocrine therapy (if hormone receptor-positive). MAIN OUTCOME MEASURES Distant relapse-free survival (DRFS) if predicted treatment-sensitive and absolute risk reduction (ARR, difference in DRFS of the two predicted groups) at median follow-up (3 years), and their 95% confidence intervals (CI). RESULTS Patients in the independent validation cohort (99% clinical Stage II–III) who were predicted to be treatment-sensitive (28% of total) had DRFS of 92% (CI 85–100) and survival benefit compared to others (absolute risk reduction (ARR) 18%; CI 6–28). Predictions were accurate if breast cancer was ER-positive (30% predicted sensitive, DRFS 97%, CI 91–100; ARR 11%, CI 0.1–21) or ER-negative (26% predicted sensitive, DRFS 83%, CI 68–100; ARR 26%, CI 4–28), and were significant in multivariate analysis after adjusting for relevant clinical-pathologic characteristics. Other genomic predictors showed paradoxically worse survival if predicted to be responsive to chemotherapy. CONCLUSION A genomic predictor combining ER status, predicted chemo-resistance, predicted chemo-sensitivity, and predicted endocrine sensitivity accurately identified patients with survival benefit following taxane-anthracycline chemotherapy.

DNA Methylation Affects the SP1-regulated Transcription of FOXF2 in Breast Cancer Cells

“…Gene Expression Profiling Data Set and Data Analysis-The gene expression profiling data set from 427 breast cancer tissues with Gene Expression Omnibus accession number GSE25066 (16) was used to analyze the relationship between combined SP1 (probe set 214732_at) and FOXF2 (probe set 206377_at) mRNA expression levels and the distant metastasisfree survival (DMFS) of the patient. Among the 427 breast cancer patients, 189 cases were classified into the basal-like subtype, and 238 cases were classified into the luminal subtype based on the PAM50 signature; 110 cases developed distant metastasis within a 5-year follow-up.…”

“…To provide further clinical evidence for the SP1/FOXF2-regulated function in the progression of different breast cancer subtypes, we mined the SP1 and FOXF2 mRNA expression data from the gene expression profiling data set of 427 breast cancer tissues (Gene Expression Omnibus accession number GSE25066) (16) and analyzed the DMFS in patients with different SP1 and FOXF2 expression statuses in the basal-like and luminal subtypes. The patients were grouped into the high SP1/high FOXF2 mRNA-expressing group (n ϭ 111), low SP1/high FOXF2 mRNA-expressing group (n ϭ 65), high SP1/low FOXF2 mRNA-expressing group (n ϭ 154), and low SP1/low FOXF2 mRNA-expressing group (n ϭ 97) using the optimal cutoff values for SP1 and FOXF2 mRNA expression.…”

Quantitative assessment Ki-67 score for prediction of response to neoadjuvant chemotherapy in breast cancer

“…Attempts have also been made to define gene expression signatures that predict therapeutic response. [21][22][23][24][25] Unfortunately, most of these models do not outperform clinical nomograms. 26 Nonetheless, novel molecular biomarkers may provide an alternative approach to establishing determinants of chemoresistance.…”

Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer

“…The Wang cohort (GEO dataset GSE2034) was composed of 180 lymph-nodenegative relapse-free patients and 106 lymph-node-negative patients that developed a distant metastasis (22). The Hatzis cohort (GSE25066) included 310 newly diagnosed patients from a prospective multicenter study conducted at the M. D. Anderson Cancer Center and 198 validation patients (99% clinical stage II-III) who received sequential taxane and anthracycline chemotherapy (18). The Kao cohort (GSE20685) was used to identify molecular and clinical subtypes of BC through gene expression profiles of 327 samples (19).…”