As we move forward, clinical decision making will rely more heavily on the genetic characteristics of the tumor and less on the clinical characteristics. Thus, identification and subsequent validation of biomarkers that can be used to accurately estimate the recurrence risk of breast cancer is a high priority. To this end, our hypothesis is that breast cancer subtypes, based upon hormone receptor and HER2 status, possess a unique constellation of genomic mutations that manifest in specific alterations in gene expression and protein signaling pathways. We further hypothesize that these major breast cancer phenotypes, contain specific signaling pathway alterations that are class-specific, drive the disease process itself, and most critically serve as candidates for biomarkers for therapy stratification and effective drug targets. Our overall objective is to identify gene sets within different subgroups of patients through molecular profiling of formalin-fixed, paraffin-embedded (FFPE) tumor samples from the E2197 clinical trial that will have prognostic utility in predicting recurrence. The ECOG E2197 clinical trial is a completed Phase III multisite trial that involved the randomization of patients (2,952) with primary breast cancer to compare the effectiveness of doxorubicin/docetaxel (AT) versus doxorubicin/cyclophosphamide (AC), in treating women with node-positive and high risk node-negative breast cancer. Our primary objective is to identify genes based upon their ability to predict recurrence within the different subgroups of E2197 patients. Additional objectives will involve 1) comparing the data generated in the whole genome (WG)-DASL (cDNA-mediated annealing, selection and ligation) assay for the OncotypeDX set of genes with data from the OncotypeDX assay which will serve as a validation of the WG-DASL platform;2) defining a set of the most significant individual genes as prognostic markers;3) comparing the prognostic value of the OncotypeDX assay from a previous study with gene sets determined in this study;4) comparing the prognostic value of genes selected from a set of 371 genes from a previous study with genes determined in this study;and 5) comparing the prognostic value of the PAM50 gene set with genes determined in this study. Toward that end, total RNA will be prepared from 868 FFPE tumor samples from E2197 classified into 4 patient subgroups as follows: 1) HR+, HER2-;2) HR+, HER2+;3) HR-, HER2+;4) HR-, HER2- and . Expression profiling of the extracted RNA will be performed on the WG-DASL platform which will interrogate 24,526 mRNA transcripts. A signature set of genes will be selected based upon their ability to predict the recurrence-free interval (RFI) as the primary endpoint and secondary endpoints of breast cancer-free survival (BCFS), and overall survival (OS). Potential biomarkers will be validated by TaqMan quantitative real-time polymerase chain reaction (qRT-PCR). Prognostic biomarkers will be prospectively validated in a subsequent study.
Available adjuvant chemotherapies, such as doxorubicin, docetaxel and cyclophosphamide, and combinations thereof, are effective adjuvant treatment for the large population of women with node-positive early-stage breast cancer, but many patients still relapse and die of their disease. Thus, identification and subsequent validation of biomarkers that can be used to accurately estimate the risk of recurrence of breast cancer is a high priority. Our hypothesis is that the major breast cancer phenotypes contain specific signaling pathway alterations that are class-specific, drive the disease process itself, and most critically serve as candidates for biomarkers for therapy stratification and effective drug targets.
| Willis, Scooter; De, Pradip; Dey, Nandini et al. (2015) Enriched transcription factor signatures in triple negative breast cancer indicates possible targeted therapies with existing drugs. Meta Gene 4:129-41 |
