Brca1-Like Profile As Predictive Biomarker In Non Myeloablative Chemotherapy (Gain Study)
CANCER RESEARCH(2016)
Abstract
Background: The BRCA1-like copy number (CN) profile can be used as a biomarker to predict which stage III breast cancer patients benefit from myeloablative, DNA double-strand-break (DSB)-inducing chemotherapy. In addition, a BRCA1-like gene expression classifier, derived from the BRCA1-like CN profile, can predict which patient group will achieve an increased pathological complete remission rate on a standard neoadjuvant regimen complemented with carboplatin/veliparib. A non-myeloablative, dose-dense schedule of epirubicin, paclitaxel and cyclophosphamide (ETC) is used in the clinic to treat stage III patients. Since ETC contains an intensified dose of DNA DSB-inducing cyclophosphamide, we tested the BRCA1-like CN profile as a predictive biomarker for ETC benefit in the GAIN trial. Methods: The GAIN trial was a prospective, multi-center, non-blinded, randomized phase III trial. Eligibility comprised histologically confirmed invasive breast cancer with at least one positive axillary or internal mammary lymph node and no signs of distant metastases. The allocated adjuvant treatment was intensified chemotherapy with sequential E (150 mg/m2), T (225 mg/m2) and C (2500, after amendment 2000 mg/m2) each 3 cycles every 2 weeks (ETC) or concurrent E (112.5 mg/m2) and C (600 mg/m2) for 4 cycles every 2 weeks followed by 10 cycles of weekly T (67.5 mg/m2) combined with 4 cycles of capecitabine (2000mg/m2) on day 1-14 in a 3-weekly cycle (EC-TX). Only the triple negative patients were used for these analyses. For samples with good quality DNA extracted from formalin-fixed paraffin-embedded tumor tissue, a library was prepared and sequenced on an Illumina HiSeq2000 platform. Copy number estimates were extracted from the sequence data by normalizing GC-content and mappability corrected read counts to the average read count. These CN profiles were classified as either BRCA1-like or non-BRCA1-like using a previously established shrunken centroid classifier with an established cut-off. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method, the difference in survival was analysed using log-rank tests. Multivariate analyses were done by generating Cox regression models with important prognostic factors. Results: Out of 424 triple negative patients, 166 patients with available tissue and a tumour cell content of at least 60% were analysed for BRCA1-like status and included in the analyses (classified as BRCA1-like: n=122). Based on clinicopathological characteristics, these patients were similar to the total group of triple negative participants. In the BRCA1-like patients, there was no significant difference in DFS or OS between ETC and EC-TX (log-rank tests n.s.). In accordance, Cox regression models confirmed these findings. Conclusion: In contrast to the predictive value of the BRCA1-like profile in myeloablative chemotherapy, it could not predict survival benefit for a non-myeloablative, non-platinum-/veliparib-containing regimen in this study population. An intensified dose of cyclophosphamide resulted in similar outcomes in BRCA1-like patients as addition of capecitabine to standard chemotherapy. These results help to define the appropriate application of the BRCA1-like profile as a predictive biomarker. Citation Format: van Rossum AGJ, Schouten PC, Weber KE, Nekljudova V, Denkert C, von Minckwitz G, Karn T, Mobus VJ, Linn SC, Loibl S, Marme F. BRCA1-like profile as predictive biomarker in non myeloablative chemotherapy (GAIN study). [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-28.
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