| Literature DB >> 22318550 |
Agnieszka Kolacinska1, Wojciech Fendler, Janusz Szemraj, Bozena Szymanska, Ewa Borowska-Garganisz, Magdalena Nowik, Justyna Chalubinska, Robert Kubiak, Zofia Pawlowska, Maria Blasinska-Morawiec, Piotr Potemski, Arkadiusz Jeziorski, Zbigniew Morawiec.
Abstract
Pathologic complete response after neoadjuvant systemic treatment appears to be a valid surrogate for better overall survival in breast cancer patients. Currently, together with standard clinicopathologic assessment, novel molecular biomarkers are being exhaustively tested in order to look into the heterogeneity of breast cancer. The aim of our study was to examine an association between 23-gene real-time-PCR expression assay including ABCB1, ABCC1, BAX, BBC3, BCL2, CASP3, CYP2D6, ERCC1, FOXC1, GAPDH, IGF1R, IRF1, MAP2, MAPK 8, MAPK9, MKI67, MMP9, NCOA3, PARP1, PIK3CA, TGFB3, TOP2A, and YWHAZ receptor status of breast cancer core biopsies sampled before neoadjuvant chemotherapy (anthracycline and taxanes) and pathologic response. Core-needle biopsies were collected from 42 female patients with inoperable locally advanced breast cancer or resectable tumors suitable for downstaging, before any treatment. Expressions of 23 genes were determined by means of TagMan low density arrays. Analysis of variance was used to select genes with discriminatory potential between receptor subtypes. We introduced a correction for false discovery rates (presented as q values) due to multiple hypothesis testing. Statistical analysis showed that seven genes out of a 23-gene real-time-PCR expression assay differed significantly in relation to pathologic response regardless of breast cancer subtypes. Among these genes, we identified: BAX (p = 0.0146), CYP2D6 (p = 0.0063), ERCC1 (p = 0.0231), FOXC1 (p = 0.0048), IRF1 (p = 0.0022), MAP2 (p = 0.0011), and MKI67 (p = 0.0332). The assessment of core biopsy gene profiles and receptor-based subtypes, before neoadjuvant therapy seems to predict response or resistance and to define new signaling pathways to provide more powerful classifiers in breast cancer, hence the need for further research.Entities:
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Year: 2012 PMID: 22318550 DOI: 10.1007/s11033-012-1576-1
Source DB: PubMed Journal: Mol Biol Rep ISSN: 0301-4851 Impact factor: 2.316