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Quantitative copy number analysis by Multiplex Ligation-dependent Probe Amplification (MLPA) of BRCA1-associated breast cancer regions identifies BRCAness

2011; BioMed Central; Volume: 13; Issue: 5 Linguagem: Inglês

10.1186/bcr3049

1465-542X

Esther H. Lips, Nadja Laddach, Suvi Savola, Marieke A. Vollebergh, Anne M.M. Oonk, Alex L.T. Imholz, Lodewyk F.A. Wessels, Jelle Wesseling, Petra M. Nederlof, Sjoerd Rodenhuis,

Gene expression and cancer classification

Abstract Introduction Our group has previously employed array Comparative Genomic Hybridization (aCGH) to assess the genomic patterns of BRCA1-mutated breast cancers. We have shown that the so-called BRCA1-like aCGH profile is also present in about half of all triple-negative sporadic breast cancers and is predictive for benefit from intensified alkylating chemotherapy. As aCGH is a rather complex method, we translated the BRCA1 aCGH profile to a Multiplex Ligation-dependent Probe Amplification (MLPA) assay, to identify both BRCA1-mutated breast cancers and sporadic cases with a BRCA1-like aCGH profile. Methods The most important genomic regions of the original aCGH based classifier (3q22-27, 5q12-14, 6p23-22, 12p13, 12q21-23, 13q31-34) were mapped to a set of 34 MLPA probes. The training set consisted of 39 BRCA1-like aCGH breast cancers and 45 non-BRCA1-like aCGH breast cancers, which had previously been analyzed by aCGH. The BRCA1-like aCGH group consisted of germline BRCA1-mutated cases and sporadic tumours with low BRCA1 gene expression and/or BRCA1 promoter methylation. We trained a shrunken centroids classifier on the training set and validation was performed on an independent test set of 40 BRCA1-like aCGH breast cancers and 32 non-BRCA1-like aCGH breast cancer tumours. In addition, we validated the set prospectively on 69 new triple-negative tumours. Results BRCAness in the training set of 84 tumours could accurately be predicted by prediction analysis of microarrays (PAM) (accuracy 94%). Application of this classifier on the independent validation set correctly predicted BRCA-like status of 62 out of 72 breast tumours (86%). Sensitivity and specificity were 85% and 87%, respectively. When the MLPA-test was subsequently applied to 46 breast tumour samples from a randomized clinical trial, the same survival benefit for BRCA1-like tumours associated with intensified alkylating chemotherapy was shown as was previously reported using the aCGH assay. Conclusions Since the MLPA assay can identify BRCA1-deficient breast cancer patients, this method could be applied both for clinical genetic testing and as a predictor of treatment benefit. BRCA1-like tumours are highly sensitive to chemotherapy with DNA damaging agents, and most likely to poly ADP ribose polymerase (PARP)-inhibitors. The MLPA assay is rapid and robust, can easily be multiplexed, and works well with DNA derived from paraffin-embedded tissues.