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

Esther H Lips,Nadja Laddach,Suvi P Savola,Petra M Nederlof,Marieke A Vollebergh,Anne Mm Oonk,Jelle Wesseling,Sjoerd Rodenhuis,Alex Lt Imholz,Lodewyk Fa Wessels

doi:10.1186/bcr3049

Abstract

IntroductionOur 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-likeaCGH 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 BRCA1aCGH profile to a Multiplex Ligation-dependent Probe Amplification (MLPA) assay, to identify both BRCA1-mutated breast cancers and sporadic cases with a BRCA1-likeaCGH profile.MethodsThe 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-likeaCGH breast cancers and 45 non-BRCA1-likeaCGH breast cancers, which had previously been analyzed by aCGH. The BRCA1-likeaCGH 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-likeaCGH breast cancers and 32 non-BRCA1-likeaCGH breast cancer tumours. In addition, we validated the set prospectively on 69 new triple-negative tumours.ResultsBRCAness 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.ConclusionsSince 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.

Highlights

Our group has previously employed array Comparative Genomic Hybridization to assess the genomic patterns of BRCA1-mutated breast cancers
We have hypothesized that these tumours harbour a homologous recombination deficiency and would be very sensitive to double strand break (DSB)-inducing chemotherapy, similar to tumours arising in BRCA1-mutation carriers. In agreement with this assumption, we have demonstrated in a retrospective analysis of a randomized controlled trial that the so-called BRCA1-likeaCGH profile was strongly predictive for benefit from intensive carboplatin-based alkylating chemotherapy [10]
Results test set prediction The classifier trained on the training set was tested in a new group of 72 tumours. This test set consisted of (i) 18 tumours from the clinical genetics centre; (ii) 8 tumours from the neoadjuvant series; and (iii) 46 triplenegative tumour samples from a randomized controlled clinical trial that studied the efficacy of intensified alkylating chemotherapy in breast cancer

Summary

Introduction

Our group has previously employed array Comparative Genomic Hybridization (aCGH) to assess the genomic patterns of BRCA1-mutated breast cancers. Our group has employed aCGH to assess the genomic patterns of BRCA1-mutated breast cancers [6] This has resulted in a BRCA1-like classifier based on specific aberrations of BRCA1-mutated breast cancers compared to sporadic tumours. This classifier allows identification of familial breast cancer cases in patients whose germ line BRCA1mutation status is unknown [6] or assists in the classification of BRCA1 variants of unknown significance [6,7]. It is currently employed in routine diagnostics in our clinical genetic centre. This concept of “BRCAness” in sporadic cancers is under study in many centres as it may have implications for treatment selection [14,15,16]

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Conclusion