BRCAness digitalMLPA profiling predicts benefit of intensified platinum-based chemotherapy in triple-negative and luminal-type breast cancer

Breast cancers arising in women with a BRCA1 or BRCA2 germline mutation are characterized by genomic instability. As both BRCA1 and BRCA2 play a role in the process of homologous recombination, non-functioning BRCA genes result in incorrect DNA repair, leading to gross genomic instability. Previously, our group has shown that BRCA1- and BRCA2-mutated tumors have a specific pattern of chromosomal gains and losses [1‐3]. These specific genomic regions were used to develop a BRCA1-like and a BRCA2-like classifier. In follow-up studies, we showed that these classifiers could be used to identify germline BRCA1- or BRCA2-mutated cases, but also tumors with other mechanisms of BRCA1 or BRCA2 inactivation such as BRCA1 promoter methylation [1, 4, 5]. In addition, the classifiers have been used in the classification of BRCA1 variants of unknown significance (VUS) [2].

Interestingly, we showed that the classifiers could not only be used to identify mechanisms of BRCA inactivation, but could also be used to predict treatment benefit. We hypothesized that a BRCA1-like or BRCA2-like profile is a read-out for a homologous recombination deficiency (HRD) phenotype and could therefore indicate tumors which would be highly sensitive to DNA-damaging agents. In several studies, we showed a remarkable benefit of high-dose alkylating chemotherapy in patients with a BRCA1-like or BRCA2-like profile [6‐9]. In addition to high-dose chemotherapy, a gene expression-based BRCA1ness test, derived from the DNA-based BRCA1-like classifier, could predict benefit from the addition of veliparib/carboplatin to paclitaxel in the ISPY2 trial [10]. The currently presented BRCA-like test could function as a companion diagnostic test.

For a clinical test, it is essential that the method is highly reliable, has a fast turnaround time, and works on small quantities of paraffin-embedded tissue material. Multiplex ligation-dependent probe amplification (MLPA) is an established method and a standardized assay applied in routine diagnostics worldwide [11‐15]. MLPA is a method based on the amplification and relative quantification of the ligated adjacent probes, which can target up to 50 different genomic regions that show diagnostically or clinically significant copy number changes in patient samples [11]. There are several advantages of MLPA over other copy number profiling methods: its fast turnaround time, suitable for degraded paraffin-embedded material, and use of standard (diagnostic) molecular laboratory equipment. In the past, we developed a multiplex ligation-dependent probe amplification (MLPA) assay to perform a BRCA1-like classification based on 34 MLPA probes [16]. The BRCA2-like copy number profile contains threefold as many genomic regions as the BRCA1-like profile, making it impossible to design a MLPA. Recently, digitalMLPA was introduced as a novel technology to measure copy number aberrations on 700 genomic locations [17], making it a perfect technique for combined BRCA1-like and BRCA2-like profiling.

In the current study, we developed a digitalMLPA assay to assess both the BRCA1-like and BRCA2-like patterns. We validated the digitalMLPA assay on an independent sample cohort. In addition, we profiled samples from a randomized controlled trial [18], to determine if the digitalMLPA has treatment predictive value. We showed that the assay could identify both triple-negative and luminal-type tumors with a remarkable good survival after high-dose double-strand break (DSB)-inducing chemotherapy.

In this study, we developed a novel digitalMLPA assay to assess BRCA1-like and BRCA2-like copy number profiles within one assay. We showed an accuracy of 91% for the BRCA1-like classification and 82% for the BRCA2-like classification using the array-based BRCA-like classification as the gold standard. The digitalMLPA correctly classified most BRCA1-mutated, BRCA1-methylated, and BRCA2-mutated tumors, with respectively 88%, 96%, and 93% correct classification. The digitalMLPA had treatment predictive power: the test could identify both TN and luminal-type tumors with remarkable good responses on high-dose chemotherapy.

The BRCA1-like and BRCA2-like classifiers were originally developed to identify BRCA1 and BRCA2 deficiency and could support decision-making in genetic counseling. We previously showed that the classifiers could identify tumors with other mechanisms of BRCA1 or BRCA2 inactivation such as promoter methylation [1, 4, 5]. In addition to the role of the test in clinical genetics decision-making, the BRCA1-like and BRCA2-like classifiers have shown to have treatment predictive value [6‐8, 21]. As BRCA1 and BRCA2 play a role in the process of DNA double-strand break repair, we believe that a copy number profile resembling BRCA1- or BRCA2-mutated tumors could indicate the specific chromosomal instability associated with defective DNA repair, i.e., HRD. A BRCA1-like or BRCA2-like profile could therefore be considered as a readout for HRD. In addition to our BRCA1/2-like tests, other (commercially) available HRD tests are on the market for breast and ovarian cancer. These are either based on genomics scars [23], mutational signatures [24], or point mutations in homologous recombination repair genes [25]. In ovarian cancer, the highest benefit of niraparib was seen in patients with HRD tumors [26, 27]. In breast cancer, trials in the (neo) adjuvant setting showed higher responses on platinum salts or alkylating chemotherapy for patients with HRD tumors vs. patients with non-HRD tumors [28, 29]. However, the lack of a control arm was a flaw in these studies [30, 31]. Of note, a randomized trial in the neoadjuvant setting comparing paclitaxel single agent with cisplatin single agent showed higher responses for HRD tumors in both arms, indicating that this test is not predictive for selective benefit of DNA-damaging agents [32]. Furthermore, in the advanced breast cancer TNT trial, no association was observed between HRD status and response rate [33]. In this latter trial, an additional explanation for genomic scars having less predictive power is that most patients were already pre-treated by other chemotherapy agents. Resistance might already have been occurred in these patients [34]. Although patients with BRCAness tumors might have benefit from conventional types of DNA-damaging therapy, like FEC, we believe that BRCAness patients will have additional benefit of high-dose DNA-damaging therapies, like the regimen applied in the Dutch high dose trial, as these are in particular highly vulnerable for this kind of tumors [6, 7]. Results of in vitro and in vivo studies point in the same direction [35].

Our BRCA1-like and BRCA2-like classifiers are breast cancer subtype specific. The BRCA1-like profile is mainly observed in TN tumors, while the BRCA2-like profile is mainly observed in luminal-type cancer. As TN and luminal-type breast tumors have distinct molecular profiles, developing two distinct classifiers, based on each subtype-specific genomic profiles, resulted in highly specific classifiers. The BRCA1-like classifier has been validated in three different studies as a predictor of high-dose chemotherapy benefit [6‐8]. Currently, a phase III trial is running in stage 3 triple-negative breast cancer, applying the BRCA1-like MLPA test (NCT02810743). For luminal-type breast cancer, the digitalMLPA is an easy-to-use, robust assay, to assess the BRCA2-like phenotype. With such a test, we could easily test retrospective series and generate data on lumina-type breast cancer, which is currently lacking in the literature due to the focus on TN tumors. There is evidence from the literature that a small group of luminal tumors may also have benefit from HRD-inducing chemotherapy. Manie et al. showed that HRD testing using genomic instability assays in luminal-type tumors resulted in a threefold increase in the identification of HRD tumors than by HRD testing solely based on BRCA mutation profiling [36]. Our BRCA2-like test has the potential to identify a subpopulation of luminal-type tumors that might benefit from high-dose DSB-inducing chemotherapy. The fact that the BRCA1-like and BRCA2-like tests are combined in one assay facilitates routine testing in a diagnostic lab.

Advantages of digitalMLPA, as compared to array- or NGS-based BRCA-like testing, include a high dynamic range for copy number detection, a robust assay, the good performance on degraded DNA, and the low input amount (≥ 20 ng) of DNA [17]. Especially, in patient samples with limited tissue material, such as core biopsies, a low input amount is a prerequisite. With digitalMLPA, a large number of genomic loci of interest can be analyzed for copy number alterations in a single reaction with low hands-on time, and results are available within 36 h. Because of the targeted approach, data analysis and result interpretation are easier than with array-based analysis and can be performed in any routine diagnostic setting.

A limitation of the current study is that we could not profile the whole randomized trial population, due to missing tissue blocks or a limited amount of DNA available. The series profiled was enriched for triple-negative and BRCA1-like tumors, as these were the samples with enough DNA left for successful digital MLPA analysis (Table 1 (D)). As we know that BRCA1-like tumors have a very low HR (ranging from 0.05 to 0.19 [6, 7]) for high-dose chemotherapy, the overall HR (0.38) in our study population is lower than in the total HER2-negative trial population (HR 0.68) [37]. However, even in this selected subgroup, we showed a significant interaction between treatment benefit and digitalMLPA BRCAness status, indicating the strong predictive power of our digitalMLPA assay. Independent validation of a different cohort will be necessary; we are currently exploring possibilities. Another suggestion for improvement would be to train a specific classifier to predict treatment benefit. However, the BRCA-like classifiers are based on the biology of BRCA tumors and thus are not merely “data-driven,” which could be seen as a strength. The third limitation is the slightly worse performance of the BRCA2-like classifier. We noticed before that BRCA2-like tumors are more alike sporadic luminal-type tumors. It appeared more difficult to find specific discriminatory regions [1, 38].

DigitalMLPA BRCAness analysis shows results comparable to previously published array-based BRCA-like testing. The digitalMLPA is a fast and reliable method to detect copy number changes in relevant regions for BRCA1- and BRCA2-like classification in one experiment in breast cancer samples. We showed that the digitalMLPA assay had treatment predictive power, in both TN and luminal-type tumors. Independent validation of patient cohorts treated with DNA DSB-inducing chemotherapy is warranted.