BRCA1-like profile predicts benefit of tandem high dose epirubicin-cyclophospamide-thiotepa in high risk breast cancer patients randomized in the WSG-AM01 trial.

BRCA1 is an important protein in the repair of DNA double strand breaks (DSBs), which are induced by alkylating chemotherapy. A BRCA1-like DNA copy number signature derived from tumors with a BRCA1 mutation is indicative for impaired BRCA1 function and associated with good outcome after high dose (HD) and tandem HD DSB inducing chemotherapy. We investigated whether BRCA1-like status was a predictive biomarker in the WSG AM 01 trial. WSG AM 01 randomized high-risk breast cancer patients to induction (2× epirubicin-cyclophosphamide) followed by tandem HD chemotherapy with epirubicin, cyclophosphamide and thiotepa versus dose dense chemotherapy (4× epirubicin-cyclophospamide followed by 3× cyclophosphamide-methotrexate-5-fluorouracil). We generated copy number profiles for 143 tumors and classified them as being BRCA1-like or non-BRCA1-like. Twenty-six out of 143 patients were BRCA1-like. BRCA1-like status was associated with high grade and triple negative tumors. With regard to event-free-survival, the primary endpoint of the trial, patients with a BRCA1-like tumor had a hazard rate of 0.2, 95% confidence interval (CI): 0.07-0.63, p = 0.006. In the interaction analysis, the combination of BRCA1-like status and HD chemotherapy had a hazard rate of 0.19, 95% CI: 0.067-0.54, p = 0.003. Similar results were observed for overall survival. These findings suggest that BRCA1-like status is a predictor for benefit of tandem HD chemotherapy with epirubicin-thiotepa-cyclophosphamide.

Future of Dutch NGS-Based Newborn Screening: Exploring the Technical Possibilities and Assessment of a Variant Classification Strategy.

In this study, we compare next-generation sequencing (NGS) approaches (targeted panel (tNGS), whole exome sequencing (WES), and whole genome sequencing (WGS)) for application in newborn screening (NBS). DNA was extracted from dried blood spots (DBS) from 50 patients with genetically confirmed inherited metabolic disorders (IMDs) and 50 control samples. One hundred IMD-related genes were analyzed. Two data-filtering strategies were applied: one to detect only (likely) pathogenic ((L)P) variants, and one to detect (L)P variants in combination with variants of unknown significance (VUS). The variants were filtered and interpreted, defining true/false positives (TP/FP) and true/false negatives (TN/FN). The variant filtering strategies were assessed in a background cohort (BC) of 4833 individuals. Reliable results were obtained within 5 days. TP results (47 patient samples) for tNGS, WES, and WGS results were 33, 31, and 30, respectively, using the (L)P filtering, and 40, 40, and 38, respectively, when including VUS. FN results were 11, 13, and 14, respectively, excluding VUS, and 4, 4, and 6, when including VUS. The remaining FN were mainly samples with a homozygous VUS. All controls were TN. Three BC individuals showed a homozygous (L)P variant, all related to a variable, mild phenotype. The use of NGS-based workflows in NBS seems promising, although more knowledge of data handling, automated variant interpretation, and costs is needed before implementation.

Robust BRCA1-like classification of copy number profiles of samples repeated across different datasets and platforms.

Breast cancers with BRCA1 germline mutation have a characteristic DNA copy number (CN) pattern. We developed a test that assigns CN profiles to be 'BRCA1-like' or 'non-BRCA1-like', which refers to resembling a BRCA1-mutated tumor or resembling a tumor without a BRCA1 mutation, respectively. Approximately one third of the BRCA1-like breast cancers have a BRCA1 mutation, one third has hypermethylation of the BRCA1 promoter and one third has an unknown reason for being BRCA1-like. This classification is indicative of patients' response to high dose alkylating and platinum containing chemotherapy regimens, which targets the inability of BRCA1 deficient cells to repair DNA double strand breaks. We investigated whether this classification can be reliably obtained with next generation sequencing and copy number platforms other than the bacterial artificial chromosome (BAC) array Comparative Genomic Hybridization (aCGH) on which it was originally developed. We investigated samples from 230 breast cancer patients for which a CN profile had been generated on two to five platforms, comprising low coverage CN sequencing, CN extraction from targeted sequencing panels (CopywriteR), Affymetrix SNP6.0, 135K/720K oligonucleotide aCGH, Affymetrix Oncoscan FFPE (MIP) technology, 3K BAC and 32K BAC aCGH. Pairwise comparison of genomic position-mapped profiles from the original aCGH platform and other platforms revealed concordance. For most cases, biological differences between samples exceeded the differences between platforms within one sample. We observed the same classification across different platforms in over 80% of the patients and kappa values of at least 0.36. Differential classification could be attributed to CN profiles that were not strongly associated to one class. In conclusion, we have shown that the genomic regions that define our BRCA1-like classifier are robustly measured by different CN profiling technologies, providing the possibility to retro- and prospectively investigate BRCA1-like classification across a wide range of CN platforms.