Genetic analysis identifies the HMMR gene as a modifier of the breast cancer risk associated with BRCA1 gene mutation, while cell biological analysis of the protein product suggests a function in regulating development of the mammary gland.

Genome-wide association studies of breast cancer have identified multiple single nucleotide polymorphisms (SNPs) that are associated with increased breast cancer risks in the general population. In a previous study, we demonstrated that the minor alleles at three of these SNPs, in FGFR2, TNRC9 and MAP3K1, also confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. Three additional SNPs rs3817198 at LSP1, rs13387042 at 2q35 and rs13281615 at 8q24 have since been reported to be associated with breast cancer in the general population, and in this study we evaluated their association with breast cancer risk in 9442 BRCA1 and 5665 BRCA2 mutation carriers from 33 study centres. The minor allele of rs3817198 was associated with increased breast cancer risk only for BRCA2 mutation carriers [hazard ratio (HR) = 1.16, 95% CI: 1.07-1.25, P-trend = 2.8 x 10(-4)]. The best fit for the association of SNP rs13387042 at 2q35 with breast cancer risk was a dominant model for both BRCA1 and BRCA2 mutation carriers (BRCA1: HR = 1.14, 95% CI: 1.04-1.25, P = 0.0047; BRCA2: HR = 1.18 95% CI: 1.04-1.33, P = 0.0079). SNP rs13281615 at 8q24 was not associated with breast cancer for either BRCA1 or BRCA2 mutation carriers, but the estimated association for BRCA2 mutation carriers (per-allele HR = 1.06, 95% CI: 0.98-1.14) was consistent with odds ratio estimates derived from population-based case-control studies. The LSP1 and 2q35 SNPs appear to interact multiplicatively on breast cancer risk for BRCA2 mutation carriers. There was no evidence that the associations vary by mutation type depending on whether the mutated protein is predicted to be stable or not.

Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. For this method RNA was extracted from lymphocytes, followed by targeted RNAseq. Next, an in-house developed tool (QURNAs) was used to calculate the enrichment score (ERS) for each splicing event. This method was thoroughly tested using two different patient cohorts with known pathogenic splice-variants in NF1. In both cohorts all 56 normal reference transcript exon splice junctions, 24 previously described and 45 novel non-reference splicing events were detected. Additionally, all expected pathogenic splice-variants were detected. Eleven patients with NF1 symptoms were subsequently tested, three of which have a known NF1 DNA variant with a putative effect on RNA splicing. This effect could be confirmed for all 3. The other eight patients were previously without any molecular confirmation of their NF1-diagnosis. A deep-intronic pathogenic splice variant could now be identified for two of them (25%). These results suggest that targeted RNAseq can be successfully used to detect pathogenic RNA splicing variants in NF1.

Considerable differences exist amongst countries in the mutation probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of mutation probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a mutation and probabilities <10% with both programs. All four probands had a BRCA2 mutation. BRCAPRO and Myriad II showed similar specificity at 10% threshold, overall BRCAPRO was more sensitive than Myriad II for the detection of mutations. Only two of the probands with an UV had probabilities >20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a mutation. BRCAPRO performs better for the detection of BRCA1 mutations than of BRCA2 mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV.

PurposeNeurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. A targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants.MethodsRNA was extracted from lymphocytes, followed by targeted NF1 RNAseq. An in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event.ResultsThis method was thoroughly tested using two different patient cohorts with known pathogenic splice-variants. In both cohorts all 56 normal reference transcript exon splice junctions, 24 previously described and 45 novel non-reference splicing events were detected. Additionally, all expected pathogenic splice-variants were detected. Eleven patients with NF1 symptoms were subsequently tested, three of which have a known NF1 DNA variant with a putative effect on RNA splicing. This effect could be confirmed for all 3. The other eight patients were previously without any molecular confirmation of their NF1-diagnosis. A deep-intronic pathogenic splice variant could now be identified for two of them (25%).ConclusionTargeted NF1 RNAseq can be successfully used to detect pathogenic RNA splicing variants, complementary to DNA based diagnostics.