BRCA1 and BRCA2 5′ noncoding region variants identified in breast cancer patients alter promoter activity and protein binding

© 2018 The Authors. Human Mutation published by Wiley Periodicals, Inc. The widespread use of next generation sequencing for clinical testing is detecting an escalating number of variants in noncoding regions of the genome. The clinical significance of the majority of these variants is currently unknown, which presents a significant clinical challenge. We have screened over 6,000 early-onset and/or familial breast cancer (BC) cases collected by the ENIGMA consortium for sequence variants in the 5′ noncoding regions of BC susceptibility genes BRCA1 and BRCA2, and identified 141 rare variants with global minor allele frequency \u3c 0.01, 76 of which have not been reported previously. Bioinformatic analysis identified a set of 21 variants most likely to impact transcriptional regulation, and luciferase reporter assays detected altered promoter activity for four of these variants. Electrophoretic mobility shift assays demonstrated that three of these altered the binding of proteins to the respective BRCA1 or BRCA2 promoter regions, including NFYA binding to BRCA1:c.-287C\u3eT and PAX5 binding to BRCA2:c.-296C\u3eT. Clinical classification of variants affecting promoter activity, using existing prediction models, found no evidence to suggest that these variants confer a high risk of disease. Further studies are required to determine if such variation may be associated with a moderate or low risk of BC

Endoglin is not expressed with cell adhesion molecules in aorta during atherogenesis in apoE-deficient mice

Endoglin (TGF-β receptor III), has been demonstrated to affect vascular endothelium and atherosclerosis. Moreover, it was also demonstrated that endoglin is involved in inflammation and plays a role in leukocyte adhesion and transmigration in vitro and in vivo but not in atherosclerosis related vessels. In this study, we wanted to evaluate endoglin expression in two different parts of the aorta (heart aortic sinus and ascending aorta) and assess its potential simultaneous expression with cell adhesion molecules in nonatherosclerotic and atherosclerotic aortas of apoEdeficient mice. Ten-week–old female apolipoprotein E-deficient mice on a C57BL/6J background (n=24) were randomly subdivided into three groups and were fed either chow diet (for another two months) or Western type diet (for another two or four months). Immunohistochemical staining of endoglin, VCAM-1 and P-selectin in aortic sinus and ascending aorta was performed. Endoglin expression was detected only in endothelial cells and varied during atherogenic process in aorta but not in aortic sinus. Moreover, its expression seemed to be weaker in aorta when compared to aortic sinus and the positivity was detected only in endothelium covering atherosclerotic lesions but not in non-atherosclerotic endothelium regardless of the plaque size. Endoglin was not expressed with P-selectin and VCAM-1 in aortic endothelium in any studied group. This study shows that endothelial expression of endoglin is related to the atherogenic process predominantly in aorta outside the heart. Moreover, endoglin is not localized with cell adhesion molecules involved in atherosclerosis, suggesting it might not participate in leukocyte accumulation in aorta of apoEdeficient mice during atherogenesis

Molecular characterization of the rare translocation t(3;10)(q26;q21) in an acute myeloid leukemia patient

Background: In acute myeloid leukemia (AML), the MDS1 and EVI1 complex locus - MECOM, also known as the ecotropic virus integration site 1 - EVI1, located in band 3q26, can be rearranged with a variety of partner chromosomes and partner genes. Here we report on a 57-year-old female with AML who presented with the rare translocation t(3;10) (q26;q21) involving the MECOM gene. Our aim was to identify the fusion partner on chromosome 10q21 and to characterize the precise nucleotide sequence of the chromosomal breakpoint. Methods: Cytogenetic and molecular-cytogenetic techniques, chromosome microdissection, next generation sequencing, long-range PCR and direct Sanger sequencing were used to map the chromosomal translocation. Results: Using a combination of cytogenetic and molecular approaches, we mapped the t(3;10)(q26;q21) to the single nucleotide level, revealing a fusion of the MECOM gene (3q26.2) and C10orf107 (10q21.2). Conclusions: The approach described here opens up new possibilities in characterizing acquired as well as congenital chromosomal aberrations. In addition, DNA sequences of chromosomal breakpoints may be a useful tool for unique molecular minimal residual disease target identification in acute leukemia patients

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes

<div><p>Background</p><p>Carriers of mutations in hereditary cancer predisposition genes represent a small but clinically important subgroup of oncology patients. The identification of causal germline mutations determines follow-up management, treatment options and genetic counselling in patients’ families. Targeted next-generation sequencing-based analyses using cancer-specific panels in high-risk individuals have been rapidly adopted by diagnostic laboratories. While the use of diagnosis-specific panels is straightforward in typical cases, individuals with unusual phenotypes from families with overlapping criteria require multiple panel testing. Moreover, narrow gene panels are limited by our currently incomplete knowledge about possible genetic dispositions.</p><p>Methods</p><p>We have designed a multi-gene panel called CZECANCA (CZEch CAncer paNel for Clinical Application) for a sequencing analysis of 219 cancer-susceptibility and candidate predisposition genes associated with frequent hereditary cancers.</p><p>Results</p><p>The bioanalytical and bioinformatics pipeline was validated on a set of internal and commercially available DNA controls showing high coverage uniformity, sensitivity, specificity and accuracy. The panel demonstrates a reliable detection of both single nucleotide and copy number variants. Inter-laboratory, intra- and inter-run replicates confirmed the robustness of our approach.</p><p>Conclusion</p><p>The objective of CZECANCA is a nationwide consolidation of cancer-predisposition genetic testing across various clinical indications with savings in costs, human labor and turnaround time. Moreover, the unified diagnostics will enable the integration and analysis of genotypes with associated phenotypes in a national database improving the clinical interpretation of variants.</p></div

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 7

<p><b>Comparison of variant detection (shown as values of variant allelic fraction; AF) in DNA reference standards</b> (NA12878, NA24149, NA24385, NA24631 and NA24143) obtained from CZECANCA analysis (x-axis) and AF from VCF files for these standards downloaded from <a href="http://jimb.stanford.edu/giab/" target="_blank">http://jimb.stanford.edu/giab/</a> (y-axis). The graph shows all variants with GATK quality >100 reached in CZECANCA analysis (including FP variants) and undetected (FN) variants. Heterozygote variants clustered in the center, while homozygote variants in right upper corner. Variant distribution was partially influenced by the differences in mean sequencing coverage targeting 100X and 300X in CZECANCA and DNA reference standards VCFs, respectively. The number of TP, TN, FP, FN, and total number of variant (= CZECANCA target) was used to calculate of sensitivity, specificity, and accuracy of CZECANCA analysis.</p

Estrogen Receptor Status Oppositely Modifies Breast Cancer Prognosis in <i>BRCA1/BRCA2</i> Mutation Carriers Versus Non-Carriers

Breast cancer (BC) prognosis in BRCA1 and BRCA2 mutation carriers has been reported contradictorily, and the significance of variables influencing prognosis in sporadic BC is not established in BC patients with hereditary BRCA1/BRCA2 mutations. In this retrospective cohort study, we analyzed the effect of clinicopathological characteristics on BC prognosis (disease-free survival [DFS] and disease-specific survival [DSS]) in hereditary BRCA1/BRCA2 mutation carriers. We enrolled 234 BRCA1/BRCA2 mutation carriers and 899 non-carriers, of whom 191 carriers and 680 non-carriers, with complete data, were available for survival analyses. We found that patients with ER-positive tumors developed disease recurrence 2.3-times more likely when they carried a BRCA1/BRCA2 mutation (23/60; 38.3% ER-positive carriers vs. 74/445; 16.6% ER-positive non-carriers; p &lt; 0.001). ER-positive mutation carriers also had a 3.4-times higher risk of death due to BC compared with ER-positive non-carriers (13/60; 21.7% vs. 28/445; 6.3%; p &lt; 0.001). Moreover, prognosis in ER-negative BRCA1/BRCA2 mutation carriers was comparable with that in ER-positive non-carriers. Our study demonstrates that ER-positivity worsens BC prognosis in BRCA1/BRCA2 mutation carriers, while prognosis for carriers with ER-negative tumors (including early-onset) is significantly better and comparable with that in ER-positive, older BC non-carriers. These observations indicate that BRCA1/BRCA2 mutation carriers with ER-positive BC represent high-risk patients

Identification of c.661_662delinsTA double substitution (p.Val221*) in <i>PALB2</i> (NM_024675).

<p>The BAM file displayed in IGV shows the <i>cis</i>-position of both substitutions in approximately 50% of forward (pink bars) and reverse (blue bars) reads, respectively.</p

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 4

<p><b>Analysis of intra-run (A), inter-run (B), and inter-laboratory (C) replicates.</b> The panels show sequencing coverages (y-axis) of the identified variants arranged according to chromosomal localizations (x-axis). We used moving average curves (average of 3 values) to compare trends in coverages. Panel (A) describes the results of an analysis of three independently processed intra-run replicates from an identical DNA sample pooled in 33 ng (considered as 100%), 24.75 ng (75%), and 16.5 ng (50%), respectively. Panel (B) demonstrates variant coverages identified in two independent inter-run (run 8 and 14) replicates. All coverage values of sample #3647 in run 14 were corrected by a factor of 1.3880 to normalize coverages between samples (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.s004" target="_blank">S4 Table</a>). Panel (C) shows coverages of variants identified in an inter-laboratory control sequenced in four laboratories (Lab) participating in panel validation (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.s005" target="_blank">S5 Table</a>). The coverages of variants identified in Lab 2, 3, and 4 were normalized to the average coverage of Lab 1 for better comparisons of coverages.</p

Coverage (y-axis) of coding sequences (x-axis) of 219 CZECANCA target genes from a routine, randomly selected run targeting 100X coverage.

<p>Note: Fully covered genes are depicted in green letters, genes with coverage <20X in a single exon are in orange letters, and genes with uncovered regions exceeding single exon or >10% of coding sequence are in red letters. Green horizontal bars (below individual graphs constructed using “Boudalyzer” script) indicate coverage ≥ 20X; red horizontal bars indicate regions covered <20X and uncovered regions.</p

CNV detection is influenced by a DNA preparation method.

<p>Panels show analyses of remaining ACMG genes (not shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.g005" target="_blank">Fig 5B and 5C</a>) from four runs performed in laboratory 1 (116 DNA samples fragmented by ultrasound) and laboratory 3 (125 DNA samples fragmented enzymatically). The numbers in parentheses express number of samples with possible CNVs from all analyzed samples in contributing laboratories. *indicate samples analyzed by MLPA negatively (FP–black) or positively (TP–red). Bin set covering exon 1 in <i>RET</i> was excluded from the analysis due to the large coverage variability.</p