PALB2 interacts with BRCA2, and biallelic mutations in PALB2 (also known as FANCN), similar to biallelic BRCA2 mutations, cause Fanconi anemia. We identified monoallelic truncating PALB2 mutations in ...10/923 individuals with familial breast cancer compared with 0/1,084 controls (P = 0.0004) and show that such mutations confer a 2.3-fold higher risk of breast cancer (95% confidence interval (c.i.) = 1.4-3.9, P = 0.0025). The results show that PALB2 is a breast cancer susceptibility gene and further demonstrate the close relationship of the Fanconi anemia-DNA repair pathway and breast cancer predisposition.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
We identified constitutional truncating mutations of the BRCA1-interacting helicase BRIP1 in 9/1,212 individuals with breast cancer from BRCA1/BRCA2 mutation-negative families but in only 2/2,081 ...controls (P = 0.0030), and we estimate that BRIP1 mutations confer a relative risk of breast cancer of 2.0 (95% confidence interval = 1.2-3.2, P = 0.012). Biallelic BRIP1 mutations were recently shown to cause Fanconi anemia complementation group J. Thus, inactivating truncating mutations of BRIP1, similar to those in BRCA2, cause Fanconi anemia in biallelic carriers and confer susceptibility to breast cancer in monoallelic carriers.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Wilms tumor is the most common childhood renal cancer. To identify mutations that predispose to Wilms tumor, we are conducting exome sequencing studies. Here we describe 11 different inactivating ...mutations in the REST gene (encoding RE1-silencing transcription factor) in four familial Wilms tumor pedigrees and nine non-familial cases. Notably, no similar mutations were identified in the ICR1000 control series (13/558 versus 0/993; P < 0.0001) or in the ExAC series (13/558 versus 0/61,312; P < 0.0001). We identified a second mutational event in two tumors, suggesting that REST may act as a tumor-suppressor gene in Wilms tumor pathogenesis. REST is a zinc-finger transcription factor that functions in cellular differentiation and embryonic development. Notably, ten of 11 mutations clustered within the portion of REST encoding the DNA-binding domain, and functional analyses showed that these mutations compromise REST transcriptional repression. These data establish REST as a Wilms tumor predisposition gene accounting for ∼2% of Wilms tumor.
We conducted a genome-wide association study for testicular germ cell tumor (TGCT), genotyping 307,666 SNPs in 730 cases and 1,435 controls from the UK and replicating associations in a further 571 ...cases and 1,806 controls. We found strong evidence for susceptibility loci on chromosome 5 (per allele OR = 1.37 (95% CI = 1.19-1.58), P = 3 × 10−13), chromosome 6 (OR = 1.50 (95% CI = 1.28-1.75), P = 10−13) and chromosome 12 (OR = 2.55 (95% CI = 2.05-3.19), P = 10−31). KITLG, encoding the ligand for the receptor tyrosine kinase KIT, which has previously been implicated in the pathogenesis of TGCT and the biology of germ cells, may explain the association on chromosome 12.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Next-generation sequencing (NGS) offers unprecedented opportunities to expand clinical genomics. It also presents challenges with respect to integration with data from other sequencing methods and ...historical data. Provision of consistent, clinically applicable variant annotation of NGS data has proved difficult, particularly of indels, an important variant class in clinical genomics. Annotation in relation to a reference genome sequence, the DNA strand of coding transcripts and potential alternative variant representations has not been well addressed. Here we present tools that address these challenges to provide rapid, standardized, clinically appropriate annotation of NGS data in line with existing clinical standards.
We developed a clinical sequencing nomenclature (CSN), a fixed variant annotation consistent with the principles of the Human Genome Variation Society (HGVS) guidelines, optimized for automated variant annotation of NGS data. To deliver high-throughput CSN annotation we created CAVA (Clinical Annotation of VAriants), a fast, lightweight tool designed for easy incorporation into NGS pipelines. CAVA allows transcript specification, appropriately accommodates the strand of a gene transcript and flags variants with alternative annotations to facilitate clinical interpretation and comparison with other datasets. We evaluated CAVA in exome data and a clinical BRCA1/BRCA2 gene testing pipeline.
CAVA generated CSN calls for 10,313,034 variants in the ExAC database in 13.44 hours, and annotated the ICR1000 exome series in 6.5 hours. Evaluation of 731 different indels from a single individual revealed 92 % had alternative representations in left aligned and right aligned data. Annotation of left aligned data, as performed by many annotation tools, would thus give clinically discrepant annotation for the 339 (46 %) indels in genes transcribed from the forward DNA strand. By contrast, CAVA provides the correct clinical annotation for all indels. CAVA also flagged the 370 indels with alternative representations of a different functional class, which may profoundly influence clinical interpretation. CAVA annotation of 50 BRCA1/BRCA2 gene mutations from a clinical pipeline gave 100 % concordance with Sanger data; only 8/25 BRCA2 mutations were correctly clinically annotated by other tools.
CAVA is a freely available tool that provides rapid, robust, high-throughput clinical annotation of NGS data, using a standardized clinical sequencing nomenclature.
The metabolism of cis-tramadol has been studied in human liver microsomes and in cDNA-expressed human cytochrome P-450 (CYP) isoforms. Human liver microsomes catalyzed the NADPH-dependent metabolism ...of tramadol to the two primary tramadol metabolites, namely, O-desmethyl-tramadol (metabolite M1) and N-desmethyl-tramadol (metabolite M2). In addition, tramadol was also metabolized to two minor secondary metabolites (each comprising < or =3.0% of total tramadol metabolism), namely, N,N-didesmethyl-tramadol (metabolite M3) and N,O-didesmethyl-tramadol (metabolite M5). Kinetic analysis revealed that multiple CYP enzymes were involved in the metabolism of tramadol to both M1 and M2. For the high-affinity enzymes involved in M1 and M2 formation, K(m) values were 116 and 1021 microM, respectively. Subsequent reaction phenotyping studies were performed with a tramadol substrate concentration of 250 microM. In studies with characterized human liver microsomal preparations, good correlations were observed between tramadol metabolism to M1 and M2 and enzymatic markers of CYP2D6 and CYP2B6, respectively. Tramadol was metabolized to M1 by cDNA-expressed CYP2D6 and to M2 by CYP2B6 and CYP3A4. Tramadol metabolism in human liver microsomes to M1 and M2 was markedly inhibited by the CYP2D6 inhibitor quinidine and the CYP3A4 inhibitor troleandomycin, respectively. In summary, this study demonstrates that cis-tramadol can be metabolized to tramadol metabolites M1, M2, M3, and M5 in human liver microsomal preparations. By kinetic analysis and the results of the reaction phenotyping studies, tramadol metabolism in human liver is catalyzed by multiple CYP isoforms. Hepatic CYP2D6 appears to be primarily responsible for M1 formation, whereas M2 formation is catalyzed by CYP2B6 and CYP3A4.
Next generation sequencing (NGS) is routinely used in clinical genetic testing. Quality management of NGS testing is essential to ensure performance is consistently and rigorously evaluated. Three ...primary metrics are used in NGS quality evaluation: depth of coverage, base quality and mapping quality. To provide consistency and transparency in the utilisation of these metrics we present the Quality Sequencing Minimum (QSM). The QSM defines the minimum quality requirement a laboratory has selected for depth of coverage (C), base quality (B) and mapping quality (M) and can be applied per base, exon, gene or other genomic region, as appropriate. The QSM format is CX_BY(P
)_MZ(P
). X is the parameter threshold for C, Y the parameter threshold for B, P
the percentage of reads that must reach Y, Z the parameter threshold for M, P
the percentage of reads that must reach Z. The data underlying the QSM is in the BAM file, so a QSM can be easily and automatically calculated in any NGS pipeline. We used the QSM to optimise cancer predisposition gene testing using the TruSight Cancer Panel (TSCP). We set the QSM as C50_B10(85)_M20(95). Test regions falling below the QSM were automatically flagged for review, with 100/1471 test regions QSM-flagged in multiple individuals. Supplementing these regions with 132 additional probes improved performance in 85/100. We also used the QSM to optimise testing of genes with pseudogenes such as
and
. In TSCP data from 960 individuals the median number of regions that passed QSM per sample was 1429 (97%). Importantly, the QSM can be used at an individual report level to provide succinct, comprehensive quality assurance information about individual test performance. We believe many laboratories would find the QSM useful. Furthermore, widespread adoption of the QSM would facilitate consistent, transparent reporting of genetic test performance by different laboratories.
Precision-cut human liver slices obtained from 11 donors were cultured for 72 h in a defined medium (serum free Williams' medium E) supplemented with 0.1 microM insulin and 0.1 microM dexamethasone ...(DEX). Liver slices were treated with 50 microM concentrations of beta -naphthoflavone (BNF), lansoprazole, rifampicin (RIF), DEX and methylclofenapate and 500 microM sodium phenobarbital (NaPB). The relative apoprotein levels of 12 cytochrome P450 (P450) enzymes were determined in liver slice microsomes using a panel of antipeptide antibodies. Treatment with BNF significantly induced mean levels of CYP1A2 apoprotein to 160% of levels in 72-h control (no test compound) human liver slice microsomes. NaPB significantly induced levels of CYP3A4 apoprotein to 255% of control and RIF significantly induced levels of CYP2C19 and CYP3A4 apoproteins to 265 and 330% of control, respectively. In addition, treatment with RIF increased levels of CYP2A6 apoprotein to 205% of control, and treatment with both NaPB and RIF increased levels of CYP2B6 apoprotein to 370 and 615% of control, respectively. However, these increases were not statistically significant, owing to a variable response between liver slice preparations from different subjects, this being apparent for all inducible P450s. In contrast, none of the compounds examined significantly increased levels of CYP2C8, CYP2C9, CYP2D6, CYP2E1, and CYP4A11 apoproteins. Levels of CYP1A1 apoprotein were not detected in any liver slice sample, either before or after treatment with the model inducers. Overall, these results demonstrate the utility of cultured human liver slices for assessing the effects of chemicals on P450 enzymes.
The analytical sensitivity of a next generation sequencing (NGS) test reflects the ability of the test to detect real sequence variation. The evaluation of analytical sensitivity relies on the ...availability of gold-standard, validated, benchmarking datasets. For NGS analysis the availability of suitable datasets has been limited. Most laboratories undertake small scale evaluations using in-house data, and/or rely on
generated datasets to evaluate the performance of NGS variant detection pipelines. Cancer predisposition genes (CPGs), such as
and
, are amongst the most widely tested genes in clinical practice today. Hundreds of providers across the world are now offering CPG testing using NGS methods. Validating and comparing the analytical sensitivity of CPG tests has proved difficult, due to the absence of comprehensive, orthogonally validated, benchmarking datasets of CPG pathogenic variants. To address this we present the ICR639 CPG NGS validation series. This dataset comprises data from 639 individuals. Each individual has sequencing data generated using the TruSight Cancer Panel (TSCP), a targeted NGS assay for the analysis of CPGs, together with orthogonally generated data showing the presence of at least one CPG pathogenic variant per individual. The set consists of 645 pathogenic variants in total. There is strong representation of the most challenging types of variants to detect, with 339 indels, including 16 complex indels and 24 with length greater than five base pairs and 74 exon copy number variations (CNVs) including 23 single exon CNVs. The series includes pathogenic variants in 31 CPGs, including 502 pathogenic variants in
or
, making this an important comprehensive validation dataset for providers of
and
NGS testing. We have deposited the TSCP FASTQ files of the ICR639 series in the European Genome-phenome Archive (EGA) under accession number EGAD00001004134.
PDF
