44 research outputs found

    A novel germline mutation of PTEN associated with brain tumours of multiple lineages

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    We have identified a novel germline mutation in the PTEN tumour suppressor gene. The mutation was identified in a patient with a glioma, and turned out to be a heterozygous germline mutation of PTEN (Arg234Gln), without loss of heterozygosity in tumour DNA. The biological consequences of this germline mutation were investigated by means of transfection studies of the mutant PTEN molecule compared to wild-type PTEN. In contrast to the wild-type molecule, the mutant PTEN protein is not capable of inducing apoptosis, induces increased cell proliferation and leads to high constitutive PKB/Akt activation, which cannot be increased anymore by stimulation with insulin. The reported patient, in addition to glioma, had suffered from benign meningioma in the past but did not show any clinical signs of Cowden disease or other hereditary diseases typically associated with PTEN germline mutations. The functional consequences of the mutation in transfection studies are consistent with high proliferative activity. Together, these findings suggest that the Arg234Gln missense mutation in PTEN has oncogenic properties and predisposes to brain tumours of multiple lineages

    A method to assess the clinical significance of unclassified variants in the BRCA1 and BRCA2 genes based on cancer family history

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    Introduction Unclassified variants (UVs) in the BRCA1/BRCA2 genes are a frequent problem in counseling breast cancer and/or ovarian cancer families. Information about cancer family history is usually available, but has rarely been used to evaluate UVs. The aim of the present study was to identify which is the best combination of clinical parameters that can predict whether a UV is deleterious, to be used for the classification of UVs. Methods We developed logistic regression models with the best combination of clinical features that distinguished a positive control of BRCA pathogenic variants (115 families) from a negative control population of BRCA variants initially classified as UVs and later considered neutral (38 families). Results The models included a combination of BRCAPRO scores, Myriad scores, number of ovarian cancers in the family, the age at diagnosis, and the number of persons with ovarian tumors and/ or breast tumors. The areas under the receiver operating characteristic curves were respectively 0.935 and 0.836 for the BRCA1 and BRCA2 models. For each model, the minimum receiver operating characteristic distance (respectively 90% and 78% specificity for BRCA1 and BRCA2) was chosen as the cutoff value to predict which UVs are deleterious from a study population of 12 UVs, present in 59 Dutch families. The p. S1655F, p. R1699W, and p. R1699Q variants in BRCA1 and the p. Y2660D, p. R2784Q, and p. R3052W variants in BRCA2 are classified as deleterious according to our models. The predictions of the p. L246V variant in BRCA1 and of the p. Y42C, p. E462G, p. R2888C, and p. R3052Q variants in BRCA2 are in agreement with published information of them being neutral. The p. R2784W variant in BRCA2 remains uncertain. Conclusions The present study shows that these developed models are useful to classify UVs in clinical genetic practic

    Genetic aberrations in glioblastoma multiforme: translocation of chromosome 10 in an O-2A-like cell line

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    We have examined the genetic aberrations in two near-diploid glioblastoma multiforme cell lines that appear to have arisen from different glial lineages. One cell line, Hu-O-2A/Gb1, expresses antigens and metabolic profiles characteristic of the oligodendrocyte-type-2 astrocyte (0-2A) lineage of the rat central nervous system. This line generates, in vitro, cells with characteristics of 0-2A progenitor cells, oligodendrocytes and astrocytes. The second cell line, IN1434, is derived from an astrocyte or a precursor cell restricted to astrocytic differentiation. In Hu-O-2A/Gb1 the sole homologue of chromosome 10 is disrupted at band 10p11–12.1 by translocation with chromosomes X and 15. The translocation breakpoint is localized between genetic markers D10S2103 and [D10S637, D10S1962, D10S355]. Other aberrations include a 5;14 translocation, deletion of the long and short arms of chromosome 16 and loss of one copy of the CDKN2 gene. IN1434 cells share some cytogenetic abnormalities with Hu-O-2A/Gb1 cells, despite their apparent derivation from a different biological origin, but also have translocations involving the long and short arms of chromosome 1 and the long arm of chromosome 7, and deletion of chromosome 13 at bands 13q12–21. © 1999 Cancer Research Campaig

    A prediction model for underestimation of invasive breast cancer after a biopsy diagnosis of ductal carcinoma in situ: based on 2892 biopsies and 589 invasive cancers

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    Background: Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) might be diagnosed with invasive breast cancer at excision, a phenomenon known as underestimation. Patients with DCIS are treated based on the risk of underestimation or progression to invasive cancer. The aim of our study was to expand the knowledge on underestimation and to develop a prediction model. Methods: Population-based data were retrieved from the Dutch Pathology Registry and the Netherlands Cancer Registry for DCIS between January 2011 and June 2012. Results: Of 2892 DCIS biopsies, 21% were underestimated invasive breast cancers. In multivariable analysis, risk factors were high-grade DCIS (odds ratio (OR) 1.43, 95% confidence interval (CI): 1.05–1.95), a palpable tumour (OR 2.22, 95% CI: 1.76–2.81), a BI-RADS (Breast Imaging Reporting and Data System) score 5 (OR 2.36, 95% CI: 1.80–3.09) and a suspected invasive component at biopsy (OR 3.84, 95% CI: 2.69–5.46). The predicted risk for underestimation ranged from 9.5 to 80.2%, with a median of 14.7%. Of the 596 invasive cancers, 39% had unfavourable features. Conclusions: The risk for an underestimated diagnosis of invasive breast cancer after a biopsy diagnosis of DCIS is considerable. With our prediction model, the individual risk of underestimation can be calculated based on routinely available preoperatively known risk factors (https://www.evidencio.com/models/show/1074)

    Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer

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    Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.Peer reviewe

    Digital vs screen-film mammography in population-based breast cancer screening:performance indicators and tumour characteristics of screen-detected and interval cancers

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    Background: Full-field digital mammography (FFDM) has replaced screen-film mammography (SFM) in most breast cancer screening programs due to technological advantages such as possibilities to adjust contrast, better image quality and transfer capabilities. This study describes the performance indicators during the transition from SFM to FFDM and the characteristics of screen-detected and interval cancers. Methods: Data of the Dutch breast cancer screening program, region North from 2004 to 2010 were linked to The Netherlands Cancer Registry (N = 902 868). Performance indicators and tumour characteristics of screen-detected and interval cancers were compared between FFDM and SFM. Results: After initial screens, recall rates were 2.1% (SFM) and 3.0% (FFDM; P <0.001). The positive predictive values (PPV) were 25.6% (SFM) and 19.9% (FFDM; P = 0.002). Detection rates were similar, as were all performance indicators after subsequent screens. Similar percentages of low-grade ductal carcinoma in situ (DCIS) were found for SFM and FFDM. Invasive cancers diagnosed after subsequent screens with FFDM were more often of high-grade (P = 0.024) and ductal type (P = 0.030). The incidence rates of interval cancers were similar for SFM and FFDM after initial (2.69/1000 vs 2.51/1000; P = 0.787) and subsequent screens (2.30 vs 2.41; P = 0.652), with similar tumour characteristics. Conclusions: FFDM resulted in similar rates of screen-detected and interval cancers, indicating that FFDM performs as well as SFM in a breast cancer screening program. No signs of an increase in low-grade DCIS (which might connote possible overdiagnosis) were seen. Nonetheless, after initial screening, which accounts for 12% of all screens, FFDM resulted in higher recall rate and lower PPV that requires attention

    Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression:Identification of a modifier of breast cancer risk at locus 11q22.3

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    Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of similar to 320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 x 10(-6)). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.</p

    Common breast cancer susceptibility alleles are associated with tumor subtypes in BRCA1 and BRCA2 mutation carriers: results from the Consortium of Investigators of Modifiers of BRCA1/2.

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    Association analysis identifies 65 new breast cancer risk loci

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    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project, funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH Grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combining of the GWAS data was supported in part by The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE, part of the GAME-ON initiative)
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