Genetic screening of Fabry patients with EcoTILLING and HRM technology

<p>Abstract</p> <p>Background</p> <p>Anderson-Fabry disease (FD) is caused by a deficit of the α-galactosidase A enzyme which leads to the accumulation of complex sphingolipids, especially globotriaosylceramide (Gb3), in all the cells of the body, causing the onset of a multi-systemic disease with poor prognosis in adulthood. In this article, we describe two alternative methods for screening the <it>GLA </it>gene which codes for the α-galactosidase A enzyme in subjects with probable FD in order to test analysis strategies which include or rely on initial pre-screening.</p> <p>Findings</p> <p>We analyzed 740 samples using EcoTILLING, comparing two mismatch-specific<ul/>endonucleases, CEL I and ENDO-1, while conducting a parallel screening of the same samples using HRM (High Resolution Melting). Afterwards, all samples were subjected to direct sequencing. Overall, we identified 12 different genetic variations: -10C>T, -12G>A, -30G>A, IVS2-76_80del5, D165H, C172Y, IVS4+16A>G, IVS4 +68 A>G, c.718_719delAA, D313Y, IVS6-22C>T, G395A. This was consistent with the high genetic heterogeneity found in FD patients and carriers. All of the mutations were detected by HRM, whereas 17% of the mutations were not found by EcoTILLING. The results obtained by EcoTILLING comparing the CEL I and ENDO-1 endonucleases were perfectly overlapping.</p> <p>Conclusion</p> <p>On the basis of its simplicity, flexibility, repeatability, and sensitivity, we believe that<ul/>HRM analysis of the <it>GLA </it>gene is a reliable presequencing screening tool. This method can be applied to any genomic feature to identify known and unknown genetic alterations, and it is ideal for conducting screening and population studies.</p

High resolution melting analysis for rapid and sensitive EGFR and KRAS mutation detection in formalin fixed paraffin embedded biopsies

<p>Abstract</p> <p>Background</p> <p>Epithelial growth factor receptor (<it>EGFR</it>) and <it>KRAS </it>mutation status have been reported as predictive markers of tumour response to <it>EGFR </it>inhibitors. High resolution melting (HRM) analysis is an attractive screening method for the detection of both known and unknown mutations as it is rapid to set up and inexpensive to operate. However, up to now it has not been fully validated for clinical samples when formalin-fixed paraffin-embedded (FFPE) sections are the only material available for analysis as is often the case.</p> <p>Methods</p> <p>We developed HRM assays, optimised for the analysis of FFPE tissues, to detect somatic mutations in <it>EGFR </it>exons 18 to 21. We performed HRM analysis for <it>EGFR </it>and <it>KRAS </it>on DNA isolated from a panel of 200 non-small cell lung cancer (NSCLC) samples derived from FFPE tissues.</p> <p>Results</p> <p>All 73 samples that harboured <it>EGFR </it>mutations previously identified by sequencing were correctly identified by HRM, giving 100% sensitivity with 90% specificity. Twenty five samples were positive by HRM for <it>KRAS </it>exon 2 mutations. Sequencing of these 25 samples confirmed the presence of codon 12 or 13 mutations. <it>EGFR </it>and <it>KRAS </it>mutations were mutually exclusive.</p> <p>Conclusion</p> <p>This is the first extensive validation of HRM on FFPE samples using the detection of <it>EGFR </it>exons 18 to 21 mutations and <it>KRAS </it>exon 2 mutations. Our results demonstrate the utility of HRM analysis for the detection of somatic <it>EGFR </it>and <it>KRAS </it>mutations in clinical samples and for screening of samples prior to sequencing. We estimate that by using HRM as a screening method, the number of sequencing reactions needed for <it>EGFR </it>and <it>KRAS </it>mutation detection can be reduced by up to 80% and thus result in substantial time and cost savings.</p

Frequently increased epidermal growth factor receptor (EGFR) copy numbers and decreased BRCA1 mRNA expression in Japanese triple-negative breast cancers

<p>Abstract</p> <p>Background</p> <p>Triple-negative breast cancer (estrogen receptor-, progesterone receptor-, and HER2-negative) (TNBC) is a high risk breast cancer that lacks specific therapy targeting these proteins.</p> <p>Methods</p> <p>We studied 969 consecutive Japanese patients diagnosed with invasive breast cancer from January 1981 to December 2003, and selected TNBCs based on the immunohistochemical data. Analyses of epidermal growth factor receptor (<it>EGFR</it>) gene mutations and amplification, and <it>BRCA</it>1 mRNA expression were performed on these samples using TaqMan PCR assays. The prognostic significance of TNBCs was also explored. Median follow-up was 8.3 years.</p> <p>Results</p> <p>A total of 110 (11.3%) patients had TNBCs in our series. Genotyping of the <it>EGFR </it>gene was performed to detect 14 known <it>EGFR </it>mutations, but none was identified. However, <it>EGFR </it>gene copy number was increased in 21% of TNBCs, while only 2% of ER- and PgR-positive, HER2-negative tumors showed slightly increased <it>EGFR </it>gene copy numbers. Thirty-one percent of TNBCs stained positive for EGFR protein by immunohistochemistry. <it>BRCA1 </it>mRNA expression was also decreased in TNBCs compared with controls. Triple negativity was significantly associated with grade 3 tumors, TP53 protein accumulation, and high Ki67 expression. TNBC patients had shorter disease-free survival than non-TNBC in node-negative breast cancers.</p> <p>Conclusion</p> <p>TNBCs have an aggressive clinical course, and <it>EGFR </it>and <it>BRCA1 </it>might be candidate therapeutic targets in this disease.</p

Characterization of Oseltamivir-Resistant 2009 H1N1 Pandemic Influenza A Viruses

Influenza viruses resistant to antiviral drugs emerge frequently. Not surprisingly, the widespread treatment in many countries of patients infected with 2009 pandemic influenza A (H1N1) viruses with the neuraminidase (NA) inhibitors oseltamivir and zanamivir has led to the emergence of pandemic strains resistant to these drugs. Sporadic cases of pandemic influenza have been associated with mutant viruses possessing a histidine-to-tyrosine substitution at position 274 (H274Y) in the NA, a mutation known to be responsible for oseltamivir resistance. Here, we characterized in vitro and in vivo properties of two pairs of oseltaimivir-sensitive and -resistant (possessing the NA H274Y substitution) 2009 H1N1 pandemic viruses isolated in different parts of the world. An in vitro NA inhibition assay confirmed that the NA H274Y substitution confers oseltamivir resistance to 2009 H1N1 pandemic viruses. In mouse lungs, we found no significant difference in replication between oseltamivir-sensitive and -resistant viruses. In the lungs of mice treated with oseltamivir or even zanamivir, 2009 H1N1 pandemic viruses with the NA H274Y substitution replicated efficiently. Pathological analysis revealed that the pathogenicities of the oseltamivir-resistant viruses were comparable to those of their oseltamivir-sensitive counterparts in ferrets. Further, the oseltamivir-resistant viruses transmitted between ferrets as efficiently as their oseltamivir-sensitive counterparts. Collectively, these data indicate that oseltamivir-resistant 2009 H1N1 pandemic viruses with the NA H274Y substitution were comparable to their oseltamivir-sensitive counterparts in their pathogenicity and transmissibility in animal models. Our findings highlight the possibility that NA H274Y-possessing oseltamivir-resistant 2009 H1N1 pandemic viruses could supersede oseltamivir-sensitive viruses, as occurred with seasonal H1N1 viruses

Murine and Bovine γδ T Cells Enhance Innate Immunity against Brucella abortus Infections

γδ T cells have been postulated to act as a first line of defense against infectious agents, particularly intracellular pathogens, representing an important link between the innate and adaptive immune responses. Human γδ T cells expand in the blood of brucellosis patients and are active against Brucella in vitro. However, the role of γδ T cells in vivo during experimental brucellosis has not been studied. Here we report TCRδ−/− mice are more susceptible to B. abortus infection than C57BL/6 mice at one week post-infection as measured by splenic colonization and splenomegaly. An increase in TCRγδ cells was observed in the spleens of B. abortus-infected C57BL/6 mice, which peaked at two weeks post-infection and occurred concomitantly with diminished brucellae. γδ T cells were the major source of IL-17 following infection and also produced IFN-γ. Depletion of γδ T cells from C57BL/6, IL-17Rα−/−, and GMCSF−/− mice enhanced susceptibility to B. abortus infection although this susceptibility was unaltered in the mutant mice; however, when γδ T cells were depleted from IFN-γ−/− mice, enhanced susceptibility was observed. Neutralization of γδ T cells in the absence of TNF-α did not further impair immunity. In the absence of TNF-α or γδ T cells, B. abortus-infected mice showed enhanced IFN-γ, suggesting that they augmented production to compensate for the loss of γδ T cells and/or TNF-α. While the protective role of γδ T cells was TNF-α-dependent, γδ T cells were not the major source of TNF-α and activation of γδ T cells following B. abortus infection was TNF-α-independent. Additionally, bovine TCRγδ cells were found to respond rapidly to B. abortus infection upon co-culture with autologous macrophages and could impair the intramacrophage replication of B. abortus via IFN-γ. Collectively, these results demonstrate γδ T cells are important for early protection to B. abortus infections

Search for Kaluza-Klein Graviton Emission in ppˉp\bar{p} Collisions at s=1.8\sqrt{s}=1.8 TeV using the Missing Energy Signature

We report on a search for direct Kaluza-Klein graviton production in a data sample of 84 ${pb}^{-1}$ of \ppb collisions at $\sqrt{s}$ = 1.8 TeV, recorded by the Collider Detector at Fermilab. We investigate the final state of large missing transverse energy and one or two high energy jets. We compare the data with the predictions from a $3+1+n$-dimensional Kaluza-Klein scenario in which gravity becomes strong at the TeV scale. At 95% confidence level (C.L.) for $n$=2, 4, and 6 we exclude an effective Planck scale below 1.0, 0.77, and 0.71 TeV, respectively.Comment: Submitted to PRL, 7 pages 4 figures/Revision includes 5 figure

An algorithm for classifying tumors based on genomic aberrations and selecting representative tumor models

<p>Abstract</p> <p>Background</p> <p>Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose.</p> <p>Method</p> <p>To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.</p> <p>Result</p> <p>We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC), colorectal cancer (CRC), and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes.</p> <p>Conclusions</p> <p>We developed an algorithm for cancer classification based on genome-wide patterns of copy number aberrations and demonstrated its superiority to existing clustering methods. The algorithm was applied to define genomic subgroups of three cancer types and identify cell lines representative of these subgroups. Our data enabled the assembly of representative cell line panels for testing drug candidates.</p