82 research outputs found

    Undefined familial colorectal cancer and the role of pleiotropism in cancer susceptibility genes.

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    Although family history is a major risk factor for colorectal cancer (CRC) a genetic diagnosis cannot be obtained in over 50Β % of familial cases when screened for known CRC cancer susceptibility genes. The genetics of undefined-familial CRC is complex and recent studies have implied additional clinically actionable mutations for CRCΒ in susceptibility genes for other cancers. To clarify the contribution of non-CRC susceptibility genes to undefined-familial CRC we conducted a mutational screen of 114 cancer susceptibility genes in 847 patients with early-onset undefined-familial CRC and 1609 controls by analysing high-coverage exome sequencing data. We implemented American College of Medical Genetics and Genomics standards and guidelines for assigning pathogenicity to variants. Globally across all 114 cancer susceptibility genes no statistically significant enrichment of likely pathogenic variants was shown (6.7Β % cases 57/847, 5.3Β % controls 85/1609; PΒ =Β 0.15). Moreover there was no significant enrichment of mutations in genes such as TP53 or BRCA2 which have been proposed for clinical testing in CRC. In conclusion, while we identified genes that may be considered interesting candidates as determinants of CRC risk warranting further research, there is currently scant evidence to support a role for genes other than those responsible for established CRC syndromes in the clinical management of familial CRC

    An enhanced genetic model of relapsed IGH-translocated multiple myeloma evolutionary dynamics

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    Most patients with multiple myeloma (MM) die from progressive disease after relapse. To advance our understanding of MM evolution mechanisms, we performed whole-genome sequencing of 80 IGH-translocated tumour-normal newly diagnosed pairs and 24 matched relapsed tumours from the Myeloma XI trial. We identify multiple events as potentially important for survival and therapy-resistance at relapse including driver point mutations (e.g., TET2), translocations (MAP3K14), lengthened telomeres, and increased genomic instability (e.g., 17p deletions). Despite heterogeneous mutational processes contributing to relapsed mutations across MM subtypes, increased AID/APOBEC activity is particularly associated with shorter progression time to relapse, and contributes to higher mutational burden at relapse. In addition, we identify three enhanced major clonal evolution patterns of MM relapse, independent of treatment strategies and molecular karyotypes, questioning the viability of β€œevolutionary herding” approach in treating drug-resistant MM. Our data show that MM relapse is associated with acquisition of new mutations and clonal selection, and suggest APOBEC enzymes among potential targets for therapy-resistant MM

    Dynamics of multi-stage infections on networks

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    This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

    Candidate gene association study in pediatric acute lymphoblastic leukemia evaluated by Bayesian network based Bayesian multilevel analysis of relevance

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    Background: We carried out a candidate gene association study in pediatric acute lymphoblastic leukemia (ALL) to identify possible genetic risk factors in a Hungarian population. Methods: The results were evaluated with traditional statistical methods and with our newly developed Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA) method. We collected genomic DNA and clinical data from 543 children, who underwent chemotherapy due to ALL, and 529 healthy controls. Altogether 66 single nucleotide polymorphisms (SNPs) in 19 candidate genes were genotyped. Results: With logistic regression, we identified 6 SNPs in the ARID5B and IKZF1 genes associated with increased risk to B-cell ALL, and two SNPs in the STAT3 gene, which decreased the risk to hyperdiploid ALL. Because the associated SNPs were in linkage in each gene, these associations corresponded to one signal per gene. The odds ratio (OR) associated with the tag SNPs were: OR = 1.69, P = 2.22x10-7 for rs4132601 (IKZF1), OR = 1.53, P = 1.95x10-5 for rs10821936 (ARID5B) and OR = 0.64, P = 2.32x10-4 for rs12949918 (STAT3). With the BN-BMLA we confirmed the findings of the frequentist-based method and received additional information about the nature of the relations between the SNPs and the disease. E.g. the rs10821936 in ARID5B and rs17405722 in STAT3 showed a weak interaction, and in case of T-cell lineage sample group, the gender showed a weak interaction with three SNPs in three genes. In the hyperdiploid patient group the BN-BMLA detected a strong interaction among SNPs in the NOTCH1, STAT1, STAT3 and BCL2 genes. Evaluating the survival rate of the patients with ALL, the BN-BMLA showed that besides risk groups and subtypes, genetic variations in the BAX and CEBPA genes might also influence the probability of survival of the patients. Conclusions: In the present study we confirmed the roles of genetic variations in ARID5B and IKZF1 in the susceptibility to B-cell ALL. With the newly developed BN-BMLA method several gene-gene, gene-phenotype and phenotype-phenotype connections were revealed. We showed several advantageous features of the new method, and suggested that in gene association studies the BN-BMLA might be a useful supplementary to the traditional frequentist-based statistical method

    A genome-wide association study identifies risk loci for childhood acute lymphoblastic leukemia at 10q26.13 and 12q23.1.

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    Genome-wide association studies (GWASs) have shown that common genetic variation contributes to the heritable risk of childhood acute lymphoblastic leukemia (ALL). To identify new susceptibility loci for the largest subtype of ALL, B-cell precursor ALL (BCP-ALL), we conducted a meta-analysis of two GWASs with imputation using 1000 Genomes and UK10K Project data as reference (totaling 1658 cases and 7224 controls). After genotyping an additional 2525 cases and 3575 controls, we identify new susceptibility loci for BCP-ALL mapping to 10q26.13 (rs35837782, LHPP, P=1.38 Γ— 10(-11)) and 12q23.1 (rs4762284, ELK3, P=8.41 Γ— 10(-9)). We also provide confirmatory evidence for the existence of independent risk loci at 9p21.3, but show that the association marked by rs77728904 can be accounted for by linkage disequilibrium with the rare high-impact CDKN2A p.Ala148Thr variant rs3731249. Our data provide further insights into genetic susceptibility to ALL and its biology

    Subclonal TP53 copy number is associated with prognosis in multiple myeloma

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    Multiple myeloma (MM) is a genetically heterogeneous cancer of bone marrow plasma cells with variable outcome. To assess the prognostic relevance of clonal heterogeneity of TP53 copy number, we profiled tumors from 1777 newly diagnosed Myeloma XI trial patients with multiplex ligation-dependent probe amplification (MLPA). Subclonal TP53 deletions were independently associated with shorter overall survival, with a hazard ratio of 1.8 (95% confidence interval, 1.2-2.8; P = .01). Clonal, but not subclonal, TP53 deletions were associated with clinical markers of advanced disease, specifically lower platelet counts (P < .001) and increased lactate dehydrogenase (P < .001), as well as a higher frequency of features indicative of genomic instability, del(13q) (P = .002) or del(1p) (P = .006). Biallelic TP53 loss-of-function by mutation and deletion was rare (2.4%) and associated with advanced disease. We present a framework for identifying subclonal TP53 deletions by MLPA, to improve patient stratification in MM and tailor therapy, enabling management strategies

    Differentiation of Chronic Lymphocytic Leukemia B Cells into Immunoglobulin Secreting Cells Decreases LEF-1 Expression

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    Lymphocyte enhancer binding factor 1 (LEF-1) plays a crucial role in B lineage development and is only expressed in B cell precursors as B cell differentiation into mature B and plasma cells silences its expression. Chronic lymphocytic leukemia (CLL) cells aberrantly express LEF-1 and its expression is required for cellular survival. We hypothesized that modification of the differentiation status of CLL cells would result in loss of LEF-1 expression and eliminate the survival advantage provided by its aberrant expression. In this study, we first established a methodology that induces CLL cells to differentiate into immunoglobulin (Ig) secreting cells (ISC) using the TLR9 agonist, CpG, together with cytokines (CpG/c). CpG/c stimulation resulted in dramatic CLL cell phenotypic and morphologic changes, expression of cytoplasmic Ig, and secretion of light chain restricted Ig. CpG/c stimulation also resulted in decreased CLL cell LEF-1 expression and increased Blimp-1 expression, which is crucial for plasma cell differentiation. Further, Wnt pathway activation and cellular survival were impaired in differentiated CLL cells compared to undifferentiated CLL cells. These data support the notion that CLL can differentiate into ISC and that this triggers decreased leukemic cell survival secondary to the down regulation of LEF-1 and decreased Wnt pathway activation

    Genetically-Based Olfactory Signatures Persist Despite Dietary Variation

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    Individual mice have a unique odor, or odortype, that facilitates individual recognition. Odortypes, like other phenotypes, can be influenced by genetic and environmental variation. The genetic influence derives in part from genes of the major histocompatibility complex (MHC). A major environmental influence is diet, which could obscure the genetic contribution to odortype. Because odortype stability is a prerequisite for individual recognition under normal behavioral conditions, we investigated whether MHC-determined urinary odortypes of inbred mice can be identified in the face of large diet-induced variation. Mice trained to discriminate urines from panels of mice that differed both in diet and MHC type found the diet odor more salient in generalization trials. Nevertheless, when mice were trained to discriminate mice with only MHC differences (but on the same diet), they recognized the MHC difference when tested with urines from mice on a different diet. This indicates that MHC odor profiles remain despite large dietary variation. Chemical analyses of urinary volatile organic compounds (VOCs) extracted by solid phase microextraction (SPME) and analyzed by gas chromatography/mass spectrometry (GC/MS) are consistent with this inference. Although diet influenced VOC variation more than MHC, with algorithmic training (supervised classification) MHC types could be accurately discriminated across different diets. Thus, although there are clear diet effects on urinary volatile profiles, they do not obscure MHC effects
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