3311 results for "*geneti*"

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• Genomic and epigenomic characterization of juvenile myelomonocytic leukemia (JMML)

  Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood. While some cases show spontaneous remission, allogeneic hematopoietic stem cell transplantation (HSCT) remains the only curative treatment option for the majority of patients, however, the 5-year event-free survival reaches only about 50%. Hyperactive RAS signaling is assumed to be the main driving event in JMML. It is caused by genetic alterations in CBL, KRAS, NF1, NRAS, or PTPN11 in about 90% of patients. So far, there is no clear understanding of how RAS pathway mutations relate to the heterogeneous disease biology and variable clinical outcome seen in JMML patients. As a consequence, established clinical and genetic markers fail to fully represent the observed disease heterogeneity. We hypothesized that DNA methylation profiling, either alone or in combination with genetic alterations, might provide a molecular basis for disease classification. Genome wide DNA methylation analysis using the HumanMethylation450 Bead Chip array was performed in a discovery cohort of 20 patients (19 JMML, 1 Noonan syndrome). The clinical relevance of our findings was assessed in an unselected sample set consisting of 147 consecutive patients with JMML (n=129) or Noonan syndrome (n=18) associated myeloproliferative disorder (n=18) registered in the EWOG-MDS 1998 & 2006 trials. Data integration was performed in a subset of patients with available exome sequencing (n=50) and expression profiling (n=15) data. This integrated approach identified three JMML subgroups characterized by distinct clinical and biological features. This analysis further suggested a molecular mechanism by which additional genetic events, presumably further activating the RAS-RAF-MEK-ERK pathway, mediate DNA hypermethylation via up-regulation of DNMTs in more aggressive JMML cases.

  Study EGAS00001002511

• Sampling of multi-centric lower grade glioma influences management and provides insight into gliomagenesis

  Rare multicentric lower-grade gliomas (LGG) represent a unique opportunity to study the heterogeneity between distinct tumor foci in a single patient, and to infer their origins and parallel patterns of evolution. In this study, we integrate clinical features, histology and immunohistochemistry for 4 patients with multicentric LGG, arising both synchronously and metachronously. For 3 patients we analyze the phylogeny of the lesions using exome sequencing, including one case with a total of 8 samples from the two lesions. We show that each tumor in multicentric LGG cases may arise independently or may diverge very early in their development, presenting as genetically and histologically distinct tumors suggesting that comprehensive sampling of these lesions can significantly alter diagnosis and management.

  Study EGAS00001002495

• Targeted next-generation sequencing detects novel gene-phenotype associations and expands the mutational spectrum in cardiomyopathie

  Cardiomyopathies are a heterogeneous group of primary diseases of the myocardium,including hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), andarrhythmogenic right ventricular cardiomyopathy (ARVC), with higher morbidity andmortality. These diseases are genetically diverse and associated with rare mutations ina large number of genes, many of which overlap among the phenotypes. To betterinvestigate the genetic overlap between these three phenotypes and to identify newgenotype-phenotype correlations, we designed a custom gene panel consisting of 115genes known to be associated with cardiomyopathic phenotypes and channelopathies.A cohort of 38 unrelated patients, 16 affected by DCM, 14 by HCM and 8 by ARVC,was recruited for the study on the basis of more severe phenotypes and family historyof cardiomyopathy and/or sudden death.

  Study EGAS00001002506

• Genome_Diversity_in_Africa_Project__Uganda

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics

  Study EGAS00001002523

• The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis.

  In the present study, we identified differentially expressed protein-coding genes from RNA transcriptional profiling performed on 11 paired cancer tissues and adjacent non-cancerous tissues. Then, we conducted GO, KEGG, PPI network and centralities analyses to study and identify changes in pathways and hub genes. The aim of this study was to improve understanding of HCC carcinogenesis by providing information concerning the genetic changes that occur during disease progression and to uncover the expression of biomarkers with potential use for clinical diagnosis, treatment, and monitoring of disease progression.

  Study EGAS00001002526

• A biobank of patient-derived pediatric brain tumor models

  Brain tumors are the leading cause of cancer-related death in children. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of pediatric brain tumors that may lead to novel therapeutic strategies. To evaluate new treatments, better preclinical models adequately reflecting the biological heterogeneity are needed. Through the Children’s Oncology Group ACNS02B3 study, we have generated and comprehensively characterized 30 patient-derived orthotopic xenograft models and 7 cell lines representing 14 molecular subgroups of pediatric brain tumors. Patient-derived orthotopic xenograft models were found to be representative of the human tumors they were derived from in terms of histology, immunohistochemistry, gene expression, DNA methylation, copy number, and mutational profiles. In vivo drug sensitivity of targeted therapeutics was associated with distinct molecular tumor subgroups and specific genetic alterations. These models and their molecular characterization provide an unprecedented resource for the cancer community to study key oncogenic drivers and to evaluate novel treatment strategies.

  Study EGAS00001002536

• The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

  Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of DNA methylation in matched primary and recurring glioblastoma tumors, using data from a highly annotated clinical cohort that was selected through a national patient registry. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected FFPE samples, and we validate bisulfite sequencing as a multipurpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional characteristics of the profiled tumor samples. On the basis of these data, we identified subtle differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study establishes an open resource for dissecting DNA methylation heterogeneity in a genetically diverse and heterogeneous cancer, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology for a national cohort, thereby leveraging existing samples and data collected as part of routine clinical practice.

  Study EGAS00001002538

• Genomic landscape of human diversity across Madagascar

  Although situated ~400 km from the east coast of Africa, Madagascar exhibits cultural, linguistic, and genetic traits from both Southeast Asia and Eastern Africa. The settlement history remains contentious; we therefore used a grid-based approach to sample at high-resolution the genomic diversity (including maternal lineages, paternal lineages, and genome-wide data) across 257 villages and 2704 Malagasy individuals. We find a common Bantu and Austronesian descent for all Malagasy individuals with a limited paternal contribution from Europe and the Middle East. Admixture and demographic growth happened recently, suggesting a rapid settlement of Madagascar during the last millennium. However, the distribution of African and Asian ancestry across the island reveals that the admixture was sex biased and happened heterogeneously across Madagascar, suggesting independent colonization of Madagascar from Africa and Asia rather than settlement by an already-admixed population. In addition, there are geographic influences on the present genomic diversity, independent of the admixture, showing that a few centuries is sufficient to produce detectable genetic structure in human populations.

  Study EGAS00001002549

• Pilot study for Illumina TST170 NGS panel on cutaneous T cell lymphoma samples

  A number of genomic studies using next generation sequencing (NGS) techniques have attempted to understand the underlying genetic basis of cutaneous T-cell lymphoma and found alterations in genes that are involved in T-cell activation, NF-kB and JAK-signal transducer and activator of transcription (STAT) pathways. 8 diagnostic skin biopsy samples (2xplaque, 6xtumour) on FFPE blocks were selected from 8 MF patients (stage IB:n=1, IIB:n=6, IVA2:n=1). An H&E was performed in order to assess percentage of tumor cells, viable cells, necrosis and immune infiltration, to determine the number of slides required for NGS. Freshly cut unstained slides were manually macrodissected prior to DNA and RNA extraction. Targeted deep sequencing was performed using panel of 170 genes associated with common solid tumours (Illumina TruSight Tumour 170 NGS panel). VCF files generated via the Illumina’s Basespace platform.

  Study EGAS00001002567

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604