3334 results for "*geneti*"

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• STAT5 is a therapeutically targetable vulnerability in cutaneous T-cell lymphoma

  Cutaneous T-cell lymphomas represent a heterogeneous group of lymphoproliferative disorders characterized by the infiltration and expansion of mature malignant T-cells into the skin. The disease encompasses distinct variants such as mycosis fungoides a skin resident variant, in which the malignant cells are restricted to skin lesions, and leukemic variant sézary syndrome characterized by circulating malignant T-cells. Here we integrated shallow whole genome sequencing and whole exome sequencing, on samples from four sézary syndrome patients and two advanced mycosis fungoides patients with blood involvement, to characterize genetic alterations and assess their therapeutic actionability. We identified an elevated copy number of 17q, resulting in increased STAT5 expression and activation, as a key factor in the pathophysiology of the disease.

  Study EGAS00001004719

• A Universal Gut Metagenomic-Derived Signature Predicts Cirrhosis

  Dysregulation of the gut microbiome has been implicated in the progression of nonalcoholic fatty liver disease (NAFLD) to advanced fibrosis and cirrhosis. To determine the diagnostic capacity of this association, stool microbiomes were compared across 163 well-characterized participants encompassing non-NAFLD controls, NAFLD-cirrhosis patients and their first-degree relatives. Interrogation of shotgun metagenomic and untargeted metabolomic profiles using the Random Forest machine learning algorithm and differential abundance analysis identified discrete metagenomic and metabolomic signatures that were similarly effective in detecting cirrhosis (diagnostic accuracy 0.91, AUC). Combining the metagenomic signature with age and serum albumin levels accurately distinguished cirrhosis in etiologically and genetically distinct cohorts from geographically separated regions. Additional inclusion of serum aspartate aminotransferase levels, which are increased in cirrhosis patients, enabled discrimination of cirrhosis from earlier stages of fibrosis. These findings demonstrate that a core set of gut microbiome species may offer universal utility as a non-invasive diagnostic test for cirrhosis.

  Study EGAS00001004600

• Measurable residual disease in elderly acute myeloid leukemia: results from the PETHEMA-FLUGAZA phase III clinical trial

  The value of measurable residual disease (MRD) in elderly patients with acute myeloid leukemia (AML) is inconsistent between those treated with intensive vs hypomethylating drugs, and unknown after semi-intensive therapy. We investigated the role of MRD in refining complete remission (CR) and treatment duration in the phase III PETHEMA-FLUGAZA clinical trial, that randomized 283 elderly AML patients to induction and consolidation with fludarabine plus cytarabine or induction and consolidation with 5-azacitidine. After consolidation, patients continued treatment if MRD≥0.01% or stopped if MRD<0.01%, assessed by multidimensional flow cytometry (MFC). On multivariate analysis including genetic risk and treatment arm, MRD status in patients achieving CR (N=72) was the only independent prognostic factor for cumulative-incidence of relapse (HR:2.95;P=.002) and relapse-free survival (HR:3.45;P=.002). A trend for longer overall survival was observed in patients with undetectable MRD (N=13/72). Although leukemic cells from most elderly AML patients display phenotypic aberrancies vs their normal counterpart (N=258/265), CD34 progenitors from cases with undetectable MRD by MFC displayed extensive genetic abnormalities identified by whole-exome sequencing. This study supports MRD assessment to refine CR after semi-intensive therapy or hypomethylating agents, but unveils that improved sensitivity is warranted to individualize treatment and prolong survival of elderly AML patients achieving undetectable MRD.

  Study EGAS00001004574

• The endometrial transcription landscape of MRKH syndrome

  The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue. In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome.

  Study EGAS00001004601

• A GWAS for cutaneous leishmaniasis in Brazil

  Our goal was to identify genetic risk factors for cutaneous leishmaniasis (CL) caused by Leishmania braziliensis. Genotyping 2066 CL cases and 2046 controls using Illumina HumanCoreExomeBeadChips provided data for 4,498,586 imputed single nucleotide variants (SNVs). Genome-wide association testing using linear mixed models took account of genetic diversity/ethnicity/admixture. Post-GWAS positional, expression quantitative trait locus (eQTL), and chromatin interaction mapping was performed in FUMA. Transcriptional data were compared between lesions and normal skin, and cytokines measured using flow cytometry and Bioplex assay.

  Study EGAS00001004596

• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  The extensive primary and secondary drug resistance in many cancer types requires rational approaches to design personalized and selective combinatorial therapies that do not only show synergistic effect in overall cancer cell killing but also result in minimal toxic side effects on non-malignant cells. To address the combinatorial explosion in the number of relevant combinations, we implemented a machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA-sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory AML patient cases, each with a different genetic background, our integrated approach accurately predicted patient-specific combinations that were shown to result not only in synergistic cancer cell co-inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our data-driven approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of non-malignant cells, and highlight the relevance of considering cell heterogeneity for personalized cancer therapy.

  Study EGAS00001004614

• 16 Year Life History and Genomic Evolution of an ER+ HER2- Breast Cancer

  We reconstructed the genomic evolution through the sixteen year history of an ER+ HER2- breast cancer patient to investigate molecular mechanisms of disease relapse and treatment resistance after long term exposure to hormonal therapy. Genomic and transcriptomic profiling was performed on primary breast tumor (2002), initial recurrence (2012) and liver metastasis (2015) tumor samples. Cell free DNA analysis was performed at eleven timepoints (2015-2017).This phylogenetic reconstruction of the life history of a single patient's cancer as well as monitoring tumor progression through liquid biopsies with the detection of a resistant clone harboring a de-novo ESR1 E380Q mutation allowed for uncovering the molecular mechanisms leading to initial relapse, metastatic spread and treatment resistance.

  Study EGAS00001004624

• The Genetic Basis of Preeclampsia in an Andean Population Adapted to High Altitude

  Study EGAS00001004625

• The proliferative history shapes the DNA methylome of B-cell tumor and predicts clinical outcome

  Here, we provide access to CLL and DLBCL DNA methylation and gene expression data in the context of a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. This approach showed that differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.

  Study EGAS00001004640

• Genomewide detection of cytosine methylation by single molecule real-time sequencing

  5-methylcytosine (5mC) is an important type of epigenetic modification. In this study, we enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model. This methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses. 

  Study EGAS00001004642