3856 results for "*geneti*"

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• PCGP Ph-like ALL

  Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

  Study EGAS00001000654

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Whole Genome Sequencing of 317 individuals from the Pacific region

  Although genetic studies of modern Oceanians have revealed varying levels of admixture with populations of East Asian ancestry, attributed to the Austronesian expansion, the early peopling history of Oceania remains poorly characterized. Additionally, it is currently unknown whether and how the settlement of the Pacific was accompanied by genetic adaptation to island environments, and if archaic introgression facilitated this process in Oceanians, who present the highest worldwide levels of combined Neanderthal and Denisovan ancestry. This study reports the first whole genome-based survey that addresses a wide range of questions related to the demographic and adaptive history of Pacific populations.

  Study EGAS00001004540

• Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

  We retrospectively collected patients (n=1047) enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017. The outcomes were duration of treatment (DOT) and overall survival (OS). Clinical features were analyzed for their influence on the treatment effect and prognosis. Next-generation sequencing (NGS) was performed to identify genetic biomarkers associated with the efficacy of pemetrexed. The median DOT was 9.1 months (95% CI: 8.5-9.8), and the median OS was 26.2 months (95% CI: 24.2-28.1). OS was positively correlated with DOT (r=0.403, P<0.001). Multivariable analysis showed that smoking status and Eastern Cooperative Oncology Group (ECOG) performance status (PS) were independently associated with DOT; smoking status, ECOG PS, targeted therapy, and EGFR/ALK/ROS1 status were independently associated with OS. NGS in 22 patients with available samples showed genes with high mutation rates were: TP53 (54.5%), EGFR (50.0%), MYC (18.2%), PIK3CA (13.6%). When grouped based on progression-free survival (PFS) reported in the PARAMOUNT study, the DOT >6.9 months set was associated with PIK3CA, ALK, BRINP3, CDKN2A, CSMD3, EPHA3, KRAS, and RB1 mutations, while ERBB2 mutation was observed only in the DOT ≤6.9 months set. This study shows that initial chemotherapy with pemetrexed is an effective regimen for advanced lung adenocarcinoma in selected Chinese patients. There is no specific genetic profile predicting the benefit of pemetrexed found by NGS. Biomarkers predicting the efficacy of pemetrexed need further exploration.

  Study EGAS00001004546

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma

  Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

  Study EGAS00001004551

• 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

• SNP array files, IDAT files, from 34 members of a Family with a high prevalence of psychosis

  We investigated the genetic causes of major mental disorders (MMDs) including schizophrenia, bipolar disorder I, major depressive disorder, and attention deficit hyperactive disorder, in a large family pedigree from Alpujarras, South of Spain, a region with a high prevalence of psychotic disorders. We applied a systematic genomic approach based on karyotyping (N=4), genotyping by genome-wide SNP array (N=33), whole-exome sequencing (N=4), and whole-genome sequencing (N=12). We performed genome-wide linkage analysis, family-based association analysis, and polygenic risk score estimates. Significant linkage was obtained at chromosome 9 (9q33.1-33.2, LOD score= 4.11), a suggestive region that contains five candidate genes ASTN2, BRINP1, C5, TLR4, and TRIM32, previously associated to MMDs. Comprehensive analysis associated the MMD phenotype with genes of the immune system with dual brain functions. Moreover, the psychotic phenotype was enriched for genes involved in synapsis. These results should be considered once studying the genetics of psychiatric disorders in other families, especially the ones from the same region, since founder effects may be related to the high prevalence.

  Study EGAS00001004592

• 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

• whole genome sequence data of multifocal hepatocellular carcinoma

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics pro?ling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual speci?city protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identi?cation of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002338