12536 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

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• Non-coding RNAs Activated by the Wnt/Beta-catenin Signaling Pathway in Hepatoblastoma

  Hepatoblastoma (HB) is the most common pediatric liver tumor, affecting mostly children under 3 years of age. This rare tumor represents 1% of all pediatric cancers. Genetic studies have shown that HB is characterized by high frequency mutations of the CTNNB1 gene encoding beta-catenin (around 75%) and relative genomic stability. Here we have analyzed the transcriptional profile of 21 HBs compared to matched non-tumor livers by Cap Analysis of Gene Expression (CAGE), which provides accurate and quantitative profiling of all transcripts. CAGE analysis revealed strong upregulation of known Wnt target coding genes in most tumors analyzed, consistent with previous transcriptomic studies. To better define the Wnt-dependent transcriptional landscape of HB, we integrated CAGE data with TCF4 ChIP-seq data from a CTNNB1-mutated cancer cell line and with the FANTOM5 genomic coordinates of TCF/LEF binding motifs. Both TCF/LEF binding motifs and ChIP-seq peaks were strongly enriched in the immediate upstream region, not only for protein-coding genes, but also for non-coding transcripts. Among the selected 112 top Wnt target genes at FDR<1.0E-6 and fold change>8, we found clear over-representation (66%) of distant transcription start sites (TSSs) representing lncRNAs and enhancer RNAs, which raises the question of their role in HB pathogenesis. Analysis of the 112 promoters using CAGEd-oPOSSUM confirmed the predominant involvement of Tcf/Lef transcription factors, together with HNF4G, GATA2, Sox3 and Ets-related genes. Finally, the 112 Wnt target signature defined 3 tumor subclasses, T1, T2 and T3, characterized by progressive alteration of the non-coding part of the transcriptome and significant differences in clinical behavior.

  Study phs001433

• Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

  The Sjögren's Genetics Network (SGENE) is an international collaboration focused on identifying and understanding the genetic variations that influence Sjögren’s pathology. Collectively, SGENE collaborators from 26 different sites (5 in the United States; 21 in foreign countries) have recruited a large cohort of geographically diverse participants of European ancestry. Recruitment, sample collection, and genotyping were performed at unique SGENE sites in compliance with local institutional review board approval. High-density SNP genotyping data were collated by the Oklahoma Medical Research Foundation (OMRF) and used to perform a GWAS of Sjögren's of European ancestry. Participants underwent extensive medical assessment for Sjögren's Syndrome using internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria. Data quality control, GWAS imputation using the Haplotype Reference Consortium, panel version 1.1, and dbGaP preparation/posting were performed at the OMRF. To facilitate research focused on understanding the genetics of Sjögren's syndrome, the Genomic Summary Results from this GWAS are being made available herein using a total of n=3232 Sjögren's cases and n=17,481 controls. A total of n=8962 controls were obtained from our SGENE collaborators or from our previous study (Lessard, et al. Nature Genetics 2013. PMID: 24097067). To achieve adequate case-to-control ratios for the GWAS analyses, population-based control GWAS data were also obtained from dbGaP (phs000428.v2.p2; phs000672.v1.p1; phs000196.v3.p1; phs000187.v1.p1). In accordance with IRB approval, subject consents, and data sharing restrictions, we are also making available the individual-level genotyping data for a subset of Sjögren's cases (n=1,199) that were genotyped at the OMRF.

  Study phs002723

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• MUSIC: Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children

  This study is an observational cohort study that will use routinely-collected clinical and cardiac (EKG, echocardiogram, CMR, exercise testing) data to assess the association between MIS-C (multisystem inflammatory syndrome in children) and cardiac outcomes within the first year after hospital discharge. Research funding will be available for EKGs, echocardiograms and MRIs in protocol windows that are not ordered by primary caregivers. Our principal goal is to determine the spectrum and early time course of coronary artery involvement, LV systolic function, and arrhythmias or conduction system abnormalities, and, using these data, to define associated clinical and laboratory factors. We will include all eligible patients, including retrospective cases beginning January 1, 2020, with follow-up (in-person or telehealth) up to one year and annual medical history forms until up to 5 years have elapsed since illness onset. Because many patients will have been identified by retrospective review, we will obtain consent at different times in their illness course. For this reason, it may be hard to reach some patients and their families. Waiver of consent will be obtained after three attempts have been made to locate the patient and family without success, as well as for the rare child who dies before informed consent can be obtained. We will include a HIPAA-compliant cryptographic algorithm to create a sharable “hashed” identifier from patient information. If blood work for research purposes is added to usual clinically-indicated blood work during follow-up visits, this will be covered by other informed consent forms. Our primary outcomes are the largest proximal Left Anterior Descending Coronary Artery (LAD) or Right Coronary Artery (RCA) z score and lowest Left Ventricular Ejection Fraction (LVEF).

  Study phs002770

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

  Background: Neuroblastoma (NB) displays important clinical and genetic heterogeneity, with emergence of new mutations at tumor progression. Patients and Methods: To study clonal evolution during treatment and follow-up, an innovative method based on circulating cell-free DNA (cfDNA) analysis by whole exome sequencing (WES) paired with target sequencing was realized in sequential liquid biopsy samples of 19 NB patients. Results: WES of the primary tumor and cfDNA at diagnosis showed overlap of Single Nucleotide Variants (SNVs) and Copy Number Alterations (CNAs), with 41% and 93% of all detected alterations common to the primary NB and cfDNA. CfDNA WES at a second time point indicated a mean of 22 new SNVs for patients with progressive disease. Relapse-specific alterations included genes of the MAPK pathway and targeted the protein kinase A signaling pathway. Deep coverage target sequencing of intermediate timepoints during treatment and follow-up identified distinct subclones. For 17 seemingly relapse-specific SNVs detected by sequencing detected these alterations in minor subclones, with relapse-emerging SNVs targeting genes of neuritogenesis and cell cycle. Furthermore a persisting, resistant clone with concomitant disappearance of other clones was identified by a mutation in the ubiquitin protein ligase HERC2. Conclusion: Modelisation of mutated allele fractions in cfDNA indicated distinct patterns of clonal evolution, with either a minor, treatment-resistant clone expanding to a major clone at relapse, or minor clones collaborating towards tumor progression. Identification of treatment-resistant clones will enable development of more efficient treatment strategies.cfDNA WES at relapse but not tumor or cfDNA WES at diagnosis, deep coverage target.

  Study EGAS00001002705

• Exploiting immune cell receptor information to quantify index switching in single cell transcriptome sequencing experiment

  By offering high sequencing speed and ultra-high-throughput at a low price, Illumina next-generation sequencing platforms has been widely adopted in recent years. However, an experiment with multiplexed library could be at risk of molecular recombination, known as “index switching”, which causes certain amount of reads to be assigned to an incorrect library. It is reported that a new advance, exclusion amplification (ExAmp) in conjunction with the patterned flow cell technology introduced on HiSeq 3000/HiSeq 4000/HiSeq X sequencing systems, potentially suffers from a higher rate of index switching than conventional bridge amplification. We took advantage of the diverse but highly cell-unique expression of immune cell receptors to quantify index switching on single cell RNA-seq data that were sequenced on HiSeq 3500 and HiSeq 4000. By utilizing the unique T-cell receptor (TCR) expression, we could quantify the spread-of-signal from many different wells (n=51 from total three batches) due to index switching. We used TraCer to reconstruct full-length TCR from all samples, and then used Kallisto to quantify TCR gene expression. We found index switching in all three batches of experiments investigated. The median percentage of incorrectly detected markers was estimated to be 4.2% (interquartile range (IQR): 2.0%-8.7%). We did not detect any consistent pattern of certain indices to be more prone for switching than others, suggesting that index switching is a stochastic process. We confirm that index switching is a problem that affects all samples run in multiplexed libraries on Illumina HiSeq 3500 and HiSeq 4000 platforms.

  Study EGAS00001002911

• Persistence of circulating tumor DNA in breast cancer patients during neoadjuvant treatment is a significant predictor of poor tumor response

  Purpose:Accurate assessment of response during neoadjuvant systemic treatment (NST) poses a major clinical challenge. Therefore, a minimally-invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions.Experimental Design: We profiled 93 genes in tissue from 193 early breast cancer patients. Patient-specific assays were designed to track ctDNA during NST from 145 patients with available plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as with clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release. Moreover, we tested the predictive value of driver events identified in the tumor.Results:At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR 0.062, 95% CI 0.01-0.48, P=0.0077). Out of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were non-responders (RCB II, n=8; RCB III, n=22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, while 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result. Conclusion:Overall, our results demonstrate that the detection and persistence of ctDNA at mid-therapy may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

  Study EGAS00001005798

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444