259 results for ""independent+of+the+choice+of+kernel"+regularization+parameter+volumetric+rendering+paper"

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• Mutational Landscape and Tumor Burden Assessed by Cell-Free DNA in Diffuse Large B-Cell Lymphoma: a Population-based Study

  Purpose: We analyzed the utility of cfDNA in a prospective population-based cohort to determine the mutational profile, assess tumor burden, and estimate its impact in response rate and outcome in patients with DLBCL. Experimental Design: One-hundred patients were diagnosed with DLBCL during the study period. Mutational status of 112 genes was studied in cfDNA by targeted next-generation sequencing. Paired formalin-fixed paraffin-embedded samples and volumetric PET/CT were assessed when available. Results: Appropriate cfDNA to perform the analyses was obtained in 79/100 cases. At least one mutation could be detected in 69/79 cases (87%). The sensitivity of cfDNA to detect the mutations was 68% (95% CI: 56.2-78.7). The mutational landscape found in cfDNA samples was highly consistent with that shown in the tissue and allowed genetic classification in 43% of the cases. A higher amount of ctDNA significantly correlated with clinical parameters related to tumor burden (elevated LDH and β2-microglobulin serum levels, advanced stage, and high-risk IPI) and total metabolic tumor volume assessed by PET/CT. In patients treated with curative intent, high ctDNA levels (>2.5 log hGE/mL) were associated with lower complete response (65% vs. 96%, P<0.004), shorter progression-free survival (65% vs. 85%, P=0.038) and overall survival (73% vs. 100%, P=0.007) at 2 years, although it did not maintain prognostic value in multivariate analyses. Conclusions: In a population-based prospective DLBCL series, cfDNA resulted an alternative source to estimate tumor burden and to determine the tumor mutational profile and genetic classification, which have prognostic implications and may contribute to a future tailored

  Study EGAS00001004733

• NHLBI TOPMed: Defining the Time-Dependent Genetic and Transcriptomic Responses to Cardiac Injury Among Patients with Arrhythmias

  The UMMS miRhythm Study is an ongoing study of adult patients undergoing an elective electrophysiology study or arrhythmia ablation procedure for a supraventricular or ventricular arrhythmia, including atrial fibrillation (AF). Atrial fibrillation is a major clinical and public health problem that is related to atrial pathologic remodeling. Few tools are available to quantify the activity or extent of this remodeling, rendering it difficult to identify individuals at risk for AF. Previous studies have suggested an important role for miRNA in cardiovascular disease through gene expression regulation, making this a promising avenue for studying AF mechanisms. The aim of the study is to determine the time-dependent changes to key circulating miRNAs in a model of planned atrial injury and remodeling via ablation. Such knowledge might provide additional insight into the biology and activity of the acute atrial injury response, and furthermore, inform new targets for development of preventative interventions or allow for better AF risk stratification. To assess pathways regulating atrial pathological remodeling, patient blood samples are collected prior to their ablation procedures and also at a regularly scheduled 1-month follow-up appointment. Plasma expression of miRNA is measured using high-throughput quantitative reverse transcriptase polymerase chain reaction (RT-qPCR), providing novel insights into the regulatory processes underlying AF, as well as acute atrial injury in vivo. Additionally, data collected from whole-genome sequencing (WGS) is used to supplement miRNA analyses and further explore new relations between genes and abnormal heart rhythm.

  Study phs001434

• Next generation sequencing of sporadic schwannomatosis samples

  Schwannomatosis (MIM #162091) is characterized by the development of multiple schwannomas without vestibular nerve involvement (which is a characteristic of neurofibromatosis type 2 - NF2). In an effort to detect novel genetic alterations predisposing to schwannomatosis, we sequenced eight tumor-blood DNA pairs from de novo schwannomatosis patients. The results of our study are present in the paper "Whole exome sequencing reveals that the majority of schwannomatosis cases remain unexplained after excluding SMARCB1 and LZTR1 germline variants" published in Acta Neuropathologica (PMID:25008767)

  Study EGAS00001000767

• DKFZ-St.Jude Medulloblastoma - 70 PAN-GATC control exomes

  Exome controls for 70 individuals, PAN-GATC cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006661

• DKFZ-St.Jude Medulloblastoma - 218 CEF control exomes

  218 control exomes, CEF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006659

• Epigentic sequence data of monocytes and macrophages

  Data for paper: Epigenetic dynamics of monocyte to macrophage differentiation with Chip Seq, NOMe, mRNA, total RNA, noncoding RNA, whole genome bisulfite seq,

  Dataset EGAD00001002201

• WGS files for Mullighan PAX5_B-ALL

  WGS files for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004446

• WES files for Mullighan PAX5_B-ALL

  WES files for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004447

• RNASeq files for Mullighan TXVI dataset

  RNASeq files for paper titled "Prognostic and therapeutic significance of leukemia subtypes and minimal residual disease measurements in pediatric acute lymphoblastic leukemia treated with contemporary risk-directed trial: a cohort study"

  Dataset EGAD00001006609

• Clonally heritable gene expression imparts a layer of diversity within cell types

  Human datasets associated with paper 'Clonally heritable gene expression imparts a layer of diversity within cell types' published in Cell Systems

  Dataset EGAD50000000231