Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: NANOPORE SEQUENCING APPROACH FOR IMMUNOGLOBULIN GENE ANALYSIS IN CHRONIC LYMPHOCYTIC LEUKEMIA

PROVIDER: PRJNA731004 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR14584500_1.fastq.gz	Fastqsanger.gz
	SRR14584501_1.fastq.gz	Fastqsanger.gz
	SRR14584502_1.fastq.gz	Fastqsanger.gz
	SRR14584503_1.fastq.gz	Fastqsanger.gz
	SRR14584504_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 36

Similar Datasets

Project description:TP53 gene mutation analysis in chronic lymphocytic leukemia by Nanopore MinION sequencing

| PRJNA336154 | ENA

Nanda2013 - B cell chronic lymphocytic leukemia A model with immune response

Project description:B cell chronic lymphocytic leukemia - A model with immune response Seema Nanda 1, , Lisette dePillis 2, and Ami Radunskaya 3, 1. Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bangalore 560065, India 2. Department of Mathematics, Harvey Mudd College, Claremont, CA 91711 3. Department of Mathematics, Pomona College, Claremont, CA, 91711, United States Abstract B cell chronic lymphocytic leukemia (B-CLL) is known to have substantial clinical heterogeneity. There is no cure, but treatments allow for disease management. However, the wide range of clinical courses experienced by B-CLL patients makes prognosis and hence treatment a significant challenge. In an attempt to study disease progression across different patients via a unified yet flexible approach, we present a mathematical model of B-CLL with immune response, that can capture both rapid and slow disease progression. This model includes four different cell populations in the peripheral blood of humans: B-CLL cells, NK cells, cytotoxic T cells and helper T cells. We analyze existing data in the medical literature, determine ranges of values for parameters of the model, and compare our model outcomes to clinical patient data. The goal of this work is to provide a tool that may shed light on factors affecting the course of disease progression in patients. This modeling tool can serve as a foundation upon which future treatments can be based. Keywords: NK cell, chronic lymphocytic leukemia, mathematical model, T cell., B-CLL.

2020-01-09 | MODEL2001090002 | BioModels

Transcription profiling of human CLL - a genomic approach to improve prognosis and predict therapeutic response in chronic lymphocytic leukemia - super series

Project description:This SuperSeries is composed of the following subset Series:; GSE10137: A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia (Mayo_Ohio); GSE10138: A Genomic Approach to Improve Prognosis and Predict Therapeutic Response in Chronic Lymphocytic Leukemia (Duke_VA) Experiment Overall Design: Refer to individual Series

2009-11-09 | E-GEOD-10139 | biostudies-arrayexpress

A capture-based next-generation sequencing panel for the molecular characterization of chronic lymphocytic leukemia

Project description:Capture-based next-generation sequencing (NGS) data generated using a custom chronic lymphocytic leukemia (CLL) gene panel designed to capture driver gene mutations, copy number alterations and immunoglobulin gene rearrangements. Samples from two different cohorts (retrospective, 25 patients; prospective, 87 patients).

| EGAS00001006975 | EGA

Project description:chronic lymphocytic leukemia sequencing

| PRJNA813751 | ENA

Rodrigues2019 - A mathematical model for chemoimmunotherapy of chronic lymphocytic leukemia

Project description:THis is a simple ordinary differential equation model describing chemoimmunotherapy of chronic lymphocytic leukemia, including descriptions of the combinatorial effects of chemotherapy and adoptive cellular immunotherapy.

2024-09-02 | BIOMD0000000879 | BioModels

Transcription profiling of genetically and clinically distinct subgroups of human B-cell chronic lymphocytic leukemia patients

Project description:We used high density oligonucleotide arrays to identify molecular correlates of genetically and clinically distinct subgroups of B-cell chronic lymphocytic leukemia (B-CLL). Gene expression profiling was used to profile the five most frequent genomic aberrations, namely deletions affecting chromosome bands 13q14, 11q22-q23, 17p13 and 6q21, and gains of genomic material affecting chromosome band 12q13. A strikingly high degree of correlation between loss or gain of genomic material and the amount of transcripts from the affected regions leads to the hypothesis of gene dosage as a significant pathogenic factor. Furthermore, the influence of the immunoglobulin variable heavy chain (VH) mutation status was determined. A clear distinction in the expression profiles of unmutated and mutated VH samples exists, which can be discovered using unsupervised learning methods. However, when samples were separated by gender, this separation could only be detected in samples from male patients. Since the samples were either hybridized onto HG-U95A arrays or onto HG-U95Av2 arrays, only genes common to both arrays were used for further analysis. This study is described in more detail in Haslinger C, et al. 2004. J Clin Oncol. 22:3937-3949; Series _keyword: CLL, chronic lymphocytic leukemia, immunoglobulin somatic hypermutation, genomic aberrations

2007-08-25 | E-GEOD-2466 | biostudies-arrayexpress

mutated IGHV3-23 CLL

Project description:Expression of stereotyped B cell receptors (BCR), i.e. non-random combinations of immunoglobulin heavy-chain variable (IGHV) genes, complementarity-determining region-3 (HCDR3), and IGV light chains, identifies discrete clusters and represents a peculiar feature of chronic lymphocytic leukemia (CLL). Expression of IGHV3-23 characterized a CLL subset with peculiar molecular and clinical features.

2009-06-13 | GSE16065 | GEO

Homo sapiens

Project description:Chronic lymphocytic leukemia xenograft

| PRJNA310110 | ENA

Homo sapiens

Project description:Chronic lymphocytic leukemia transcriptomes

| PRJNA222528 | ENA