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Trascriptional profiling of proliferating and resting fracntions in ibrutinib-treated CLL

GSE249956 Homo sapiens (human) RNA-seq (gene expression) 40 samples Submitted 2024/04/02 Platform GPL24676Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 40 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Chronic lymphocytic leukemiaThis series is part of our curated briefing on it.
Samples
40 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Early reappearance of intraclonal proliferative subpopulations in ibrutinib-resistant chronic lymphocytic leukemiaLeukemia · 2024
Summary (written by the submitters)
Bruton’s tyrosine kinase (BTK) inhibitors such as ibrutinib represent an effective strategy for treatment of chronic lymphocytic leukemia (CLL), although ~30% of patients eventually undergo disease progression. Here we investigated the long-term modulation of the CXCR4dim/CD5bright proliferative fraction (PF) and the CXCR4bright/CD5dim resting fraction (RF) in CLL samples, and their correlation with therapeutic outcome and emergence of ibrutinib resistance.
Read the full summary ↓
Longitudinal tracking by flow cytometry revealed that PF, initially suppressed by ibrutinib, reappeared upon early disease progression suggesting that PF evaluation could represent a sensitive and specific marker of CLL progression upon ibrutinib treatment. Transcriptomic analyses of PF at progression revealed similar proliferation signatures between pre- and post-treatment PF, demonstrating the emergence upon progression of a newly proliferating cell population.
Published in
Early reappearance of intraclonal proliferative subpopulations in ibrutinib-resistant chronic lymphocytic leukemia
Pozzo F, Forestieri G, Vit F et al. · Leukemia 2024 · PMID 38914716 · doi:10.1038/s41375-024-02301-y
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE249956_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1051488 and SRA study SRP477495. Searching any of these in the dataset finder brings you back here.

Samples in this study

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