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Chronic Lymphocytic Leukemia in African Ancestry Population is Characterized by Increased Genomic Instability

GSE246521 Homo sapiens (human) RNA-seq (gene expression) 350 samples Submitted 2025/02/12 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 350 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
350 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
Genomic characterization of chronic lymphocytic leukemia in patients of African ancestryBlood cancer journal · 2025
Summary (written by the submitters)
Despite the considerable effort to characterize the genomic landscape of chronic lymphocytic leukemia (CLL), published data have been almost exclusively derived from patients of European Ancestry (EA), with significant underrepresentation of minorities, including patients of African Ancestry (AA). Furthermore, although over a decade has passed since the initial observations of AA CLL patients suggesting an increased frequency of adverse prognostic factors and inferior clinical outcomes when compared to EA CLL, the differences between populations remain poorly understood.
Read the full summary ↓
To begin to address this gap, we explored whether ancestry differences exist in the genetic and transcriptomic features of 157 AA and 440 EA individuals diagnosed with CLL. In our study focused on 59 putative driver genes, we found an increased frequency of mutations in driver genes in AA CLL, including mutations in genes of the DNA damage repair (DDR) pathway. Telomere erosion was also increased in AA CLL, amplifying the notion of increased genomic instability in AA CLL. Furthermore, we found enrichment of the Tumor Necrosis Factor-alpha (TNFα) Signaling via NF-κB pathway in AA CLL compared to EA CLL, suggesting that tumor promoting inflammation plays an important role in AA CLL. In summary, we found higher frequency of mutations in genes from the DDR pathway along with shorter telomers and higher transcription of NFkB pathway genes. These results suggest that genomic instability is more prevalent in AA CLL than EA CLL. Future studies are needed to show that it may be a driver of poor prognosis among AA CLL patients.
Published in
Genomic characterization of chronic lymphocytic leukemia in patients of African ancestry
Bonolo de Campos C, McCabe CE, Bruins LA et al. · Blood cancer journal 2025 · PMID 39910036 · doi:10.1038/s41408-024-01207-3
This dataset
Open GSE246521 in finder → Find more human RNA-seq datasets → Chronic lymphocytic leukemia landscape →
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.

Series matrix ↓
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 GSE246521_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1033563 and SRA study SRP469131. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39910036) ↗
Study design
A cohort of 350 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run CLL001 … CLL350 and carry no group information.

Samples in this study

+ 310 more — browse all 350 samples with per-sample file links →

More Chronic lymphocytic leukemia datasets

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.