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Biologic characteristics of B-lymphoblastic leukemia correspond to immunoglobulin gene diversity [sequencing]

GSE200557 Homo sapiens (human) Single-cell RNA-seq 69 samples Submitted 2025/04/08 Platform GPL24676Platform GPL15520
At a glance

Single-cell RNA-seq · human · 69 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
69 samples: 5 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
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.
Summary (written by the submitters)
It remains unclear whether the variable biologic features of B-lymphoblastic leukemia (B-ALL) reflect distinct cells of origin in the hierarchy of early B cell development. Recombination activating genes (RAG) 1 and 2 rearrange the immunoglobulin heavy chain (IgH) locus in B lymphoid progenitors, resulting in unique variable (Vh), diversity (D), and joining (Jh) gene rearrangements.
Read the full summary ↓
To test whether discrete properties of each B-ALL reflect derivation from distinct developmental B cell stages, we assessed the relationship between IgH variable gene (IGHV) characteristics and gene expression. Using targeted, pre-treatment IgH sequencing of 22 patients’ B-ALL, we discovered 2 distinct groups: leukemias with RAG-mediated intra-clonal IGHV sequence diversification (‘diverse’; N=9, 40.9%) and those lacking diversity (‘homogeneous’; N=10, 45.5%). Three patients (13.6%) lacked a dominant IgH sequence. In the ‘diverse’ cohort, we observed extensive subclone evolution arising from Vh gene recombination after neoplastic transformation (median: 482 subclones; range 2-2600). In the ‘homogeneous’ cohort, all IgH clones lacked subclone evolution. The ‘diverse’ cohort demonstrated enriched expression of genes associated with regulation of a hematopoietic stem cell state, while ‘homogeneous’ cases showed enriched expression of genes involving cell fate commitment. Furthermore, distinct IgH clonotypes within a single patient could be individually diverse or homogenous. Single cell analysis indicated that within a single patient, only occasional IgH clonotypes were expressed; IGHV-expressing leukemia cells were characterized by distinctive phenotypes including RAG1 pathway up-expression. In summary, pre-treatment IgH composition reflects the B cell stage at leukemic initiation and provides insights about the biologic mechanisms of genetic diversity in B-ALL.
This dataset
Open GSE200557 in finder → Find more human RNA-seq datasets → Acute lymphoblastic 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 GSE200557_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA825267 and SRA study SRP369117. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in triplicate
RB ×38 18-TB ×4 13-TB ×3 17-TB ×3 12-TB ×2 07-TBL0074_bulkRNA ×1 07-TBL0074_scRNA ×1 07-TBL0074_scVDJ ×1 +16 more

Supports a between-group comparison across 50 samples.

How we read this: 5 replicated groups read from 69 sample titles; they account for 50 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 29 more — browse all 69 samples with per-sample file links →

More Acute lymphoblastic 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.