GEO series

Single-cell network pharmacology predicts total therapies targeting multiple developmental clones in B-cell acute lymphoblastic leukemia

GSE235787 Homo sapiens (human) Single-cell RNA-seq 20 samples Submitted 2024/03/21 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 20 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Topic: Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples: 20 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: Single-cell systems pharmacology identifies development-driven drug response and combination therapy in B cell acute lymphoblastic leukemiaCancer cell · 2024

Summary (written by the submitters)

Taking the advantage of the human bone marrow (BM) scRNA-seq in Human cell atlas census of immune cells study, we resolved B lineage into comprehensive human B-cell development stages and identified their landscape in B-ALL. L-asparaginase is the cornerstone of combination protocols in acute lymphoblastic leukemia (ALL).

Read the full summary ↓

After profiled B cell acute lymphoblastic leukemia (B-ALL) patient drug sensitivities ex vivo and applied network-based systems pharmacology analyses to examine signal circuitry, we revealed that the B-cell differentiation are correlated with the L-asparaginase response in B-ALL. Further multiomics analysis confirmed that L-asparaginase resistant B-ALL had higher percentage of Pre-pro-B like cells and less Pro-B like cells. By targeting BCL2, the key hub genes in Pre-pro-B cell network, Venetoclax combined with L-asparaginase can produce better outcome as demonstrated by in vitro and in vivo evaluations. In conclusion, our results identified B-ALL heterogeneity in L-asparaginase-resistant signature and BCL2 signaling and B-cell maturation stage, consistent with L-asparaginase response, providing unique opportunities for total clonal therapy.

Published in

Single-cell systems pharmacology identifies development-driven drug response and combination therapy in B cell acute lymphoblastic leukemia

Huang X, Li Y, Zhang J et al. · Cancer cell 2024 · PMID 38593781 · doi:10.1016/j.ccell.2024.03.003

This dataset

Open GSE235787 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 GSE235787_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 PRJNA987621 and SRA study SRP445875. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38593781) ↗

Samples in this study

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+ 20 more — browse all 20 samples with per-sample file links →

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