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Transcriptomic profiling of bone marrow cells from CML mouse models and newly diagnosed patients treated with SOS1 inhibitor BI-3406 and/or imatinib

GSE303378 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/06/22 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 48 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 myeloid leukemiaThis series is part of our curated briefing on it.
Samples
48 samples: 7 conditions, mostly with about 4 replicates eachGroups 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)
Despite the success of BCR-ABL1 tyrosine kinase inhibitors (TKIs) like imatinib in treating chronic myeloid leukemia (CML), therapeutic resistance and disease persistence remain significant challenges. This study investigated the potential of BI-3406, a selective SOS1 inhibitor (a key activator of RAS signaling), either alone or in combination with imatinib.
Read the full summary ↓
Using preclinical CML models, including transgenic mice and patient samples, it was observed that BI-3406 and imatinib administration were well-tolerated. Although both drugs partially reduced splenomegaly and leukocytosis individually, combination therapy showed a significantly greater therapeutic effect. This combination extended survival, normalized spleen architecture, and sharply reduced leukemic stem and progenitor cells, suggesting a synergistic impact on leukemic burden and stem cell compartments. In vitro assays confirmed that BI-3406 potentiated the cytotoxic effects of imatinib in CML cell lines, increasing apoptosis. Notably, in primary bone marrow cells from patients with the imatinib-resistant T315I mutation, BI-3406 not only synergized with ponatinib but also restored sensitivity to imatinib, offering a potential strategy to overcome drug resistance. RNA sequencing revealed that BI-3406 alone triggered a compensatory anabolic transcriptional program, while imatinib suppressed key proliferative and metabolic pathways. However, combination therapy produced more profound reprogramming, simultaneously reinforcing anti-proliferative effects and activating immune and inflammatory pathways. These conserved effects across murine and human samples support the translational potential of this dual-targeting strategy. In conclusion, SOS1 inhibition with BI-3406, in combination with TKIs, dismantles oncogenic signaling, suppresses leukemic stemness, and reprograms the immune microenvironment. This dual-targeting approach holds promise as a novel therapeutic strategy to enhance TKI efficacy and overcome resistance in CML.
This dataset
Open GSE303378 in finder → Find more RNA-seq datasets → Chronic myeloid 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 GSE303378_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 PRJNA1294971 and SRA study SRP602785. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly with about 4 replicates each
Bone marrow, Mouse, BCR-ABL–, untreated, ×4 Bone marrow, Mouse, BCR-ABL+, vehicle, ×4 Bone marrow, Mouse, BCR-ABL+, IMA, ×4 Bone marrow, Mouse, BCR-ABL+, BI3406, ×4 Bone marrow, Mouse, BCR-ABL+, IMA+BI3406, ×4 Bone marrow, Mouse, BCR-ABL+, SOS1KO, ×4 Bone marrow, Mouse, BCR-ABL+, SOS1KO+IMA, ×4 Bone marrow MNCs, Human, Patient 1, untreated ×1 +19 more

Supports a case/control comparison: 15 samples read as cases, 4 as controls.

How we read this: 7 replicated groups read from 48 sample titles; they account for 28 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

+ 8 more — browse all 48 samples with per-sample file links →

More Chronic myeloid leukemia datasets

Search all RNA-seq datasets in GEO →

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