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Expression data of multiple myeloma patients at various stages of disease

GSE226176 Homo sapiens Expression profiling by high throughput sequencing 23 samples Submitted 2025/06/30 Platform GPL11154
Summary
Bone marrow plasma cell samples were obtained from 23 multiple myeloma patients at various stages of disease from the Seattle Cancer Care Institute. RNASeq gene expression profiling was applied to CD138+ purified plasma cells. We trained a machine learning algorithm on mmSYGNAL program activity to develop a risk classification scheme for multiple myeloma and applied it to the 23 patient’s gene expression profiles. Unlike other risk prediction methods we applied mmSYGNAL was able to accurately predict disease progression risk at primary diagnosis, pre- and post-transplant and even after multiple relapses, making it useful for individualized dynamic risk assessment throughout the disease trajectory.
Published in
Individualized dynamic risk assessment and treatment selection for multiple myeloma
Murie C, Turkarslan S, Patel AP et al. · British journal of cancer 2025 · PMID 40169765 · doi:10.1038/s41416-025-02987-6
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Direct links to NCBI, no account and no request form: the whole study as GSE226176_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 23 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA939129 and SRA study SRP424732. Searching any of these in the dataset finder brings you back here.

Study design
15 × MM vs 8 × 9944

Supports a between-group comparison across 23 samples.

2 replicated groups read from 23 sample titles; they account for 23 of them. Check it against the sample list below before relying on it.

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