GEO series

Development of small molecule miR-17-92 inhibitors [RNA-Seq]

GSE203620 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/05/21 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 36 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: Mus musculus (mouse)
Samples: 36 samples: 9 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)

MicroRNAs (miRNAs) are conserved small non-coding RNAs that regulate gene expression at the posttranscriptional level by pairing to the 3’ UTR of other genes. miR-17-92 is a key regulator of lymphocyte biology, controlling e.g. cell proliferation, survival as well as differentiation and function of different T cell subsets. miR-17-92 is amplified in human lymphomas and other malignancies and is also involved in additional disorders including immune, cardiovascular and neurodegenerative diseases as well as in aging.

Read the full summary ↓

Given the importance of miR-17-92 in such a variety of diseases we aim at exploiting it as a therapeutic target. miRNAs can be inhibited through the administration of nucleotide-based inhibitors. Major disadvantages are their transient effect, instability and poor in vivo delivery. In contrast, small molecules permeate cells easily, are intracellularly stable and large libraries are available for high-throughput screening. We screened 60’000 compounds using a luciferase reporter assay and identified small molecules which modulate miR-17 reporter activity. Treatment of mouse naïve CD4 or CD8 T cells with one of the hit compounds resulted in similar phenotypes as in miR-17-92 deficient mice (different target derepression and reduced in vitro T cell differentiation). Screening of 172 chemically related compounds identified 2 analogs with improved potency. Treatment of primary human CD4 or CD8 cells as well as different tumor cell lines overexpressing the miR-17-92 cluster resulted in reduced proliferation and activation and increased cell death.

This dataset

Open GSE203620 in finder → Find more mouse RNA-seq datasets →

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 GSE203620_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 PRJNA841604. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 conditions, mostly with about 4 replicates each

RNAseq_Naive_WT_DMSO ×4 RNAseq_24h_WT_DMSO ×4 RNAseq_24h_WT_Comp_25 ×4 RNAseq_24h_WT_Comp_B ×4 RNAseq_24h_WT_Comp_M ×4 RNAseq_48h_WT_DMSO ×4 RNAseq_48h_WT_Comp_25 ×4 RNAseq_48h_WT_Comp_B ×4 +1 more

Supports a between-group comparison across 36 samples.

How we read this: 9 replicated groups read from 36 sample titles; they account for 36 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

GSM6180737 RNAseq_Naive_WT_DMSO_R1 RNAseq_Naive_WT_DMSO
GSM6180738 RNAseq_Naive_WT_DMSO_R2 RNAseq_Naive_WT_DMSO
GSM6180739 RNAseq_Naive_WT_DMSO_R3 RNAseq_Naive_WT_DMSO
GSM6180740 RNAseq_Naive_WT_DMSO_R4 RNAseq_Naive_WT_DMSO
GSM6180741 RNAseq_24h_WT_DMSO_R1 RNAseq_24h_WT_DMSO
GSM6180742 RNAseq_24h_WT_DMSO_R2 RNAseq_24h_WT_DMSO
GSM6180743 RNAseq_24h_WT_DMSO_R3 RNAseq_24h_WT_DMSO
GSM6180744 RNAseq_24h_WT_DMSO_R4 RNAseq_24h_WT_DMSO
GSM6180745 RNAseq_24h_WT_Comp_25_R1 RNAseq_24h_WT_Comp_25
GSM6180746 RNAseq_24h_WT_Comp_25_R2 RNAseq_24h_WT_Comp_25
GSM6180747 RNAseq_24h_WT_Comp_25_R3 RNAseq_24h_WT_Comp_25
GSM6180748 RNAseq_24h_WT_Comp_25_R4 RNAseq_24h_WT_Comp_25
GSM6180749 RNAseq_24h_WT_Comp_B_R1 RNAseq_24h_WT_Comp_B
GSM6180750 RNAseq_24h_WT_Comp_B_R2 RNAseq_24h_WT_Comp_B
GSM6180751 RNAseq_24h_WT_Comp_B_R3 RNAseq_24h_WT_Comp_B
GSM6180752 RNAseq_24h_WT_Comp_B_R4 RNAseq_24h_WT_Comp_B
GSM6180753 RNAseq_24h_WT_Comp_M_R1 RNAseq_24h_WT_Comp_M
GSM6180754 RNAseq_24h_WT_Comp_M_R2 RNAseq_24h_WT_Comp_M
GSM6180755 RNAseq_24h_WT_Comp_M_R3 RNAseq_24h_WT_Comp_M
GSM6180756 RNAseq_24h_WT_Comp_M_R4 RNAseq_24h_WT_Comp_M
GSM6180757 RNAseq_48h_WT_DMSO_R1 RNAseq_48h_WT_DMSO
GSM6180758 RNAseq_48h_WT_DMSO_R2 RNAseq_48h_WT_DMSO
GSM6180759 RNAseq_48h_WT_DMSO_R3 RNAseq_48h_WT_DMSO
GSM6180760 RNAseq_48h_WT_DMSO_R4 RNAseq_48h_WT_DMSO
GSM6180761 RNAseq_48h_WT_Comp_25_R1 RNAseq_48h_WT_Comp_25
GSM6180762 RNAseq_48h_WT_Comp_25_R2 RNAseq_48h_WT_Comp_25
GSM6180763 RNAseq_48h_WT_Comp_25_R3 RNAseq_48h_WT_Comp_25
GSM6180764 RNAseq_48h_WT_Comp_25_R4 RNAseq_48h_WT_Comp_25
GSM6180765 RNAseq_48h_WT_Comp_B_R1 RNAseq_48h_WT_Comp_B
GSM6180766 RNAseq_48h_WT_Comp_B_R2 RNAseq_48h_WT_Comp_B
GSM6180767 RNAseq_48h_WT_Comp_B_R3 RNAseq_48h_WT_Comp_B
GSM6180768 RNAseq_48h_WT_Comp_B_R4 RNAseq_48h_WT_Comp_B
GSM6180769 RNAseq_48h_WT_Comp_M_R1 RNAseq_48h_WT_Comp_M
GSM6180770 RNAseq_48h_WT_Comp_M_R2 RNAseq_48h_WT_Comp_M
GSM6180771 RNAseq_48h_WT_Comp_M_R3 RNAseq_48h_WT_Comp_M
GSM6180772 RNAseq_48h_WT_Comp_M_R4 RNAseq_48h_WT_Comp_M

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