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Loss of FBXO11 establishes a stem cell program in acute myeloid leukemia by dysregulating LONP1 [RNA-seq]

GSE183843 Homo sapiens (human) RNA-seq (gene expression) 23 samples Submitted 2025/12/04 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 23 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)
Samples
23 samples: 8 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.
Paper
Loss of FBXO11 establishes a stem cell program in acute myeloid leukemia by dysregulating LONP1The Journal of clinical investigation · 2026
Summary (written by the submitters)
Purpose: The goals of this study are to compare the transcriptome profile of human cord blood derived CD34+ cells expressing shRNA targeting FBXO11, LONP1 or non-targeting shRNA, combined with or without over-expression of FLAG-FBXO11 or LONP1 by RNAseq. Methods: mRNA profiles of CD34+ cord blood cells with combinations of FBXO11 or LONP1 knockdown or over-expression were generated by RNAseq.
Published in
Loss of FBXO11 establishes a stem cell program in acute myeloid leukemia by dysregulating LONP1
Kincross H, Mo YA, Wang X et al. · The Journal of clinical investigation 2026 · PMID 41289019 · doi:10.1172/JCI181943
This dataset
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.

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 GSE183843_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA762096 and SRA study SRP336419. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
shCT ×3 shFBXO11_9 ×3 shLONP1_1 ×3 Empty ×3 FBXO11 ×3 LONP1 ×3 shLONP1_FBXO11 ×3 shFBXO11_LONP1 ×2

Supports a between-group comparison across 23 samples.

How we read this: 8 replicated groups read from 23 sample titles; they account for 23 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
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