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Halofantrine protects photoreceptors in multiple models of retinal degeneration [organoids]

GSE327431 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/08/06 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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
Halofantrine protects photoreceptors in multiple models of retinal degenerationResearch square · 2026
Summary (written by the submitters)
Inherited retinal degenerative diseases (IRDs), including retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA), cause progressive vision impairment due to photoreceptor degeneration. We previously demonstrated the protective effects of reserpine in models of CEP290-LCA and in the female Rhodopsin-P23H rat model of autosomal dominant RP.
Read the full summary ↓
Given that reserpine is limited by side effects, we expanded our compound screen using retinal organoids from the rd16 mouse model of CEP290-LCA to include structurally diverse small molecules that may converge on proteostasis pathways. Follow-up evaluations in Rhodopsin-P23H rats, human CEP290-LCA retinal organoids, and rd10 mice (a model of PDE6B-RP) identified halofantrine as the most promising molecule, conferring strong protection on both rod and cone photoreceptors and demonstrating therapeutic potential across the divergent IRD models tested. Transcriptome analysis revealed a convergent molecular response to halofantrine across these models, primarily through upregulation of oxidative phosphorylation and ribosomal processes. Notably, halofantrine elicited significant improvements in retinal function, as assessed by electroretinography, despite pharmacokinetically limited and transient retinal exposure after subconjunctival injection in Rhodopsin-P23H rats. Our studies highlight the potential of halofantrine as a gene-independent therapy and suggest that it may be developed for ocular delivery via eye drops for the treatment of IRDs.
Published in
Halofantrine protects photoreceptors in multiple models of retinal degeneration
Kim M, Mondal AK, Chen HY et al. · Research square 2026 · PMID 42183349 · doi:10.21203/rs.3.rs-9511432/v1
This dataset
Open GSE327431 in finder → Find more human 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 GSE327431_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 PRJNA1450703 and SRA study SRP690272. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42183349) ↗
Study design
15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. 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
Datasets on a similar topic

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