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Cycling Alpha Cells in Regenerative Drug-Treated Human Pancreatic Islets Serve As Key Beta Cell Progenitors

GSE266427 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2024/12/05 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
16 samples: 16 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
Cycling alpha cells in regenerative drug-treated human pancreatic islets may serve as key beta cell progenitorsCell reports. Medicine · 2024
Summary (written by the submitters)
Diabetes results from an inadequate number of insulin-producing human beta cells. There is currently no effective means to restore beta cell mass in millions of people with diabetes. Although the DYRK1A inhibitors, either alone or in combination with GLP1 receptor agonists (GLP1) or TGF superfamily inhibitors (LY), induce beta cell replication and increase beta cell mass, the precise mechanisms of action remain elusive.
Read the full summary ↓
We performed single cell RNA sequencing on human pancreatic islets treated with a DYRK1A inhibitor, either alone, or with GLP1 or LY. We identify Cycling Alpha Cells as the most responsive cells to DYRK1A inhibition. Lineage trajectory analyses suggest that Cycling Alpha Cells may serve as precursor cells that transdifferentiate into beta cells. In addition to shedding light onto the mechanisms of action of DYRK1A inhibitors, our findings suggest that the proper target for regenerative drugs in human islets may be Cycling Alpha Cells.
Published in
Cycling alpha cells in regenerative drug-treated human pancreatic islets may serve as key beta cell progenitors
Karakose E, Wang X, Wang P et al. · Cell reports. Medicine 2024 · PMID 39626675 · doi:10.1016/j.xcrm.2024.101832
This dataset
Open GSE266427 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 GSE266427_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1107156 and SRA study SRP505397. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39626675) ↗
Study design
16 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 16 sample titles: 16 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.