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CD24+ human dental papilla cells as translational seed cells for dentin-pulp regeneration via BMP2/SIRT1 metabolic axis

GSE303466 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/04/26 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 12 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.
Summary (written by the submitters)
Regeneration of the dentin-pulp complex is a central goal in dental tissue engineering, essential for restoring both structural integrity and biological function of damaged teeth. However, the inherent heterogeneity of dental stem cells limits our understanding of lineage-specific subsets critical for efficient odontogenesis and regenerative outcomes.
Read the full summary ↓
Here, we identify a distinct subpopulation of human dental papilla cells (hDPCs) marked by CD24 expression. CD24⁺ hDPCs exhibit robust odontogenic differentiation capacity, preferential localization to odontoblast-generating regions during tooth development, and accumulation beneath reparative dentin in carious teeth. Functionally, CD24⁺ hDPCs drive coordinated regeneration of well-vascularized pulp and structurally integrated dentin tissues in both ectopic murine and preclinical in situ minipig models, significantly outperforming conventional dental pulp stem cells. Mechanistically, we delineate a BMP2-driven metabolic axis in which elevated BMP signaling sustains SIRT1 expression and promotes mitochondrial metabolism. Inhibition of BMP signaling disrupts this axis, activating WNT signaling, reducing SIRT1 expression, compromising antioxidant and autophagic responses, and consequently diminishing odontogenic capacity. Furthermore, BMP signaling in CD24⁺ hDPCs induces VEGF expression, enhancing endothelial cell recruitment and neovascularization via paracrine effects. CD24 also acts as a downstream marker of odontogenic BMP signaling, reflecting BMP pathway activation and correlating with odontogenic potential, although it does not directly mediate differentiation. Together, our findings characterize CD24⁺ hDPCs as a regeneration-competent subpopulation that integrates mitochondrial metabolism and signaling crosstalk to enable coordinated dentin and pulp regeneration, representing a translationally relevant cell source for dental tissue engineering.
This dataset
Open GSE303466 in finder → Find more 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 GSE303466_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 PRJNA1295489. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 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 12 sample titles: 12 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.