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IGF-1 Peptide Mimetic-functionalized Hydrogels Enhance MSC Survival and Immunomodulatory Activity

GSE275505 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2025/07/16 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 22 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
22 samples: 22 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)
Human mesenchymal stem cells (MSCs) have demonstrated promise when delivered to damaged tissue or tissue defects for their cytokine secretion and inflammation modulation behaviors that can promote repair. Insulin-like growth factor 1 (IGF-1) has been shown to augment MSCs’ viability and survival and promote their secretion of cytokines that signal to endogenous cells, in the treatment of myocardial infarction, wound healing, and age-related diseases.
Read the full summary ↓
Biomaterial cell carriers can be functionalized with growth factor-mimetic peptides to enhance MSC function while promoting cell retention and minimizing off-target effects seen with direct administration of soluble growth factors. Here, we functionalized alginate hydrogels with three distinct IGF-1 peptide mimetics and the integrin-binding peptide, cyclic RGD. One IGF-1 peptide mimetic (IGM-3) was found to activate Akt signaling and support survival of serum-deprived MSCs. MSCs encapsulated in alginate hydrogels that presented both IGM-3 and cRGD showed a significant reduction in pro-inflammatory cytokine secretion when challenged with interleukin-1β. Finally, MSCs cultured within the cRGD/IGM-3 hydrogels were able to blunt pro-inflammatory gene expression of human primary cells from degenerated intervertebral discs. These studies indicate the potential to leverage cell adhesive and IGF-1 growth factor peptide mimetics together to control therapeutic secretory behavior of MSCs.
This dataset
Open GSE275505 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 GSE275505_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 PRJNA1151131 and SRA study SRP528154. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
22 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 22 sample titles: 22 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

Search all human RNA-seq datasets in GEO →

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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.