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De Novo Design of Integrin α5β1 Modulating Proteins for Regenerative Medicine

GSE272058 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2025/08/01 Platform GPL30173
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: 10 conditions, mostly in duplicateGroups 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
De Novo Design of Integrin α5β1 Modulating Proteins to Enhance Biomaterial PropertiesAdvanced materials (Deerfield Beach, Fla.) · 2025
Summary (written by the submitters)
Integrin α5β1 is crucial for cell attachment and migration in development and tissue regeneration, and α5β1 binding proteins could have considerable utility in regenerative medicine and next-generation therapeutics. We use computational protein design to create de novo α5β1-specific modulating miniprotein binders, called NeoNectins, that bind to and stabilize the open state of α5β1.
Read the full summary ↓
When immobilized onto titanium surfaces and throughout 3D hydrogels, the NeoNectins outperform native fibronectin and RGD peptide in enhancing cell attachment and spreading, and NeoNectin-grafted titanium implants outperformed fibronectin and RGD-grafted implants in animal models in promoting tissue integration and bone growth. NeoNectins should be broadly applicable for tissue engineering and biomedicine.
Published in
De Novo Design of Integrin α5β1 Modulating Proteins to Enhance Biomaterial Properties
Wang X, Guillem-Marti J, Kumar S et al. · Advanced materials (Deerfield Beach, Fla.) 2025 · PMID 40489013 · doi:10.1002/adma.202500872
This dataset
Open GSE272058 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 GSE272058_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 PRJNA1134765 and SRA study SRP519438. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40489013) ↗
Study design
10 conditions, mostly in duplicate
MCF 10A, fibronectin, ×2 hMSC, fibronectin, ×2 hMSC, binder, ×2 hMSC, control (titanium surface), ×2 hOBS, fibronectin, ×2 hOBS, binder, ×2 hOBS, control (titanium surface), ×2 hFF, fibronectin, ×2 +4 more

Supports a between-group comparison across 20 samples.

How we read this: 10 replicated groups read from 22 sample titles; they account for 20 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
Datasets on a similar topic

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