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Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma

GSE276715 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/07/31 Platform GPL20301
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: 3 × UM-Chor1, DARPin_E3_5, vs 3 × UM-Chor1, T-DARPin_A2, vs 3 × UM-Chor1, T-DARPin_B1, vs 3 × UM-Chor1, T-DARPin_D4,Groups 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
Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordomaScience advances · 2025
Summary (written by the submitters)
The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT’s regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation.
Read the full summary ↓
Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as susceptibility to pharmacologic inhibition and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.
Published in
Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma
Umbaugh CS, Groth M, Erkut C et al. · Science advances 2025 · PMID 40901948 · doi:10.1126/sciadv.adu2796
This dataset
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.

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 GSE276715_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1158741 and SRA study SRP531516. Searching any of these in the dataset finder brings you back here.

Study design
3 × UM-Chor1, DARPin_E3_5, vs 3 × UM-Chor1, T-DARPin_A2, vs 3 × UM-Chor1, T-DARPin_B1, vs 3 × UM-Chor1, T-DARPin_D4,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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