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ATF4-Mediated Metabolic Stress Response as a Therapeutic Vulnerability in Chordoma [PDX RNA-seq]

GSE275636 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2024/08/31 Platform GPL26167
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples
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)
Chordoma, a rare and challenging primary bone malignancy, currently lacks effective targeted therapies. Despite surgical resection and adjuvant radiotherapy, prognosis remains poor. Recent preclinical studies have highlighted potential therapeutic targets, including the transcription factor TBXT, although clinical outcomes have been modest.
Read the full summary ↓
In this study, we investigated the therapeutic potential of tRNA synthetase inhibitors, specifically halofuginone and halofuginol, in chordoma treatment. We conducted extensive drug screening, identifying these compounds as effective in reducing cell viability in chordoma cell lines through an ATF4-mediated stress response rather than TBXT regulation. Our findings were validated using RNA sequencing, which revealed significant upregulation of ATF4 and associated stress response genes. Additionally, halofuginone demonstrated significant tumour growth inhibition in an in vivo patient-derived xenograft model. These results suggest that targeting metabolic stress pathways via ATF4 activation presents a novel therapeutic approach for chordoma, warranting further clinical investigation.
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 GSE275636_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 PRJNA1152352 and SRA study SRP528578. Searching any of these in the dataset finder brings you back here.

Study design
A cohort of 10 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run sampleno1 … sampleno5 and carry no group information.

Samples in this study
Datasets on a similar topic

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