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Effect of mitochondrial electron transport chain blockade on transcriptomic profile in human H460 cells

GSE265923 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/05/09 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 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
Electron transport chain inhibition increases cellular dependence on purine transport and salvageCell metabolism · 2024
Summary (written by the submitters)
Cancer cells reprogram their metabolism to support cell growth and proliferation in harsh environments. To assess how human cells respond to defective mitochondrial respiration, we analyzed metabolomics profiles in cells with deficient electron transport chain (ETC). We found that ETC deficiency induces an accumulation of purine nucleotides.
Read the full summary ↓
Additionally, we revealed that ETC blockade suppressed de novo purine nucleotide biosynthesis while enhanced purine salvage. This metabolic rewiring of purine nucleotide biosynthesis is not regulated at the transcriptional level. Instead, stable isotope tracing experiments showed that ETC blockade promoted the oxidative branch of pentose phosphate pathway to elevate phosphoribosyl diphosphate to drive purine salvage. In summary, our findings delineate how cells remodel purine metabolism in response to ETC blockade, and uncover a new metabolic vulnerability in tumors with low respiration.
Published in
Electron transport chain inhibition increases cellular dependence on purine transport and salvage
Wu Z, Bezwada D, Cai F et al. · Cell metabolism 2024 · PMID 38876105 · doi:10.1016/j.cmet.2024.05.014
This dataset
Open GSE265923 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 GSE265923_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 PRJNA1104752 and SRA study SRP504129. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38876105) ↗
Study design
6 conditions, mostly in duplicate
H460 cells, parental, DMSO ×3 H460 cells, parental, IACS, ×3 H460 cells, control, DMSO ×2 H460 cells, control, IACS, ×2 H460 cells,NDI1, DMSO ×2 H460 cells,NDI1, IACS, ×2 H460 cells,control, DMSO ×1 H460 cells,control, IACS, ×1 +2 more

Supports a between-group comparison across 14 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 14 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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