Disruption of deoxynucleotide biosynthesis leads to RASproto-oncogene activation and perturbation of mitochondrial metabolism.
RNA-seq (gene expression) · human · 42 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
- 42 samples: 42 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.
- Paper
- Disruption of deoxyribonucleotide triphosphate biosynthesis leads to RAS proto-oncogene activation and perturbation of mitochondrial metabolismThe Journal of biological chemistry · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE261897_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1089523 and SRA study SRP496373. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 42 sample titles: 42 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.
- GSM8153730 RASJP1_Non Treated Rep 1
- GSM8153731 RASJP2_Non Treated Rep 2
- GSM8153732 RASJP3_Non Treated Rep 3
- GSM8153733 RASJP4_T 10 Rep 1
- GSM8153734 RASJP5_T 10 Rep 2
- GSM8153735 RASJP6_T 10 Rep 3
- GSM8153736 RASJP7_T 30 Rep 1
- GSM8153737 RASJP8_T 30 Rep 2
- GSM8153738 RASJP9_T 30 Rep 3
- GSM8153739 RASJP10_T 10 C 10 THU 100 Rep 1
- GSM8153740 RASJP11_T 10 C 10 THU 100 Rep 2
- GSM8153741 RASJP12_T 10 C 10 THU 100 Rep 3
- GSM8153742 RASJP13_T 30 C 10 THU 100 Rep 1
- GSM8153743 RASJP14_T 30 C 10 THU 100 Rep 2
- GSM8153744 RASJP15_T 30 C 10 THU 100 Rep 3
- GSM8153745 RASJP16_C 10 U 100 Rep 1
- GSM8153746 RASJP17_C 10 U 100 Rep 2
- GSM8153747 RASJP18_C 10 U 100 Rep 3
- GSM8153748 RAS OUT HYP DEEP 1_Non-Treated Rep 1
- GSM8153749 RAS OUT HYP DEEP 2_10 T Rep 1
- GSM8153750 RAS OUT HYP DEEP 3_30 T Rep 1
- GSM8153751 RAS OUT HYP DEEP 4_Non-Treated Rep 2
- GSM8153752 RAS OUT HYP DEEP 5_10 T Rep 2
- GSM8153753 RAS OUT HYP DEEP 6_30 T Rep 2
- GSM8153754 RAS OUT HYP DEEP 7_10 T + 10 C + 100 THU Rep 1
- GSM8153755 RAS OUT HYP DEEP 8_30 T + 10 C + 100 THU Rep 1
- GSM8153756 RAS OUT HYP DEEP 9_Non-Treated Rep 3
- GSM8153757 RAS OUT HYP DEEP 10_10 T + 10 C + 100 THU Rep 2
- GSM8153758 RAS OUT HYP DEEP 11_30 T + 10 C + 100 THU Rep 2
- GSM8153759 RAS OUT HYP DEEP 12_Non-Treated Rep 4
- GSM8153760 RAS OUT HYP DEEP 13_10 C + 100 THU Rep 1
- GSM8153761 RAS OUT HYP DEEP 14_10 T Rep 3
- GSM8153762 RAS OUT HYP DEEP 15_30 T Rep 3
- GSM8153763 RAS OUT HYP DEEP 16_10 C + 100 THU Rep 2
- GSM8153764 RAS OUT HYP DEEP 17_10 T Rep 4
- GSM8153765 RAS OUT HYP DEEP 18_30 T Rep 4
- GSM8153766 RAS OUT HYP DEEP 19_10 T + 10 C + 100 THU Rep 3
- GSM8153767 RAS OUT HYP DEEP 20_30 T + 10 C + 100 THU Rep 3
- GSM8153768 RAS OUT HYP DEEP 21_10 C + 100 THU Rep 3
- GSM8153769 RAS OUT HYP DEEP 22_10 T + 10 C + 100 THU Rep 4
+ 2 more — browse all 42 samples with per-sample file links →
- GSE312758 TMEM97 is A Cholesterol Sensing Onco-Protein and Sustains Mitochondrial Energetics Through Lipid Biosynthesis 24 samples shares mitochondrial, biosynthesis
- GSE266113 Cannabidiol ameliorates mitochondrial disease via PPARg activation 24 samples shares mitochondrial, activation
- GSE274283 Bulk RNA sequencing analysis of a iPSC-derived neurons, microglia and astrocytes models of mitochondrial unfolded protein response (UPRmt) activation. 18 samples shares mitochondrial, activation
- GSE224689 Regulatory principles of human mitochondrial gene expression revealed by kinetic analysis of the RNA life cycle. 113 samples shares mitochondrial
- GSE301408 Mitochondrial double-stranded RNA triggers chronic stress in aged neurons 100 samples shares mitochondrial
- GSE224662 Regulatory principles of human mitochondrial gene expression revealed by kinetic analysis of the RNA life cycle 98 samples shares mitochondrial
- GSE317520 Mitochondrial DNA Mutations Drive Tumor Heterogeneity in Papillary Thyroid Carcinoma 92 samples shares mitochondrial
- GSE293278 ADAR1 regulates dsRNA formation in nuclear and mitochondrial transcripts through editing-dependent and -independent mechanisms 24 samples shares mitochondrial
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.