Developing a pan cancer therapy based on DISE inducing short RNAs
RNA-seq (gene expression) · human · 17 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
- 17 samples: 17 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.
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 GSE330327_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 PRJNA1463639 and SRA study SRP698613. 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 17 sample titles: 17 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.
- GSM9723882 N2L - liver from sNT1-LPP treated mice
- GSM9723883 N3L - liver from sNT1-LPP treated mice
- GSM9723884 N4L - liver from sNT1-LPP treated mice
- GSM9723885 C1L - liver from sCAG-LPP treated mice
- GSM9723886 C2L - liver from sCAG-LPP treated mice
- GSM9723887 C3L - liver from sCAG-LPP treated mice
- GSM9723888 C4L - liver from sCAG-LPP treated mice
- GSM9723889 N2TL - PC3 tumor from sNT1-LPP treated mice
- GSM9723890 N3TL - PC3 tumor from sNT1-LPP treated mice
- GSM9723891 N4TR - PC3 tumor from sNT1-LPP treated mice
- GSM9723892 N8TR - PC3 tumor from sNT1-LPP treated mice
- GSM9723893 N9TR - PC3 tumor from sNT1-LPP treated mice
- GSM9723894 C1TR - PC3 tumor from sCAG-LPP treated mice
- GSM9723895 C3TR - PC3 tumor from sCAG-LPP treated mice
- GSM9723896 C5TL - PC3 tumor from sCAG-LPP treated mice
- GSM9723897 C7TR - PC3 tumor from sCAG-LPP treated mice
- GSM9723898 C10TR - PC3 tumor from sCAG-LPP treated mice
- GSE261554 Targeting Vdac2 overcomes immunotherapy resistance by inducing tumor cell death and inflammation 180 samples shares inducing, therapy
- GSE270777 MYC couples SWI/SNF and metabolic reprogramming to sustain minimal residual disease in mTORC1-activated cancer cells [RNA-seq] 18 samples shares dise
- GSE243750 SEX-DEPENDENT APOE4 NEUTROPHIL-MICROGLIA INTERACTIONS DRIVE COGNITIVE IMPAIRMENT IN ALZHEIMER'S DISEASE 288 samples shares dise
- GSE270779 MYC couples SWI/SNF and metabolic reprogramming to sustain minimal residual disease in mTORC1-activated cancer cells 64 samples shares dise
- GSE274037 A microglia clonal inflammatory disorder in Alzheimer’s Disease 54 samples shares dise
- GSE299631 Spatiotemporal organisation of residual disease in mouse and human BRCA1-deficient mammary tumors and breast cancer 50 samples shares dise
- GSE272074 Latent Epigenetic Programs in Müller Glia Contribute to Stress, Injury, and Disease Response in the Retina [scRNA-seq] 48 samples shares dise
- GSE288077 Metabolic dysfunction-associated steatotic liver disease may increase intrahepatic interferon gene signatures in patients with chronic hepatitis B 35 samples shares dise
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.