RNA sensing induced by chromosome missegregation augments anti-tumor immunity II
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: 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
- RNA sensing induced by chromosome missegregation augments anti-tumor immunityMolecular cell · 2025
Read the full summary ↓
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 GSE281348_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 PRJNA1183422 and SRA study SRP543870. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 6 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.
- GSM8619076 H1944.SCR.DMSO.J2.rep1 H1944.SCR.DMSO.J2
- GSM8619077 H1944.SCR.DMSO.J2.rep2 H1944.SCR.DMSO.J2
- GSM8619078 H1944.SCR.MPS1i.J2.rep1 H1944.SCR.MPS1i.J2
- GSM8619079 H1944.SCR.MPS1i.J2.rep2 H1944.SCR.MPS1i.J2
- GSM8619080 H1944.SCR.IFNb.J2.rep1 H1944.SCR.IFNb.J2
- GSM8619081 H1944.SCR.IFNb.J2.rep2 H1944.SCR.IFNb.J2
- GSM8619082 H1944.IFNAR1sg.DMSO.J2.rep1 H1944.IFNAR1sg.DMSO.J2
- GSM8619083 H1944.IFNAR1sg.DMSO.J2.rep2 H1944.IFNAR1sg.DMSO.J2
- GSM8619084 H1944.IFNAR1sg.MPS1i.J2.rep1 H1944.IFNAR1sg.MPS1i.J2
- GSM8619085 H1944.IFNAR1sg.MPS1i.J2.rep2 H1944.IFNAR1sg.MPS1i.J2
- GSM8619086 H1944.IFNAR1sg.IFNb.J2.rep1 H1944.IFNAR1sg.IFNb.J2
- GSM8619087 H1944.IFNAR1sg.IFNb.J2.rep2 H1944.IFNAR1sg.IFNb.J2
- GSE281351 RNA sensing induced by chromosome missegregation augments anti-tumor immunity V 16 samples shares missegregation, chromosome, anti-tumor, augments, immunity, sensing, induced
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- GSE272885 In vivo double knockout CAR-T screen identifies synergistic gene pairs that enhance anti-tumor immunity [bulk RNA-seq] 48 samples shares anti-tumor, immunity
- GSE282589 A tri-specific antibody engages T and myeloid cells to augment anti-tumor immunity [bulk RNA-seq] 33 samples shares anti-tumor, immunity
- GSE281102 A tri-specific antibody engages T and myeloid cells to augment anti-tumor immunity 25 samples shares anti-tumor, immunity
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- GSE300275 TRPML3 regulates expression of development-related neuronal genes, and augments starvation-induced autophagy mediated transcriptional regulation in HEK cells 12 samples shares augments, induced
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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.