In vivo armed macrophages curb liver metastasis through tumor reactive T cell rejuvenation
RNA-seq (gene expression) · mouse · 36 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
- Mus musculus (mouse)
- Samples
- 36 samples: 10 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
- In vivo armed macrophages curb liver metastasis through tumor-reactive T-cell rejuvenationNature communications · 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 GSE273615_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 PRJNA1142502 and SRA study SRP523378. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 13 samples read as cases, 6 as controls.
How we read this: 10 replicated groups read from 36 sample titles; they account for 24 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.
- GSM8433816 TA33.Combo
- GSM8433817 TA33
- GSM8433820 SIINFEKL
- GSM8433821 OVA
- GSM8433822 SIINFEKL.Combo
- GSM8433823 OVA.Combo
- GSM8433828 Liver, liOVA_IL12, rep1 Liver, liOVA_IL12,
- GSM8433829 Liver, liOVA_IL12, rep2 Liver, liOVA_IL12,
- GSM8433830 Tumor, liOVA_IL12, rep1 Tumor, liOVA_IL12,
- GSM8433831 Tumor, liOVA_IL12, rep2 Tumor, liOVA_IL12,
- GSM8433832 Liver, liOVA_IFNa, rep1 Liver, liOVA_IFNa,
- GSM8433833 Liver, liOVA_IFNa, rep2 Liver, liOVA_IFNa,
- GSM8433834 Tumor, liOVA_IFNa, rep1 Tumor, liOVA_IFNa,
- GSM8433835 Tumor, liOVA_IFNa, rep2 Tumor, liOVA_IFNa,
- GSM8433836 Liver, liOVA
- GSM8433837 Tumor, liOVA
- GSM8433838 Liver, liOVA_IL12_INFa, rep1 Liver, liOVA_IL12_INFa,
- GSM8433839 Liver, liOVA_IL12_INFa, rep2 Liver, liOVA_IL12_INFa,
- GSM8433840 Tumor, liOVA_IL12_INFa, rep1 Tumor, liOVA_IL12_INFa,
- GSM8433841 Tumor, liOVA_IL12_INFa, rep2 Tumor, liOVA_IL12_INFa,
- GSM8433842 TA33L
- GSM8433843 TA33T
- GSM8433844 TA33L.Combo
- GSM8433845 TA33T.Combo
- GSM8433862 Healthy intestine control - biological rep 1 Healthy intestine contr…
- GSM8433863 Healthy intestine control - biological rep 2 Healthy intestine contr…
- GSM8433864 Healthy intestine control - biological rep 3 Healthy intestine contr…
- GSM8433865 Healthy liver control - biological rep 1 Healthy liver control
- GSM8433866 Healthy liver control - biological rep 2 Healthy liver control
- GSM8433867 Healthy liver control - biological rep 3 Healthy liver control
- GSM8433868 Liver metastases - biological rep 1 Liver metastases
- GSM8433869 Liver metastases - biological rep 2 Liver metastases
- GSM8433870 Liver metastases - biological rep 3 Liver metastases
- GSM8433871 Tumor cell line - biological rep 1 Tumor cell line
- GSM8433872 Tumor cell line - biological rep 2 Tumor cell line
- GSM8433873 Tumor cell line - biological rep 3 Tumor cell line
No close match found for this topic, so these are simply the most-viewed datasets of the same kind.
- GSE241708 Genomic context sensitizes regulatory elements to genetic disruption 154 samples
- GSE237089 Non-CG DNA methylation and MeCP2 stabilize repeated tuning of long genes that distinguish closely related neuron types. 108 samples
- GSE314329 Inflammatory Monocytes Constrain YAP-Induced Cell Proliferation 34 samples
- GSE266690 Single cell approaches define neural stem cell niches and identify microglial ligands that enhance precursor-mediated remyelination 33 samples
- GSE102346 Regulation of m6A transcripts by the 3ʹ→5ʹ RNA helicase YTHDC2 is essential for a successful meiotic program in the mammalian germline 32 samples
- GSE60615 miRNAs in Treg-derived Exosomes 24 samples
- GSE260699 Spatially tuneable multi-omics sequencing using light-driven combinatorial barcoding of molecules in tissues 17 samples
- GSE274621 Single cell transcriptomes and spatial architecture of pancreatic pre-invasive lesions reveal acinar metaplastic cells' heterogeneity 2 samples
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.