Targeting CD206+ macrophages disrupts the establishment of a key anti-tumor immune axis
RNA-seq (gene expression) · mouse · 245 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
- 245 samples: 245 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
- Targeting CD206+ macrophages disrupts the establishment of a key antitumor immune axisThe Journal of experimental medicine · 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 GSE281472_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 PRJNA1183905 and SRA study SRP544117. 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 245 sample titles: 245 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.
- GSM8619055 B78_DT_GEX
- GSM8619056 B78_DT_ADT
- GSM8621251 IPICRC003.T1.rna.tcell
- GSM8621252 IPICRC032.T1.rna.tcell
- GSM8621253 IPICRC053.T1.rna.tcell
- GSM8621254 IPICRC093.T1.rna.tcell
- GSM8621255 IPICRC090.T1.rna.tcell
- GSM8621256 IPICRC096.T1.rna.tcell
- GSM8621257 IPICRC099.T1.rna.tcell
- GSM8621258 IPICRC101.T1.rna.tcell
- GSM8621259 IPICRC103.T1.rna.tcell
- GSM8621260 IPICRC105.T1.rna.tcell
- GSM8621261 IPICRC106.T1.rna.tcell
- GSM8621262 IPICRC111.T1.rna.tcell
- GSM8621263 IPICRC117.T1.rna.tcell
- GSM8621264 IPICRC125.T1.rna.tcell
- GSM8621265 IPIGYN012.T1.rna.tcell
- GSM8621266 IPIGYN024.T1.rna.tcell
- GSM8621267 IPIGYN030.T1.rna.tcell
- GSM8621268 IPIGYN032.T1.rna.tcell
- GSM8621269 IPIGYN036.T1.rna.tcell
- GSM8621270 IPIGYN037.T1.rna.tcell
- GSM8621271 IPIGYN038.T1.rna.tcell
- GSM8621272 IPIGYN055.T1.rna.tcell
- GSM8621273 IPIGYN056.T1.rna.tcell
- GSM8621274 IPIGYN062.T1.rna.tcell
- GSM8621275 IPIGYN065.T1.rna.tcell
- GSM8621276 IPIGYN066.T1.rna.tcell
- GSM8621277 IPIGYN072.T1.rna.tcell
- GSM8621278 IPIGYN073.T1.rna.tcell
- GSM8621279 IPIGYN090.T1.rna.tcell
- GSM8621280 IPIGYN096.T1.rna.tcell
- GSM8621281 IPIGYN100.T1.rna.tcell
- GSM8621282 IPIGYN111.T1.rna.tcell
- GSM8621283 IPIGYN112.T1.rna.tcell
- GSM8621284 IPIGYN114.T1.rna.tcell
- GSM8621285 IPIGYN120.T1.rna.tcell
- GSM8621286 IPIGYN121.T1.rna.tcell
- GSM8621287 IPIGYN123.T1.rna.tcell
- GSM8621288 IPIGYN126.T1.rna.tcell
+ 205 more — browse all 245 samples with per-sample file links →
- GSE297064 Targeting circulating mechanoresponsive monocytes and macrophages to reduce fibrosis 12 samples shares macrophages, targeting
- GSE289625 RNA exonuclease REXO4 resolves m6A-marked R-loops and suppresses anti-tumor immunity [RNAseq] 28 samples shares anti-tumor
- GSE336821 Establishment and characterization of patient-derived in-vitro and in-vivo models of penile squamous cell carcinoma 10 samples shares establishment
- GSE156337 Onco-fetal reprogramming of endothelial cells drives immunosuppressive macrophages in Hepatocellular Carcinoma 186 samples shares macrophages
- GSE333477 Dynamicity of Topoisomerase 1 binding at super-enhancers regulates TLR-responsive gene expression program in macrophages 106 samples shares macrophages
- GSE270148 Myeloid progenitor dysregulation fuels immunosuppressive macrophages in tumours 85 samples shares macrophages
- GSE35495 Genome-wide analysis of human and mouse macrophages, resting and activated 73 samples shares macrophages
- GSE246923 Opposing tumor cell-intrinsic and -extrinsic roles of the IRF1 transcription factor in anti-tumor immunity 49 samples shares anti-tumor
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.