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Inducible CCR2+ nonclassical monocytes mediate the regression of cancer metastasis

GSE277303 Mus musculus (mouse) RNA-seq (gene expression) 42 samples Submitted 2024/11/15 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
42 samples: 11 conditions, mostly in triplicateGroups 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
Inducible CCR2+ nonclassical monocytes mediate the regression of cancer metastasisThe Journal of clinical investigation · 2024
Summary (written by the submitters)
Classical monocytes (CMs) can be converted into conventional dominant Nr4a1-dependent nonclassical monocytes (N-NCMs). Upon activation of Nod2 signaling, CM also can be converted into noncanonical Nod2-dependent inducible NCMs (I-NCMs). The transcriptional profiles and typical markers specific for those two NCM subsets yet to be determined.
Read the full summary ↓
To transcriptionally characterize N-NCM and I-NCM, we performed transcriptional profiling analysis using RNAseq data obtained from the flow-sorted NCM subsets. Through the comprehensive RNAseq analysis, we identified typical transcriptional markers specific to N-NCM and I-NCM. By virtue of those specific markers, we identified the potential I-NCM populations in multiple cellular settings.
Published in
Inducible CCR2+ nonclassical monocytes mediate the regression of cancer metastasis
Liu X, Ren Z, Tan C et al. · The Journal of clinical investigation 2024 · PMID 39545417 · doi:10.1172/JCI179527
This dataset
Open GSE277303 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE277303_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1161691 and SRA study SRP533002. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39545417) ↗
Study design
11 conditions, mostly in triplicate
M01_Blood_CD274posNCM_wtB6 ×5 M01_Blood_wtB6_MDP_CM ×5 M01_Blood_wtB6_MDP_NCM ×5 M01_Blood_Nod2KO_MDP_NCM ×5 M01_Blood_NCM_wtB6 ×3 M01_Blood_NCM_Nod2KO ×3 M01_Blood_NCM_Nr4a1KO_MDP ×3 M01_Blood_CM_Nr4a1KO_MDP ×3 +4 more

Supports a between-group comparison across 41 samples.

How we read this: 11 replicated groups read from 42 sample titles; they account for 41 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.

Samples in this study

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.