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Macrophage ontogeny underlies differences in tumor-specific education in brain malignancies

GSE86573 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2016/11/10 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 20 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.
Summary (written by the submitters)
Recent efforts have uncovered immense transcriptional and ontogenetic diversity among tissue-resident macrophages, each with their own transcriptional profile endowing the cell with its tissue-specific functions. However, it is currently unknown whether the origins of different macrophage populations may affect their roles in malignancy.
Read the full summary ↓
Given potential artifacts associated with irradiation-based lineage tracing, it remains unclear if bone marrow-derived macrophages (BMDM) are even present in tumors of the brain, a tissue where there is no homeostatic involvement of peripherally-derived myeloid cells. Here, we employed multiple models of murine brain malignancy and genetic lineage tracing models to demonstrate that BMDM are indeed abundant in primary and metastatic brain tumors. Transcriptional profiling of tumor-associated BMDM and resident microglia showed that these cells acquire substantially different gene expression profiles. Our data suggest that transcriptional networks in each cell population are associated with tumor-mediated education, yet are also influenced by chromatin landscapes established before tumor initiation. Furthermore, we demonstrate that microglia specifically repress Itga4 (CD49D), enabling its utility as a discriminatory marker between brain-resident microglia and peripherally-derived macrophages in both primary and metastatic disease in mouse and human.
This dataset
Open GSE86573 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 GSE86573_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 PRJNA345301 and SRA study SRP090798. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27840052) ↗
Study design
20 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 20 sample titles: 20 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.

Samples in this study
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.