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Acyl-coA Binding Protein neutralization improves cancer immunosurveillance

GSE242119 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/09/11 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 3 × Istoype vs 3 × AntiDBI vs 3 × VDJ Istoype vs 3 × VDJ AntiDBIGroups 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)
The plasma concentrations of acyl coenzyme A binding protein (ACBP, also known as diazepam-binding inhibitor, DBI, or ‘endozepine’) increase with age and obesity, two parameters that are also the most important risk factors for cancer. In mice bearing MCA205 fibrosarcoma, antibody mediated ACBP/DBI neutralization enhanced the anticancer T-cell response in the context of chemoimmunotherapy. T-cells infiltrating MCA205 tumors were sorted and submitting to single-cell TCR sequencing and single-cell RNA sequencing (scRNAseq) to identify the mechanisms driving this improvement.
This dataset
Open GSE242119 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 GSE242119_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1011354 and SRA study SRP457871. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Istoype vs 3 × AntiDBI vs 3 × VDJ Istoype vs 3 × VDJ AntiDBI

Supports a between-group comparison across 12 samples.

How we read this: 4 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.

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.