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Checkpoint Blockade Cancer Immunotherapy Targets Tumor-Specific Mutant Antigens

GSE62771 Mus musculus (mouse) RNA-seq (gene expression) 22 samples Submitted 2014/11/07 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 22 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
22 samples: 8 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.
Summary (written by the submitters)
Cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) and Programmed death-1 (PD-1) are immunoregulatory receptors expressed on T cells that play important roles in suppressing immune responses to cancer. Although monoclonal antibodies that target CTLA-4 or PD-1 stimulate therapeutic anti-tumour T cell responses, the tumour antigens recognized by checkpoint blockade immunotherapy remain undefined.
Read the full summary ↓
Herein, we use genomics and bioinformatics approaches to identify tumour-specific mutant proteins as a major class of T cell rejection antigens following αPD-1 and/or αCTLA-4 treatment of mice bearing progressively growing sarcomas. We validate this conclusion by showing that (a) the predicted mutant epitopes associate with MHC class I molecules of the tumour; (b) T cells specific for these mutant epitopes infiltrate tumours; and (c) therapeutic vaccines incorporating these mutant epitopes induce tumour rejection comparably to checkpoint blockade immunotherapy. Whereas, T cells with the same antigen specificity are present in progressively growing tumours in control mice, tumour-specific T cells in αPD-1- and/or αCTLA-4-treated mice express some overlapping but mostly treatment-specific transcriptional profiles that render them capable of tumour rejection. Thus, tumour-specific mutant antigens are not only important targets of checkpoint blockade therapy but also can be used to identify tumour antigen-specific T cells that function as biomarkers of successful anti-tumour responses.
This dataset
Open GSE62771 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 GSE62771_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 PRJNA265091 and SRA study SRP049335. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25428507) ↗
Study design
8 conditions, mostly in triplicate
aCTLA4_mLama4_neg ×3 aCTLA4_mLama4_pos ×3 aPD1_mLama4_neg ×3 aPD1_plus_aCTLA4_mLama4_pos ×3 Control_Ab_mLama4_neg ×3 Control_Ab_mLama4_pos ×3 aPD1_mLama4_pos ×2 aPD1_plus_aCTLA4_mLama4_neg ×2

Supports a between-group comparison across 22 samples.

How we read this: 8 replicated groups read from 22 sample titles; they account for 22 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

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