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mRNA expressions in pre-treatment melanomas undergoing anti-PD-1 checkpoint inhibition therapy

GSE78220 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2016/03/18 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 28 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
Homo sapiens (human)
Topic
MelanomaThis series is part of our curated briefing on it.
Samples
28 samples: 26 × PtGroups 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)
PD-1 immune checkpoint blockade provides significant clinical benefits for cancer patients. However, factors influencing innate sensitivity remain incompletely catalogued. We analyzed the somatic mutanomes and transcriptomes of pretreatment melanoma biopsies. Mutations in cell adhesion genes and the DNA repair gene BRCA2 were enriched in responding tumors, and a high mutational load associated with improved survival.
Read the full summary ↓
Innately resistant tumors displayed frequent transcriptomic up-expression of genes that enriched for mesenchymal transition, cell adhesion, ECM organization, wound-healing and angiogenesis. The transcriptomes of innate resistance also enriched for signatures indicating up-regulation of these processes. Notably, MAPK-targeted therapy (MAPKi) induced similar signatures in melanoma, suggesting that a form of MAPKi resistance mediates cross-resistance to anti-PD-1 therapy. Co-enrichment of IPRIM (Innate anti-PD-1 Resistance Induced by MAPKi) signatures defined a transcriptomic subset across advanced cancers, suggesting that attenuating processes underlying these signatures may augment anti-PD1 responses. Thus, multi-factorial determinants influence anti-PD-1 patterns in melanoma.
This dataset
Open GSE78220 in finder → Find more human RNA-seq datasets → Melanoma landscape →
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 GSE78220_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 PRJNA312948 and SRA study SRP070710. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26997480) ↗
Study design
26 × Pt

Supports a between-group comparison across 26 samples.

How we read this: 1 replicated groups read from 28 sample titles; they account for 26 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
More Melanoma datasets

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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.