GEO series

Methylation changes in pre MAPKi treatment and post MAPKi resistance Melanomas

GSE65183 Homo sapiens (human) DNA methylation 144 samples Submitted 2015/09/15 Platform GPL13534

At a glance

DNA methylation · human · 144 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 144 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI.

Summary (written by the submitters)

Melanoma resistance to MAPK- or T cell checkpoint-targeted therapies represents a major clinical challenge, and treatment failures of MAPK-targeted therapies due to acquired resistance often require salvage immunotherapies. We show that genomic analysis of acquired resistance to MAPK inhibitors revealed key driver genes but failedto adequately account for clinical resistance.

Read the full summary ↓

From a large-scale comparative analysis of temporal transcriptomes from patient-matched tumor biopsies, we discovered highly recurrent differential expression and signature outputs of c-MET, LEF1 and YAP1 as drivers of acquired MAPK inhibitor resistance. Moreover, integration of gene- and signature-based transcriptomic analysis revealed profound CD8 T cell deficiency detected in half of resistant melanomas in association with downregulation of dendritic cells and antigen presentation. We also propose a major methylomic basis to transcriptomic evolution under MAPK inhibitor selection. Thus, this database provides a rich informational resource, and the current landscape represents a benchmark to understanding melanoma therapeutic resistance.

This dataset

Open GSE65183 in finder → Find more human methylation datasets →

Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE65183_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA273361. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26359985) ↗

Samples in this study

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+ 144 more — browse all 144 samples with per-sample file links →

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