← BioTransfer GEO Dataset Finder
GEO series

Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma

GSE61544 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2014/09/19 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 14 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)
Samples
14 samples
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)
Increased MITF expression contributes to melanoma progression and resistance to BRAF pathway inhibition. We show that, unexpectedly, lack of MITF is associated with more severe resistance to a range of inhibitors. Indeed, the presence of endogenous MITF was essential for robust drug responses. Both in primary and acquired resistance, MITF levels inversely correlated with expression of several activated receptor tyrosine kinases, most commonly AXL.
Read the full summary ↓
The MITF-low/AXL-high/drug resistance phenotype was seen in roughly half of BRAF mutant and the majority of NRAS mutant melanoma cell lines. The dichotomous behavior of MITF in drug response was corroborated in vemurafenib-resistant biopsies, including MITF high and low clones in a relapsed patient. Drug cocktails containing AXL inhibitor enhanced melanoma cell elimination by BRAF or ERK inhibition. Our results demonstrate that a low MITF/AXL ratio predicts early resistance to multiple targeted drugs, and warrant clinical validation of AXL inhibitors to combat resistance of BRAF and NRAS mutant MITF-low melanomas.
This dataset
Open GSE61544 in finder → Find more human 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 GSE61544_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 PRJNA261431 and SRA study SRP047299. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25502142) ↗
Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 14 more — browse all 14 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.