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Therapy induced tumour secretomes promote resistance and tumour progression

GSE64741 Homo sapiens (human) RNA-seq (gene expression) 41 samples Submitted 2015/03/26 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 41 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
41 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)
Drug resistance invariably limits the clinical efficacy of targeted therapy with kinase inhibitors against cancer. We found that targeted therapy with BRAF, ALK, or EGFR inhibitors induces a complex network of secreted signals in drug-stressed melanoma and lung adenocarcinoma cells. This therapy-induced secretome (TIS) stimulates the outgrowth, infiltration and metastasis of drug-resistant cancer clones in the tumour.
Read the full summary ↓
Additionally, the TIS supports the survival of drug-sensitive cells, contributing to incomplete tumour regression. We used transcriptomic analysis of sensitive tumour cells and xenograft tumours treated with vehicle, vemurafenib, or crizotinib to identify the transcriptional drivers and to dissect the TIS in melanoma (A375, Colo800, UACC62) and lung adenocarcinoma (H3122). In addition, we utilize cell type–specific mRNA purification by translating ribosome affinity purification (TRAP) to identify pathways that are up-regulated in resistant cells (A375R) in response to the regressing tumour microenvironment.
This dataset
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.

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 GSE64741_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA271773 and SRA study SRP051765. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 41 more — browse all 41 samples with per-sample file links →

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