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Acute and chronic treatment of trametinib plus lapatinib in patient-derived xenografts (PDX) of pancreatic adenocarcinoma (PDAC)

GSE98399 Homo sapiens (human) Expression microarray 43 samples Submitted 2017/05/02 Platform GPL570
At a glance

Expression microarray · human · 43 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Topic
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
43 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with limited effective treatment options. PDAC tumors frequently harbor the constitutively activated form of KRAS which drives proliferative signaling, but directly targeting KRAS has so far been unsuccessful. To overcome this limitation, combinatorial treatment strategies have been developed to inhibit upstream activators and downstream effectors of KRAS signaling.
Read the full summary ↓
One such combination using trametinib, a MEK1/2 inhibitor, and lapatinib, an EGFR/HER2 inhibitor, substantially reduced tumor growth in a patient-derived xenograft (PDX) model of PDAC. Although trametinib and lapatinib are both known to inhibit the canonical MAPK signaling cascade, the effects of this combination on other important pathways in pancreatic cancer remains unclear. To investigate this, we analyze global gene expression profiles from PDX models of PDAC treated with trametinib, lapatinib, or their combination. Our results show that trametinib induces similar yet less significant expression changes compared to combination while lapatinib has little to no effect as a monotherapy in the acute treatment setting. In the chronic treatment setting, we show that tumors exposured to prolonged treatment with trametinib plus lapatinib eventually leads to adapative resistance. Expression analyses of resistant tumors revealed concominant gene expression changes in upstream receptor tyrosine kinases (RTKs).
This dataset
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.

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 (GSE98399_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA384991. Searching any of these in the dataset finder brings you back here.

Samples in this study

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