GEO series

Xenografting of advanced stage breast cancer preserves the genomic and clonal architecture and captures luminal tumors harboring mutations and gene rearrangements in ESR1

GSE46604 Homo sapiens (human) Expression microarray 272 samples Submitted 2013/12/22 Platform GPL8269

At a glance

Expression microarray · human · 272 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Homo sapiens (human)
Topic: Breast cancerThis series is part of our curated briefing on it.
Samples: 272 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

End-stage breast cancers are clonally heterogeneous and harbor many poorly-understood treatment resistance mechanisms. We therefore established multiple Patient-Derived-Xenograft (PDX) models to study genomic events driving advanced disease. Comparative whole-genome sequencing of paired primary tumors and their PDX models demonstrated that PDX retain the vast majority of the structural variations and copy number aberrations seen within the originating tumor, and with high fidelity.

Read the full summary ↓

Variant allele fractions (VAF) were preserved, even for rare mutations. Clonal representation is therefore a transplantable phenotype, indicating that genomic heterogeneity can be regulated in a tumor-autonomous mechanism, indifferent to host immune status. Mutations and gene rearrangements were documented in the ESR1 gene in three of five sequenced luminal PDX/progenitor tumor pairs (amplification, point mutation and translocation), and were associated with clinical endocrine response phenotypes, differential PDX estradiol responsiveness and all induced estradiol-independent growth in standard cell lines. PDX models are therefore a significant new tool for fundamental studies on the molecular basis for resistance to endocrine treatment in advanced breast cancer.

This dataset

Open GSE46604 in finder → Find more human microarray datasets → Breast cancer landscape →

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 (GSE46604_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: 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 PRJNA217715. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 24055055) ↗

Samples in this study

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+ 272 more — browse all 272 samples with per-sample file links →

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GSE104675 Role for the Transcriptional Activator ZRF1 in Breast Cancer Progression and Endocrine Resistance 6 samples same disease briefing
GSE325486 ESR1 mutations shape the clonal dynamics, genetic diversity and cellular states of acquired resistance to CDK4/6 inhibitors 57 samples shares esr1, mutations
GSE310672 Progesterone receptors drive advanced breast cancer phenotypes including circulating tumor- and stem-like cell expansion in the context of ESR1 mutation [RNA-seq] 48 samples shares esr1, advanced
GSE281302 ESR1 Y537S and D538G mutations drive resistance to CDK4/6 inhibitors in estrogen receptor-positive breast cancer 36 samples shares esr1, mutations

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