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Single-cell analysis reveals a stem cell program in human metastatic breast cancer cells (Human patients - mammary cells)

GSE70554 Homo sapiens (human) Single-cell RNA-seq 271 samples Submitted 2015/07/20 Platform GPL20665
At a glance

Single-cell RNA-seq · human · 271 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
271 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
Despite major advances in understanding the molecular and genetic basis of cancer, metastasis remains the cause of >90% of cancer-related mortality1. Understanding metastasis initiation and progression is critical to develop new therapeutic strategies to treat and prevent metastatic disease.
Read the full summary ↓
Prevailing theories hypothesize that metastases are seeded by rare tumor cells with unique properties, which may function like stem cells in their ability to initiate and propagate metastatic tumors.2 3-5 However, the identity of metastasis-initiating cells in human breast cancer remains elusive, and whether metastases are hierarchically organized is unknown.2 Here we show at the single-cell level that early stage metastatic cells possess a distinct stem-like gene expression signature. To identify and isolate metastatic cells from patient-derived xenograft (PDX) models of human breast cancer, we developed a highly sensitive FACS-based assay, which allowed us to enumerate metastatic cells in mouse peripheral tissues. We compared gene signatures in metastatic cells from tissues with low vs. high metastatic burden. Metastatic cells from low-burden tissues were distinct due to their increased expression of stem cell, EMT, pro-survival, and dormancy-associated genes. In contrast, metastatic cells from high-burden tissues were similar to primary tumor cells, which were more heterogeneous and expressed higher levels of luminal differentiation genes. Transplantation of stem-like metastatic cells from low-burden tissues showed that they have significant tumor-initiating capacity, and differentiate to produce luminal-like cancer cells. Progression to high metastatic burden was associated with increased proliferation and cMYC expression, which could be attenuated by treatment with cyclin dependent kinase (CDK) inhibitors. These findings support a hierarchical model for metastasis, where metastases are initiated by stem-like cells that proliferate and differentiate to produce advanced metastatic disease.
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 (GSE70554_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA289006. Searching any of these in the dataset finder brings you back here.

Samples in this study

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