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ESR1 mutations shape the clonal dynamics, genetic diversity and cellular states of acquired resistance to CDK4/6 inhibitors [RNA-seq]

GSE324093 Homo sapiens (human) Single-cell RNA-seq 32 samples Submitted 2026/05/28 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 32 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
32 samples: 16 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
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)
Resistance to targeted therapies remains a major challenge in cancer treatment. While clonal selection of pre-existing or de novo mutations explains a subset of resistance events, definitive genetic drivers are often lacking, highlighting a possible role for non-coding alterations or other genetic alterations not detected by standard sequencing methods, as well as transcriptional plasticity.
Read the full summary ↓
In estrogen receptor-positive (ER+) breast cancer, CDK4/6 inhibitors (CDK4/6i) combined with endocrine therapy (ET) are a standard first-line treatment, however, most patients eventually develop resistance. Although RB1 loss has been implicated in CDK4/6i resistance, its low prevalence suggests additional, context-dependent resistance mechanisms. To investigate the interplay between genetic evolution, clonal dynamics, and cellular plasticity during resistance, we used a high-complexity DNA barcoding system (CloneTracer) and multi-omic profiling in MCF7 models expressing wild-type or Y537S mutant ER. Barcoding revealed that resistance to palbociclib and abemaciclib is driven by the selection of rare pre-existing subclones, rather than stochastic acquisition of resistance. The Y537S mutation shaped the clonal architecture of palbociclib resistance, increasing subclonal diversity and promoting persistent ER signaling, but had less impact on abemaciclib resistance. Whole-exome sequencing uncovered distinct genetic landscapes across models, including RB1 loss in a palbociclib-resistant clone. ATAC-seq and RNA-seq analyses showed that mutant ER reprograms chromatin and transcriptional states during resistance, particularly in palbociclib-treated cells. Single-cell RNA-seq revealed further heterogeneity, with coexisting subpopulations harboring divergent resistance-associated programs within single clones. Finally, in vivo xenograft studies demonstrated site-specific clonal outgrowth in mutant ER metastases and overlap between metastatic and CDK4/6i-resistant subclones, supporting the dual role of specific populations in therapeutic resistance and tumor dissemination. Together, our findings highlight the cooperative roles of genetic drivers and cellular plasticity in resistance to CDK4/6i and suggest that strategies targeting both may be required to overcome therapeutic failure.
This dataset
Open GSE324093 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 GSE324093_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: 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 PRJNA1433412 and SRA study SRP681681. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 conditions, mostly in duplicate
WT_Vehicle_1 ×2 WT_Vehicle_2 ×2 WT_Vehicle_3 ×2 WT_PalboR_1 ×2 WT_PalboR_2 ×2 WT_PalboR_3 ×2 WT_AbemaR_1 ×2 WT_AbemaR_2 ×2 +8 more

Supports a between-group comparison across 32 samples.

How we read this: 16 replicated groups read from 32 sample titles; they account for 32 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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