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CDK4/6 Inhibition reprograms the Breast Cancer immunopeptidome via Rb-Dependent chromatin and transcriptomic remodeling

GSE287955 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2025/11/12 Platform GPL24676Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 14 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
14 samples: 3 × MDA_Abema vs 3 × MDA_DMSO vs 3 × CAMA1_Abema vs 3 × CAMA1_DMSOGroups 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.
Paper
CDK4/6 inhibition reprograms the breast cancer immunopeptidome via Rb-dependent chromatin and transcriptomic remodelingCell reports · 2025
Summary (written by the submitters)
The Cyclin-dependent kinase 4/6 inhibitors (CDK4/6is) are standard-of-care therapies for metastatic hormone receptor-positive (HR+) breast cancer, yet their immunomodulatory effects remain underexplored. Here, we demonstrate that CDK4/6 inhibition with Abemaciclib reprograms the tumor antigen landscape by increasing MHC-I presentation and reshaping the immunopeptidome in HR+ and triple-negative breast cancer (TNBC) cells.
Read the full summary ↓
Through multiomics integration, we reveal that this remodeling is driven by retinoblastoma protein (Rb)-dependent transcriptional and chromatin reprogramming, reflected by increased H3K27ac deposition and enhanced chromatin accessibility revealed by ATAC-seq. CDK4/6 inhibition dephosphorylates Rb, enhancing its interaction with BET family proteins and inducing chromatin remodeling that upregulates antigen-source transcripts. We identify novel Abemaciclib-induced MHC-I peptides, including antigens derived from non-coding genomic regions, which can enhance tumor immunogenicity. These findings reveal a previously unrecognized role of CDK4/6is in shaping tumor antigenicity and suggest that combining CDK4/6is with immunotherapy could broaden antigenic targets in breast cancer.
Published in
CDK4/6 inhibition reprograms the breast cancer immunopeptidome via Rb-dependent chromatin and transcriptomic remodeling
Minati R, Cahuzac M, Perrault J et al. · Cell reports 2025 · PMID 41391145 · doi:10.1016/j.celrep.2025.116676
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 GSE287955_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 PRJNA1215355 and SRA study SRP559691. Searching any of these in the dataset finder brings you back here.

Study design
3 × MDA_Abema vs 3 × MDA_DMSO vs 3 × CAMA1_Abema vs 3 × CAMA1_DMSO

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 12 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
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