GEO series
Diverse immune suppressing cancer communications with myeloid cells prevent T cell activation and recruitment and provide resistance to cell cycle inhibitor therapy
GSE211434
Homo sapiens (human)
Single-cell RNA-seq
81 samples
Submitted 2024/12/11
Platform GPL16791
At a glance
Single-cell RNA-seq · human · 81 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
- 81 samples: 81 samples, each with a distinct title — no replicated groupsGroups 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
- Cellular interactions within the immune microenvironment underpins resistance to cell cycle inhibition in breast cancersNature communications · 2025
Summary (written by the submitters)
Cancer cells evolve and acquire the ability to develop resistance to therapy and change their environment. A key mechanism involves altering communication with non-malignant cells in the tumor microenvironment (TME). By corrupting the signals for growth and survival, evolving tumors engineer a pro-tumor TME which contributes to the development of treatment resistance.
Read the full summary ↓
However, the specific interactions between malignant and non-malignant cells that predispose drug resistance and their changes during treatment remain widely unknown. Here we examined the composition, communication, and phenotypic diversity of tumor-associated cell populations in serial biopsies from the FELINE clinical trial. Early-stage ER+ breast cancers receiving endocrine therapy (letrozole) alone or in combination with the CDK4/6 cell cycle inhibitor ribociclib were analyzed using single-cell RNA sequencing (scRNAseq). Our analyses reveal cancer cells from ribociclib resistant tumors stimulate macrophage differentiation towards an immune-suppressive phenotype through upregulation of a broad diversity of cytokines and growth factors. This shift in phenotype leads to reduced macrophage cell IL-15/-18 crosstalk with CD8+ T-cell via IL-2/15RA/18R receptors, resulting in reduced T-cell activation and recruitment. Given cell cycle inhibitors known inhibitory effect on immune cell activation, in addition to also blocking cancer cell proliferation, maintenance of immune stimulatory cellular populations and signals that promote T-cell abundance and cytotoxicity is critical for treatment response. Our results show how altered communication promotes an immune-cold TME that predisposes tumors to develop CDK4/6 inhibitor resistance. A successful treatment strategy will require both the prevention of cancer division and also activation of a cytotoxic T-cell response.
Published in
Griffiths JI, Cosgrove PA, Medina EF et al.
· Nature communications 2025
· PMID 40032842
· doi:10.1038/s41467-025-56279-x
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 GSE211434_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: 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 PRJNA870315. Searching any of these in the dataset finder brings you back here.
Study design
81 samples, each with a distinct title — no replicated groups
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 81 sample titles: 81 distinct titles with little repetition. 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
- GSM6469941 FELINE trial, patient P048, day 0, Combination ribociclib
- GSM6469942 FELINE trial, patient P048, day 14, Combination ribociclib
- GSM6469943 FELINE trial, patient P048, day 180, Combination ribociclib
- GSM6469944 FELINE trial, patient P049, day 0, Combination ribociclib
- GSM6469945 FELINE trial, patient P049, day 14, Combination ribociclib
- GSM6469946 FELINE trial, patient P049, day 180, Combination ribociclib
- GSM6469947 FELINE trial, patient P051, day 0, Combination ribociclib
- GSM6469948 FELINE trial, patient P051, day 14, Combination ribociclib
- GSM6469949 FELINE trial, patient P051, day 180, Combination ribociclib
- GSM6469950 FELINE trial, patient P053, day 0, Combination ribociclib
- GSM6469951 FELINE trial, patient P053, day 14, Combination ribociclib
- GSM6469952 FELINE trial, patient P053, day 180, Combination ribociclib
- GSM6469953 FELINE trial, patient P058, day 0, Combination ribociclib
- GSM6469954 FELINE trial, patient P058, day 14, Combination ribociclib
- GSM6469955 FELINE trial, patient P058, day 180, Combination ribociclib
- GSM6469956 FELINE trial, patient P059, day 0, Combination ribociclib
- GSM6469957 FELINE trial, patient P059, day 14, Combination ribociclib
- GSM6469958 FELINE trial, patient P059, day 180, Combination ribociclib
- GSM6469959 FELINE trial, patient P060, day 0, Letrozole alone
- GSM6469960 FELINE trial, patient P060, day 14, Letrozole alone
- GSM6469961 FELINE trial, patient P060, day 180, Letrozole alone
- GSM6469962 FELINE trial, patient P062, day 0, Letrozole alone
- GSM6469963 FELINE trial, patient P062, day 14, Letrozole alone
- GSM6469964 FELINE trial, patient P062, day 180, Letrozole alone
- GSM6469965 FELINE trial, patient P063, day 0, Letrozole alone
- GSM6469966 FELINE trial, patient P063, day 14, Letrozole alone
- GSM6469967 FELINE trial, patient P063, day 180, Letrozole alone
- GSM6469968 FELINE trial, patient P068, day 0, Combination ribociclib
- GSM6469969 FELINE trial, patient P068, day 14, Combination ribociclib
- GSM6469970 FELINE trial, patient P068, day 180, Combination ribociclib
- GSM6469971 FELINE trial, patient P072, day 0, Combination ribociclib
- GSM6469972 FELINE trial, patient P072, day 14, Combination ribociclib
- GSM6469973 FELINE trial, patient P072, day 180, Combination ribociclib
- GSM6469974 FELINE trial, patient P074, day 0, Combination ribociclib
- GSM6469975 FELINE trial, patient P074, day 14, Combination ribociclib
- GSM6469976 FELINE trial, patient P074, day 180, Combination ribociclib
- GSM6469977 FELINE trial, patient P075, day 0, Combination ribociclib
- GSM6469978 FELINE trial, patient P075, day 14, Combination ribociclib
- GSM6469979 FELINE trial, patient P075, day 180, Combination ribociclib
- GSM6469980 FELINE trial, patient P078, day 0, Combination ribociclib
+ 41 more — browse all 81 samples with per-sample file links →
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Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.