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Evolution of myeloid-mediated immunotherapy resistance in prostate cancer

GSE274229 Homo sapiens (human) Single-cell RNA-seq 52 samples Submitted 2024/12/04 Platform GPL24676Platform GPL24247
At a glance

Single-cell RNA-seq · human · 52 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)
Topic
Prostate cancerThis series is part of our curated briefing on it.
Samples
52 samples: 52 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
Sialylated glycoproteins suppress immune cell killing by binding to Siglec-7 and Siglec-9 in prostate cancerThe Journal of clinical investigation · 2024
Summary (written by the submitters)
Patients with advanced metastatic castration-resistant prostate cancer (mCRPC) are refractory to immune checkpoint inhibitors (ICIs), partly because there are immunosuppressive myeloid cells in tumours. However, the heterogeneity of myeloid cells has made them difficult to target, making blockade of the colony stimulating factor-1 receptor (CSF1R) clinically ineffective.
Read the full summary ↓
Here we use single-cell profiling on patient biopsies across the disease continuum and find that a distinct population of tumour-associated macrophages with elevated levels of SPP1 transcripts (SPP1hi-TAMs) becomes enriched with the progression of prostate cancer to mCRPC. In syngeneic mouse modelling, an analogous macrophage population suppresses CD8+ T cell activity in vitro and promotes ICI resistance in vivo. Furthermore, Spp1hi-TAMs are not responsive to anti-CSF1R antibody treatment. Pathway analysis identifies adenosine signalling as a potential mechanism for SPP1hi-TAM-mediated immunotherapeutic resistance. Indeed, pharmacological inhibition of adenosine A2A receptors (A2ARs) significantly reverses Spp1hi-TAM-mediated immunosuppression in CD8+ T cells in vitro and enhances CRPC responsiveness to programmed cell death protein 1 (PD-1) blockade in vivo. Consistent with preclinical results, inhibition of A2ARs using ciforadenant in combination with programmed death 1 ligand 1 (PD-L1) blockade using atezolizumab induces clinical responses in patients with mCRPC. Moreover, inhibiting A2ARs results in a significant decrease in SPP1hi-TAM abundance in CRPC, indicating that this pathway is involved in both induction and downstream immunosuppression. Collectively, these findings establish SPP1hi-TAMs as key mediators of ICI resistance in mCRPC through adenosine signalling, emphasizing their importance as both a therapeutic target and a potential biomarker for predicting treatment efficacy.
Published in
Sialylated glycoproteins suppress immune cell killing by binding to Siglec-7 and Siglec-9 in prostate cancer
Wen RM, Stark JC, Marti GEW et al. · The Journal of clinical investigation 2024 · PMID 39436703 · doi:10.1172/JCI180282
This dataset
Open GSE274229 in finder → Find more RNA-seq datasets → Prostate cancer landscape →
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 GSE274229_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 PRJNA1143590 and SRA study SRP523989. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39436703) ↗
Study design
52 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 52 sample titles: 52 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

+ 12 more — browse all 52 samples with per-sample file links →

More Prostate cancer datasets

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