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Chromosomal instability can favor macrophage-mediated immune response and induce a broad, vaccination-like anti-tumor IgG response [scRNA-Seq]

GSE261555 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2024/03/18 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
2 samples
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
Chromosomal instability induced in cancer can enhance macrophage-initiated immune responses that include anti-tumor IgGeLife · 2024
Summary (written by the submitters)
Chromosomal instability (CIN), a state in which cells undergo mitotic aberrations that generate chromosome copy number variations, generates aneuploidy and is thought to drive cancer evolution. Although associated with poor prognosis and reduced immune response, CIN generates aneuploidy-induced stresses that could be exploited for immunotherapies.
Read the full summary ↓
Macrophages, particularly, have been understudied in the CIN context. Here, through MPS1 inhibition-induced CIN in poorly immunogenic B16F10 mouse melanoma, we find that CIN- afflicted cancer cells skew macrophages towards an anti-cancer phenotype while also pushing them away from a pro-cancer one. We confirm these findings via RNA-sequencing, protein expression, and short-term tumor studies. These results further translate to in vivo efficacy in suppressing tumor growth: Mice can survive challenges of CIN-afflicted tumors. Long-term survival, however, is dependent on CD47 expression and IgG opsonization. Mice bearing CIN- afflicted tumors with wild-type CD47 levels see prolonged survival compared to their chromosomally stable counterparts, but all succumb. Mice bearing CIN-afflicted CD47 knockout tumors, however, show 28% long-term survival. When CD47 knockout was further paired with IgG opsonization, survival rate increased to 97%. Successful rejection and clearance of CIN- afflicted tumors induced de novo anti-cancer IgG antibodies that were multi-epitope and functionally promoted macrophage-mediated phagocytosis. These de novo IgG antibodies could also suppress in vitro tumoroid and in vivo tumor growth in a CD47 knockout context. These results highlight an unexpected therapeutic benefit from CIN when paired with maximal macrophage anti-cancer activity: an anti-cancer vaccination-like antibody response that can lead to durable cures and further potentiate cell-mediated acquired immunity.
Published in
Chromosomal instability induced in cancer can enhance macrophage-initiated immune responses that include anti-tumor IgG
Hayes BH, Wang M, Zhu H et al. · eLife 2024 · PMID 38805560 · doi:10.7554/eLife.88054
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 GSE261555_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 PRJNA1087433 and SRA study SRP495109. Searching any of these in the dataset finder brings you back here.

Samples in this study

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