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Crosstalk between myeloid and B cells shapes the distinct microenvironments of primary and secondary liver cancer

GSE235057 Homo sapiens (human) Single-cell RNA-seq 29 samples Submitted 2023/06/19 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 29 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
29 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.
Summary (written by the submitters)
The tumor microenvironment is distinctive in primary and secondary liver cancer. B cells represent an important component of immune infiltrates. Here, we demonstrated that B cells are an important regulator in hepatocellular carcinoma (HCC) and colorectal cancer liver metastasis (CRLM) microenvironments. B cells displayed distinct developmental trajectories in HCC and CRLM.
Read the full summary ↓
Single-cell analysis revealed that IgG+ plasma cells preferentially accumulated in HCC while IgA+ plasma cells were preferentially enriched in CRLM. Mechanistically, IgG+ plasma cells in HCC were recruited by tumor-associated macrophages via the CXCR3-CXCL10 axis, whereas IgA+ plasma cells in CRLM were recruited by metastatic tumor cells via CCR10-CCL28 signaling. Functionally, IgG+ plasma cells preferentially promoted pro-tumorigenic macrophages formation in HCC, and IgA+ plasma cells preferentially induced granulocytic myeloid-derived suppressor cells activation in CRLM. Clinically, increased infiltration of IgG+ plasma cells and macrophages in HCC was correlated to worse survival, while increased intratumoral IgA+ plasma cells and neutrophils in CRLM indicated poor prognosis. Taken together, this study demonstrated plasma and myeloid cell-mediated immunosuppression in HCC and CRLM, suggesting that selectively modulating primary or secondary tumor-related immunosuppressive regulatory networks might reprogram the microenvironment and provide an immunotherapeutic strategy for treating liver cancer.
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 GSE235057_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 PRJNA984270. Searching any of these in the dataset finder brings you back here.

Samples in this study

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