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Single-cell RNA sequencing defines the interplay between tumor cells, virus and microenvironment in nasopharyngeal carcinoma

GSE120926 Homo sapiens (human) Single-cell RNA-seq 56 samples Submitted 2024/11/18 Platform GPL11154Platform GPL20795
At a glance

Single-cell RNA-seq · human · 56 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
Nasopharyngeal carcinomaThis series is part of our curated briefing on it.
Samples
56 samples: 6 conditions, mostly in triplicateGroups 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
Single-cell transcriptomic analysis defines the interplay between tumor cells, viral infection, and the microenvironment in nasopharyngeal carcinomaCell research · 2020
Summary (written by the submitters)
Purpose: While viruses play critival roles in many human malignancies, the influence of virus infection on the tumor microenviroment(TME) and how this impacts disease progression are poorly characterized. Methods: we applied both Smart-seq2 and 10X Genomics chemistry to ~104000 cells from 19 EBV+ NPC patients and 7 nonmalignant nasopharyngeal biopsies.
Read the full summary ↓
Results: 1. We have defined the complex interplay between tumor cells, virus infection, and the TME at single-cell resolution. 2. An epithelial-immune dual feature of malignant cells was discovered and associated with poor prognosis. 3. Stromal and immune cells in the TME were remodeled by tumor cells and virus infection. 4. EBV gene expression was found to correlate with complement factor expression in malignant cells, which, in turn, mediated T cell modulation and recruitment. 5. We subtyped NPC patients into 5 groups with different prognoses according to their respective TME compositions. Conclusion: Our results provide new insights into the multicellular ecosystem of NPC and offer important clinical implications.
Published in
Single-cell transcriptomic analysis defines the interplay between tumor cells, viral infection, and the microenvironment in nasopharyngeal carcinoma
Jin S, Li R, Chen MY et al. · Cell research 2020 · PMID 32901110 · doi:10.1038/s41422-020-00402-8
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 GSE120926_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 PRJNA495040 and SRA study SRP164416. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
primary tumor of NPC patient ×18 primar tumor of NPC patient ×16 primary tumor of NPC patient C ×9 nonmalignant narsopharyngeal biopsy of patien… ×7 Single_cell_RNA-seq(Smart-seq2) of Homo sapie… ×3 Single_cell_RNA-seq(Smart-seq2) of Homo sapie… ×3

Supports a between-group comparison across 56 samples.

How we read this: 6 replicated groups read from 56 sample titles; they account for 56 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

+ 16 more — browse all 56 samples with per-sample file links →

More Nasopharyngeal carcinoma datasets

Search all human RNA-seq datasets in GEO →

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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.