GEO series

The interactions among Tumor-infiltrating T lymphocytes (TILS) induced by Stellera chamaejasme and anti-PD-1 therapy with Sing-cell Expression Profiling

GSE186854 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2024/10/29 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 10 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: Mus musculus (mouse)
Samples: 10 samples: 10 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.

Summary (written by the submitters)

Tumor-infiltrating T lymphocytes (TILS) plays a pivotal role in immunotherapy, but the dynamic relationships of the T cells reacted on the therapy remains elusive. T cell receptor (TCR) repertoire, serving as lineage tags, could track these tumor-infiltrating T lymphocytes. Here, in order to deconvolve TILS heterogeneity after therapy in a comprehensive catalog, we presented single T-cell analysis by RNA-seq and TCR tracking of a 22,590 T cells from colorectal carcinoma under control conditions and during Stellera chamaejasme and anti-PD-1 activation.

Read the full summary ↓

We reveal a highly complex microenvironment which profoundly molds T lymphocytes, as well as the combinatorial impact of TCR utilization on phenotypic diversity. scRNA-seq identified distinct CD8 T cells subtypes CD8 naïve and CD8 cytoxic cells(CD8 CTL), also, CD4 T cell subpopulations Regulatory T(Tregs) cells and T helper cell 17(Th-17). Stellera chamaejasme activation triggered CTSW, ICOS, etc. in CD8 T cells, whose the dramatic differentiation into from a single time point. At the same time, Stellera chamaejasme plus anti-PD-1 therapy have a strikingly effect on the balance between Tregs and Th-17. Our integrated analyses provide a powerful avenue to disclose the TILS in CRC based on TCR and demonstrate novel functional interactions among TILS subpopulations during Stellera chamaejasme plus anti-PD-1 therapy.

This dataset

Open GSE186854 in finder → Find more mouse RNA-seq datasets →

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 GSE186854_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 PRJNA776330 and SRA study SRP343815. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

10 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 10 sample titles: 10 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

GSM5662353 310-10xscRNA-seq
GSM5662354 920-10xscRNA-seq
GSM5662355 G2_470-10xscRNA-seq
GSM5662356 G3_210-10xscRNA-seq
GSM5662357 G3_320-10xscRNA-seq
GSM5662358 310-10xscTCR-seq
GSM5662359 920-10xscTCR-seq
GSM5662360 G2_470-10xscTCR-seq
GSM5662361 G3_210-10xscTCR-seq
GSM5662362 G3_320-10xscTCR-seq

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