GEO series

Distinct transcriptional programs characterize neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade [bulk TCR-seq]

GSE176022 Homo sapiens (human) Single-cell RNA-seq 102 samples Submitted 2021/07/21 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 102 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: 102 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)

Immune checkpoint blockade (ICB) has revolutionized cancer treatment, but most patients do not respond. PD-1 blockade “unleashes” CD8 T cells, including those specific for mutation-associated neoantigens (MANA), but factors in the tumor microenvironment can inhibit responses by dampening MANA-specific T cell function. Recent advances in single cell transcriptomics are revealing global T cell dysfunction programs in tumor-infiltrating lymphocytes (TIL).

Read the full summary ↓

However, the vast majority of TIL do not recognize tumor antigens and little is known about transcriptional programs of true MANA-specific TIL. Here, we use an integrated approach to identify MANA-specific T cell clones using the MANA functional expansion of specific T cells (MANAFEST) assay in neoadjuvant anti-PD-1-treated lung cancers and use their TCR CDR3 as barcodes to track them and analyze their transcriptional programs and function in the tumor microenvironment using single cell RNA sequencing. We find both MANA-and virus-specific clones in TIL and adjacent normal lung, regardless of response status. MANA-specific, influenza (flu)-specific and EBV-specific TIL each have unique transcriptional programs. Most MANA-specific clones are tissue resident memory (TRM) cells, an incompletely activated cytolytic program, including EOMES deficiency, and higher levels of genes encoding T cell inhibitory molecules and Tox2. Notably, MANA-specific T cells express low levels of IL-7R and are functionally less responsive to IL-7 compared with tissue-resident flu-specific clones. MANA-specific clones from anti-PD-1 non-responding tumors express TCR with markedly lower ligand-dependent signaling capability, are largely confined to HOBIThi TRM subsets and coordinately up-regulate genes encoding specific checkpoints, killer inhibitory receptors, and intracellular inhibitors of T cell activation and cytotoxicity. These findings provide mechanistic and potential therapeutic insights into overcoming resistance to PD-1 blockade.

This dataset

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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 GSE176022_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 PRJNA734593 and SRA study SRP330502. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 34290408) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 102 more — browse all 102 samples with per-sample file links →

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