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Reprogramming engineered autologous T cells to overcome resistance in Merkel cell carcinoma [scRNA-seq]

GSE326661 Homo sapiens (human) Single-cell RNA-seq 22 samples Submitted 2026/05/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 22 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
Merkel cell carcinomaThis series is part of our curated briefing on it.
Samples
22 samples: 22 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)
Immune checkpoint inhibitors (CPIs) have transformed Merkel cell carcinoma (MCC) outcomes, but most patients with MCC develop resistance. We identified TCRMCC1, a highly-avid, HLA-A*02:01-restricted T cell receptor (TCR) targeting the Merkel Cell Polyoma Virus (MCPyV) oncoprotein LTAg15–23. Seven patients with CPI-refractory metastatic MCPyV+ MCC received TCRMCC1-transduced cells (TTCR-MCC1) following lymphodepleting chemotherapy or HLA-enhancing interventions (radiation or IFNg-1b [Actimmune®]), with concurrent CPIs (NCT03747484).
Read the full summary ↓
TTCR-MCC1 trafficked to tumor sites and expressed a gene expression profile compatible with T cell activation, with tumor regression observed in two patients. However, therapeutic activity was limited by HLA class I silencing, a common mechanism of immune escape in MCC. In one patient, delayed tumor regression coincided with endogenous effector immune activation and restoration of MCC HLA expression, implying robust local responses could reverse HLA silencing. To overcome this barrier, we engineered CD4 and CD8 TTCR-MCC1 to co-express CD8ab and a CD200R-CD28 switch receptor, enabling CD4 T cell engagement and T cell co-stimulation. These modifications enhanced tumor infiltration, increased HLA expression, and improved control of HLAlow MCC in vivo in mice. These findings support the feasibility of TCR-engineered cell therapy for MCPyV+ MCC and provide a blueprint for overcoming immune evasion via targeted localized enhancement of antigen presentation.
This dataset
Open GSE326661 in finder → Find more human RNA-seq datasets → Merkel cell carcinoma landscape →
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 GSE326661_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 PRJNA1446726 and SRA study SRP688470. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
22 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 22 sample titles: 22 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
More Merkel cell 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.