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Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomer

GSE284793 Homo sapiens (human) RNA-seq (gene expression) 17 samples Submitted 2025/07/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 17 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Merkel cell carcinomaThis series is part of our curated briefing on it.
Samples
17 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.
Paper
Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomerMolecular oncology · 2026
Summary (written by the submitters)
Merkel cell carcinoma (MCC) is a highly aggressive skin cancer with the poorest prognosis, posited to be derived from Merkel cells. Emerging evidence, however, suggests other potential origins for MCC including hematological lineages. Given the high fatality of MCCs and that many arise in the immune suppressed population, often precluding the use of immunotherapy, it is important to determine the cell of origin for these cancers to elucidate targetable pathways to enable novel treatment approaches.
Read the full summary ↓
We utilized targeted and multi-omics approaches to explore expression patterns at both the protein and RNA level of MCCs. Western blotting, immunofluorescence, and immunohistochemistry were performed for two patient-derived MCC samples, one MCC cell line, and 92 FFPE samples, respectively, for numerous B-cell markers. Further, RNA sequencing was performed on 17 FFPE patient-derived MCC samples and evaluated by principal component analysis for differentially expressed genes between samples based on sex and MCPyV status. Finally, weighted gene correlation network analysis (WGCNA) and cell type enrichment analyses were employed to determine pathway and cell type enrichment, respectively. MCC patient-derived and cell line samples heterogeneously expressed B-cell and neuroendocrine markers including PAX5, TdT, IgA, CD19, CK20, and chromogranin A. Further, transcriptome analysis demonstrated differentially expressed genes based on sex and MCPyV status. MCPyV+ tumors notably demonstrated significant upregulation of genes involved in immune cell function and downregulation of processes related to neuronal activity. Finally, WGCNA highlighted enrichment for pathways involved in immune function including B-cell differentiation. Cell type enrichment analysis highlighted enrichment for multipotent stem cells, several immune cell types, and keratinocytes. Our findings together with previous results indicate that MCCs are not derived from Merkel cells and instead from multiple or divergent cell types, including those of B-cell lineage. Further, MCC cell of origin may depend on patient and tumour specific characteristics including sex and cell type/differentiation state of a cell infected by the MCPyV. Our work highlights the need for a more personalized approach to diagnosis/characterization and treatment of MCCs given the variability of potentially targetable pathways.
Published in
Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomer
Jeremian R, Sivachandran S, Galati M et al. · Molecular oncology 2026 · PMID 40761160 · doi:10.1002/1878-0261.70107
This dataset
Open GSE284793 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 GSE284793_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1200673 and SRA study SRP552743. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40761160) ↗
Study design
A cohort of 17 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run MCC3 … MCC91 and carry no group information.

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.