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Genomic and transcriptomic analysis of Japanese melanoma reveals candidate biomarkers for immune checkpoint inhibitor responders.

GSE282471 Homo sapiens (human) RNA-seq (gene expression) 111 samples Submitted 2025/11/21 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 111 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
MelanomaThis series is part of our curated briefing on it.
Samples
111 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
Genomic and transcriptomic analyses of melanoma in Japanese patients reveal candidate biomarkers for immune checkpoint inhibitor respondersCommunications medicine · 2026
Summary (written by the submitters)
Background Immune checkpoint inhibitor (ICI) has greatly improved the prognosis of advanced melanoma. Whereas the efficacy in Japanese patients has been found to be lower than Caucasian, the genomic and transcriptomic features associated with response to ICI of Japanese melanomas remain to be elucidated. Patients and methods Total 129 tumour samples from 78 melanoma patients, who received therapeutic regimens with or without ICI treatment, were collected at 13 institutions in Japan.
Read the full summary ↓
We performed exome and RNA sequencing and investigated the association of genomic and transcriptomic factors with clinical efficacy of ICI therapy. Time-course data were also analysed. This is the first and largest genomic cohort study for Japanese melanoma, in which tumour samples were prospectively analysed. Results Number of somatic SNVs of Japanese melanomas is lower than that of TCGA Caucasian data due to the biased distribution of WHO subtypes. Driver subtypes of BRAF, NRAS and NF1 was less prevalent but Triple Wildtype predominantly existed in the Japanese cohort. Whereas exome-wide survey revealed no significant association of mutated genes with ICI response, by transcriptomic analysis we identified inflammation-associated genes including several chemokines and cytokines were highly expressed in responders. Follicular helper T cells estimated by immune-cell composition analysis were found significantly enriched in responders (p = 0.0422). Through time-course transcriptome analysis, in addition to several cytotoxic T-cell genes as previously reported, MARCO on tumour-associated macrophages was found induced by ICI treatment in responders (p = 0.0040). The protein expression of these genes was confirmed by immunohistochemical and multiplex immunofluorescent analyses. Some of these genes can be useful biomarkers for prediction of ICI response in the treatment of Japanese melanoma. Conclusions Through prospective genomic and transcriptomic analyses of Japanese melanoma samples, candidate biomarkers for ICI treatment were identified.
Published in
Genomic and transcriptomic analyses of melanoma in Japanese patients reveal candidate biomarkers for immune checkpoint inhibitor responders
Kimura T, Tanaka N, Maekawa T et al. · Communications medicine 2026 · PMID 41501359 · doi:10.1038/s43856-025-01341-4
This dataset
Open GSE282471 in finder → Find more human RNA-seq datasets → Melanoma 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 GSE282471_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 PRJNA1188980. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41501359) ↗
Study design
A cohort of 111 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 mRNA_Melanoma_rep1 … mRNA_Melanoma_rep111 and carry no group information.

Samples in this study

+ 71 more — browse all 111 samples with per-sample file links →

More Melanoma datasets

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