GEO series

Immunogenomics and spatial proteomic mapping highlight distinct neuro-immune architectures in melanoma vs. non-melanoma-derived brain metastasis

GSE245467 Homo sapiens (human) RNA-seq (gene expression) 54 samples Submitted 2024/09/11 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 54 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: 54 samples: 54 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.
Paper: Immunogenomics and spatial proteomic mapping highlight distinct neuro-immune architectures in melanoma vs. non-melanoma-derived brain metastasisBJC reports · 2024

Summary (written by the submitters)

Brain metastases (BrMs) are a devastating complication of solid tumors with challenging clinical management. In this study, immunogenomic and digital spatial analyses were applied to interrogate the peripheral blood and tumor specimens derived from 53 unique patients with metastatic brain tumors originating from different solid tumors including melanoma, breast cancer, lung cancer and renal cell carcinoma.

Read the full summary ↓

In the peripheral blood, lower levels of neutrophil -lymphocytes ratio (NLR) were detected at time of craniotomy in patients with melanoma-derived brain metastasis (MBM) vs. non-melanoma- derived brain metastasis (non-MBM). Independently from the primary tumor of derivation, patients with BrMs and increased NLR levels were characterized by shorter overall survival (OS) following craniotomy. In the tumor microenvironment (TME), molecular evaluations performed on FFPEs revealed higher expression of genes and mRNA signatures identifying NK cells, CD8 cells and B cells in MBM (n=13) vs. non-MBM brain metastasis (n=41). Focusing on CD8 cells, higher infiltration of CD8+ cells were observed in patients with MBM with longer OS following craniotomy. Spatial proteomic analysis further highlighted the infiltration of CD8+ cells, antigen presenting cells- (HLA-DR+, CD11c+, B2M+), agonists of T cell activity (CD137+, CD40+) and B cells (CD20+) enriched in MBM vs non-MBM. On the contrary, an increased expression of genes associated with neuro-development, cell- cell adhesion, neutrophil enrichment together with the increased infiltrations of cells promoting neuro-differentiation (Neun+, S100+), immune regulatory functions (CD25+, CD127+), and granulocytes aggregation (CD66b+) were observed in non-MBM vs. MBM. These findings highlight that the TME of BrMs plays a pivotal role in the pathogenesis and therapeutic resistance of BrMs derived from different solid tumors. Our results also suggest that distinct neuro-immune interplay may contribute to treatment resistance in BrMs.

Published in

Immunogenomics and spatial proteomic mapping highlight distinct neuro-immune architectures in melanoma vs. non-melanoma-derived brain metastasis

Mendoza-Valderrey A, Dettmann E, Hanes D et al. · BJC reports 2024 · PMID 39516255 · doi:10.1038/s44276-024-00060-y

This dataset

Open GSE245467 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 GSE245467_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 PRJNA1030422 and SRA study SRP467610. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39516255) ↗

Study design

54 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 54 sample titles: 54 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

GSM7851674 MELBRM1-B
GSM7851675 MELBRM2-B
GSM7851676 MELBRM3-B
GSM7851677 MELBRM4-B
GSM7851678 MELBRM5-B
GSM7851679 MELBRM6-B
GSM7851680 MELBRM7-B
GSM7851681 MELBRM8-B
GSM7851682 MELBRM9-B
GSM7851683 MELBRM10-B
GSM7851684 MELBRM11-B
GSM7851685 MELBRM12-B
GSM7851686 MELBRM13-B
GSM7851687 BREBRM19-B
GSM7851688 BREBRM20-B
GSM7851689 BREBRM21-B
GSM7851690 BREBRM23-B
GSM7851691 BREBRM24-B
GSM7851692 BREBRM25-B
GSM7851693 BREBRM28-B
GSM7851694 BREBRM30-B
GSM7851695 BREBRM32-B
GSM7851696 BREBRM45-B
GSM7851697 BREBRM46-B
GSM7851698 BREBRM47-B
GSM7851699 BREBRM48-B
GSM7851700 BREBRM49-B
GSM7851701 BREBRM51-B
GSM7851702 BREBRM52-B
GSM7851703 BREBRM53-B
GSM7851704 BREBRM54-B
GSM7851705 LUNBRM14-B
GSM7851706 LUNBRM15-B
GSM7851707 LUNBRM17-B
GSM7851708 LUNBRM18-B
GSM7851709 LUNBRM27-B
GSM7851710 LUNBRM31-B
GSM7851711 LUNBRM33-B
GSM7851712 LUNBRM34-B
GSM7851713 LUNBRM35-B

+ 14 more — browse all 54 samples with per-sample file links →

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Search all human RNA-seq datasets in GEO →

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