GEO series

Prior targeted therapy treatment and cellular composition modulate the effects of Axl inhibition on myeloid cells in the human in vitro melanoma tumor microenvrionment

GSE310271 Homo sapiens (human) Single-cell RNA-seq 8 samples Submitted 2026/07/31 Platform GPL34295

At a glance

Single-cell RNA-seq · human · 8 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)
Topic: MelanomaThis series is part of our curated briefing on it.
Samples: 8 samples: 8 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)

Axl has gained momentum as a promising target in cancer therapy due to its contribution to both cancer progression and immunosuppression. While pre-clinical studies in mice have demonstrated its potential as a dual target - to be both tumoricidal and immunostimulatory - clinical trials have reported mixed results. We built a human in vitro model system to understand how prior standard-of-care treatment in the context of melanoma impacts the effects of the small molecule Axl inhibitor bemcentinib on myeloid cells in the tumor microenirnoment.

Read the full summary ↓

In our previous work we reported differences in macrophage state and activity primarily resulted from whether the melanoma cells they were co-cultured with had prior trametinib + dabrafenib treatment, and that this then impacted the macrophage resposne to Axl inhibition. We also showed that the addition of donor-matched dendritic cells to the in vitro system resulted in a dampened macrophage response. In this current work, we generated single-cell RNA-sequencing data to understand the changes in cell signaling that underlie our previously reported observations.

This dataset

Open GSE310271 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 GSE310271_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 PRJNA1365680 and SRA study SRP646168. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 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 8 sample titles: 8 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

GSM9293152 DMSO co-culture of untreated A375 + HMDM
GSM9293153 Bemcentinib co-culture of untreated A375 + HMDM
GSM9293154 DMSO co-culture of injured A375 + HMDM
GSM9293155 Bemcentinib co-culture of injured A375 + HMDM
GSM9293156 DMSO tri-culture of untreated A375 + HMDM + HMDDC
GSM9293157 Bemcentinib tri-culture of untreated A375 + HMDM + HMDDC
GSM9293158 DMSO tri-culture of injured A375 + HMDM + HMDDC
GSM9293159 Bemcentinib tri-culture of injured A375 + HMDM + HMDDC

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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.