← BioTransfer GEO Dataset Finder
GEO series

Key Regulatory Elements of the TGFβ-LRRC15 Axis Predict Disease Progression and Immunotherapy Resistance Across Cancer Types

GSE290255 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2025/10/08 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 12 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)
Samples
12 samples: 12 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)
Transforming growth factor-beta (TGFβ) has dual roles in cancer, initially suppressing tumors but later promoting metastasis and immune evasion. Efforts to inhibit TGFβ have been largely unsuccessful due to significant toxicity and indiscriminate immunosuppression. Leucine-rich repeat-containing protein 15 (LRRC15) is a TGFβ-regulated antigen expressed by mesenchymal-derived cancer cells and cancer-associated fibroblasts (CAFs).
Read the full summary ↓
In preclinical studies, ablation of TGFβ-driven LRRC15+ CAFs increased tumor infiltration of CD8+ T cells. However, the underlying pathobiological mechanisms prompting TGFβ’s upregulation of LRRC15 expression are unclear. Using an integrated approach combining functional compound screening with single-cell RNA sequencing, we reveal key genomic features regulating TGFβ’s ability to increase LRRC15 expression on cancer cells. Construction of gene regulatory networks converged our analyses on four key genes—MMP2, SPARC, TGFβR2, and WNT5B—central to TGFβ-induced LRRC15 pathobiology. Validation of these genes in cell models and their use in predicting immunotherapy responses highlight their potential in refining immunotherapy strategies and personalizing co-treatment options.
This dataset
Open GSE290255 in finder → Find more human RNA-seq datasets →
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 GSE290255_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 PRJNA1226657 and SRA study SRP565567. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 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 12 sample titles: 12 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.