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Adipose-Tumor Crosstalk contributes to CXCL5 Mediated Immune Evasion in PDAC

GSE274713 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2024/08/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 30 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
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
30 samples: 6 × Sample_HPNE vs 6 × Sample_Mia vs 6 × Sample_Panc1Groups 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
Depletion of tumor-derived CXCL5 improves T cell infiltration and anti-PD-1 therapy response in an obese model of pancreatic cancerJournal for immunotherapy of cancer · 2025
Summary (written by the submitters)
BACKGROUND: CXCR1/2 inhibitors are being implemented with immunotherapies in PDAC clinical trials. CXCL ligands are a family of cytokines responsible for stimulating these receptors; while typically secreted by activated immune cells, fibroblasts, and even adipocytes, they are also secreted by immune-evasive cancer cells. CXCL ligand release is known to occur in response to inflammatory stimuli, whether pathogenic (bacterial) or endogenous (obesity).
Read the full summary ↓
Obesity has been linked to poor patient outcome and altered anti-tumor immunity in pancreatic cancer. Importantly, adipose-derived cytokines and chemokines have been implicated as potential drivers of tumor cell immune evasion; cumulatively these findings suggest that targeting CXC ligands may be beneficial in the context of obesity. METHODS: RNA-sequencing of human PDAC cell lines was used to assess differential influences of adipose conditioned media on the cancer cell transcriptome. In addition, the adipose-induced secretome of PDAC cells was validated with ELISA for induced CXCL5 secretion. Human tissue data from CPTAC was used to correlate IL-1β and TNF expression with both CXCL5 mRNA and protein levels. CRISPR-Cas9 was used to knock out CXCL5 from a murine PDAC cell line in order to assess orthotopic tumor studies in syngeneic, diet-induced obese mice. Flow cytometry was used to compare the immune profiles between tumors. Mice were monitored for differences in tumor size at endpoint in combination with Anti-PD-1 immune checkpoint blockade therapy. RESULTS: Human adipose conditioned media (hAT-CM) stimulates CXCL5 secretion from PDAC cells via either IL-1β or TNF; neutralization of both is required to significantly block release of CXCL5 from tumor cells. Ablation of CXCL5 from tumors promoted an enriched immune phenotype with an unanticipatedly increased number of exhausted CD8 T cells. Application of anti-PD-1 treatment to control tumors failed to alter tumor growth, yet treatment of CXCL5 deficient tumors showed response by significantly diminished tumor mass. CONCLUSIONS: In summary, our findings show that both TNF and IL-1β can stimulate CXCL5 release from PDAC cells in vitro, which correlates with expression in patient data. CXCL5 depletion in vivo alone is sufficient to promote T cell infiltration into tumors, increasing efficacy of checkpoint blockade inhibition and alleviating tumor burden.
Published in
Depletion of tumor-derived CXCL5 improves T cell infiltration and anti-PD-1 therapy response in an obese model of pancreatic cancer
Walsh RM, Ambrose J, Jack JL et al. · Journal for immunotherapy of cancer 2025 · PMID 40121029 · doi:10.1136/jitc-2024-010057
This dataset
Open GSE274713 in finder → Find more human RNA-seq datasets → Pancreatic cancer 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 GSE274713_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 PRJNA1147698 and SRA study SRP526176. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40121029) ↗
Study design
6 × Sample_HPNE vs 6 × Sample_Mia vs 6 × Sample_Panc1

Supports a between-group comparison across 18 samples.

How we read this: 3 replicated groups read from 30 sample titles; they account for 18 of them. 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
More Pancreatic cancer datasets

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