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Lipid metabolism reprograming by SREBP1-PCSK9 targeting sensitizes pancreatic cancer to immunochemotherapy

GSE290259 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/02/28 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples: 3 × KPC cell, shNC vs 3 × PANC02 cell, shNC vs 3 × PANC02 cell, shSrebf1 vs 2 × KPC cell, shSrebf1Groups 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
Lipid metabolism reprograming by SREBP1-PCSK9 targeting sensitizes pancreatic cancer to immunochemotherapyCancer communications (London, England) · 2025
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma (PDAC) treatment is challenging. Determining the metabolic pathways that regulate lipids will provide new insights into PDAC therapeutic strategies. Sterol regulatory element binding transcription factor 1 (SREBP-1) regulates multiple cancer pathways; however, its role in the tumor immune microenvironment and cancer immunotherapy is unknown.
Read the full summary ↓
Herein, we integrated our large PDAC cohort data and identified that SREBP-1, as a master transcriptional regulator of lipogenesis, aggravated lipid metabolism reprogramming in PDAC. Furthermore, interrupting lipid metabolism by targeting SREBP-1 suppressed PDAC cell growth and enhanced antitumor immunity in vitro and in vivo. We demonstrated that SREBP-1 binds to the PD-L1 (programmed cell death 1 ligand 1) promoter to suppress its transcription. Importantly, SREBP-1 binds to the PCSK9 (proprotein convertase subtilisin/kexin type 9) promoter, which regulated PD-L1 levels via lysosome-mediated degradation and aggravated tumor microenvironment immunosuppression. Targeting the SREBP-1- PCSK9 axis using available drugs sustained the remission of aggressive PDAC by synergizing with anti-PD-1 and gemcitabine. In summary, targeting lipid metabolism suppressed tumor growth and relieved tumor immunosuppression in PDAC.
Published in
Lipid metabolism reprograming by SREBP1-PCSK9 targeting sensitizes pancreatic cancer to immunochemotherapy
Lao M, Zhang X, Li Z et al. · Cancer communications (London, England) 2025 · PMID 40439109 · doi:10.1002/cac2.70038
This dataset
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.

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 GSE290259_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1226923 and SRA study SRP565651. Searching any of these in the dataset finder brings you back here.

Study design
3 × KPC cell, shNC vs 3 × PANC02 cell, shNC vs 3 × PANC02 cell, shSrebf1 vs 2 × KPC cell, shSrebf1

Supports a between-group comparison across 11 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 11 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
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