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The RNA-binding protein HuR impairs adipose tissue anabolism in pancreatic cancer cachexia

GSE284803 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2026/01/01 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples: 5 × Sham vs 5 × PDACGroups 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
Impaired Adipose Anabolism in Pancreatic Cancer Cachexia Is Reversed by HuR InhibitionJournal of cachexia, sarcopenia and muscle · 2026
Summary (written by the submitters)
Cachexia, a wasting condition defined by chronic loss of fat and muscle, is a frequent complication of pancreatic ductal adenocarcinoma (PDAC) that negatively impacts quality of life and confers poor patient survival. Nutritional supplementation cannot fully reverse adipose and muscle tissue wasting, and the mechanisms underlying this phenotype are unclear.
Read the full summary ↓
This work aims to define the relative contributions of catabolism and anabolism to adipose wasting in PDAC-bearing mice. Human antigen R (HuR) is an RNA-binding protein recently shown to suppress adipogenesis. We hypothesize that fat wasting results from a loss of adipose anabolism driven by increased HuR activity in adipocytes of PDAC mice.
Published in
Impaired Adipose Anabolism in Pancreatic Cancer Cachexia Is Reversed by HuR Inhibition
Arneson-Wissink PC, Pelz K, Worley B et al. · Journal of cachexia, sarcopenia and muscle 2026 · PMID 41852200 · doi:10.1002/jcsm.70253
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 GSE284803_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 PRJNA1200692. Searching any of these in the dataset finder brings you back here.

Study design
5 × Sham vs 5 × PDAC

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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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