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Effect of MetAP2 Inhibitor Evexomostat (SDX-7320) on Gene Expression in MC38 Tumors from Lean and Obese Mice

GSE295063 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/12/01 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples
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
Evexomostat (SDX-7320), a methionine aminopeptidase type 2 inhibitor, stimulates weight loss and inhibits obesity-accelerated tumor growthFrontiers in oncology · 2026
Summary (written by the submitters)
The objective of this study was to test the anti-tumor activity of the MetAP2 inhibitor evexomostat (SDX-7320) on sub-cutaneous MC38 allografts in lean and obese mice. Mice with established MC38 tumors were treated with evexomostat (SDX-7320) 6 mg/kg by sub-cutaneous injection every 4 days beginning when tumors were 75-100 mm3 for a total of 5 doses. Upon study termination, mice were euthanized and tumor tissue from N=4 mice/group was dissected, weighed, and placed into RNAlater for subsequent isolation of polyA+ RNA, cDNA library construction and sequencing.
Published in
Evexomostat (SDX-7320), a methionine aminopeptidase type 2 inhibitor, stimulates weight loss and inhibits obesity-accelerated tumor growth
Cornelius P, Mayes BA, Dannenberg AJ et al. · Frontiers in oncology 2026 · PMID 41789003 · doi:10.3389/fonc.2026.1751681
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 GSE295063_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 PRJNA1252740 and SRA study SRP579714. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 16 more — browse all 16 samples with per-sample file links →

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