Back

Multi-Omics Integrative Analysis of the Aspirin-Gut-Brain-Glioma Axis: Transcriptomic, Proteomic, Epigenetic, Mendelian Randomization, and Single-Cell Transcriptomic Evidence Converges on NEO1/Hepcidin Iron Reprogramming and Ferroptosis Vulnerability

Ma, C.; Zhang, F.; Wu, F.; Shi, C.; Wu, X.; Tan, X.

2026-06-02 oncology
10.64898/2026.06.01.26354602 medRxiv
Show abstract

Background: Despite epidemiological interest in aspirin's chemopreventive potential against glioma, the underlying multi-layered molecular mechanisms -- spanning COX-2/PGE2 signaling, iron metabolism, ferroptosis, epigenetic regulation, and the NEO1/hepcidin regulatory axis -- have not been systematically characterized at the multi-omics level. Methods: We conducted an integrative multi-omics analysis leveraging TCGA-GBM (n=172) and TCGA-LGG (n=534) transcriptomes, CPTAC GBM proteomics (n=99), TCGA HM450K DNA methylation data (GBM n=140, LGG n=516), GEO aspirin perturbation datasets, IEU OpenGWAS summary statistics, and independent single-cell RNA-seq data (GSE131928, 28 GBM patients). Eight analytical tracks were executed: (1) COX-2/PGE2 pathway profiling, (2) BBB tight junction characterization, (3) GEO-derived aspirin response signature projection, (4) gut-brain axis evaluation, (5) Mendelian randomization (MR) using PTGS2 cis-SNPs, (6) iron metabolism and ferroptosis pathway analysis, (7) NEO1/HFE2/BMP6/HAMP regulatory axis characterization with multi-omics validation, and (8) single-cell transcriptomic validation across GBM malignant cell states. Results: Transcriptomic analysis revealed profound reprogramming of the NEO1/hepcidin iron regulatory axis in GBM: HAMP (hepcidin) was massively upregulated (log2FC=+2.92, P=5.0e-37), accompanied by TFRC upregulation (log2FC=+1.38, HR=2.30, P=3.6e-42) and NEO1 downregulation (log2FC=-0.57, HR=0.59, P=4.6e-6). De novo HM450K methylation analysis revealed HAMP as the dominant epigenetic target in the iron network, exhibiting the strongest hypomethylation signal (DeltaBeta=-0.265, P=1.4e-48), while NEO1 and TFRC showed constitutively low baseline methylation (Beta<0.05). Gene set enrichment analysis identified ferroptosis driver genes (NES=+1.861, P=0.030) and the iron deficiency response pathway (NES=+1.698, P=0.010) as the most significantly enriched pathways in GBM. Molecular subtype analysis revealed that the mesenchymal GBM subtype exhibits the highest iron metabolism gene expression. Mendelian randomization established a causal relationship between PTGS2 expression and glioma risk (IVW OR=1.31, P=1.1e-4). Single-cell RNA-seq analysis validated that iron metabolism gene expression is heterogeneously distributed across malignant cell states, with the mesenchymal state exhibiting the highest HAMP expression and elevated ferroptosis vulnerability. GPX4 was universally highly expressed across all cell states, indicating pan-GBM dependence on GPX4-mediated ferroptosis suppression. Conclusions: This multi-omics investigation reveals that the NEO1/hepcidin iron regulatory axis is epigenetically reprogrammed in glioma, driving iron-dependent vulnerability that bridges COX-2 signaling with ferroptosis susceptibility. The convergent evidence from transcriptomics, proteomics, epigenomics, and causal inference provides a comprehensive mechanistic framework for aspirin's protective effects against glioma and identifies the NEO1/HAMP/TFRC axis as a promising therapeutic target.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
Neuro-Oncology
30 papers in training set
Top 0.2%
6.8%
2
Cancer Cell
38 papers in training set
Top 0.2%
6.4%
3
Clinical Epigenetics
53 papers in training set
Top 0.2%
4.9%
4
Acta Neuropathologica Communications
81 papers in training set
Top 0.1%
4.9%
5
Nature Communications
4913 papers in training set
Top 35%
4.3%
6
Journal of Clinical Investigation
164 papers in training set
Top 1%
3.6%
7
Clinical Cancer Research
58 papers in training set
Top 0.5%
3.6%
8
Neuro-Oncology Advances
24 papers in training set
Top 0.2%
3.6%
9
Cancer Research
116 papers in training set
Top 0.8%
3.6%
10
Neuroscience & Biobehavioral Reviews
43 papers in training set
Top 0.1%
3.6%
11
Cancer Letters
32 papers in training set
Top 0.1%
3.1%
12
Frontiers in Oncology
95 papers in training set
Top 1%
2.7%
50% of probability mass above
13
Cell Reports Medicine
140 papers in training set
Top 2%
2.6%
14
Scientific Reports
3102 papers in training set
Top 45%
2.6%
15
eLife
5422 papers in training set
Top 40%
1.8%
16
JNCI: Journal of the National Cancer Institute
16 papers in training set
Top 0.3%
1.7%
17
PLOS ONE
4510 papers in training set
Top 56%
1.5%
18
Theranostics
33 papers in training set
Top 0.7%
1.5%
19
Molecular Cancer
14 papers in training set
Top 0.4%
1.5%
20
npj Precision Oncology
48 papers in training set
Top 0.8%
1.2%
21
Cancers
200 papers in training set
Top 4%
1.2%
22
Acta Neuropathologica
51 papers in training set
Top 0.9%
1.1%
23
iScience
1063 papers in training set
Top 23%
1.1%
24
International Journal of Molecular Sciences
453 papers in training set
Top 12%
1.0%
25
BMC Medicine
163 papers in training set
Top 6%
0.9%
26
Annals of Oncology
13 papers in training set
Top 0.8%
0.9%
27
Communications Medicine
85 papers in training set
Top 0.9%
0.8%
28
Molecular Oncology
50 papers in training set
Top 0.8%
0.8%
29
Cell Reports
1338 papers in training set
Top 32%
0.8%
30
Brain
154 papers in training set
Top 5%
0.7%