# Revealing propionate metabolism-related genes in glioblastoma and investigating their underlying mechanisms

**Authors:** Yuchen Sun, Huijuan Wang

PMC · DOI: 10.3389/fonc.2025.1529369 · 2025-04-17

## TL;DR

This study identifies six genes related to propionate metabolism that may predict outcomes in glioblastoma patients and could guide treatment strategies.

## Contribution

The study discovers six novel propionate metabolism-related genes as potential prognostic biomarkers for glioblastoma.

## Key findings

- Six PMRGs (SARDH, ACHE, ADSL, PNPLA3, MAPK1, SREBF2) were linked to glioblastoma prognosis.
- Risk score and MGMT promoter status were confirmed as independent prognostic factors.
- qRT-PCR validated altered expression of PNPLA3, SARDH, and ADSL in tumor tissues.

## Abstract

Propionate metabolism may affect tumor growth and aggressiveness, but the role of propionate metabolism-related genes (PMRGs) in glioblastoma (GBM) remains poorly understood.

Differentially expressed PMRGs (DE-PMRGs) were identified by comparing differentially expressed genes (DEGs) between GBM and normal tissues using TCGA-GBM, GSE42669, GSE162631 datasets. Functional enrichment analysis of DE-PMRGs was performed, followed by univariate Cox regression and least absolute shrinkage with selection operator (LASSO) analysis to identify potential prognostic biomarkers. In addition, prognostic models were developed and validated using independent cohorts. Genomic enrichment analysis (GSEA) was used to assess immune-related pathways in different risk subgroups. Finally, biomarker expression was confirmed using quantitative reverse transcription polymerase chain reaction (qRT-PCR).

Differential expression analysis identified a total of 180 DE-PMRGs, which were strongly associated with drug response and insulin signaling pathways. Six biomarkers (SARDH, ACHE, ADSL, PNPLA3, MAPK1 and SREBF2) were identified to be associated with prognosis. The accuracy of the prognostic model was confirmed using the GSE42669 dataset, with risk score and MGMT promoter status identified as independent prognostic factors. GSEA showed enrichment of immune response activation and cell cycle regulatory pathways. qRT-PCR validation showed up-regulation of PNPLA3 and SARDH, and down-regulation of ADSL, in tumor tissues.

This study identified six PMRGs (SARDH, ACHE, ADSL, PNPLA3, MAPK1 and SREBF2) as potential prognostic biomarkers for glioblastoma. These biomarkers reveal the role of propionate metabolism in the progression of glioblastoma and may serve as important indicators of patient prognosis and treatment strategies.

## Linked entities

- **Genes:** SARDH (sarcosine dehydrogenase) [NCBI Gene 1757], ACHE (acetylcholinesterase (Yt blood group)) [NCBI Gene 43], ADSL (adenylosuccinate lyase) [NCBI Gene 158], PNPLA3 (patatin like domain 3, 1-acylglycerol-3-phosphate O-acyltransferase) [NCBI Gene 80339], MAPK1 (mitogen-activated protein kinase 1) [NCBI Gene 5594], SREBF2 (sterol regulatory element binding transcription factor 2) [NCBI Gene 6721]
- **Diseases:** glioblastoma (MONDO:0018177)

## Full-text entities

- **Genes:** SARDH (sarcosine dehydrogenase) [NCBI Gene 1757] {aka BPR-2, DMGDHL1, SAR, SARD, SDH}, MGMT (O-6-methylguanine-DNA methyltransferase) [NCBI Gene 4255], MAPK1 (mitogen-activated protein kinase 1) [NCBI Gene 5594] {aka ERK, ERK-2, ERK2, ERT1, MAPK2, NS13}, ACHE (acetylcholinesterase (Yt blood group)) [NCBI Gene 43] {aka ACEE, ARACHE, N-ACHE, YT}, INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, PNPLA3 (patatin like domain 3, 1-acylglycerol-3-phosphate O-acyltransferase) [NCBI Gene 80339] {aka ADPN, C22orf20, iPLA(2)epsilon}, SREBF2 (sterol regulatory element binding transcription factor 2) [NCBI Gene 6721] {aka SREBP-2, SREBP2, bHLHd2}, ADSL (adenylosuccinate lyase) [NCBI Gene 158] {aka AMPS, ASASE, ASL}
- **Diseases:** tumor (MESH:D009369), GBM (MESH:D005909)
- **Chemicals:** Propionate (MESH:D011422)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

10 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12043635/full.md

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Source: https://tomesphere.com/paper/PMC12043635