Integrative eQTL and Mendelian randomization analysis reveals key genetic markers in mesothelioma

Our plain-English summary of Integrative eQTL and Mendelian randomization analysis reveals key genetic markers in mesothelioma, by J. Li, X. Wang, Y. Lin, et al (Respiratory Research, 2025).

The study

• Authors: J. Li, X. Wang, Y. Lin, Z. Li, W. Xiong
• Journal: Respiratory Research
• Published: 2025;26(1):140
• Cited by: 4 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Background: Mesothelioma is a rare cancer that originates from the pleura and peritoneum, with its incidence increasing due to asbestos exposure. Patients are frequently diagnosed at advanced stages, resulting in poor survival rates. Therefore, the identification of molecular markers for early detection and diagnosis is essential.

Methods: Three mesothelioma datasets were downloaded from the GEO database for differential gene expression analysis. Instrumental variables (IVs) were identified based on expression quantitative trait locus (eQTL) data for Mendelian randomization (MR) analysis using mesothelioma Genome-Wide Association Study (GWAS) data from the FINNGEN database. The intersecting genes from MR-identified risk genes and differentially expressed genes were identified as key co-expressed genes for mesothelioma. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), as well as immune cell correlation analysis, were performed to elucidate the roles of key genes in mesothelioma. Additionally, the differential expression of key genes in mesothelioma was validated in independent GEO datasets and TCGA datasets. This integrative research combining multiple databases and analytical methods established a robust model for identifying mesothelioma risk genes.

Results: The research conducted in our study identified 1608 genes that were expressed differentially in mesothelioma GEO datasets. By combining these genes with 192 genes from MR analysis, we identified 14 key genes. Notably, MPZL1, SOAT1, TACC3, and CYBRD1 are linked to a high risk of mesothelioma, while TGFBR3, NDRG2, EPAS1, CPA3, MNDA, PRKCD, MTUS1, ALOX15, LRRN3, and ITGAM are associated with a lower risk. These genes were found to be enriched in pathways associated with superoxide metabolism, cell cycle regulation, and proteasome function, all of which are linked to the development of mesothelioma. Noteworthy observations included a significant infiltration of M1 macrophages and CD4 + T cells in mesothelioma, with genes SOAT1, MNDA, and ITGAM showing a positive correlation with the level of M1 macrophage infiltration. Furthermore, the differential expression analyses conducted on the GEO validation set and TCGA data confirmed the significance of the identified key genes.

Conclusion: This integrative eQTL and Mendelian randomization analysis provides evidence of a positive causal association between 14 key co-expressed genes and mesothelioma genetically. These disease critical genes are implicated in correlations with biological processes and infiltrated immune cells related to mesothelioma. Moreover, our study lays a theoretical foundation for further research into the mechanisms of mesothelioma and potential clinical applications.

© 2025. The Author(s).

In plain English

This computer-based genetic study used only public databases. It did not measure asbestos exposure. The authors compared gene activity in 105 mesothelioma and 19 normal mesothelial tissue samples from three public datasets. They also used Mendelian randomization, a statistical method based on inherited genetic variants. It linked genetic markers for 19,942 genes to FinnGen mesothelioma data (218,792 samples, European populations). They found 1608 genes with altered activity in mesothelioma and 182 genes statistically linked to mesothelioma risk. Fourteen genes appeared in both lists. Higher activity of four genes (MPZL1, SOAT1, TACC3, CYBRD1) was linked to higher odds of mesothelioma. For MPZL1 the odds ratio was 1.728 (95% confidence interval 1.143 to 2.612). Ten other genes were linked to lower odds. A computer algorithm estimated higher proportions of two immune cell types, M1 macrophages and CD4 naive T cells, in mesothelioma than in control samples. The authors concluded their analysis provides genetic evidence of a causal association between the 14 genes and mesothelioma. They noted small sample sizes and European-only genetic data, and said experimental studies are still needed.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Computer-based genetic study using public data. It compared gene expression between samples and combined this with two-sample Mendelian randomization based on eQTL data (genetic variants linked to gene activity) and GWAS data. It also included enrichment and immune cell analyses.
• Who was studied: Training set from three public GEO datasets: 105 mesothelioma samples and 19 normal mesothelial tissue samples. Validation set GSE51024: 55 mesothelioma and 41 normal samples. TCGA: 86 mesothelioma samples compared with 110 normal lung tissue samples. FinnGen mesothelioma GWAS: 218,792 samples. The genetic data came from European populations.
• Exposure: No asbestos or fiber exposure was studied. The 'exposure' in the Mendelian randomization analysis was the genetically predicted activity (expression) of 19,942 human genes.
• Main results:
  • In the training set, 1608 genes had different activity in mesothelioma compared with normal samples: 791 more active and 817 less active.
  • Mendelian randomization identified 182 genes associated with mesothelioma: 90 high-risk and 92 low-risk.
  • Combining the two analyses gave 14 key genes.
  • Higher expression of four genes was positively associated with mesothelioma: MPZL1 (OR 1.728; 95% CI 1.143 to 2.612; P = 0.009), SOAT1 (OR 1.579; 95% CI 1.050 to 2.374; P = 0.028), TACC3 (OR 1.964; 95% CI 1.057 to 3.649; P = 0.033) and CYBRD1 (OR 1.771; 95% CI 1.019 to 3.078; P = 0.043).
  • Ten genes were identified as low-risk genes: LRRN3, TGFBR3, NDRG2, EPAS1, CPA3, MNDA, PRKCD, MTUS1, ALOX15 and ITGAM.
  • Example of a low-risk gene: ITGAM expression was negatively associated with mesothelioma (OR 0.179; 95% CI 0.043 to 0.751; P = 0.019).
  • A leave-one-out sensitivity analysis found no horizontal pleiotropy. This is a check that the genetic markers do not affect mesothelioma through other routes.
  • The 14 genes showed different expression levels in mesothelioma in the GSE51024 validation set and in TCGA data.
  • The key genes were enriched in biological processes including phagocytosis, superoxide anion generation and superoxide metabolism.
  • The CIBERSORT algorithm estimated the immune cell makeup from the gene expression data. Compared with control tissue, it gave significantly higher proportions of CD4 naive T cells and M1 macrophages in mesothelioma.
  • Estimated M1 macrophage levels were positively correlated with expression of SOAT1, MNDA and ITGAM, and negatively correlated with ALOX15 and LRRN3.
  • Higher levels of SOAT1 and TACC3 were linked to shorter survival (p less than 0.05). Higher NDRG2 expression was linked to a more favorable prognosis. The main text does not state which patient data were used.
• The authors' conclusion: The authors concluded that their analysis provides genetic evidence of a causal association (in their words, a 'positive causal association') between 14 key co-expressed genes and mesothelioma.
• Limitations the authors state:
  • Mesothelioma is rare, so sample sizes in the GEO and TCGA databases were limited.
  • TCGA has no normal mesothelial samples, so normal lung tissue was used for comparison.
  • The genetic data came only from European populations, which may limit how far the findings apply to other populations.
  • The 14-gene model needs further screening and confirmation in experimental studies.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Mesothelioma.

Medical terms in this study, explained in our Lexicon: Mesothelioma, Pleura, Peritoneum, Asbestos Exposure, Superoxide, Macrophage.

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