Identification <scp>LEF1</scp> as a Potential Novel Biomarker for Abdominal Aortic Aneurysms Based on Comprehensive Bioinformatics Analysis

Abdominal aortic aneurysm (AAA), a life-threatening cardiovascular disorder, necessitates the identification of novel molecular biomarkers to facilitate early diagnosis and precision therapeutic interventions. In this study, we employed an integrative bioinformatics strategy to systematically identify and characterise a potential biomarker for AAA. By reanalyzing GEO datasets and applying Lasso regression, we identified 10 candidate genes, whose intersection with known AAA-associated genes pinpointed LEF1 as a pivotal regulator. Single-cell transcriptomic analysis further demonstrated that LEF1 is predominantly expressed in aortic wall-resident T cells, suggesting a spatially restricted regulatory role. Functional enrichment analysis highlighted significant associations with MHC class II protein complex binding and ribosomal structural integrity, implicating LEF1 in immune and translational regulation. Immunohistochemical analysis demonstrated significantly elevated expression of CD3, CD4 and CD8 markers in AAA tissues compared to controls. Flow cytometry and immunofluorescence analyses confirmed LEF1 co-localisation with both CD8<sup>+</sup> effector T cells and CD4<sup>+</sup> memory T cells, with significantly enhanced LEF1 expression in AAA specimens versus controls. Overall, our study systematically discovered an important hub gene LEF1, which may serve as a biomarker for AAA.

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Journal
Journal of Cellular and Molecular Medicine
Published
2025-11-01
DOI
https://doi.org/10.1111/jcmm.70921
Primary Topic
Aortic aneurysm repair treatments
Type
article
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article

Identification LEF1 as a Potential Novel Biomarker for Abdominal Aortic Aneurysms Based on Comprehensive Bioinformatics Analysis

Hanshen Luo, Xinyi Liu, Pan He, Jiong Jiong Guo et al.
Journal of Cellular and Molecular Medicine
Aortic aneurysm repair treatments
article

Identification LEF1 as a Potential Novel Biomarker for Abdominal Aortic Aneurysms Based on Comprehensive Bioinformatics Analysis

Hanshen Luo, Xinyi Liu, Pan He, Jiong Jiong Guo, Yuehang Yang
article en

Abstract

Abdominal aortic aneurysm (AAA), a life-threatening cardiovascular disorder, necessitates the identification of novel molecular biomarkers to facilitate early diagnosis and precision therapeutic interventions. In this study, we employed an integrative bioinformatics strategy to systematically identify and characterise a potential biomarker for AAA. By reanalyzing GEO datasets and applying Lasso regression, we identified 10 candidate genes, whose intersection with known AAA-associated genes pinpointed LEF1 as a pivotal regulator. Single-cell transcriptomic analysis further demonstrated that LEF1 is predominantly expressed in aortic wall-resident T cells, suggesting a spatially restricted regulatory role. Functional enrichment analysis highlighted significant associations with MHC class II protein complex binding and ribosomal structural integrity, implicating LEF1 in immune and translational regulation. Immunohistochemical analysis demonstrated significantly elevated expression of CD3, CD4 and CD8 markers in AAA tissues compared to controls. Flow cytometry and immunofluorescence analyses confirmed LEF1 co-localisation with both CD8<sup>+</sup> effector T cells and CD4<sup>+</sup> memory T cells, with significantly enhanced LEF1 expression in AAA specimens versus controls. Overall, our study systematically discovered an important hub gene LEF1, which may serve as a biomarker for AAA.

Journal of Cellular and Molecular MedicineVol. 29(21)
Union Hospital (HK), Capital Medical University (CN), Beijing Anzhen Hospital (CN), Wuhan Union Hospital (CN), Henan Provincial Chest Hospital (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 51%
Aortic aneurysm repair treatments
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Identification <scp>LEF1</scp> as a Potential Novel Biomarker for Abdominal Aortic Aneurysms Based on Comprehensive Bioinformatics Analysis — Hanshen Luo, Xinyi Liu, et al. · Journal of Cellular and Molecular Medicine (2025) | TGRS Research Map | TGRS