ArticleBioMed research international2021
Identification of Molecular Characteristics and New Prognostic Targets for Thymoma by Multiomics Analysis.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Molecular profiling of rare thymoma using next-generation sequencing: meta-analysis.Radiology and oncology · 2023Pooled it
- Amyloid A Amyloidosis Secondary to Thymoma.Diagnostics (Basel, Switzerland) · 2025Article
- Non-Mutational Key Features in the Biology of Thymomas.Cancers · 2024Review
- The Molecular Landscape of Thymic Epithelial Tumors: A Comprehensive Review.International journal of molecular sciences · 2024Review
- Thymoma: An Overview.Diagnostics (Basel, Switzerland) · 2023Review
- Epigenetics of Thymic Epithelial Tumors.Cancers · 2023Review
- An unusual ectopic thymoma clonal evolution analysis: A case report.Open life sciences · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThymoma is a heterogeneous tumor originated from thymic epithelial cells. The molecular mechanism of thymoma remains unclear.
methodsThe expression profile, methylation, and mutation data of thymoma were obtained from TCGA database. The coexpression network was constructed using the variance of gene expression through WGCNA. Enrichment analysis using clusterProfiler R package and overall survival (OS) analysis by Kaplan-Meier method were carried out for the intersection of differential expression genes (DEGs) screened by limma R package and important module genes. PPI network was constructed based on STRING database for genes with significant impact on survival. The impact of key genes on the prognosis of thymoma was evaluated by ROC curve and Cox regression model. Finally, the immune cell infiltration, methylation modification, and gene mutation were calculated.
resultsWe obtained eleven coexpression modules, and three of them were higher positively correlated with thymoma. DEGs in these three modules mainly involved in MAPK cascade and PPAR pathway. LIPE, MYH6, ACTG2, KLF4, SULT4A1, and TF were identified as key genes through the PPI network. AUC values of LIPE were the highest. Cox regression analysis showed that low expression of LIPE was a prognostic risk factor for thymoma. In addition, there was a high correlation between LIPE and T cells. Importantly, the expression of LIPE was modified by methylation. Among all the mutated genes, GTF2I had the highest mutation frequency.
conclusionThese results suggested that the molecular mechanism of thymoma may be related to immune inflammation. LIPE may be the key genes affecting prognosis of thymoma. Our findings will help to elucidate the pathogenesis and therapeutic targets of thymoma.
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