ArticleJournal of thoracic disease2019
The Cancer Genome Atlas dataset-based analysis of aberrantly expressed genes by GeneAnalytics in thymoma associated myasthenia gravis: focusing on T cells.
Article in Journal of thoracic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- The Molecular Landscape of Thymic Epithelial Tumors: A Comprehensive Review.International journal of molecular sciences · 2024Review
- DCAF12 and HSPA1A May Serve as Potential Diagnostic Biomarkers for Myasthenia Gravis.BioMed research international · 2022Article
- Identification of Molecular Characteristics and New Prognostic Targets for Thymoma by Multiomics Analysis.BioMed research international · 2021Article
- Autoimmune disorders and paraneoplastic syndromes in thymoma.Journal of thoracic disease · 2020Review
- Pathology of thymoma-where are we today?Journal of thoracic disease · 2020Review
- Correlation of genomic alterations and PD-L1 expression in thymoma.Journal of thoracic disease · 2020Review
- Investigation of BTLA tagging variants with risk of esophagogastric junction adenocarcinoma.Bioscience reports · 2019Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMyasthenia gravis (MG) is a group of autoimmune disease which could be accompanied by thymoma. Many differences have been observed between thymoma-associated MG (TAMG) and non-MG thymoma (NMG). However, the molecular difference between them remained unknown. This study aimed to explore the differentially expressed genes (DEGs) between the two categories and to elucidate the possible pathogenesis of TAMG further.
methodsDEGs were calculated using the RNA-Sequencing data from 11 TAMG and 10 NMG in The Cancer Genome Atlas (TCGA) database. GeneAnalytics was performed to characterize the associations between DEGs and tissues and cells, diseases, gene ontology (GO) terms, pathways, phenotypes, and drug/compounds, respectively. Genes related to T cells were sorted out using LifeMapDiscovery Cells and Tissues Database. Genes directly related to the phenotype of autoimmune diseases that were identified by VarElect were validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).
resultsThe expression level of 169 genes showed a significant difference between the two groups, with 94 up-regulated and 75 down-regulated. Overexpression of six genes (
conclusionsOverexpression of sBTLA, CCR7, TNFRSF25 and ANKRD55 was identified and validated by RT-qPCR, which could partly explain the underlying pathogenesis in TAMG.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.