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Elucidating the role of TWIST1 in ulcerative colitis: a comprehensive bioinformatics and machine learning approach.
Ou, Wenjie; Qi, Zhaoxue; Liu, Ning; Zhang, Junzi; Mi, Xuguang; Song, Yuan; Fang, Yanqiu; Cui, Baiying; Hou, Junjie; Yuan, Zhixin.
Afiliación
  • Ou W; School of Clinical Medicine, Changchun University of Chinese Medicine, Changchun, Jilin, China.
  • Qi Z; Department of Secretory Metabolism, The First Hospital of Jilin University, Changchun, Jilin, China.
  • Liu N; General Surgery of The First Clinical Hospital of Jilin Academy of Chinese Medicine Sciences, Changchun, Jilin, China.
  • Zhang J; School of Clinical Medicine, Changchun University of Chinese Medicine, Changchun, Jilin, China.
  • Mi X; Department of Central Laboratory, Jilin Provincial People's Hospital, Changchun, Jilin, China.
  • Song Y; Department of Gastroenterology, Jilin Provincial People's Hospital, Changchun, Jilin, China.
  • Fang Y; Department of Central Laboratory, Jilin Provincial People's Hospital, Changchun, Jilin, China.
  • Cui B; School of Clinical Medicine, Changchun University of Chinese Medicine, Changchun, Jilin, China.
  • Hou J; Department of Comprehensive Oncology, Jilin Provincial People's Hospital, Changchun, Jilin, China.
  • Yuan Z; Department of Emergency Surgery, Jilin Provincial People's Hospital, Changchun, Jilin, China.
Front Genet ; 15: 1296570, 2024.
Article en En | MEDLINE | ID: mdl-38510272
ABSTRACT

Background:

Ulcerative colitis (UC) is a common and progressive inflammatory bowel disease primarily affecting the colon and rectum. Prolonged inflammation can lead to colitis-associated colorectal cancer (CAC). While the exact cause of UC remains unknown, this study aims to investigate the role of the TWIST1 gene in UC.

Methods:

Second-generation sequencing data from adult UC patients were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and characteristic genes were selected using machine learning and Lasso regression. The Receiver Operating Characteristic (ROC) curve assessed TWIST1's potential as a diagnostic factor (AUC score). Enriched pathways were analyzed, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). Functional mechanisms of marker genes were predicted, considering immune cell infiltration and the competing endogenous RNA (ceRNA) network.

Results:

We found 530 DEGs, with 341 upregulated and 189 downregulated genes. TWIST1 emerged as one of four potential UC biomarkers via machine learning. TWIST1 expression significantly differed in two datasets, GSE193677 and GSE83687, suggesting its diagnostic potential (AUC = 0.717 in GSE193677, AUC = 0.897 in GSE83687). Enrichment analysis indicated DEGs associated with TWIST1 were involved in processes like leukocyte migration, humoral immune response, and cell chemotaxis. Immune cell infiltration analysis revealed higher rates of M0 macrophages and resting NK cells in the high TWIST1 expression group, while TWIST1 expression correlated positively with M2 macrophages and resting NK cell infiltration. We constructed a ceRNA regulatory network involving 1 mRNA, 7 miRNAs, and 32 long non-coding RNAs (lncRNAs) to explore TWIST1's regulatory mechanism.

Conclusion:

TWIST1 plays a significant role in UC and has potential as a diagnostic marker. This study sheds light on UC's molecular mechanisms and underscores TWIST1's importance in its progression. Further research is needed to validate these findings in diverse populations and investigate TWIST1 as a therapeutic target in UC.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza