Ladinin 1 Shortens Survival via Promoting Proliferation and Enhancing Invasiveness in Lung Adenocarcinoma.
Chao-Yuan ChangYung-Chi HuangHung-Hsing ChiangYu-Yuan WuKuan-Li WuYung-Yun ChangLian-Xiu LiuYing-Ming TsaiYa-Ling HsuPublished in: International journal of molecular sciences (2022)
Lung cancer is one of the deadliest cancers worldwide, including in Taiwan. The poor prognosis of the advanced lung cancer lies in delayed diagnosis and non-druggable targets. It is worth paying more attention to these ongoing issues. Public databases and an in-house cohort were used for validation. The KM plotter was utilized to discover the clinical significance. GSEA and GSVA were adopted for a functional pathway survey. Molecular biological methods, including proliferation, migration, and the EMT methods, were used for verification. Based on public databases, the increased expression of Ladinin 1 (LAD1) was presented in tumor and metastatic sites. Furthermore, an in-house cohort revealed a higher intensity of LAD1 in tumor rather than in normal parts. The greater the expression of LAD1 was, the shorter the duration of lung adenocarcinoma (LUAD) patient survival. Moreover, the association of B3GNT3 with LAD1 affected the survival of LUAD patients. Functional analyses using GSEA and GSVA revealed the associations with survival, migration, invasion, and EMT. Biologic functions supported the roles of LAD1 in proliferation via the cell cycle and migration in EMT. This study reveals that LAD1 plays a major role in regulating proliferation and migration in lung cancer and impacts survival in LUAD. It is worth investing in further studies and in the development of drugs targeting LAD1.
Keyphrases
- poor prognosis
- cell cycle
- long non coding rna
- epithelial mesenchymal transition
- free survival
- signaling pathway
- end stage renal disease
- healthcare
- chronic kidney disease
- small cell lung cancer
- rheumatoid arthritis
- cell proliferation
- squamous cell carcinoma
- newly diagnosed
- single cell
- emergency department
- cross sectional
- machine learning
- drug delivery
- cell migration
- artificial intelligence
- patient reported
- patient reported outcomes
- electronic health record
- adverse drug