Dataset Information


Bioinformatics analysis and experimental validation of TTK as a biomarker for prognosis in non-small cell lung cancer.

ABSTRACT: BACKGROUND:Despite the prominent development of medical technology in recent years, the prognosis of non-small cell lung cancer (NSCLC) is still not optimistic. It is crucial to identify more reliable diagnostic biomarkers for the early diagnosis and personalized therapy of NSCLC and clarify the molecular mechanisms underlying NSCLC progression. METHODS:In the present study, bioinformatics analysis was performed on three datasets obtained from the Gene Expression Omnibus to identify the NSCLC-associated differentially expressed genes (DEGs). Immunohistochemistry-based tissue microarray of human NSCLC was used to experimental validating the potential targets obtained from bioinformatics analysis. RESULTS:By using protein-protein interaction (PPI) network analysis, Kaplan-Meier plotter, and Gene Expression Profiling Interactive Analysis, we selected 40 core DEGs for further study. Then, a re-analysis of 40 selected genes via Kyoto Encyclopedia of Genes and Genomes pathway enrichment showed that nine key genes involved in the cell cycle and p53 signaling pathway participated in the development of NSCLC. Then, we checked the protein level of nine key genes by semi-quantitative of IHC and checked the distribution at a single-cell level. Finally, we validated dual-specificity protein kinase TTK as a biomarker for prognosis in a tissue microarray. High TTK expression associated with a higher histological stage, advanced TNM stage, high frequency of positive lymph nodes, and worse 5-year overall survival. CONCLUSIONS:We found nine key genes were enriched in the cell cycle and p53 signaling pathway. TTK could be considered as a potential therapeutic target and for the prognosis biomarker of NSCLC. These findings will provide new insights for the development of individualized therapeutic targets for NSCLC.


PROVIDER: S-EPMC7538683 | BioStudies | 2020-01-01

REPOSITORIES: biostudies

Similar Datasets

2018-01-01 | S-EPMC5928894 | BioStudies
2018-05-07 | PXD007726 | Pride
2018-01-01 | S-EPMC5790447 | BioStudies
2019-01-01 | S-EPMC6492458 | BioStudies
2020-01-01 | S-EPMC7606241 | BioStudies
2020-01-01 | S-EPMC6908938 | BioStudies
2015-01-01 | S-EPMC4741454 | BioStudies
2017-01-01 | S-EPMC5754439 | BioStudies
2019-01-01 | S-EPMC7235396 | BioStudies
2009-01-01 | S-EPMC2682006 | BioStudies