Analysis of the regulatory mechanisms of prognostic immune factors in thyroid cancer.
1/5 보강
[OBJECTIVE] To explore the regulatory mechanism of immune prognostic factors in thyroid cancer.
APA
Tian Y, Xie T, Sun X (2022). Analysis of the regulatory mechanisms of prognostic immune factors in thyroid cancer.. Frontiers in oncology, 12, 1059591. https://doi.org/10.3389/fonc.2022.1059591
MLA
Tian Y, et al.. "Analysis of the regulatory mechanisms of prognostic immune factors in thyroid cancer.." Frontiers in oncology, vol. 12, 2022, pp. 1059591.
PMID
36591507
Abstract
[OBJECTIVE] To explore the regulatory mechanism of immune prognostic factors in thyroid cancer.
[METHODS] Based on the TCGA database and GEO database, this study used bioinformatics methods to study the potential regulatory mechanism of thyroid cancer prognosis, analyzed the differentially expressed genes and differential miRNAs between thyroid cancer and normal paracancerous tissues by R software, and constructed lasso risk factors. The immune prognostic factors of thyroid cancer were obtained from the model, and the miRDB website was used to predict the possibility of differential miRNA target binding of the immune prognostic factors and correlation analysis was performed, and finally verified by cell experiments.
[RESULTS] There were 1413 differentially expressed genes between thyroid cancer and normal paracancerous tissues, among which 21 immune-related genes were prognostic factors with significant differences in expression; lasso risk model obtained AKAP12, APOC1, TIMP3, ADAMTS9, ANK2, HTRA3, SYNDIG1 , ADAMTS5 and DACT1 were nine prognostic factors. A total of 58 differential miRNAs were found in thyroid cancer tissues and non-cancerous tissues. The possibility of differential miRNA targeting and binding of immune prognostic factors on the miRDB website and cell experiments was analyzed.
[CONCLUSIONS] The potential miRNA regulatory mechanism of immune prognostic factors in thyroid cancer has been explored.
[METHODS] Based on the TCGA database and GEO database, this study used bioinformatics methods to study the potential regulatory mechanism of thyroid cancer prognosis, analyzed the differentially expressed genes and differential miRNAs between thyroid cancer and normal paracancerous tissues by R software, and constructed lasso risk factors. The immune prognostic factors of thyroid cancer were obtained from the model, and the miRDB website was used to predict the possibility of differential miRNA target binding of the immune prognostic factors and correlation analysis was performed, and finally verified by cell experiments.
[RESULTS] There were 1413 differentially expressed genes between thyroid cancer and normal paracancerous tissues, among which 21 immune-related genes were prognostic factors with significant differences in expression; lasso risk model obtained AKAP12, APOC1, TIMP3, ADAMTS9, ANK2, HTRA3, SYNDIG1 , ADAMTS5 and DACT1 were nine prognostic factors. A total of 58 differential miRNAs were found in thyroid cancer tissues and non-cancerous tissues. The possibility of differential miRNA targeting and binding of immune prognostic factors on the miRDB website and cell experiments was analyzed.
[CONCLUSIONS] The potential miRNA regulatory mechanism of immune prognostic factors in thyroid cancer has been explored.
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