Altered threonine tyrosine kinase (TTK) expression is associated with adverse clinical outcomes in breast tumors: An in silico approach

Authors

DOI:

https://doi.org/10.33448/rsd-v12i13.44285

Keywords:

Biomarkers; Breast Neoplasms; Computational biology.

Abstract

The most common and lethal malignancy in women on a global scale remains breast cancer. Threonine tyrosine kinase (TTK) has been shown to be a critical mitotic spindle assembly checkpoint (SAC) molecule, resulting in correct chromosome segregation and maintenance of genomic stability. Therefore, the present study was carried out to evaluate the expression pattern of threonine tyrosine kinase (TTK) in breast cancer and its potential prognostic and predictive value for therapeutic response using bioinformatics tools. Web platforms containing clinical information and cDNA microarray data were selected to perform in silico analyzes of the potential threonine tyrosine kinase (TTK) marker. The threonine tyrosine kinase (TTK) gene was found to be differentially expressed in tumor samples when compared to healthy breast tissue samples (p<0.0001) and the TNBC subtype exhibited the highest expression of threonine tyrosine kinase (TTK) relative to the other subtypes (p<0.0001). Furthermore, Kaplan-Meier curves revealed that high threonine tyrosine kinase (TTK) levels corresponded to an unfavorable outcome for overall survival (p<0.0001), as well as for recurrence-free survival (p<0.0001) and distant metastasis-free survival (p<0.0001). Finally, differential expression of threonine tyrosine kinase (TTK) was related to the response of breast cancer patients to different therapies. Our cumulative results demonstrate that threonine tyrosine kinase (TTK) may be a promising biomarker for predicting prognosis and therapeutic response in breast cancer patients.

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Published

27/11/2023

How to Cite

SILVA, G. B. R. da .; CRUZ, B. S. .; VIEIRA, J. G. .; UZUM, J. M. .; NASCIMENTO, R. G. do .; PEREIRA, G. J. V. . Altered threonine tyrosine kinase (TTK) expression is associated with adverse clinical outcomes in breast tumors: An in silico approach. Research, Society and Development, [S. l.], v. 12, n. 13, p. e40121344285, 2023. DOI: 10.33448/rsd-v12i13.44285. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/44285. Acesso em: 16 may. 2024.

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Health Sciences