Kaiso Protein Expression Correlates with Overall Survival in TNBC Patients.
Artur BocianPiotr KędzierawskiJanusz KopczyńskiOlga WabikAnna WawruszakMichał KiełbusPaulina MiziakAndrzej StepulakPublished in: Journal of clinical medicine (2023)
Triple-negative breast cancers (TNBCs) are histologically heterogenic invasive carcinomas of no specific type that lack distinctive histological characteristics. The prognosis for women with TNBC is poor. Regardless of the applied treatments, recurrences and deaths are observed 3-5 years after the diagnosis. Thus, new diagnostic markers and targets for personalized treatment are needed. The subject of our study-the Kaiso transcription factor has been found to correlate with the invasion and progression of breast cancer. The publicly available TCGA breast cancer cohort containing Illumina HiSeq RNAseq and clinical data was explored in the study. Additionally, Kaiso protein expression was assessed in formalin-fixed and paraffin-embedded tissue archive specimens using the tissue microarray technique. In this retrospective study, Kaiso protein expression (nuclear localization) was compared with several clinical factors in the cohort of 103 patients with TNBC with long follow-up time. In univariate and multivariate analysis, high Kaiso protein but not mRNA expression was correlated with better overall survival and disease-free survival, as well as with premenopausal age. The use of radiotherapy was correlated with better disease-free survival (DFS) and overall survival (OS). However, given the heterogeneity of TNBC and context-dependent molecular diversity of Kaiso signaling in cancer progression, these results must be taken with caution and require further studies.
Keyphrases
- free survival
- transcription factor
- end stage renal disease
- early stage
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- radiation therapy
- squamous cell carcinoma
- postmenopausal women
- peritoneal dialysis
- papillary thyroid
- childhood cancer
- machine learning
- big data
- small molecule
- cell migration
- deep learning
- rectal cancer
- binding protein
- locally advanced
- smoking cessation
- protein protein