Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer.

BACKGROUND

Kinesin superfamily (KIFs) has a long-reported significant influence on the initiation, development, and progress of breast cancer. However, the prognostic value of whole family members was poorly done. Our study intends to demonstrate the value of kinesin superfamily members as prognostic biomarkers as well as a therapeutic target of breast cancer.

METHODS

Comprehensive bioinformatics analyses were done using data from TCGA, GEO, METABRIC, and GTEx. LASSO regression was done to select tumor-related members. Nomogram was constructed to predict the overall survival (OS) of breast cancer patients. Expression profiles were testified by quantitative RT-PCR and immunohistochemistry. Transcription factor, GO and KEGG enrichments were done to explore regulatory mechanism and functions.

RESULTS

A total of 20 differentially expressed KIFs were identified between breast cancer and normal tissue with 4 (KIF17, KIF26A, KIF7, KIFC3) downregulated and 16 (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF20B, KIF22, KIF23, KIF24, KIF26B, KIF2C, KIF3B, KIF4A, KIFC1) overexpressed. Among which, 11 overexpressed KIFs (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF23, KIF2C, KIF4A, KIFC1) significantly correlated with worse OS, relapse-free survival (RFS) and distant metastasis-free survival (DMFS) of breast cancer. A 6-KIFs-based risk score (KIF10, KIF15, KIF18A, KIF18B, KIF20A, KIF4A) was generated by LASSO regression with a nomogram validated an accurate predictive efficacy. Both mRNA and protein expression of KIFs are experimentally demonstrated upregulated in breast cancer patients. Msh Homeobox 1 (MSX1) was identified as transcription factors of KIFs in breast cancer. GO and KEGG enrichments revealed functions and pathways affected in breast cancer.

CONCLUSION

Overexpression of tumor-related KIFs correlate with worse outcomes of breast cancer patients and can work as potential prognostic biomarkers.