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Bioinformatic and Experimental Analyses Reveal That KIF4A Is a Biomarker of Therapeutic Sensitivity and Predicts Prognosis in Cervical Cancer Patients

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Abstract

Objective

This study aims to investigate the expression, prognostic value, and function of kinesin superfamily 4A (KIF4A) in cervical cancer.

Methods

Cervical cancer cell lines (Hela and SiHa) and TCGA data were used for experimental and bioinformatic analyses. Overall survival (OS) and progression free survival (PFS) were compared between patients with high or low KIF4A expression. Copy number variation (CNV) and somatic mutations of patients were visualized and GISTIC 2.0 was used to identify significantly altered sites. The function of KIF4A was also explored based on transcriptome analysis and validated by experimental methods. Chemotherapeutic and immunotherapeutic benefits were inferred using multiple reference databases and algorithms.

Results

Patients with high KIF4A expression had better OS and PFS. KIF4A could inhibit proliferation and migration and induce G1 arrest of cervical cancer cells. Higher CNV load was observed in patients with low KIF4A expression, while the group with low KIF4A expression displayed more significantly altered sites. A total of 13 genes were found to mutate more in the low KIF4A expression group, including NOTCH1 and PUM1. The analysis revealed that low KIF4A expression may indicate an immune escape phenotype, and patients in this group may benefit more from immunotherapy. With respect to chemotherapy, cisplatin and gemcitabine may respond better in patients with high KIF4A expression, while 5-fluorouracil etc. may be responded better in patients with low KIF4A expression

Conclusion

KIF4A is a tumor suppressor gene in cervical cancer, and it can be used as a prognostic and therapeutic biomarker in cervical cancer.

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Author notes

  1. The authors contributed equally to this work.

Authors and Affiliations

  1. Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430030, China

    Jie Wu, Lan Li, Hao Zhong, Hao-han Zhang, Jing Li, Hui-bo Zhang, Ya-qi Zhao, Bin Xu & Qi-bin Song

  2. Department of Bioinformatics, Wissenschaftszentrum Weihenstephan, Technical University of Munich, Freising, 85354, Germany

    Hui-bo Zhang

Authors
  1. Jie Wu
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  2. Lan Li
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  3. Hao Zhong
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  4. Hao-han Zhang
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  5. Jing Li
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  6. Hui-bo Zhang
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  7. Ya-qi Zhao
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  8. Bin Xu
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  9. Qi-bin Song
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Corresponding authors

Correspondence to Bin Xu or Qi-bin Song.

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The authors declare no conflicts of interest.

Additional information

This work was supported by grants from Wuhan University Medical Faculty Innovation Seed Fund Cultivation Project (No. TFZZ2018025), Xiao-ping CHEN Foundation for the Development of Science and Technology of Hubei Province (No. CXPJJH12000001-2020313) and the National Natural Science Foundation of China (No. 81670123 and No. 81670144).

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Wu, J., Li, L., Zhong, H. et al. Bioinformatic and Experimental Analyses Reveal That KIF4A Is a Biomarker of Therapeutic Sensitivity and Predicts Prognosis in Cervical Cancer Patients. CURR MED SCI 42, 1273–1284 (2022). https://doi.org/10.1007/s11596-022-2636-y

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  • DOI: https://doi.org/10.1007/s11596-022-2636-y

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