Kinesins in Bladder Cancer: Integrating Molecular Mechanisms and Treatment Approaches

Usamah Sayed1, Noor Mazin Basheer2, Malathi H3

  • 1Faculty of Allied Medical Sciences, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan.

Insights

Kinesin superfamily proteins (KIFs) drive bladder cancer progression by supporting hallmarks like proliferation and invasion. Targeting these motors offers a promising therapeutic strategy for this challenging disease.

Area of Science:

  • Oncology
  • Molecular Biology
  • Cell Biology

Background:

  • Bladder cancer presents significant challenges due to frequent recurrence and limited therapeutic options.
  • Understanding the underlying molecular defects is crucial for developing effective treatments.
  • Kinesin superfamily proteins (KIFs) are increasingly recognized for their role in cancer development.

Purpose of the Study:

  • To review the current evidence on the role of KIFs in bladder cancer pathogenesis.
  • To highlight specific KIFs (KIF4A, KIF14, KIF20A, KIFC1) as oncogenic drivers and potential therapeutic targets.
  • To explore the prognostic significance of KIFs in bladder cancer.

Main Methods:

  • This review synthesizes existing scientific literature and evidence.
  • Analysis focuses on the function of specific KIFs in cancer hallmarks.
  • Expression levels and clinical correlations are examined.

Main Results:

  • Several KIFs, including KIF4A, KIF14, KIF20A, and KIFC1, are identified as key oncogenic regulators in bladder cancer.
  • KIFs facilitate cancer hallmarks such as proliferation, invasion, metastasis, and chemoresistance.
  • Overexpression of certain KIFs correlates with advanced disease stage and poorer patient survival.

Conclusions:

  • KIFs represent promising prognostic biomarkers and therapeutic targets for bladder cancer.
  • Targeting KIF motor activity may overcome chemoresistance and enhance immunotherapy efficacy.
  • Exploiting cancer cell dependence on KIFs offers a potential clinical application strategy.

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