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<p>Breast Cancer (BC) is the leading cancer worldwide, and it is heterogeneous utmost importance to understand the molecular mechanisms of breast carcinogenesis to develop early detection biomarkers and therapeutics for BC management. Recent research has highlighted the role of the kinesin-3 family as a marker in breast cancer progression. This study focuses on analysing the expression profiles of KIF14, KIF1A, and KIF1B, key members of the kinesin-3 family, to understand their potential involvement in breast cancer. To achieve the study's objective, we performed expression profiling of these genes at the mRNA level using real-time PCR. Additionally, we have performed in silico validation using online databases and various bioinformatics tools. Our comprehensive analysis reveals significant differential expression patterns of KIF14, KIF1A, and KIF1B at the mRNA level across hormone receptor-positive and hormone receptor-negative breast cancer cell lines. These findings were validated using GEO datasets. Additionally, some of the genes which are involved in the interactions analysed by the PPI network further link them to vital biological processes such as microtubule dynamics, mitosis, and spindle apparatus organisation, as demonstrated by Gene Ontology and KEGG pathway analyses. Kaplan–Meier survival analysis indicates that the expression of these genes are strongly associated with poor survival outcomes in breast cancer patients. Moreover, our investigation into the interaction between chemotherapeutic drugs and these genes suggests that treatment may reduce their expression, highlighting potential pathways to enhance therapeutic strategies. The study demonstrates the potential role of KIF14, KIF1A, and KIF1B in breast cancer carcinogenesis. These findings demonstrate that these genes are significantly overexpressed in breast cancer cell lines, with pronounced upregulation observed in aggressive subtypes. Furthermore, elevated expression of these genes correlates with poor survival outcomes, highlighting their potential role as key biomarkers of disease progression. Consequently, targeting these genes may represent a promising therapeutic strategy to improve prognosis and treatment efficacy in aggressive breast cancer subtypes.</p>

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Bioinformatic analysis of the prognostic value of KIF14, KIF1A, and KIF1B in breast cancer

  • 期刊论文

  • 发表日期：

    2026年3月27日

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  • Shagufta,
  • Mehreen Aftab,
  • Kanu Priya,
  • Showket Hussain

摘要

Breast Cancer (BC) is the leading cancer worldwide, and it is heterogeneous utmost importance to understand the molecular mechanisms of breast carcinogenesis to develop early detection biomarkers and therapeutics for BC management. Recent research has highlighted the role of the kinesin-3 family as a marker in breast cancer progression. This study focuses on analysing the expression profiles of KIF14, KIF1A, and KIF1B, key members of the kinesin-3 family, to understand their potential involvement in breast cancer. To achieve the study's objective, we performed expression profiling of these genes at the mRNA level using real-time PCR. Additionally, we have performed in silico validation using online databases and various bioinformatics tools. Our comprehensive analysis reveals significant differential expression patterns of KIF14, KIF1A, and KIF1B at the mRNA level across hormone receptor-positive and hormone receptor-negative breast cancer cell lines. These findings were validated using GEO datasets. Additionally, some of the genes which are involved in the interactions analysed by the PPI network further link them to vital biological processes such as microtubule dynamics, mitosis, and spindle apparatus organisation, as demonstrated by Gene Ontology and KEGG pathway analyses. Kaplan–Meier survival analysis indicates that the expression of these genes are strongly associated with poor survival outcomes in breast cancer patients. Moreover, our investigation into the interaction between chemotherapeutic drugs and these genes suggests that treatment may reduce their expression, highlighting potential pathways to enhance therapeutic strategies. The study demonstrates the potential role of KIF14, KIF1A, and KIF1B in breast cancer carcinogenesis. These findings demonstrate that these genes are significantly overexpressed in breast cancer cell lines, with pronounced upregulation observed in aggressive subtypes. Furthermore, elevated expression of these genes correlates with poor survival outcomes, highlighting their potential role as key biomarkers of disease progression. Consequently, targeting these genes may represent a promising therapeutic strategy to improve prognosis and treatment efficacy in aggressive breast cancer subtypes.