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  • Network-Based Identification of Paclitaxel-Associated Targets and Regulatory Mechanisms in HER2-Positive Breast Cancer

  • Houra Naraghi,1,* Hamid Latifi-Navid,2 Zahra-Soheila Soheili,3 Ayyoob Arpanaei,4 Mohsen Farhadpour,5
    1. Department of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB)
    2. Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB)
    3. Department of Molecular Medicine, National Institute of Genetic Engineering and Biotechnology (NIGEB)
    4. PhD, Industrial Biotechnology, Department of Industrial and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran/ Scion, 49 Sala Street, Rotorua 3020, New Zealand
    5. PhD, Phytochemistry; Department of Plant Bioproducts, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran


  • Introduction: Breast cancer remains one of the most prevalent malignancies globally, with HER2-positive subtypes characterized by aggressive tumor progression and unfavorable clinical outcomes. Although paclitaxel (PTX) is a cornerstone chemotherapeutic agent for breast cancer, the precise molecular mechanisms governing its therapeutic efficacy remain incompletely understood. This study aimed to identify key molecular targets, biological pathways, and regulatory networks associated with the selected PTX target genes TUBB1, TUBB3 and MAPT as well as MKI67 in HER2-positive breast cancer using a bioinformatics approach.
  • Methods: PTX-associated and breast cancer-related genes were collected from publicly available databases and literature sources. Protein–protein interactions (PPI) and protein-drug interactions were modeled to determine hub genes based on topological parameters. Functional enrichment analyses were performed to explore the biological concepts behind of the identified targets. Gene regulatory networks (GRN) involving transcription factors and microRNAs were also reconstructed to investigate potential regulatory mechanisms.
  • Results: Network analysis is expected to uncover crucial hub genes that intersect with our selected targets, highlighting central mediators of PTX-mediated responses. Functional enrichment analysis is anticipated to reveal significant pathways associated with cell cycle regulation, apoptosis, microtubule organization, DNA damage response, and cancer-related signaling networks. Furthermore, regulatory network analysis is projected to highlight key transcription factors and microRNAs that may contribute to PTX sensitivity and resistance. Collectively, these analyses are estimated to provide a systems-level understanding of the molecular interactions underlying PTX activity in HER2-positive breast cancer.
  • Conclusion: Ultimately, this study shows how computational tools can help unravel complex drug responses. By turning these expected findings into practical insights, this work aims to facilitate the discovery of new treatment targets and drug combinations to improve outcomes in HER2-positive breast cancer.
  • Keywords: HER2-positive breast cancer, Paclitaxel (PTX), Network Analysis, Bioinformatics

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