HPV as a Molecular Hacker: Computational Exploration of HPV-Driven Changes in Host Regulatory Networks

HPV病毒作为分子黑客:HPV驱动的宿主调控网络变化的计算探索

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Abstract

Human Papillomavirus (HPV), particularly high-risk strains such as HPV16 and HPV18, is a leading cause of cervical cancer and a significant risk factor for several other epithelial malignancies. While the oncogenic mechanisms of viral proteins E6 and E7 are well characterized, the broader effects of HPV infection on host transcriptional regulation remain less clearly defined. This study explores the hypothesis that conserved genomic motifs within the HPV genome may act as molecular decoys, sequestering human transcription factors (TFs) and thereby disrupting normal gene regulation in host cells. Such interactions could contribute to oncogenesis by altering the transcriptional landscape and promoting malignant transformation.We conducted a computational analysis of the genomes of high-risk HPV types using MEME-ChIP for de novo motif discovery, followed by Tomtom for identifying matching human TFs. Protein-protein interactions among the predicted TFs were examined using STRING, and biological pathway enrichment was performed with Enrichr. The analysis identified conserved viral motifs with the potential to interact with host transcription factors (TFs), notably those from the FOX, HOX, and NFAT families, as well as various zinc finger proteins. Among these, SMARCA1, DUX4, and CDX1 were not previously associated with HPV-driven cell transformation. Pathway enrichment analysis revealed involvement in several key biological processes, including modulation of Wnt signaling pathways, transcriptional misregulation associated with cancer, and chromatin remodeling. These findings highlight the multifaceted strategies by which HPV may influence host cellular functions and contribute to pathogenesis. In this context, the study underscores the power of in silico approaches for elucidating viral-host interactions and reveals promising therapeutic targets in computationally predicted regulatory network changes.

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