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<p>Cervical cancer (CC), a leading cause of death in women, is a preventable disease prevalent in low- or middle-income countries due to fewer vaccination strategies against human papillomavirus (HPV). Our review highlights the roles of key signaling cascades in HPV-driven cervical carcinogenesis, including the phosphoinositide 3 kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR), Wnt/β-catenin, Janus kinase/ Signal Transducer and Activator of Transcription (JAK/STAT), C-X-C motif chemokine ligand 12/ C-X-C chemokine receptor type 4, ferroptosis, and Activator Protein-1 pathways. The relationship between HPV E7 and Histone Deacetylases (HDAC) contributes to immune evasion and oncogenesis in CC, underscoring the potential of HDAC inhibitors, including synthetic and natural ones, as targeted treatment alternatives. We further summarize the therapeutic potential and translational obstacles of small-molecule inhibitors (SMIs) that target diverse oncogenic drivers in CC, such as Lysyl oxidase-like 2, HPV oncoproteins, Murine Double Minute X, DNA Methyltransferases, Glutathione Peroxidase 4, JAK/STAT, topoisomerases, etc. There have been promising advances in targeting these molecules, demonstrating their potential to improve tumor growth, apoptosis, and resistance mechanisms. The potential of SMIs to change therapy tactics for advanced CC is highlighted by their inclusion into clinical trials, particularly those targeting B lymphoma Mo-MLV insertion region 1 homolog, Nuclear receptor-binding SET domain protein 2, and angiogenesis. Proteomic signatures, circRNAs, p16, HPV DNA, and DNA methylation patterns are among the emerging molecular biomarkers that are shaping targeted therapy and early detection methods for CC. In addition, this review also discusses bioinformatics and artificial intelligence (AI) approaches, including deep learning algorithms and omics-based analyses, which offer powerful tools for identifying CC biomarkers, facilitating rapid detection, and informing personalized treatment plans. Although resistance and heterogeneity are still problems, emerging precision medicine approaches are reshaping the way CC is controlled. These include the use of SMIs and innovative biomarkers.</p>

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Pathways to precision medicine in cervical cancer: a comprehensive review of small molecule inhibitors, biomarkers and computational approaches

  • 期刊论文

  • 发表日期：

    2025年10月15日

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  • Nandini Purohit,
  • Yajushi Mishra,
  • Poonampriya Hazarika,
  • Abilash Valsala Gopalakrishnan,
  • Reshma Murali

摘要

Cervical cancer (CC), a leading cause of death in women, is a preventable disease prevalent in low- or middle-income countries due to fewer vaccination strategies against human papillomavirus (HPV). Our review highlights the roles of key signaling cascades in HPV-driven cervical carcinogenesis, including the phosphoinositide 3 kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR), Wnt/β-catenin, Janus kinase/ Signal Transducer and Activator of Transcription (JAK/STAT), C-X-C motif chemokine ligand 12/ C-X-C chemokine receptor type 4, ferroptosis, and Activator Protein-1 pathways. The relationship between HPV E7 and Histone Deacetylases (HDAC) contributes to immune evasion and oncogenesis in CC, underscoring the potential of HDAC inhibitors, including synthetic and natural ones, as targeted treatment alternatives. We further summarize the therapeutic potential and translational obstacles of small-molecule inhibitors (SMIs) that target diverse oncogenic drivers in CC, such as Lysyl oxidase-like 2, HPV oncoproteins, Murine Double Minute X, DNA Methyltransferases, Glutathione Peroxidase 4, JAK/STAT, topoisomerases, etc. There have been promising advances in targeting these molecules, demonstrating their potential to improve tumor growth, apoptosis, and resistance mechanisms. The potential of SMIs to change therapy tactics for advanced CC is highlighted by their inclusion into clinical trials, particularly those targeting B lymphoma Mo-MLV insertion region 1 homolog, Nuclear receptor-binding SET domain protein 2, and angiogenesis. Proteomic signatures, circRNAs, p16, HPV DNA, and DNA methylation patterns are among the emerging molecular biomarkers that are shaping targeted therapy and early detection methods for CC. In addition, this review also discusses bioinformatics and artificial intelligence (AI) approaches, including deep learning algorithms and omics-based analyses, which offer powerful tools for identifying CC biomarkers, facilitating rapid detection, and informing personalized treatment plans. Although resistance and heterogeneity are still problems, emerging precision medicine approaches are reshaping the way CC is controlled. These include the use of SMIs and innovative biomarkers.