Thomas Skutella

Integrated Analysis, Machine Learning, Molecular Docking and Dynamics of CDK1 Inhibitors in Epithelial Ovarian Cancer: A Multifaceted Approach Towards Targeted Therapy

Epithelial ovarian cancer (EOC) remains one of the deadliest gynecologic malignancies, largely due to late diagnosis and treatment resistance. The main objective of this study is to identify and validate CDK1 as a high-confidence therapeutic target in EOC and to assess the dual-target inhibitory potential of the natural compound Naringin against both CDK1 and its regulator WEE1. This study employed an integrative pipeline combining transcriptomic profiling, protein–protein interaction network analysis, machine learning, and molecular simulations to identify key oncogenic regulators in EOC. CDK1 emerged as a central hub gene, exhibiting strong association with poor prognosis and signaling convergence. CDK1 overexpression correlated with adverse survival outcomes and robust involvement in critical oncogenic pathways. Molecular docking and dynamics simulations assessed the binding efficacy of seven compounds with CDK1 and WEE1, with Naringin showing high-affinity binding, stable complex formation, and minimal predicted toxicity. This study underscores the power of computational-experimental integration in accelerating oncology drug discovery, providing visual and quantitative evidence that systematically connect the study’s aim to its findings.

HPV-Driven Immune Evasion in Cervical Cancer: Transcriptomic Identification of Downregulated Hub Genes and Suppressed Leukocyte Migration Pathways

Cervical cancer progression, particularly in the context of HPV infection, is driven by complex transcriptional alterations within the tumor microenvironment. Understanding the molecular mechanisms underlying HPV-induced immune evasion is crucial for developing effective therapeutic strategies. Transcriptomic analyses were performed using three independent datasets (GSE127265, GSE166466, and GSE218460) to identify differentially expressed genes (DEGs) between HPV-positive and HPV-negative cervical cancer samples. Protein–protein interaction networks were constructed using Cytoscape and STRING, and immune infiltration was assessed via the TIMER database. A total of 572 DEGs were commonly identified between tumor and normal tissues, with HPV-positive samples showing distinct transcriptional profiles. Several downregulated hub genes were associated with immune regulation and receptor tyrosine kinase signaling. Immune infiltration analysis revealed altered dendritic cell and T cell patterns, indicating HPV-mediated immune modulation. Pathway enrichment identified the leukocyte transendothelial migration pathway as a key mechanism impaired by HPV infection. These findings highlight the critical role of immune-related hub genes in HPV-driven cervical cancer progression and suggest potential therapeutic targets to counteract HPV-induced immune suppression.