RESUMEN
The development of cancer is influenced by several variables, including altered protein expression, and signaling pathways. Cancers are inherently heterogeneous and exhibit genetic and epigenetic aberrations; therefore, developing therapies that act on numerous biological targets is encouraged. To achieve this, two approaches are employed: combination therapy and dual/multiple targeting chemotherapeutics. Two enzymes, histone deacetylases (HDACs) and ribonucleotide reductase (RR), are crucial for several biological functions, including replication and repair of DNA, division of cells, transcription of genes, etc. However, it has been noted that different cancers exhibit abnormal functions of these enzymes. Potent inhibitors for each of these proteins have been extensively researched. Many medications based on these inhibitors have been successfully food and drug administration (FDA) approved, and the majority are undergoing various stages of clinical testing. This review discusses various studies of HDAC and RR inhibitors in combination therapy and dual-targeting chemotherapeutics.
Asunto(s)
Neoplasias , Ribonucleótido Reductasas , Humanos , Ribonucleótido Reductasas/uso terapéutico , Histona Desacetilasas/metabolismo , Inhibidores de Histona Desacetilasas/farmacología , Inhibidores de Histona Desacetilasas/uso terapéutico , Neoplasias/genéticaRESUMEN
INTRODUCTION: Critical issues in the therapeutic management of cervical cancer (CC) include therapy resistance and treatment failure. The development of therapy resistance is a multifaceted, progressive process, including genetic and epigenetic abnormalities. The present study aimed to identify genes that may contribute to therapy resistance in CC. MATERIALS AND METHODS: We have created an extensive list of the genes in cancer that are therapy-resistant using a text-mining approach. The list was compared with the TCGA-CESC dataset to identify the differentially expressed therapy resistance genes (DETRGs) in CC. We used online resources (UALCAN, DNMIVD, cBio- Portal, HCMDB, OncoDB, ShinyGO, HPA, KM Plotter, TIMER, and DGIdb) to determine the potential association between methylation and expression of therapy resistance genes with the prognosis and clinical outcomes in CC. RESULTS: The systematic analysis identified 71 out of 91 DETRGs showed aberrant DNA methylation. The overlapping analysis identified 25 genes to show an inverse correlation between methylation and expression. Further, differential expression or methylation could be helpful in CC staging, HPV association, prediction of metastasis and prognosis. The study identified seven driver genes in CC. The PPIN identifies ten hub genes (HGs) associated with CC staging, cancer hallmarks, and prognosis to affect long-term survival. CONCLUSION: Our thorough investigation uncovered several novel genes and pathways that might contribute to therapy resistance in CC. The genes identified in our study may serve as a biomarker, prognostic indicator, and therapeutic target in CC.