RESUMEN
Aurora Kinase A (AURKA) plays a central role as a serine/threonine kinase in regulating cell cycle progression and mitotic functions. Over the years, extensive research has revealed the multifaceted roles of AURKA in cancer development and progression. AURKA's dysregulation is frequently observed in various human cancers, including hepatocellular carcinoma (HCC). Its overexpression in HCC has been associated with aggressive phenotypes and poor clinical outcomes. This review comprehensively explores the molecular mechanisms underlying AURKA expression in HCC and its functional implications in cell migration, invasion, epithelial-to-mesenchymal transition, metastasis, stemness, and drug resistance. This work focuses on the clinical significance of AURKA as a diagnostic and prognostic biomarker for HCC. High levels of AURKA expression have been correlated with shorter overall and disease-free survival in various cohorts, highlighting its potential utility as a sensitive prognostic indicator. Recent insights into AURKA's role in modulating the tumour microenvironment, particularly immune cell recruitment, may provide valuable information for personalized treatment strategies. AURKA's critical involvement in modulating cellular pathways and its overexpression in cancer makes it an attractive target for anticancer therapies. This review discusses the evidence about novel and selective AURKA inhibitors for more effective treatments for HCC.
RESUMEN
Hepatocellular carcinoma (HCC) is the sixth-most common type of cancer worldwide and chronic Hepatitis C virus (HCV) represents the main etiological factor in developed countries. HCV promotes hepatocarcinogenesis through persistent liver inflammation and dysregulation of cell signaling pathways. The introduction of direct-acting antivirals (DAAs) resulted in a significant improvement in the eradication of the virus, with an expected reduction of HCC incidence. However, the risk of HCC development can persist after DAA treatment. Recent studies have investigated the potential use of molecular biomarkers that predict HCC occurrence or recurrence helping the stratification of patients under surveillance. This review aimed to summarize all pre-clinical exploration of predictive biomarkers to identify DAA-treated patients at risk for HCC development. Dysregulated microRNAs, lncRNAs, histone modifications, cytokines, proteins, and sphingolipids represent various classes of HCC risk predictors identified in two different biological sources (tissue and serum). The non-invasive serum markers can provide a more accessible means to perform clinical monitoring and predict the risk of HCC. In addition, conditions like cirrhosis, predisposing to HCC, strongly correlate with most of the molecular predictors identified, supporting the value of these molecules as possible biomarkers of HCC in DAA-treated patients.
RESUMEN
Background: Hepatic resection, radiofrequency ablation (RF), and liver transplantation (LT) represent the only available curative treatments for early stage hepatocellular carcinoma (HCC). Various studies showed that the 5-year overall survival (OS) rate reaches â¼70% after resection and â¼60% after RF. Objective: To improve the success rate of curative therapies and consequently the OS, an improvement in patients' selection and management should be pursued. In this regard, microRNAs (miRNAs) can be helpful prognostic biomarkers. Materials and Methods: In this retrospective study, a miRNA array profiling was performed on 34 HCC blood samples which is collected before therapy (T0), 1 month (T1), and 6 months (T2) after curative treatments (resection and RF) to identify noninvasive biomarker candidates for therapy response and OS. MiRNAs were validated in 80 blood HCC samples using quantitative real-time PCR (qRT-PCR). Patients were divided into complete responder (CR) and partial responder and progressive disease (PRPD). Results: Among the selected miRNAs, miR-3201 is significantly associated with treatment response in the validation phase, showing a 23% reduction (P = .026) in CR compared to PRPD. MiR-3201 was able to distinguish CR from PRPD (area under the curve [AUC] = 0.69, 71% sensitivity, 70% specificity, P = .0036). Furthermore, lower levels of miR-3201 were associated with longer OS (hazard ratio [HR] = 2.61, P = .0006). Conclusions: Blood miR-3201 could be used as a prognostic biomarker for curative therapy response and OS in HCC.