Hepatocellular carcinoma (HCC) metabolism is redirected to glycolysis to enhance the production of metabolic compounds employed by cancer cells to produce proteins, lipids, and nucleotides in order to maintain a high proliferative rate. This mechanism drives towards uncontrolled growth and causes a further increase in reactive oxygen species (ROS), which could lead to cell death. HCC overcomes the problem generated by ROS increase by increasing the antioxidant machinery, in which key mechanisms involve glutathione, nuclear factor erythroid 2-related factor 2 (Nrf2), and hypoxia-inducible transcription factor (HIF-1α). These mechanisms could represent optimal targets for innovative therapies. The tumor microenvironment (TME) exerts a key role in HCC pathogenesis and progression. Various metabolic machineries modulate the activity of immune cells in the TME. The deregulated metabolic activity of tumor cells could impair antitumor response. Lactic acid–lactate, derived from the anaerobic glycolytic rate of tumor cells, as well as adenosine, derived from the catabolism of ATP, have an immunosuppressive activity. Metabolic reprogramming of the TME via targeted therapies could enhance the treatment efficacy of anti-cancer immunotherapy. This review describes the metabolic pathways mainly involved in the HCC pathogenesis and progression. The potential targets for HCC treatment involved in these pathways are also discussed.

Hepatocellular carcinoma (HCC) is a malignancy characterized by neoangiogenesis that is determined by an augmented production of proangiogenesis factors by tumor and adjacent cells. This unbalanced angiogenesis process is a key feature of HCC carcinogenesis and progression. Proangiogenic factors also have a relevant role in the generation and maintenance of an immunosuppressive tumor microenvironment. Several therapeutic options for HCC treatment are based on the inhibition of angiogenesis, both in the early/intermediate stages of the disease and in the late stages of the disease. Conventional treatment options employing antiangiogenic approaches provide for the starving of tumors of their blood supply to avoid the refueling of oxygen and nutrients. An emerging alternative point of view is the normalization of vasculature leading to enhance tumor perfusion and oxygenation, potentially capable, when proposed in combination with other treatments, to improve delivery and efficacy of other therapies, including immunotherapy with checkpoint inhibitors. The introduction of novel biomarkers can be useful for the definition of the most appropriate dose and scheduling for these combination treatment approaches. The present review provides a wide description of the pharmaceutical compounds with an antiangiogenic effect proposed for HCC treatment and investigated in clinical trials, including antibodies and small-molecule kinase inhibitors.

Hepatocellular carcinoma (HCC) is the second most lethal tumor, with a 5-year survival rate of 18%. Early stage HCC is potentially treatable by therapies with curative intent, whereas chemoembolization/radioembolization and systemic therapies are the only therapeutic options for intermediate or advanced HCC. Drug resistance is a critical obstacle in the treatment of HCC that could be overcome by the use of targeted nanoparticle-based therapies directed towards specific tumor-associated antigens (TAAs) to improve drug delivery. Glypican 3 (GPC3) is a member of the glypican family, heparan sulfate proteoglycans bound to the cell surface via a glycosylphosphatidylinositol anchor. The high levels of GPC3 detected in HCC and the absence or very low levels in normal and non-malignant liver make GPC3 a promising TAA candidate for targeted nanoparticle-based therapies. The use of nanoparticles conjugated with anti-GPC3 agents may improve drug delivery, leading to a reduction in severe side effects caused by chemotherapy and increased drug release at the tumor site. In this review, we describe the main clinical features of HCC and the common treatment approaches. We propose the proteoglycan GPC3 as a useful TAA for targeted therapies. Finally, we describe nanotechnology approaches for anti-GPC3 drug delivery systems based on NPs for HCC treatment.

Pancreatic ductal adenocarcinoma (PDAC) accounts for 90% of all pancreatic cancers, with a 5-year survival rate of 7% and 80% of patients diagnosed with advanced or metastatic malignancies. Despite recent advances in diagnostic testing, surgical techniques, and systemic therapies, there remain limited options for the effective treatment of PDAC. There is an urgent need to develop targeted therapies that are able to differentiate between cancerous and non-cancerous cells to reduce side effects and better inhibit tumor growth. Antibody-targeted strategies are a potentially effective option for introducing innovative therapies. Antibody-based immunotherapies and antibody-conjugated nanoparticle-based targeted therapies with antibodies targeting specific tumor-associated antigens (TAA) can be proposed. In this context, glypican-1 (GPC1), which is highly expressed in PDAC and not expressed or expressed at very low levels in non-malignant lesions and healthy pancreatic tissues, is a useful TAA that can be achieved by a specific antibody-based immunotherapy and antibody-conjugated nanoparticle-based targeted therapy. In this review, we describe the main clinical features of PDAC. We propose the proteoglycan GPC1 as a useful TAA for PDAC-targeted therapies. We also provide a digression on the main developed approaches of antibody-based immunotherapy and antibody-conjugated nanoparticle-based targeted therapy, which can be used to target GPC1.

Although extensive advancements have been made in treatment against hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfied. It is now clearly established that extensive epigenetic changes act as a driver in human tumors. This study exploits HCC epigenetic deregulation to define a novel prognostic model for monitoring the progression of HCC. We analyzed the genome-wide DNA methylation profile of 374 primary tumor specimens using the Illumina 450 K array data from The Cancer Genome Atlas. We initially used a novel combination of Machine Learning algorithms (Recursive Features Selection, Boruta) to capture early tumor progression features. The subsets of probes obtained were used to train and validate Random Forest models to predict a Progression Free Survival greater or less than 6 months. The model based on 34 epigenetic probes showed the best performance, scoring 0.80 accuracy and 0.51 Matthews Correlation Coefficient on testset. Then, we generated and validated a progression signature based on 4 methylation probes capable of stratifying HCC patients at high and low risk of progression. Survival analysis showed that high risk patients are characterized by a poorer progression free survival compared to low risk patients. Moreover, decision curve analysis confirmed the strength of this predictive tool over conventional clinical parameters. Functional enrichment analysis highlighted that high risk patients differentiated themselves by the upregulation of proliferative pathways. Ultimately, we propose the oncogenic MCM2 gene as a methylation-driven gene of which the representative epigenetic markers could serve both as predictive and prognostic markers. Briefly, our work provides several potential HCC progression epigenetic biomarkers as well as a new signature that may enhance patients surveillance and advances in personalized treatment.