Search

Multiple myeloma (MM) is an incurable hematological disease characterized by the uncontrolled growth of plasma cells primarily in the bone marrow. Although its treatment consists of the administration of combined therapy regimens mainly based on immunomodulators and proteosome inhibitors, MM remains incurable, and most patients suffer from relapsed/refractory disease with poor prognosis and survival. The robust results achieved by immunotherapy targeting MM-associated antigens CD38 and CD319 (also known as SLAMF7) have drawn attention to the development of new immune-based strategies and different innovative compounds in the treatment of MM, including new monoclonal antibodies, antibody-drug conjugates, recombinant proteins, synthetic peptides, and adaptive cellular therapies. In this context, Syndecan1 (CD138 or SDC1), a transmembrane heparan sulfate proteoglycan that is upregulated in malignant plasma cells, has gained increasing attention in the panorama of MM target antigens, since its key role in MM tumorigenesis, progression and aggressiveness has been largely reported. Here, our aim is to provide an overview of the most important aspects of MM disease and to investigate the molecular functions of CD138 in physiologic and malignant cell states. In addition, we will shed light on the CD138-based therapeutic approaches currently being tested in preclinical and/or clinical phases in MM and discuss their properties, mechanisms of action and clinical applications.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers with a very low survival rate at 5 years. The use of chemotherapeutic agents results in only modest prolongation of survival and is generally associated with the occurrence of toxicity effects. Antibody-based immunotherapy has been proposed for the treatment of PDAC, but its efficacy has so far proved limited. The proteoglycan glypican-1 (GPC1) may be a useful immunotherapeutic target because it is highly expressed on the surface of PDAC cells, whereas it is not expressed or is expressed at very low levels in benign neoplastic lesions, chronic pancreatitis, and normal adult tissues. Here, we developed and characterized a specific mouse IgM antibody (AT101) targeting GPC1. Methods We developed a mouse monoclonal antibody of the IgM class directed against an epitope of GPC1 in close proximity to the cell membrane. For this purpose, a 46 amino acid long peptide of the C-terminal region was used to immunize mice by an in-vivo electroporation protocol followed by serum titer and hybridoma formation. Results The ability of AT101 to bind the GPC1 protein was demonstrated by ELISA, and by flow cytometry and immunofluorescence analysis in the GPC1-expressing "PDAC-like" BXPC3 cell line. In-vivo experiments in the BXPC3 xenograft model showed that AT101 was able to bind GPC1 on the cell surface and accumulate in the BXPC3 tumor masses. Ex-vivo analyses of BXPC3 tumor masses showed that AT101 was able to recruit immunological effectors (complement system components, NK cells, macrophages) to the tumor site and damage PDAC tumor tissue. In-vivo treatment with AT101 reduced tumor growth and prolonged survival of mice with BXPC3 tumor (p

Abstract Background Nanoparticles represent one of the most important innovations in the medical field. Among nanocarriers, polymeric nanoparticles (PNPs) attracted much attention due to their biodegradability, biocompatibility, and capacity to increase efficacy and safety of encapsulated drugs. Another important improvement in the use of nanoparticles as delivery systems is the conjugation of a targeting agent that enables the nanoparticles to accumulate in a specific tissue. Despite these advantages, the clinical translation of therapeutic approaches based on nanoparticles is prevented by their interactions with blood proteins. In fact, the so-formed protein corona (PC) drastically alters the biological identity of the particles. Adsorbed activated proteins of the complement cascade play a pivotal role in the clearance of nanoparticles, making them more easily recognized by macrophages, leading to their rapid elimination from the bloodstream and limiting their efficacy. Since the mouse is the most used preclinical model for human disease, this work compared human and mouse PC formed on untargeted PNPs (uPNPs) and targeted PNPs (tPNPs), paying particular attention to complement activation. Results Mouse and human serum proteins adsorbed differently to PNPs. The differences in the binding of mouse complement proteins are minimal, whereas human complement components strongly distinguish the two particles. This is probably due to the human origin of the Fc portion of the antibody used as targeting agent on tPNPs. tPNPs and uPNPs mainly activate complement via the classical and alternative pathways, respectively, but this pattern did not affect their binding and internalization in macrophages and only a limited consumption of the activity of the human complement system was documented. Conclusions The results clearly indicate the presence of complement proteins on PNPs surface but partially derived from an unspecific deposition rather than an effective complement activation. The presence of a targeting antibody favors the activation of the classical pathway, but its absence allows an increased activation of the alternative pathway. This results in similar opsonization of both PNPs and similar phagocytosis by macrophages, without an impairment of the activity of circulating complement system and, consequently, not enhancing the susceptibility to infection. Graphical abstract

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover hidden patterns from complex NGS data and to solve various PGx problems. In this review, we provide a comprehensive overview of the NGS approaches that can be employed and the different PGx studies implicating the use of NGS data. We also provide an excursus of the ML algorithms that can exert a role as fundamental strategies in the PGx field to improve personalized medicine in cancer.

Abstract Background Glioma grade 4 (GG4) tumors, including astrocytoma IDH-mutant grade 4 and the astrocytoma IDH wt are the most common and aggressive primary tumors of the central nervous system. Surgery followed by Stupp protocol still remains the first-line treatment in GG4 tumors. Although Stupp combination can prolong survival, prognosis of treated adult patients with GG4 still remains unfavorable. The introduction of innovative multi-parametric prognostic models may allow refinement of prognosis of these patients. Here, Machine Learning (ML) was applied to investigate the contribution in predicting overall survival (OS) of different available data (e.g. clinical data, radiological data, or panel-based sequencing data such as presence of somatic mutations and amplification) in a mono-institutional GG4 cohort. Methods By next-generation sequencing, using a panel of 523 genes, we performed analysis of copy number variations and of types and distribution of nonsynonymous mutations in 102 cases including 39 carmustine wafer (CW) treated cases. We also calculated tumor mutational burden (TMB). ML was applied using eXtreme Gradient Boosting for survival (XGBoost-Surv) to integrate clinical and radiological information with genomic data. Results By ML modeling (concordance (c)- index = 0.682 for the best model), the role of predicting OS of radiological parameters including extent of resection, preoperative volume and residual volume was confirmed. An association between CW application and longer OS was also showed. Regarding gene mutations, a role in predicting OS was defined for mutations of BRAF and of other genes involved in the PI3K-AKT-mTOR signaling pathway. Moreover, an association between high TMB and shorter OS was suggested. Consistently, when a cutoff of 1.7 mutations/megabase was applied, cases with higher TMB showed significantly shorter OS than cases with lower TMB. Conclusions The contribution of tumor volumetric data, somatic gene mutations and TBM in predicting OS of GG4 patients was defined by ML modeling.

Antibody-Drug Conjugates (ADCs) represent an innovative class of potent anti-cancer compounds that are widely used in the treatment of hematologic malignancies and solid tumors. Unlike conventional chemotherapeutic drug-based therapies, that are mainly associated with modest specificity and therapeutic benefit, the three key components that form an ADC (a monoclonal antibody bound to a cytotoxic drug via a chemical linker moiety) achieve remarkable improvement in terms of targeted killing of cancer cells and, while sparing healthy tissues, a reduction in systemic side effects caused by off-tumor toxicity. Based on their beneficial mechanism of action, 15 ADCs have been approved to date by the market approval by the Food and Drug Administration (FDA), the European Medicines Agency (EMA) and/or other international governmental agencies for use in clinical oncology, and hundreds are undergoing evaluation in the preclinical and clinical phases. Here, our aim is to provide a comprehensive overview of the key features revolving around ADC therapeutic strategy including their structural and targeting properties, mechanism of action, the role of the tumor microenvironment and review the approved ADCs in clinical oncology, providing discussion regarding their toxicity profile, clinical manifestations and use in novel combination therapies. Finally, we briefly review ADCs in other pathological contexts and provide key information regarding ADC manufacturing and analytical characterization.

IntroductionMicroRNAs represent interesting targets for new therapies because their altered expression influences tumor development and progression. miR-17 is a prototype of onco-miRNA, known to be overexpressed in B-cell non-Hodgkin lymphoma (B-NHL) with peculiar clinic-biological features. AntagomiR molecules have been largely studied to repress the regulatory functions of up-regulated onco-miRNAs, but their clinical use is mainly limited by their rapid degradation, kidney elimination and poor cellular uptake when injected as naked oligonucleotides.MethodsTo overcome these problems, we exploited CD20 targeted chitosan nanobubbles (NBs) for a preferential and safe delivery of antagomiR17 to B-NHL cells.ResultsPositively charged 400 nm-sized nanobubbles (NBs) represent a stable and effective nanoplatform for antagomiR encapsulation and specific release into B-NHL cells. NBs rapidly accumulated in tumor microenvironment, but only those conjugated with a targeting system (antiCD20 antibodies) were internalized into B-NHL cells, releasing antagomiR17 in the cytoplasm, both in vitro and in vivo. The result is the down-regulation of miR-17 level and the reduction in tumor burden in a human-mouse B-NHL model, without any documented side effects.DiscussionAnti-CD20 targeted NBs investigated in this study showed physico-chemical and stability properties suitable for antagomiR17 delivery in vivo and represent a useful nanoplatform to address B-cell malignancies or other cancers through the modification of their surface with specific targeting antibodies.

A novel coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is the cause of coronavirus disease 2019 (COVID-19). It emerged in China in 2019 and has since spread worldwide. COVID-19 has a wide spectrum of clinical scenarios, ranging from totally asymptomatic to death. Prevention remains the best approach against SARS-CoV-2 infection and a number of strategies have been adopted, including social and medical interventions. Some vaccines have been proposed and several pharmacological approaches, mainly based on repurposing drugs, are currently under investigation and require validation. This review summarizes the ongoing clinical trials using pharmacological strategies, including vaccines, as prophylaxis to avoid SARS-CoV-2 infection or limit its transmission, and as early treatment of COVID-19 to prevent severe clinical outcomes.

Nanoparticles (NPs) are versatile candidates for nanomedical applications due to their unique physicochemical properties. However, their clinical applicability is hindered by their undesirable recognition by the immune system and the consequent immunotoxicity, as well as their rapid clearance in vivo. After injection, NPs are usually covered with layers of proteins, called protein coronas (PCs), which alter their identity, biodistribution, half-life, and efficacy. Therefore, the characterization of the PC is for in predicting the fate of NPs in vivo. The aim of this review was to summarize the state of the art regarding the intrinsic factors closely related to the NP structure, and extrinsic factors that govern PC formation in vitro. In addition, well-known opsonins, including complement, immunoglobulins, fibrinogen, and dysopsonins, such as histidine-rich glycoprotein, apolipoproteins, and albumin, are described in relation to their role in NP detection by immune cells. Particular emphasis is placed on their role in mediating the interaction of NPs with innate and adaptive immune cells. Finally, strategies to reduce PC formation are discussed in detail.

The use of zebrafish (ZF) embryos as an in vivo model is increasingly attractive thanks to different features that include easy handling, transparency, and the absence of adaptive immunity until 4–6 weeks. These factors allow the development of xenografts that can be easily analyzed through fluorescence techniques. In this work, ZF were exploited to characterize the efficiency of drug-loaded polymeric NPs as a therapeutical approach for B-cell malignancies. Fluorescent probes, fluorescent transgenic lines of ZF, or their combination allowed to deeply examine biodistribution, elimination, and therapeutic efficacy. In particular, the fluorescent signal of nanoparticles (NPs) was exploited to investigate the in vivo distribution, while the colocalization between the fluorescence in macrophages and NPs allows following the elimination pathway of these polymeric NPs. Xenotransplanted human B-cells (Nalm-6) developed a reproducible model useful for demonstrating drug delivery by polymeric NPs loaded with doxorubicin and, as a consequence, the arrest of tumor growth and the reduction in tumor burden. ZF proved to be a versatile model, able to rapidly provide answers in the development of animal models and in the characterization of the activity and the efficacy of drug delivery systems.

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.

Nanoparticle-based therapies have been proposed in oncology research using various delivery methods to increase selectivity toward tumor tissues. Enhanced drug delivery through nanoparticle-based therapies could improve anti-tumor efficacy and also prevent drug resistance. However, there are still problems to overcome, such as the main biological interactions of nanocarriers. Among the various nanostructures for drug delivery, drug delivery based on polymeric nanoparticles has numerous advantages for controlling the release of biological factors, such as the ability to add a selective targeting mechanism, controlled release, protection of administered drugs, and prolonging the circulation time in the body. In addition, the functionalization of nanoparticles helps to achieve the best possible outcome. One of the most promising applications for nanoparticle-based drug delivery is in the field of onco-hematology, where there are many already approved targeted therapies, such as immunotherapies with monoclonal antibodies targeting specific tumor-associated antigens; however, several patients have experienced relapsed or refractory disease. This review describes the major nanocarriers proposed as new treatments for hematologic cancer, describing the main biological interactions of these nanocarriers and the related limitations of their use as drug delivery strategies.

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.

Glioblastoma (GBM) is the most frequent and aggressive primary central nervous system tumor. Surgery followed by radiotherapy and chemotherapy with alkylating agents constitutes standard first-line treatment of GBM. Complete resection of the GBM tumors is generally not possible given its high invasive features. Although this combination therapy can prolong survival, the prognosis is still poor due to several factors including chemoresistance. In recent years, a comprehensive characterization of the GBM-associated molecular signature has been performed. This has allowed the possibility to introduce a more personalized therapeutic approach for GBM, in which novel targeted therapies, including those employing tyrosine kinase inhibitors (TKIs), could be employed. The GBM tumor microenvironment (TME) exerts a key role in GBM tumor progression, in particular by providing an immunosuppressive state with low numbers of tumor-infiltrating lymphocytes (TILs) and other immune effector cell types that contributes to tumor proliferation and growth. The use of immune checkpoint inhibitors (ICIs) has been successfully introduced in numerous advanced cancers as well as promising results have been shown for the use of these antibodies in untreated brain metastases from melanoma and from non-small cell lung carcinoma (NSCLC). Consequently, the use of PD-1/PD-L1 inhibitors has also been proposed in several clinical trials for the treatment of GBM. In the present review, we will outline the main GBM molecular and TME aspects providing also the grounds for novel targeted therapies and immunotherapies using ICIs for GBM.

Chronic lymphocytic leukemia (CLL) is characterized by low CD20 expression, in part explained by an epigenetic-driven downregulation triggered by mutations of the NOTCH1 gene. In the present study, by taking advantage of a wide and well-characterized CLL cohort (n=537), we demonstrate that CD20 expression is downregulated in SF3B1-mutated CLL to an extent similar to NOTCH1-mutated CLL. In fact, SF3B1-mutated CLL cells show common features with NOTCH1- mutated CLL cells, including a gene expression profile enriched in NOTCH1-related gene sets and elevated expression of the active intracytoplasmic NOTCH1. Activation of the NOTCH1 signaling and downregulation of surface CD20 in SF3B1-mutated CLL cells correlate with overexpression of an alternatively spliced form of DVL2, a component of the Wnt pathway and negative regulator of the NOTCH1 pathway. These findings were confirmed by separately analyzing the CD20dim and CD20bright cell fractions from SF3B1-mutated cases as well as by DVL2 knockout experiments in CLL-like cell models. Together, the clinical and biological features that characterize NOTCH1-mutated CLL may also be recapitulated in SF3B1-mutated CLL, contributing to explain the poor prognosis of this CLL subset and providing the rationale for expanding therapies based on novel agents to SF3B1-mutated CLL.

In chronic lymphocytic leukemia (CLL), the hypoxia-inducible factor 1 (HIF-1) regulates the response of tumor cells to hypoxia and their protective interactions with the leukemic microenvironment. In this study, we demonstrate that CLL cells from TP53-disrupted (TP53dis) patients have constitutively higher expression levels of the α-subunit of HIF-1 (HIF-1α) and increased HIF-1 transcriptional activity compared to the wild-type counterpart. In the TP53dis subset, HIF-1α upregulation is due to reduced expression of the HIF-1α ubiquitin ligase von Hippel-Lindau protein (pVHL). Hypoxia and stromal cells further enhance HIF-1α accumulation, independently of TP53 status. Hypoxia acts through the downmodulation of pVHL and the activation of the PI3K/AKT and RAS/ERK1-2 pathways, whereas stromal cells induce an increased activity of the RAS/ERK1-2, RHOA/RHOA kinase and PI3K/AKT pathways, without affecting pVHL expression. Interestingly, we observed that higher levels of HIF-1A mRNA correlate with a lower susceptibility of leukemic cells to spontaneous apoptosis, and associate with the fludarabine resistance that mainly characterizes TP53dis tumor cells. The HIF-1α inhibitor BAY87-2243 exerts cytotoxic effects toward leukemic cells, regardless of the TP53 status, and has anti-tumor activity in Em-TCL1 mice. BAY87-2243 also overcomes the constitutive fludarabine resistance of TP53dis leukemic cells and elicits a strongly synergistic cytotoxic effect in combination with ibrutinib, thus providing preclinical evidence to stimulate further investigation into use as a potential new drug in CLL.

Chitosan is a natural polysaccharide that is considered to be biocompatible, biodegradable and non-toxic. The polymer has been used in drug delivery applications for its positive charge, which allows for adhesion with and recognition of biological tissues via non-covalent interactions. In recent times, chitosan has been used for the preparation of graft copolymers with thermoresponsive polymers such as poly-N-vinylcaprolactam (PNVCL) and poly-N-isopropylamide (PNIPAM), allowing the combination of the biodegradability of the natural polymer with the ability to respond to changes in temperature. Due to the growing interest in the utilization of thermoresponsive polymers in the biological context, it is necessary to increase the knowledge of the key principles of thermoresponsivity in order to obtain comparable results between different studies or applications. In the present review, we provide an overview of the basic principles of thermoresponsivity, as well as a description of the main polysaccharides and thermoresponsive materials, with a special focus on chitosan and poly-N-Vinyl caprolactam (PNVCL) and their biomedical applications.

Microgels can be considered soft, porous and deformable particles with an internal gel structure swollen by a solvent and an average size between 100 and 1000 nm. Due to their biocompatibility, colloidal stability, their unique dynamicity and the permeability of their architecture, they are emerging as important candidates for drug delivery systems, sensing and biocatalysis. In clinical applications, the research on responsive microgels is aimed at the development of “smart” delivery systems that undergo a critical change in conformation and size in reaction to a change in environmental conditions (temperature, magnetic fields, pH, concentration gradient). Recent achievements in biodegradable polymer fabrication have resulted in new appealing strategies, including the combination of synthetic and natural-origin polymers with inorganic nanoparticles, as well as the possibility of controlling drug release remotely. In this review, we provide a literature review on the use of dual and multi-responsive chitosan-grafted-poly-(N-vinylcaprolactam) (CP) microgels in drug delivery and oncological applications.

Poly-N-Vinylcaprolactam (PNVCL) is a thermoresponsive polymer that exhibits lower critical solution temperature (LCST) between 25 and 50 °C. Due to its alleged biocompatibility, this polymer is becoming popular for biomedical and environmental applications. PNVCL with carboxyl terminations has been widely used for the preparation of thermoresponsive copolymers, micro- and nanogels for drug delivery and oncological therapies. However, the fabrication of such specific targeting devices needs standardized and reproducible preparation methods. This requires a deep understanding of how the miscibility behavior of the polymer is affected by its structural properties and the solution environment. In this work, PNVCL-COOH polymers were prepared via free radical polymerization (FRP) in order to exhibit LCST between 33 and 42 °C. The structural properties were investigated with NMR, FT-IR and conductimetric titration and the LCST was calculated via UV-VIS and DLS. The LCST is influenced by the molecular mass, as shown by both DLS and viscosimetric values. Finally, the behavior of the polymer was described as function of its concentration and in presence of different biologically relevant environments, such as aqueous buffers, NaCl solutions and human plasma.

Hepatocellular carcinoma (HCC) can be classified as a prototypical inflammation-driven cancer that generally arises from a background of liver cirrhosis, but that in the presence of nonalcoholic steatohepatitis (NASH), could develop in the absence of fibrosis or cirrhosis. Tumor-promoting inflammation characterizes HCC pathogenesis, with an epidemiology of the chronic liver disease frequently encompassing hepatitis virus B (HBV) or C (HCV). HCC tumor onset and progression is a serial and heterogeneous process in which intrinsic factors, such as genetic mutations and chromosomal instability, are closely associated with an immunosuppressive tumor microenvironment (TME), which may have features associated with the etiopathogenesis and expression of the viral antigens, which favor the evasion of tumor neoantigens to immune surveillance. With the introduction of direct-acting antiviral (DAA) therapies for HCV infection, sustained virological response (SVR) has become very high, although occurrence of HCC and reactivation of HBV in patients with co-infection, who achieved SVR in short term, have been observed in a significant proportion of treated cases. In this review, we discuss the main molecular and TME features that are responsible for HCC pathogenesis and progression. Peculiar functional aspects that could be related to the presence and treatment of HCV/HBV viral infections are also dealt with.

Oligonucleotide (ON) therapeutics are molecular target agents composed of chemically synthesized DNA or RNA molecules capable of inhibiting gene expression or protein function. How ON therapeutics can efficiently reach the inside of target cells remains a problem still to be solved in the majority of potential clinical applications. The chemical structure of ON compounds could affect their capability to pass through the plasma membrane. Other key factors are nuclease degradation in the extracellular space, renal clearance, reticulo-endothelial system, and at the target cell level, the endolysosomal system and the possible export via exocytosis. Several delivery platforms have been proposed to overcome these limits including the use of lipidic, polymeric, and inorganic nanoparticles, or hybrids between them. The possibility of evaluating the efficacy of the proposed therapeutic strategies in useful in vivo models is still a pivotal need, and the employment of zebrafish (ZF) models could expand the range of possibilities. In this review, we briefly describe the main ON therapeutics proposed for anticancer treatment, and the different strategies employed for their delivery to cancer cells. The principal features of ZF models and the pros and cons of their employment in the development of ON-based therapeutic strategies are also discussed.

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Furthermore, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state.

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.

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.

Despite recent discoveries in genetics and molecular fields, glioblastoma (GBM) prognosis still remains unfavorable with less than 10% of patients alive 5 years after diagnosis. Numerous studies have focused on the research of biological biomarkers to stratify GBM patients. We addressed this issue in our study by using clinical/molecular and image data, which is generally available to Neurosurgical Departments in order to create a prognostic score that can be useful to stratify GBM patients undergoing surgical resection. By using the random forest approach [CART analysis (classification and regression tree)] on Survival time data of 465 cases, we developed a new prediction score resulting in 10 groups based on extent of resection (EOR), age, tumor volumetric features, intraoperative protocols and tumor molecular classes. The resulting tree was trimmed according to similarities in the relative hazard ratios amongst groups, giving rise to a 5-group classification tree. These 5 groups were different in terms of overall survival (OS) (p < 0.000). The score performance in predicting death was defined by a Harrell’s c-index of 0.79 (95% confidence interval [0.76−0.81]). The proposed score could be useful in a clinical setting to refine the prognosis of GBM patients after surgery and prior to postoperative treatment.

Immunotherapy by using immune checkpoint inhibitors (ICI) has dramatically improved the treatment options in various cancers, increasing survival rates for treated patients. Nevertheless, there are heterogeneous response rates to ICI among different cancer types, and even in the context of patients affected by a specific cancer. Thus, it becomes crucial to identify factors that predict the response to immunotherapeutic approaches. A comprehensive investigation of the mutational and immunological aspects of the tumor can be useful to obtain a robust prediction. By performing a pan-cancer analysis on gene expression data from the Cancer Genome Atlas (TCGA, 8055 cases and 29 cancer types), we set up and validated a machine learning approach to predict the potential for positive response to ICI. Support vector machines (SVM) and extreme gradient boosting (XGboost) models were developed with a 10×5-fold cross-validation schema on 80% of TCGA cases to predict ICI responsiveness defined by a score combining tumor mutational burden and TGF- β signaling. On the remaining 20% validation subset, our SVM model scored 0.88 accuracy and 0.27 Matthews Correlation Coefficient. The proposed machine learning approach could be useful to predict the putative response to ICI treatment by expression data of primary tumors.

Mantle cell lymphoma patients have variable clinical courses, ranging from indolent cases that do not require immediate treatment to aggressive, rapidly progressing diseases. Thus, diagnostic tools capable of stratifying patients according to their risk of relapse and death are needed. This study included 83 samples from the Fondazione Italiana Linfomi MCL-0208 clinical trial. Through gene expression profiling and quantitative real-time PCR we analyzed 46 peripheral blood and 43 formalin-fixed paraffin-embedded lymph node samples. A prediction model to classify patients was developed. By analyzing the transcriptome of 27 peripheral blood samples, two subgroups characterized by a differential expression of genes from the B-cell receptor pathway (B-cell receptorlow and B-cell receptorhigh) were identified. The prediction model based on the quantitative real-time PCR values of six representative genes (AKT3, BCL2, BTK, CD79B, PIK3CD, and SYK), was used to classify the 83 cases (43 B-cell receptorlow and 40 B-cell receptorhigh). The B-cell receptorhigh signature associated with shorter progression-free survival (P=0.0074), selected the mantle cell lymphoma subgroup with the shortest progression-free survival and overall survival (P=0.0014 and P=0.029, respectively) in combination with high (>30%) Ki-67 staining, and was an independent predictor of short progression- free survival along with the Mantle Cell Lymphoma International Prognostic Index-combined score. Moreover, the clinical impact of the 6- gene signature related to the B-cell receptor pathway identified a mantle cell lymphoma subset with shorter progression-free survival intervals also in an external independent mantle cell lymphoma cohort homogenously treated with different schedules. In conclusion, this 6-gene signature associates with a poor clinical response in the context of the MCL- 0208 clinical trial. (clinicaltrials.gov identifier: 02354313).

Chronic lymphocytic leukaemia (CLL) is a clinically heterogeneous disease characterised by the accumulation/expansion of a clonal population of neoplastic cells with the morphological appearance of small mature B lymphocytes in blood, bone marrow, and lymphoid organs. Stimulation through the B cell receptor (BCR) plays a prominent role in the selection and expansion of the malignant clone in CLL. On the other hand, other external signals delivered by several cell types including T lymphocytes, macrophages, stromal cells, endothelial cells, and follicular dendritic cells, operating through either direct BCR-independent cell-cell contact or indirect production of paracrine soluble factors, synergistically cooperate in regulating proliferation and survival of CLL cells. In this context, CD49d is known to play a pivotal role in mediating both cell-cell and cell-matrix interactions in CLL-involved tissues, eventually delivering pro-survival signals and protecting CLL cells from drug-induced damages. In the present review, we focused on functional and physical interactions of CD49d with other microenvironmental receptors, including CD38 and BCR, and other specific CD49d-dependent interactions in lymph node and bone marrow microenvironments responsible for growth and survival-supporting signals, eventually influencing CLL prognosis and therapeutic options.

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.

In chronic lymphocytic leukemia the balance between the pro-apoptotic and anti-apoptotic members of the bcl-2 family is involved in the pathogenesis, chemorefractoriness and clinical outcome. Moreover, the recently proposed anti-bcl-2 molecules, such as ABT-199, have emphasized the potential role of of bcl-2 family proteins in the context of target therapies. We investigated bax/bcl-2 ratio by flow cytometry in 502 patients and identified a cut off of 1.50 to correlate bax/bcl-2 ratio with well-established clinical and biological prognosticators. Bax/bcl-2 was 1.50 or over in 263 patients (52%) with chronic lymphocytic leukemia. Higher bax/bcl-2 was associated with low Rai stage, lymphocyte doubling time over 12 months, beta-2 microglobulin less than 2.2 mg/dL, soluble CD23 less than 70 U/mL and a low risk cytogenetic profile (P

Background CD69 is expressed in several hemopoietic cells and is an early activation marker in chronic lymphocytic leukemia. Chronic lymphocytic leukemia is a clinically heterogeneous disease which needs novel prognostic parameters which can be easily and efficiently managed.Design and Methods We investigated CD69 by flow cytometry in a series of 417 patients affected by chronic lymphocytic leukemia and compared this to other biological and clinical prognosticators.Results CD69 was associated with Rai stages (P=0.00002), β2-microglobulin (P=0.0005) and soluble CD23 (P