Therapeutic Targets and Emerging Treatments in Advanced Chondrosarcoma

Simple SummaryChondrosarcomas develop chemoresistance to standard anticancer drugs, making it difficult to control unresectable or metastatic chondrosarcomas. To improve the clinical outcomes of chondrosarcoma, new treatment approaches, such as molecule-targeting agents and immunotherapy, are needed. Recent research has revealed promising biomarkers and therapeutic targets for chondrosarcoma. In addition, several molecule-targeting agents have shown favorable antitumor activities in several clinical studies in patients with advanced sarcomas, including chondrosarcoma. This review summarizes recent basic studies on biomarkers and therapeutic targets and recent clinical studies on treating chondrosarcomas.AbstractDue to resistance to standard anticancer agents, it is difficult to control the disease progression in patients with metastatic or unresectable chondrosarcoma. Novel therapeutic approaches, such as molecule-targeting drugs and immunotherapy, are required to improve clinical outcomes in patients with advanced chondrosarcoma. Recent studies have suggested several promising biomarkers and therapeutic targets for chondrosarcoma, including IDH1/2 and COL2A1. Several molecule-targeting agents and immunotherapies have shown favorable antitumor activity in clinical studies in patients with advanced chondrosarcomas. This review summarizes recent basic studies on biomarkers and molecular targets and recent clinical studies on the treatment of chondrosarcomas.     

In Silico Identification of Potential Druggable Binding Sites on CIN85 SH3 Domain

Protein-protein interactions (PPIs) play a pivotal role in the regulation of many physiological processes. The dysfunction of some PPIs interactions led to the alteration of different biological pathways causing various diseases including cancer. In this context, the inhibition of PPIs represents an attractive strategy for the design of new antitumoral agents. In recent years, computational approaches were successfully used to study the interactions between proteins, providing useful hints for the design of small molecules able to modulate PPIs. Targeting PPIs presents several challenges mainly due to the large and flat binding surface that lack the typical binding pockets of traditional drug targets. Despite these hurdles, substantial progress has been made in the last decade resulting in the identification of PPI modulators where some of them even found clinical use. This study focuses on MUC1-CIN85 PPI which is involved in the migration and invasion of cancer cells. Particularly, we investigated the presence of druggable binding sites on the CIN85 surface which provided new insights for the structure-based design of novel MUC1-CIN85 PPI inhibitors as anti-metastatic agents.     

Aptamer modules as sensors and detectors

Aptamers comprise a range of molecular recognition scaffolds that can be engineered to bind to a legion of different proteins and other targets with excellent specificity and affinity. Because these non-natural oligonucleotides are accessible entirely synthetically, aptamers can be equipped with all sorts of reporter groups and can be coupled to many different carriers, surfaces, nanoparticles, or other biomolecules. They can be used in a highly modular fashion and often recognize their targets by a mechanism in which the aptamer undergoes considerable structural rearrangement, which can be exploited for transducing a binding event into a signal. As a consequence, aptamers have been adapted to a huge variety of "read-out configurations" and are increasingly used as capture agents in many different bioanalytical methods. But despite considerable success with these applications, many remaining challenges must still be overcome for the more widespread incorporation of aptasensors in clinical and environmental biosensing and diagnostics to take place. Some particularly noteworthy progress on this front is currently being made with aptasensor configurations that can be used for the multiplexed sensing of many analytes in parallel. In this Account, we describe some of the concepts involved in transducing the binding of a ligand into a signal through various physico-chemical interactions. Research in this area usually involves the combination of the molecular biology of proteins and nucleic acids with biotechnology, synthetic chemistry, physical chemistry, and surface physics. We begin with a brief introduction of the properties and characteristics that qualify aptamers as capture agents for many different analytes and their suitability as highly versatile biosensor components. We then address approaches that apply to surface acoustic wave configurations, drawing largely from our own contributions to aptasensor development, before moving on to describe previous and recent progress in multiplexed aptasensors. Obtaining proteome-wide profiles in cells, organs, organisms, or full populations requires the ability to accurately measure many different analytes in small sample volumes over a broad dynamic range. Multiplexed sensing is an invaluable tool in this endeavor. We discuss what we consider the biggest obstacles to the broader clinical use of aptasensor-based diagnostics and our perspective on how they can be surmounted. Finally,we explore the tremendous potential of aptamer-based sensors that can specifically discriminate between diseased and healthy cells. Progress in these areas will greatly expand the range of aptasensor applications, leading to enhanced diagnosis of diseases in clinical practice and, ultimately, improved patient care.     

Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders

Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine.     

Molecular Contrast Optical Coherence Tomography and Its Applications in Medicine

The growing need to understand the molecular mechanisms of diseases has prompted the revolution in molecular imaging techniques along with nanomedicine development. Conventional optical coherence tomography (OCT) is a low-cost in vivo imaging modality that provides unique high spatial and temporal resolution anatomic images but little molecular information. However, given the widespread adoption of OCT in research and clinical practice, its robust molecular imaging extensions are strongly desired to combine with anatomical images. A range of relevant approaches has been reported already. In this article, we review the recent advances of molecular contrast OCT imaging techniques, the corresponding contrast agents, especially the nanoparticle-based ones, and their applications. We also summarize the properties, design criteria, merit, and demerit of those contrast agents. In the end, the prospects and challenges for further research and development in this field are outlined.     

Insights into the Pharmacological Effects of Flavonoids: The Systematic Review of Computer Modeling

Computer modeling is a method that is widely used in scientific investigations to predict the biological activity, toxicity, pharmacokinetics, and synthesis strategy of compounds based on the structure of the molecule. This work is a systematic review of articles performed in accordance with the recommendations of PRISMA and contains information on computer modeling of the interaction of classical flavonoids with different biological targets. The review of used computational approaches is presented. Furthermore, the affinities of flavonoids to different targets that are associated with the infection, cardiovascular, and oncological diseases are discussed. Additionally, the methodology of bias risks in molecular docking research based on principles of evidentiary medicine was suggested and discussed. Based on this data, the most active groups of flavonoids and lead compounds for different targets were determined. It was concluded that flavonoids are a promising object for drug development and further research of pharmacology by in vitro, ex vivo, and in vivo models is required.     

Thinking Small: Small Molecules as Potential Synergistic Adjuncts to Checkpoint Inhibition in Melanoma

Metastatic melanoma remains the deadliest form of skin cancer. Immune checkpoint inhibition (ICI) immunotherapy has defined a new age in melanoma treatment, but responses remain inconsistent and some patients develop treatment resistance. The myriad of newly developed small molecular (SM) inhibitors of specific effector targets now affords a plethora of opportunities to increase therapeutic responses, even in resistant melanoma. In this review, we will discuss the multitude of SM classes currently under investigation, current and prospective clinical combinations of ICI and SM therapies, and their potential for synergism in melanoma eradication based on established mechanisms of immunotherapy resistance.     

A Comparison of Brain-State Dynamics across Common Anesthetic Agents in Male Sprague-Dawley Rats

Anesthesia is a powerful tool in neuroscientific research, especially in sleep research where it has the experimental advantage of allowing surgical interventions that are ethically problematic in natural sleep. Yet, while it is well documented that different anesthetic agents produce a variety of brain states, and consequently have differential effects on a multitude of neurophysiological factors, these outcomes vary based on dosages, the animal species used, and the pharmacological mechanisms specific to each anesthetic agent. Thus, our aim was to conduct a controlled comparison of spontaneous electrophysiological dynamics at a surgical plane of anesthesia under six common research anesthetics using a ubiquitous animal model, the Sprague-Dawley rat. From this direct comparison, we also evaluated which anesthetic agents may serve as pharmacological proxies for the electrophysiological features and dynamics of unconscious states such as sleep and coma. We found that at a surgical plane, pentobarbital, isoflurane and propofol all produced a continuous pattern of burst-suppression activity, which is a neurophysiological state characteristically observed during coma. In contrast, ketamine-xylazine produced synchronized, slow-oscillatory activity, similar to that observed during slow-wave sleep. Notably, both urethane and chloral hydrate produced the spontaneous, cyclical alternations between forebrain activation (REM-like) and deactivation (non-REM-like) that are similar to those observed during natural sleep. Thus, choice of anesthesia, in conjunction with continuous brain state monitoring, are critical considerations in order to avoid brain-state confounds when conducting neurophysiological experiments.     

Molecular Selection,Modification and Development of Therapeutic Oligonucleotide Aptamers

Monoclonal antibodies are the dominant agents used in inhibition of biological target molecules for disease therapeutics, but there are concerns of immunogenicity, production, cost and stability. Oligonucleotide aptamers have comparable affinity and specificity to targets with monoclonal antibodies whilst they have minimal immunogenicity, high production, low cost and high stability, thus are promising inhibitors to rival antibodies for disease therapy. In this review, we will compare the detailed advantages and disadvantages of antibodies and aptamers in therapeutic applications and summarize recent progress in aptamer selection and modification approaches. We will present therapeutic oligonucleotide aptamers in preclinical studies for skeletal diseases and further discuss oligonucleotide aptamers in different stages of clinical evaluation for various disease therapies including macular degeneration, cancer, inflammation and coagulation to highlight the bright commercial future and potential challenges of therapeutic oligonucleotide aptamers.     

Novel Emerging Molecular Targets in Non-Small Cell Lung Cancer

In the scenario of systemic treatment for advanced non-small cell lung cancer (NSCLC) patients, one of the most relevant breakthroughs is represented by targeted therapies. Throughout the last years, inhibitors of the epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-Ros oncogene 1 (ROS1), and V-raf murine sarcoma viral oncogene homolog B (BRAF) have been approved and are currently used in clinical practice. However, other promising molecular drivers are rapidly emerging as therapeutic targets. This review aims to cover the molecular alterations with a potential clinical impact in NSCLC, including amplifications or mutations of the mesenchymal–epithelial transition factor (MET), fusions of rearranged during transfection (RET), rearrangements of the neurotrophic tyrosine kinase (NTRK) genes, mutations of the Kirsten rat sarcoma viral oncogene (KRAS) and phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA), as well as amplifications or mutations of human epidermal growth factor receptor 2 (HER2). Additionally, we summarized the current status of targeted agents under investigation for such alterations. This revision of the current literature on emerging molecular targets is needed as the evolving knowledge on novel actionable oncogenic drivers and targeted agents is expected to increase the proportion of patients who will benefit from tailored therapeutic approaches.     

Dissecting Response to Cancer Immunotherapy by Applying Bayesian Network Analysis to Flow Cytometry Data

Cancer immunotherapy, specifically immune checkpoint blockade, has been found to be effective in the treatment of metastatic cancers. However, only a subset of patients achieve clinical responses. Elucidating pretreatment biomarkers predictive of sustained clinical response is a major research priority. Another research priority is evaluating changes in the immune system before and after treatment in responders vs. nonresponders. Our group has been studying immune networks as an accurate reflection of the global immune state. Flow cytometry (FACS, fluorescence-activated cell sorting) data characterizing immune cell panels in peripheral blood mononuclear cells (PBMC) from gastroesophageal adenocarcinoma (GEA) patients were used to analyze changes in immune networks in this setting. Here, we describe a novel computational pipeline to perform secondary analyses of FACS data using systems biology/machine learning techniques and concepts. The pipeline is centered around comparative Bayesian network analyses of immune networks and is capable of detecting strong signals that conventional methods (such as FlowJo manual gating) might miss. Future studies are planned to validate and follow up the immune biomarkers (and combinations/interactions thereof) associated with clinical responses identified with this computational pipeline.     

Exploiting Folding and Degradation Machineries To Target Undruggable Proteins: What Can a Computational Approach Tell Us?

Advances in genomics and proteomics have unveiled an ever-growing number of key proteins and provided mechanistic insights into the genesis of pathologies. This wealth of data showed that changes in expression levels of specific proteins, mutations, and post-translational modifications can result in (often subtle) perturbations of functional protein–protein interaction networks, which ultimately determine disease phenotypes. Although many such validated pathogenic proteins have emerged as ideal drug targets, there are also several that escape traditional pharmacological regulation; these proteins have thus been labeled “undruggable”. The challenges posed by undruggable targets call for new sorts of molecular intervention. One fascinating solution is to perturb a pathogenic protein's expression levels, rather than blocking its activities. In this Concept paper, we shall discuss chemical interventions aimed at recruiting undruggable proteins to the ubiquitin proteasome system, or aimed at disrupting protein-protein interactions in the chaperone-mediated cellular folding machinery: both kinds of intervention lead to a decrease in the amount of active pathogenic protein expressed. Specifically, we shall discuss the role of computational strategies in understanding the molecular determinants characterizing the function of synthetic molecules typically designed for either type of intervention. Finally, we shall provide our perspectives and views on the current limitations and possibilities to expand the scope of rational approaches to the design of chemical regulators of protein levels.     

PET and SPECT Imaging of the EGFR Family (RTK Class I) in Oncology

The human epidermal growth factor receptor family (EGFR-family, other designations: HER family, RTK Class I) is strongly linked to oncogenic transformation. Its members are frequently overexpressed in cancer and have become attractive targets for cancer therapy. To ensure effective patient care, potential responders to HER-targeted therapy need to be identified. Radionuclide molecular imaging can be a key asset for the detection of overexpression of EGFR-family members. It meets the need for repeatable whole-body assessment of the molecular disease profile, solving problems of heterogeneity and expression alterations over time. Tracer development is a multifactorial process. The optimal tracer design depends on the application and the particular challenges of the molecular target (target expression in tumors, endogenous expression in healthy tissue, accessibility). We have herein summarized the recent preclinical and clinical data on agents for Positron Emission Tomography (PET) and Single Photon Emission Tomography (SPECT) imaging of EGFR-family receptors in oncology. Antibody-based tracers are still extensively investigated. However, their dominance starts to be challenged by a number of tracers based on different classes of targeting proteins. Among these, engineered scaffold proteins (ESP) and single domain antibodies (sdAb) show highly encouraging results in clinical studies marking a noticeable trend towards the use of smaller sized agents for HER imaging.     

Checkpoint Kinase 1 Pharmacological Inhibition Synergizes with DNA-Damaging Agents and Overcomes Platinum Resistance in Basal-Like Breast Cancer

Basal-like breast cancer is an incurable disease with limited therapeutic options, mainly due to the frequent development of anti-cancer drug resistance. Therefore, identification of druggable targets to improve current therapies and overcome these resistances is a major goal. Targeting DNA repair mechanisms has reached the clinical setting and several strategies, like the inhibition of the CHK1 kinase, are currently in clinical development. Here, using a panel of basal-like cancer cell lines, we explored the synergistic interactions of CHK1 inhibitors (rabusertib and SAR020106) with approved therapies in breast cancer and evaluated their potential to overcome resistance. We identified a synergistic action of these inhibitors with agents that produce DNA damage, like platinum compounds, gemcitabine, and the PARP inhibitor olaparib. Our results demonstrated that the combination of rabusertib with these chemotherapies also has a synergistic impact on tumor initiation, invasion capabilities, and apoptosis in vitro. We also revealed a biochemical effect on DNA damage and caspase-dependent apoptosis pathways through the phosphorylation of H2AX, the degradation of full-length PARP, and the increase of caspases 3 and 8 activity. This agent also demonstrated synergistic activity in a platinum-resistant cell line, inducing an increase in cell death in response to cisplatin only when combined with rabusertib, while no toxic effect was found on non-tumorigenic breast tissue-derived cell lines. Lastly, the combination of CHK1 inhibitor with cisplatin and gemcitabine resulted in more activity than single or double combinations, leading to a higher apoptotic effect. In conclusion, in our study we identify therapeutic options for the clinical development of CHK1 inhibitors, and confirm that the inhibition of this kinase can overcome acquired resistance to cisplatin.     

Mechanisms and Αpplications of Ιnterleukins in Cancer Immunotherapy

Over the past years, advances in cancer immunotherapy have resulted in innovative and novel approaches in molecular cancer diagnostics and cancer therapeutic procedures. However, due to tumor heterogeneity and inter-tumoral discrepancy in tumor immunity, the clinical benefits are quite restricted. The goal of this review is to evaluate the major cytokines-interleukins involved in cancer immunotherapy and project their basic biochemical and clinical applications. Emphasis will be given to new cytokines in pre-clinical development, and potential directions for future investigation using cytokines. Furthermore, current interleukin-based approaches and clinical trial data from combination cancer immunotherapies will also be discussed. It appears that continuously increasing comprehension of cytokine-induced effects, cancer stemness, immunoediting, immune-surveillance as well as understanding of molecular interactions emerging in the tumor microenvironment and involving microRNAs, autophagy, epithelial-mesenchymal transition (EMT), inflammation, and DNA methylation processes may hold much promise in improving anti-tumor immunity. To this end, the emerging in-depth knowledge supports further studies on optimal synergistic combinations and additional adjuvant therapies to realize the full potential of cytokines as immunotherapeutic agents.     

Challenges and opportunities in computer-aided molecular design

In this paper, the significant development, current challenges and future opportunities in the field of chemical product design using computer-aided molecular design (CAMD) tools are highlighted. With the gaining of focus on the design of novel and improved chemical products, the traditional heuristic based approaches may not be effective in designing optimal products. This leads to the vast development and application of CAMD tools, which are methods that combine property prediction models with computer-assisted search in the design of various chemical products. The introduction and development of different classes of property prediction methods in the overall product design process is discussed. The exploration and application of CAMD tools in numerous single component product designs, mixture design, and later in the integrated process-product design are reviewed in this paper. Difficulties and possible future extension of CAMD are then discussed in detail. The highlighted challenges and opportunities are mainly about the needs for exploration and development of property models, suitable design scale and computational effort as well as sustainable chemical product design framework. In order to produce a chemical product in a sustainable way, the role of each level in a chemical product design enterprise hierarchy is discussed. In addition to process parameters and product quality, environment, health and safety performance are required to be considered in shaping a sustainable chemical product design framework. On top of these, recent developments and opportunities in the design of ionic liquids using molecular design techniques have been discussed.     

Characterization of Aptamer-Protein Complexes by X-ray Crystallography and Alternative Approaches

Aptamers are oligonucleotide ligands, either RNA or ssDNA, selected for high-affinity binding to molecular targets, such as small organic molecules, proteins or whole microorganisms. While reports of new aptamers are numerous, characterization of their specific interaction is often restricted to the affinity of binding (K(D)). Over the years, crystal structures of aptamer-protein complexes have only scarcely become available. Here we describe some relevant technical issues about the process of crystallizing aptamer-protein complexes and highlight some biochemical details on the molecular basis of selected aptamer-protein interactions. In addition, alternative experimental and computational approaches are discussed to study aptamer-protein interactions.     

Molecular Biology in Treatment Decision Processes—Neuro-Oncology Edition

Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at the forefront of large-scale data acquisition and well positioned towards both the production and analysis of large-scale oncologic data with the potential for clinically driven endpoints and advancement of patient outcomes. Neuro-oncology is comprised of malignancies that often carry poor prognosis and significant neurological sequelae. The analysis of radiation therapy mediated treatment and the potential for computationally mediated analyses may lead to more precise therapy by employing large scale data. We analysed the state of the literature pertaining to large scale data, computational analysis, and the advancement of molecular biomarkers in neuro-oncology with emphasis on radiation oncology. We aimed to connect existing and evolving approaches to realistic avenues for clinical implementation focusing on low grade gliomas (LGG), high grade gliomas (HGG), management of the elderly patient with HGG, rare central nervous system tumors, craniospinal irradiation, and re-irradiation to examine how computational analysis and molecular science may synergistically drive advances in personalised radiation therapy (RT) and optimise patient outcomes.