Personalized nanomedicine: paving the way to the practical clinical utility of genomics and nanotechnology advancements

Canine models of human cancer: Bridging the gap to improve precision medicine

Dogs are remarkable, adaptable, and dependable creatures that have evolved alongside humans while contributing tremendously to our survival. Our canine companions share many similarities to human disease, particularly cancer. With the advancement of next-generation sequencing technology, we are beginning to unravel the complexity of cancer and the vast intra- and intertumoral heterogeneity that makes treatment difficult. Consequently, precision medicine has emerged as a therapeutic approach to improve patient survival by evaluating and classifying an individual tumor's molecular profile. Many canine and human cancers share striking similarities in terms of genotypic, phenotypic, clinical, and histological presentations. Dogs are superior to rodent models of cancer because they are a naturally heterogeneous population in which tumors occur spontaneously, are exposed to similar environmental conditions, and show more similarities in key modulators of tumorigenesis and clinical response, including the immune system, drug metabolism, and gut microbiome. In this chapter, we will explore various canine models of human cancers and emphasize the dog's critical role in advancing precision medicine and improving the survival of both man and man's best friend.

Dissecting miRNA–Gene Networks to Map Clinical Utility Roads of Pharmacogenomics-Guided Therapeutic Decisions in Cardiovascular Precision Medicine

MicroRNAs (miRNAs) create systems networks and gene-expression circuits through molecular signaling and cell interactions that contribute to health imbalance and the emergence of cardiovascular disorders (CVDs). Because the clinical phenotypes of CVD patients present a diversity in their pathophysiology and heterogeneity at the molecular level, it is essential to establish genomic signatures to delineate multifactorial correlations, and to unveil the variability seen in therapeutic intervention outcomes. The clinically validated miRNA biomarkers, along with the relevant SNPs identified, have to be suitably implemented in the clinical setting in order to enhance patient stratification capacity, to contribute to a better understanding of the underlying pathophysiological mechanisms, to guide the selection of innovative therapeutic schemes, and to identify innovative drugs and delivery systems. In this article, the miRNA–gene networks and the genomic signatures resulting from the SNPs will be analyzed as a method of highlighting specific gene-signaling circuits as sources of molecular knowledge which is relevant to CVDs. In concordance with this concept, and as a case study, the design of the clinical trial GESS (NCT03150680) is referenced. The latter is presented in a manner to provide a direction for the improvement of the implementation of pharmacogenomics and precision cardiovascular medicine trials.

A Risk-Stratification Machine Learning Framework for the Prediction of Coronary Artery Disease Severity: Insights From the GESS Trial

Our study aims to develop a data-driven framework utilizing heterogenous electronic medical and clinical records and advanced Machine Learning (ML) approaches for: (i) the identification of critical risk factors affecting the complexity of Coronary Artery Disease (CAD), as assessed via the SYNTAX score; and (ii) the development of ML prediction models for accurate estimation of the expected SYNTAX score. We propose a two-part modeling technique separating the process into two distinct phases: (a) a binary classification task for predicting, whether a patient is more likely to present with a non-zero SYNTAX score; and (b) a regression task to predict the expected SYNTAX score accountable to individual patients with a non-zero SYNTAX score. The framework is based on data collected from the GESS trial (NCT03150680) comprising electronic medical and clinical records for 303 adult patients with suspected CAD, having undergone invasive coronary angiography in AHEPA University Hospital of Thessaloniki, Greece. The deployment of the proposed approach demonstrated that atherogenic index of plasma levels, diabetes mellitus and hypertension can be considered as important risk factors for discriminating patients into zero- and non-zero SYNTAX score groups, whereas diastolic and systolic arterial blood pressure, peripheral vascular disease and body mass index can be considered as significant risk factors for providing an accurate estimation of the expected SYNTAX score, given that a patient belongs to the non-zero SYNTAX score group. The experimental findings utilizing the identified set of important risk factors indicate a sufficient prediction performance for the Support Vector Machine model (classification task) with an F-measure score of ~0.71 and the Support Vector Regression model (regression task) with a median absolute error value of ~6.5. The proposed data-driven framework described herein present evidence of the prediction capacity and the potential clinical usefulness of the developed risk-stratification models. However, further experimentation in a larger clinical setting is needed to ensure the practical utility of the presented models in a way to contribute to a more personalized management and counseling of CAD patients.

A quantitative view on multivalent nanomedicine targeting

Although the concept of selective delivery has been postulated over 100 years ago, no targeted nanomedicine has been clinically approved so far. Nanoparticles modified with targeting ligands to promote the selective delivery of therapeutics towards a specific cell population have been extensively reported. However, the rational design of selective particles is still challenging. One of the main reasons for this is the lack of quantitative theoretical and experimental understanding of the interactions involved in cell targeting. In this review, we discuss new theoretical models and experimental methods that provide a quantitative view of targeting. We show the new advancements in multivalency theory enabling the rational design of super-selective nanoparticles. Furthermore, we present the innovative approaches to obtain key targeting parameters at the single-cell and single molecule level and their role in the design of targeting nanoparticles. We believe that the combination of new theoretical multivalent design and experimental methods to quantify receptors and ligands aids in the rational design and clinical translation of targeted nanomedicines.

Integration of pharmacogenomics and theranostics with nanotechnology as quality by design (QbD) approach for formulation development of novel dosage forms for effective drug therapy

To cater to medication needs in the future healthcare system, we need to shift from the conventional system of drug delivery to modern molecular signature-based drug delivery systems. The current drug therapies are either less effective, ineffective, or produce numerous adverse reactions. One scientific principle or discipline cannot adequately address all the problems, so we need an innovative application of the current scientific principles. Here we are proposing a novel concept of nanoformulation based on pharmacogenomics and theranostics for personalized error-free and targeted therapeutic agent delivery. The addition of more knowledge about the human genome opens the new way to study disease-gene, gene-drug, and drug-effect interactions, which is the basis of future medicines. Pharmacogenomics provides information about the disease etiology, role in genes in disease pathophysiology, disease biomarkers, drug targets, drug effects, and the fate of drugs inside the body. Theranostics approach utilizes the above information in diagnosis, treatment, and monitoring of the disease on a real-time basis. Personalized dosage forms can be formulated into a nanoformulation that provides a better therapeutic effect and minimizes adverse drug reactions. The therapeutic system needs to be shifted from the principle of one drug fits all to one drug unique population. In the present manuscript, we tried to conceptualize a modern therapeutic system by combining the three approaches viz. pharmacogenomics, theranostics, and nanotechnology applied in the area of formulation development to produce a multifunctional single tiny entity.

Towards analyzing the potential of exosomes to deliver microRNA therapeutics

Exosome selectivity mechanisms underlying exosome-target cell interactions and the specific traits affecting their capability to communicate still remain unclear. Moreover, the capacity of exosomes to efficiently deliver their molecular cargos intracellularly needs precise investigation towards establishing functional exosome-based delivery platforms exploitable in the clinical practice. The current study focuses on: (a) exosome production from normal MRC-5 and Vero cells growing in culture, (b) physicochemical characterization by dynamic light scattering (DLS) and cryo-transmission electron microscopy; (c) cellular uptake studies of rhodamine-labeled exosomes in normal and cancer cells, providing to exosomes either "autologous" or "heterologous" cellular delivery environments; and (d) loading exogenous Alexa Fluor 488-labeled siRNA into exosomes for the assessment of their delivering capacity by immunofluorescence in a panel of recipient cells. The data obtained thus far indicate that MRC-5 and Vero exosomes, indeed exhibit an interesting delivering profile, as promising "bio-shuttles," being pharmacologically exploitable in the context of theranostic applications.

Translational considerations in nanomedicine: The oncology perspective

Nanoparticles can provide effective control of the release rate and tissue distribution of their drug payload, leading to major pharmacokinetic and pharmacodynamic changes vis-à-vis the conventional administration of free drugs. In the last two decades, we have witnessed major progress in the synthesis and characterization of engineered nanoparticles for imaging and treatment of cancers, resulting in the approval for clinical use of several products and in new and promising approaches. Despite these advances, clinical applications of nanoparticle-based therapeutic and imaging agents remain limited due to biological, immunological, and translational barriers. There is a need to make high impact advances toward translation. In this review, we address biological, toxicological, immunological, and translational aspects of nanomedicine and discuss approaches to move the field forward productively. Overcoming these barriers may dramatically improve the development potential and role of nanomedicines in the oncology field and help meet the high expectations.

Bridging the Knowledge of Different Worlds to Understand the Big Picture of Cancer Nanomedicines

Explosive growth of nanomedicines continues to significantly impact the therapeutic strategies for effective cancer treatment. Despite the significant progress in the development of advanced nanomedicines, successful clinical translation remains challenging. As cancer nanomedicine is a multidisciplinary field, the fundamental problem is that the knowledge gaps stem from different vantage points in the understanding of cancer nanomedicines. The complexities and heterogenecity of both nanomedicines and cancer are further demanding the integration of highly diverse expertise to develop clinically translatable cancer nanomedicines. This progress report aims to discuss the current understanding of cancer nanomedicines between different research areas in terms of nanoparticle engineering, formulation, tumor patho-physiology and clinical medicine, as well as to identify the knowledge gaps lying at the interface between the different fields of research in nanomedicine. Here we also highlight for the necessity to harmonize the multidisciplinary effort in the research of nanomedicines in order to bridge the knowledge and to advance the full understanding in cancer nanomedicines. A paradigm shift is needed in the strategic development of disease specific nanomedicines in order to foster the successful translation into clinic of future cancer nanomedicines.

Promise and peril in nanomedicine: the challenges and needs for integrated systems biology approaches to define health risk

In the 1966s visionary film 'Fantastic Voyage' a submarine crew was shrunk to 100 nm in size and injected into the body of an injured scientist to repair his damaged brain. The movie (written by Harry Kleiner; directed by Richard Fleischer; novel by Isaac Asimov) drew attention to the potential power of engineered nanoscale structures and devices to construct, monitor, control, treat, and repair individual cells. Even more interesting was the fact that the film elegantly noted that the structure had to be miniaturized to a size that is not detected by the body's immune surveillance system, and highlighted the many physiological barriers that are encountered on the submarine's long journey to the target. Although the concept of miniaturizing humans remains an element of science fiction, targeted drug delivery through nanobots to treat diseases such as cancer is now a reality. The ability of nanobots to evade immune surveillance is one of the most attractive features of nanoscale materials that are exploited in the field of medicine for molecular diagnostics, targeted drug delivery, and therapy of diseases. This article will provide a concise opinion on the state-of-the-art, the challenges, and the use of systems biology-another equally revolutionary field of science-to assess the unique health hazards of nanomaterial exposures. WIREs Nanomed Nanobiotechnol 2018, 10:e1465. doi: 10.1002/wnan.1465 This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials.

Enabling personalized cancer medicine decisions: The challenging pharmacological approach of PBPK models for nanomedicine and pharmacogenomics (Review)

The existing tumor heterogeneity and the complexity of cancer cell biology critically demand powerful translational tools with which to support interdisciplinary efforts aiming to advance personalized cancer medicine decisions in drug development and clinical practice. The development of physiologically based pharmacokinetic (PBPK) models to predict the effects of drugs in the body facilitates the clinical translation of genomic knowledge and the implementation of in vivo pharmacology experience with pharmacogenomics. Such a direction unequivocally empowers our capacity to also make personalized drug dosage scheme decisions for drugs, including molecularly targeted agents and innovative nanoformulations, i.e. in establishing pharmacotyping in prescription. In this way, the applicability of PBPK models to guide individualized cancer therapeutic decisions of broad clinical utility in nanomedicine in real-time and in a cost-affordable manner will be discussed. The latter will be presented by emphasizing the need for combined efforts within the scientific borderlines of genomics with nanotechnology to ensure major benefits and productivity for nanomedicine and personalized medicine interventions.

Harnessing pharmacological knowledge for personalized medicine and pharmacotyping: Challenges and lessons learned

The contribution of the genetic make-up to an individual’s capacity has long been recognized in modern pharmacology as a crucial factor leading to therapy inefficiency and toxicity, negatively impacting the economic burden of healthcare and restricting the monitoring of diseases. In practical terms, and in order for drug prescription to be improved toward meeting the personalized medicine concept in drug delivery, the maximum clinical outcome for most, if not all, patients must be achieved, i.e., pharmacotyping. Such a direction although promising and of high expectation from the society, it is however hardly to be afforded for healthcare worldwide. To overcome any existed hurdles, this means that practical clinical utility of personalized medicine decisions have to be documented and validated in the clinical setting. The latter implies for drug delivery the efficient implementation of previously gained in vivo pharmacology experience with pharmacogenomics knowledge. As an approach to work faster and in a more productive way, the elaboration of advanced physiologically based pharmacokinetics models is discussed. And in better clarifying this topic, the example of tamoxifen is thoroughly presented. Overall, pharmacotyping represents a major challenge in modern therapeutics for which pharmacologists need to work in successfully fulfilling this task.

Controlled release of 5-fluorouracil from microporous zeolites

Zeolite particles with different pore diameter and particle size were loaded with the model anticancer drug 5-fluorouracil. The loaded zeolites were characterized by means of SEM, XRD, DSC, XPS, N2 physisorption and FT-IR. Higher loading of 5-FU was observed for NaX-FAU than BEA. Release studies were carried out in HCl 0.1N. Release of 5-FU from NaX-FAU showed exponential-type behaviour with the drug fully released within 10 min. In the case of BEA, the kinetics of 5-FU shows a multi-step profile with prolonged release over time. Molecular dynamics simulations showed that diffusion of the drug molecule through the BEA framework is lower than for NaX-FAU due to increased van der Waals interaction between the drug and the framework. The effect of zeolitic particles on the viability of Caco-2 monolayers showed that the NaX-FAU particles cause a reduction of cell viability in a more pronounced way compared with the BEA particles.

FROM THE CLINICAL EDITOR

This article describes zeolite-based nanoparticles in generating time-controlled release of 5-FU from zeolite preparations for anti-cancer therapy.