Artificial intelligence in cardiovascular prevention: new ways will open new doors.

Prevention and effective treatment of cardiovascular disease are progressive issues that grow in tandem with the average age of the world population. Over recent decades, the potential role of artificial intelligence in cardiovascular medicine has been increasingly recognized because of the incredible amount of real-world data (RWD) regarding patient health status and healthcare delivery that can be collated from a variety of sources wherein patient information is routinely collected, including patient registries, clinical case reports, reimbursement claims and billing reports, medical devices, and electronic health records. Like any other (health) data, RWD can be analysed in accordance with high-quality research methods, and its analysis can deliver valuable patient-centric insights complementing the information obtained from conventional clinical trials. Artificial intelligence application on RWD has the potential to detect a patient's health trajectory leading to personalized medicine and tailored treatment. This article reviews the benefits of artificial intelligence in cardiovascular prevention and management, focusing on diagnostic and therapeutic improvements without neglecting the limitations of this new scientific approach.

New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine.

Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

Gene expression in organoids: an expanding horizon.

Recent development of human three-dimensional organoid cultures has opened new doors and opportunities ranging from modelling human development in vitro to personalised cancer therapies. These new in vitro systems are opening new horizons to the classic understanding of human development and disease. However, the complexity and heterogeneity of these models requires cutting-edge techniques to capture and trace global changes in gene expression to enable identification of key players and uncover the underlying molecular mechanisms. Rapid development of sequencing approaches made possible global transcriptome analyses and epigenetic profiling. Despite challenges in organoid culture and handling, these techniques are now being adapted to embrace organoids derived from a wide range of human tissues. Here, we review current state-of-the-art multi-omics technologies, such as single-cell transcriptomics and chromatin accessibility assays, employed to study organoids as a model for development and a platform for precision medicine.

ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs.

Single-cell RNA sequencing technology has enabled in-depth analysis of intercellular heterogeneity in various diseases. However, its full potential for precision medicine has yet to be reached. Towards this, we propose A Single-cell Guided Pipeline to Aid Repurposing of Drugs (ASGARD) that defines a drug score to recommend drugs by considering all cell clusters to address the intercellular heterogeneity within each patient. ASGARD shows significantly better average accuracy on single-drug therapy compared to two bulk-cell-based drug repurposing methods. We also demonstrated that it performs considerably better than other cell cluster-level predicting methods. In addition, we validate ASGARD using the drug response prediction method TRANSACT with Triple-Negative-Breast-Cancer patient samples. We find that many top-ranked drugs are either approved by the Food and Drug Administration or in clinical trials treating corresponding diseases. In conclusion, ASGARD is a promising drug repurposing recommendation tool guided by single-cell RNA-seq for personalized medicine. ASGARD is free for educational use at https://github.com/lanagarmire/ASGARD .

Quantitative protein biomarker panels: a path to improved clinical practice through proteomics.

The utilisation of protein biomarker panels, rather than individual protein biomarkers, offers a more comprehensive representation of human physiology. It thus has the potential to improve diagnosis, prognosis and the differentiation of responders from nonresponders in the context of precision medicine. Although several proteomic techniques exist for measuring biomarker panels, the integration of proteomics into clinical practice has been limited. In this Commentary, we highlight the significance of quantitative protein biomarker panels in clinical medicine and outline the challenges that must be addressed in order to identify the most promising panels and implement them in clinical routines to realise their medical potential. Furthermore, we argue that the absolute quantification of protein panels through targeted mass spectrometric assays remains the most promising technology for translating proteomics into routine clinical applications due to its high flexibility, low sample costs, independence from affinity reagents and low entry barriers for its integration into existing laboratory workflows.

[Differences due to socio-economic status, genetic background and sex in cancer and precision medicine - An intersectional approach to close the care gap for marginalized groups]. / Unterschiede durch sozioökomische Benachteiligung, genetischen Hintergrund und Geschlecht bei Tumorerkrankungen.

Malignant tumor diseases constitute the 2nd most common cause of death and due to our extended life expectancy cancer per se has substantially increased, being highly prevalent after cardiovascular diseases. Evidence also generated from the COVID-19 pandemic, that defined gender differences exist in symptom and disease courses, and have advocated the need to assess gender, ethnic/racial and minority differences in cancer care and treatment more meticulously. It is becoming increasingly evident that in novel cancer care/precision oncology, representation of minorities, elderly and frail patients in clinical trials remains largely unbalanced, thus distribution of cancer success is iniquitous. This article focusses on these aspects and suggests solutions, how this can be improved.

COVID-19 Mortality in the Colorado Center for Personalized Medicine Biobank.

Over 6.37 million people have died from COVID-19 worldwide, but factors influencing COVID-19-related mortality remain understudied. We aimed to describe and identify risk factors for COVID-19 mortality in the Colorado Center for Personalized Medicine (CCPM) Biobank using integrated data sources, including Electronic Health Records (EHRs). We calculated cause-specific mortality and case-fatality rates for COVID-19 and common pre-existing health conditions defined by diagnostic phecodes and encounters in EHRs. We performed multivariable logistic regression analyses of the association between each pre-existing condition and COVID-19 mortality. Of the 155,859 Biobank participants enrolled as of July 2022, 20,797 had been diagnosed with COVID-19. Of 5334 Biobank participants who had died, 190 were attributed to COVID-19. The case-fatality rate was 0.91% and the COVID-19 mortality rate was 122 per 100,000 persons. The odds of dying from COVID-19 were significantly increased among older men, and those with 14 of the 61 pre-existing conditions tested, including hypertensive chronic kidney disease (OR: 10.14, 95% CI: 5.48, 19.16) and type 2 diabetes with renal manifestations (OR: 5.59, 95% CI: 3.42, 8.97). Male patients who are older and have pre-existing kidney diseases may be at higher risk for death from COVID-19 and may require special care.

Integrating AI/ML Models for Patient Stratification Leveraging Omics Dataset and Clinical Biomarkers from COVID-19 Patients: A Promising Approach to Personalized Medicine.

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare system. Identifying the genomics and clinical biomarkers for effective patient stratification and management is critical to controlling the spread of the disease. Omics datasets provide a wealth of information that can aid in understanding the underlying molecular mechanisms of COVID-19 and identifying potential biomarkers for patient stratification. Artificial intelligence (AI) and machine learning (ML) algorithms have been increasingly used to analyze large-scale omics and clinical datasets for patient stratification. In this manuscript, we demonstrate the recent advances and predictive accuracies in AI- and ML-based patient stratification modeling linking omics and clinical biomarker datasets, focusing on COVID-19 patients. Our ML model not only demonstrates that clinical features are enough of an indicator of COVID-19 severity and survival, but also infers what clinical features are more impactful, which makes our approach a useful guide for clinicians for prioritization best-fit therapeutics for a given cohort of patients. Moreover, with weighted gene network analysis, we are able to provide insights into gene networks that have a significant association with COVID-19 severity and clinical features. Finally, we have demonstrated the importance of clinical biomarkers in identifying high-risk patients and predicting disease progression.

Recent Development of Supramolecular Cancer Theranostics Based on Cyclodextrins: A Review.

With the development of personalized medical demands for precise diagnosis, rational management and effective cancer treatment, supramolecular theranostic systems have received widespread attention due to their reversibly switchable structures, sensitive response to biological stimuli and integration ability for multiple capabilities in a single platform with a programmable fashion. Cyclodextrins (CDs), benefiting from their excellent characteristics, such as non-toxicity, easy modification, unique host-guest properties, good biocompatibility, etc., as building blocks, serve as an all-purpose strategy for the fabrication of a supramolecular cancer theranostics nanodevice that is capable of biosafety, controllability, functionality and programmability. This review focuses on the supramolecular systems of CD-bioimaging probes, CD-drugs, CD-genes, CD-proteins, CD-photosensitizers and CD-photothermal agents as well as multicomponent cooperation systems with regards to building a nanodevice with functions of diagnosis and (or) therapeutics of cancer treatment. By introducing several state-of-the-art examples, emphasis will be placed on the design of various functional modules, the supramolecular interaction strategies under the fantastic topological structures and the hidden "bridge" between their structures and therapeutic efficacy, aiming for further comprehension of the important role of a cyclodextrin-based nanoplatform in advancing supramolecular cancer theranostics.

Mapping CircRNA-miRNA-mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection.

Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fully explored as yet. The current study aimed to holistically map the regulatory networks driven by SARS-CoV-2 related circRNAs, miRNAs and mRNAs to uncover plausible interactions and interplay amongst them in order to explore possible therapeutic options in SARS-CoV-2 infection. Patient datasets were analyzed systematically in a unified approach to explore circRNA, miRNA, and mRNA expression profiles. CircRNA-miRNA-mRNA network was constructed based on cytokine storm related circRNAs forming a total of 165 circRNA-miRNA-mRNA pairs. This study implies the potential regulatory role of the obtained circRNA-miRNA-mRNA network and proposes that two differentially expressed circRNAs hsa_circ_0080942 and hsa_circ_0080135 might serve as a potential theranostic agents for SARS-CoV-2 infection. Collectively, the results shed light on the functional role of circRNAs as ceRNAs to sponge miRNA and regulate mRNA expression during SARS-CoV-2 infection.

Rapid tissue prototyping with micro-organospheres.

In vitro tissue models hold great promise for modeling diseases and drug responses. Here, we used emulsion microfluidics to form micro-organospheres (MOSs), which are droplet-encapsulated miniature three-dimensional (3D) tissue models that can be established rapidly from patient tissues or cells. MOSs retain key biological features and responses to chemo-, targeted, and radiation therapies compared with organoids. The small size and large surface-to-volume ratio of MOSs enable various applications including quantitative assessment of nutrient dependence, pathogen-host interaction for anti-viral drug screening, and a rapid potency assay for chimeric antigen receptor (CAR)-T therapy. An automated MOS imaging pipeline combined with machine learning overcomes plating variation, distinguishes tumorspheres from stroma, differentiates cytostatic versus cytotoxic drug effects, and captures resistant clones and heterogeneity in drug response. This pipeline is capable of robust assessments of drug response at individual-tumorsphere resolution and provides a rapid and high-throughput therapeutic profiling platform for precision medicine.

Leading Edge: Intratumor Delivery of Monoclonal Antibodies for the Treatment of Solid Tumors.

Immunotherapies based on immune checkpoint blockade have shown remarkable clinical outcomes and durable responses in patients with many tumor types. Nevertheless, these therapies lack efficacy in most cancer patients, even causing severe adverse events in a small subset of patients, such as inflammatory disorders and hyper-progressive disease. To diminish the risk of developing serious toxicities, intratumor delivery of monoclonal antibodies could be a solution. Encouraging results have been shown in both preclinical and clinical studies. Thus, intratumor immunotherapy as a new strategy may retain efficacy while increasing safety. This approach is still an exploratory frontier in cancer research and opens up new possibilities for next-generation personalized medicine. Local intratumor delivery can be achieved through many means, but an attractive approach is the use of gene therapy vectors expressing mAbs inside the tumor mass. Here, we summarize basic, translational, and clinical results of intratumor mAb delivery, together with descriptions of non-viral and viral strategies for mAb delivery in preclinical and clinical development. Currently, this is an expanding research subject that will surely play a key role in the future of oncology.

Why "sex as a biological variable" conflicts with precision medicine initiatives.

Policies that require male-female sex comparisons in all areas of biomedical research conflict with the goal of improving health outcomes through context-sensitive individualization of medical care. Sex, like race, requires a rigorous, contextual approach in precision medicine. A "sex contextualist" approach to gender-inclusive medicine better aligns with this aim.

Applications of Gold and Silver Nanoparticles in Theranostics.

Nanotechnology sculptures the current scenario of science and technology. The word nano refers 'small' which ranges from 10 to 100 nm in size. Silver and gold nanoparticles can be synthesized at nanoscale and have unique biological properties like antibacterial, antifungal, antiviral, antiparasitic, antiplatelet, anti-inflammatory, and anti-tumor activity. In this mini review, we shall discuss the various applications of silver and gold nanoparticles (AuNPs) in the field of therapy, imaging, biomedical devices and in cancer diagnosis. The usage of silver nanoparticles(AgNPs) in dentistry and dental implants, therapeutic abilities like wound dressings, silver impregnated catheters, ventricular drainage catheters, combating orthopedic infections, and osteointegration will be elaborated. Gold nanoparticles in recent years have garnered large importance in bio medical applications. They are being used in diagnosis and have recently seen a surge in therapeutics. In this mini review, we shall see about the various applications of AuNP and AgNP, and highlight their evolution in theranostics.

Genome tumor profiling in endometrial cancer and clinical relevance in endometrial cancer management: a retrospective single-center experience.

OBJECTIVE: Next-generation sequencing (NGS) analysis has become an essential tool for endometrial carcinoma management. Moreover, molecular-driven therapies play an increasingly remarkable role in the era of precision oncology. This study aims to determine the clinical relevance of NGS testing in endometrial carcinoma management by analyzing the clinical benefit of NGS-driven targeted therapies. METHODS: A single-center retrospective study was conducted on 25 endometrial carcinoma patients who underwent Foundation Medicine CDx assay at Fondazione Policlinico Universitario Agostino Gemelli, IRCCS (Rome, Italy). Tumor samples were analyzed by Foundation One CDx. A descriptive analysis of tumor genome profiles was performed. Assessment of clinical benefit according to RECIST 1.1 criteria was analyzed for patients who received a tailored treatment according to actionable targets identified by NGS testing. RESULTS: Out of 25 endometrial carcinoma patients, 11 received targeted therapy. One patient was excluded from the clinical benefit assessment because of COVID-19-related death 1 month after starting the treatment. Eight of the remaining 10 patients benefited from targeted therapies, with an overall clinical benefit rate of 80%. A targeted agent belonging to the PI3K pathway was given to seven patients, with evidence of three partial responses (42.9%), three stable diseases (42.9%), and one progressive disease (14.2%) according to RECIST 1.1 criteria. One complete response (33.3%), one stable disease (33.3%), and one progressive disease (33.3%) were observed in the three patients treated with poly(ADP-ribose) polymerase (PARP) inhibitors according to their homologous recombination deficiency (HRD) status. CONCLUSION: This study highlights the importance of characterizing the mutation profile of patient tumors through NGS. Our findings suggest a clinical benefit of using NGS-driven targeted therapies in endometrial carcinoma patients. However, this personalized approach could benefit the health system in terms of cost-effectiveness by reducing the costs of inappropriate, ineffective, and often expensive treatments.