Expert Review of Precision Medicine and Drug Development最新文献

{"title":"Precision medicine in cardiac electrophysiology: where we are and where we need to go","authors":"A. Correa, S. Haider, W. Aronow","doi":"10.1080/23808993.2020.1754127","DOIUrl":"https://doi.org/10.1080/23808993.2020.1754127","url":null,"abstract":"ABSTRACT Introduction The treatment of arrhythmias is complex and there are many options including drug therapy, ablation techniques, and implantable devices. Selection of the right treatment strategy is complicated by the fact that patients with apparently the same clinical picture may respond differently to a given therapy, indicating some underlying molecular and cellular differences. We now know this is mediated in a large part by the genetics, and patients with similar phenotypes may have differing genotypes. Understanding this genotype–phenotype relationship is key in modern medicine. Areas covered We have conducted an exhaustive review of the literature surrounding the genetic basis of arrhythmias and have presented a comprehensive summary of the available information. We have demonstrated how understanding the underlying genetic and molecular derangements in arrhythmias has resulted in effective targeted treatments. We have further highlighted novel therapies in arrhythmia management based on emerging genomic research. Expert opinion The future of cardiac electrophysiology, and indeed all cardiovascular medicine, lies in the development of targeted therapies that can effectively treat the individual patient, based on their specific genetic attributes and variations. Future genetic research which drives the development of innovative therapies holds the promise of delivering such personalized therapies in cardiac electrophysiology.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1754127","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44856064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging precision therapies for gastric cancer","authors":"E. Cartwright, A. Athauda, I. Chau","doi":"10.1080/23808993.2020.1760089","DOIUrl":"https://doi.org/10.1080/23808993.2020.1760089","url":null,"abstract":"ABSTRACT Introduction Gastric cancer (GC) is a leading cause of cancer-related death and a significant global health burden. Chemotherapy remains the mainstay of treatment in advanced disease and only trastuzumab in combination with upfront fluoropyrimidine/platinum chemotherapy for human epidermal growth factor receptor 2 (HER2) positive disease and ramucirumab together with paclitaxel in the second line have demonstrated a significant survival benefit over chemotherapy alone. Despite the focus on a molecularly targeted approach, treatment gains have been modest and GC remains an area of great unmet need. Areas covered In this review, we provide an overview of the continuum of care in GC, the molecular characterization of GC, targeted therapies currently under investigation and the role of immunotherapy. Expert commentary Gastric cancer is a heterogeneous disease. A targeted approach based upon molecular phenotype holds promise for improving outcomes.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1760089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42725853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic background of coronary artery disease: clinical implications and perspectives","authors":"M. Camilli, G. Iannaccone, M. D. Del Buono, F. Crea, N. Aspromonte","doi":"10.1080/23808993.2020.1746640","DOIUrl":"https://doi.org/10.1080/23808993.2020.1746640","url":null,"abstract":"ABSTRACT Introduction Both genetic background and life-style factors influence coronary artery disease (CAD) individual risk and clinical manifestations. Areas covered Over the last decades, cardiovascular disease (CVD) emerged as the most important cause of morbidity and mortality worldwide, leading the scientific community to nourish increased interest in cardiovascular risk factors control. Several cohort studies have shown that a family history of ischemic heart disease is common among patients suffering from CAD, suggesting that genetic factors play a role of utmost relevance. The techniques used to study the genetic basis of these diseases have evolved from linkage studies to candidate gene studies and genome-wide association studies (GWAS). Linkage studies have been able to identify genetic variants associated with monogenic diseases, whereas genome-wide association studies have been more successful in determining genetic variants associated with complex diseases. However, family context transmits not only genetic information, but also attitudes and lifestyle habits which proved to significantly influence the overall cardiovascular risk. Expert opinion In the era of patient-tailored management, the aim of this review is to summarize the genetic background of patients with CAD, focusing on the most updated gene-targeted therapies, providing potential future perspectives of pharmacogenetics utility in daily clinical practice.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1746640","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46532013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacogenomics of drugs used to treat brain disorders","authors":"R. Cacabelos","doi":"10.1080/23808993.2020.1738217","DOIUrl":"https://doi.org/10.1080/23808993.2020.1738217","url":null,"abstract":"ABSTRACT Introduction Neuropsychiatric disorders (NPDs) (neurodevelopmental, mental, neurodegenerative, neurotoxic, complex disorders) are the third major problem of health in developed countries. About 10-20% of direct costs are attributed to pharmacological treatment; however, drug effectiveness is lower than 30% in most NPDs. Pharmacogenomics accounts for 60-90% variability in pharmacokinetics and pharmacodynamics. Areas covered Main areas covered include (i) organization of the pharmacogenetic machinery (pathogenic, mechanistic, metabolic, transporter, pleiotropic genes); (ii) pharmacogenomics of antidepressants, antipsychotics, anxiolytics, antiepileptics, anti-Alzheimer, anti-Parkinson, and anti-stroke drugs; and (iii) adverse drug reactions and pharmaco-resistance. Expert commentary The pharmacogenomics of NPDs is still primitive, but sufficient to help physicians to optimize pharmacological treatment by reducing ADRs (extrapyramidal symptoms, tardive dyskinesia, neurotoxicity, cerebrovascular damage) and unnecessary costs. Over 50% of psychotropic drugs are incorrectly prescribed. CYP enzymes participate in the metabolism of over 90% of drugs for the treatment of NPDs. Only 20% of the population is potentially extensive metabolizer for 80% of current psychotropic agents. Consequently, the introduction of pharmacogenomic procedures in the clinical setting is an urgent need for improving drug efficacy and safety.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1738217","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42585222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward gene therapy in rheumatoid arthritis","authors":"E. Young, D. Gould, S. Hart","doi":"10.1080/23808993.2020.1736942","DOIUrl":"https://doi.org/10.1080/23808993.2020.1736942","url":null,"abstract":"ABSTRACT Introduction Rheumatoid arthritis (RA) is an autoimmune disease of the joint, affecting 0.24% of the global population. Many patients only respond partially or not at all to current therapies while the systemic complications of immunosuppression associated with these treatments are unacceptable. Genetic therapies for RA have the potential to improve treatments by targeting delivery to the disease site, enhancing efficacy, and avoiding adverse effects. Areas covered The route of administration, delivery vector, nucleic acid type, and target gene must be carefully selected to develop an effective RA gene therapy. Drawing from examples of RA gene therapies investigated in animal models and clinical trials, this review discusses how these strategies may be used to translate RA gene therapy into the clinic. Expert opinion Existing RA treatments lack specificity to the joint. Genetic delivery systems can include targeting properties, such as disease-responsive promoters or cell-targeting moieties, to overcome this. Non-viral vectors, in particular, can be engineered easily to possess these properties and, unlike viral vectors, display low immunogenicity. Contrary to current drugs, gene therapy can be delivered intra-articularly, providing sustained levels of the therapeutic. Targeted vectors may also achieve this, but with a single systemic injection, simultaneously delivering the therapeutic to all affected joints.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1736942","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43798400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence-enabled electrocardiogram: can we identify patients with unrecognized atrial fibrillation?","authors":"A. Kashou, Itzhak Z. Attia, Xiaoxi Yao, P. Friedman, P. Noseworthy","doi":"10.1080/23808993.2020.1735935","DOIUrl":"https://doi.org/10.1080/23808993.2020.1735935","url":null,"abstract":"Atrial fibrillation (AF) is known to affect at least 30 million people worldwide [1,2], although this may be an underestimation. AF can be asymptomatic and fleeting and often goes undetected. In fact, it has been estimated that approximately one million Americans live with unrecognized AF [3]. The proportion of patients with paroxysmal AF versus persistent AF varies with age (with paroxysmal AF more common in patients <50 years), and it is estimated that about 25% of patients with AF have a paroxysmal pattern [4]. Identifying patients with undiagnosed AF is important as they have a fivefold increased risk of stroke [1,2] and the first manifestation of AF may be a disabling stroke. Furthermore, AF-related strokes carry a particularly poor prognosis [3,5]. When AF is recognized, interventions including oral anticoagulation or left atrial appendage closure can lower stroke risk and mortality [5,6]. Due to its frequently paroxysmal nature, AF is often under detected. Currently, prolonged electrocardiographic monitoring is implemented to detect patients with suspected AF – a process that is expensive, resource intensive, and at times poorly tolerated. In nearly 5,000 patients referred for continuous 24-hour monitoring, the prevalence of paroxysmal AF was 2.5% [7]. It has been estimated that even among a highrisk cohort of patients with ischemic strokes, 20% remain cryptogenic despite thorough diagnostic evaluation [5]. Apart from the low yield, long-term cardiac monitoring is resource intensive, expensive, and impractical for broad-scale application. A frequent clinical dilemma is whether or not to anticoagulate patients without documented AF based on incomplete information; studies of empiric anticoagulation following embolic stroke of uncertain source have found no benefit and harm (i.e. bleeding) [8,9]. Therefore, it is essential to detect paroxysmal AF to guide therapy to prevent stroke. Recently, we developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm using over 500,000 normal sinus rhythm standard 10-second 12-lead ECGs from over 180,000 patients using machine learning to identify those with a high likelihood of undocumented AF [10]. This work demonstrated that the application of a convolutional neural network (CNN) to a single ECG recorded during sinus rhythm could effectively identify paroxysmal AF, with an area under the receiver operator curve (AUC) of 0.87 (95% confidence interval [CI], 0.86–0.88), sensitivity of 79.0% (95% CI, 77.5–80.4%), specificity of 79.5% (95% CI, 79.0–79.9%), F1 score of 39.2% (95% CI, 38.1–40.3%), and overall accuracy of 79.4% (95% CI, 79.0–79.9%). The diagnostic yield improved when applied to patients with multiple ECGs (AUC 0.90). With the impressive performance of the AI-ECG algorithm, the question becomes: what is the AI seeing that the human eye is missing? Due to the nature of CNNs, identification of the signal features selected by the AI is currently not possible. We presume that ","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1735935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45795186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A meta-analysis on diagnostic accuracy of serum HLA-G level in breast cancer","authors":"S. Sayad, Seyyed Amir Yasin Ahmadi, M. Moradi, Reza Nekouian, K. Anbari, F. Shahsavar","doi":"10.1080/23808993.2020.1735936","DOIUrl":"https://doi.org/10.1080/23808993.2020.1735936","url":null,"abstract":"ABSTRACT Background: According to the role of human leukocyte antigen (HLA)-G in tumor progression and tumor escape from immune system as well as diagnostic role of biomarkers in breast cancer, this meta-analysis is designed to reach a pooled diagnostic accuracy for this biomarker. Methods: The present work is a meta-analysis on diagnostic accuracy studies using preferred reporting items for systematic reviews and meta-analyses guideline. All documents studying the serum level of HLA-G both in breast cancer patients and in healthy controls using receiver operating characteristics (ROC) curve with reporting area under ROC curve (AUC) were eligible for inclusion. Results: Five articles including 754 participants were eligible for quantitative synthesis. The range of AUC of the selected studies was 0.735–0.953. The pooled AUC was 0.922 (95% confidence interval [CI] 0.903–0.941) based on fixed effect model (P < 0.001) and 0.896 (95% CI 0.834–0.959) based on random effect model (P < 0.001). Conclusion: This meta-analysis updated the level of evidence for using serum HLA-G in diagnosis of breast cancer. However, this piece of evidence cannot be used as a diagnostic tool. This biomarker can be used for investigation of recurrence and response to treatment in future. Further studies are suggested to complete this evidence gap.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1735936","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42553731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic sequencing in severe epilepsy: a step closer to precision medicine","authors":"M. Esposito, Ilaria Lagorio, D. Peroni, A. Bonuccelli, A. Orsini, P. Striano","doi":"10.1080/23808993.2020.1732203","DOIUrl":"https://doi.org/10.1080/23808993.2020.1732203","url":null,"abstract":"ABSTRACT Introduction: The large number of different syndromes and seizure types, together with an inter-individual variable response to antiepileptic drugs (AEDs), makes the treatment of epilepsy challenging. Areas covered: Early infantile Epileptic encephalopathies (EIEE) are a group of neurodevelopmental disorders consisting of early-onset refractory seizures often accompanied by important developmental delay or regression. The last two decades have seen major advancement in the diagnosis of epilepsy thanks both to modern neuroimaging but, primarily, to new methods in molecular genetics and gene sequencing. The application of Next-Generation Sequencing (NGS) techniques has already helped to understand the genetic diversity and underlying pathogenic mechanisms in severe epilepsy of childhood. Furthermore, the use of Whole Exome Sequencing (WES) in parent–offspring trios has also helped to identify de novo mutations in patients with EIEE. Tailored treatments are already applicable in some monogenic epilepsy, but these are a minority of cases. Expert commentary: In our opinion, the future of epilepsy treatment will be multidisciplinary and possibly very different from the currently almost empiric approach and we are confident that a ‘precision medicine’ will be applicable on large scale.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1732203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43865201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Renal Cell Carcinoma: genomic landscape and clinical implications","authors":"G. Aurilio, M. Santoni, A. Cimadamore, F. Massari, M. Scarpelli, A. López-Beltran, Liang Cheng, N. Battelli, F. Nolè, R. Montironi","doi":"10.1080/23808993.2020.1733407","DOIUrl":"https://doi.org/10.1080/23808993.2020.1733407","url":null,"abstract":"ABSTRACT Introduction: The route to precision medicine in Renal Cell Carcinoma (RCC) is still full of challenges for worldwide uro-oncologists. This is mainly related to the high complexity of the genomic landscape of this tumor. Area covered: In this review, we focused on the most recent advances on RCC genomic scenario and its clinical and prognostic implications. In particular, we describe the main gene alterations that occur during RCC development and progression. At this purpose, we extensively analyzed the available literature from Pubmed archives on this field. Expert commentary: Summarizing all available data and taking separately each putative biomarker illustrated, we feel to conclude that there is a certain correlation between the alterations occurring in BAP1, PBMR1, and SETD2 genes and the prognosis of RCC patients. However, apart from this individual analysis, the mutational scenario in RCC seems to be even more intricate. The evolution of RCC will pass through the optimization of emerging laboratory techniques and to a progressive integration of these methodologies within daily clinical practice and in the context of randomized trials.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1733407","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48532608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The emerging role of precision medicine in the treatment of endometrial cancer","authors":"M. Toboni, D. Mutch","doi":"10.1080/23808993.2020.1732204","DOIUrl":"https://doi.org/10.1080/23808993.2020.1732204","url":null,"abstract":"ABSTRACT Introduction: Uterine cancer is the most common gynecologic malignancy with a high cure rate for early stage disease. Surgical and standard chemotherapy have provided modest results. Precision therapies targeting molecular pathways have recently produced encouraging results. Areas covered: This paper describes molecular pathways including PI3 K/AKT/mTor, VEGF, and angiogenesis, HER2/neu and EGFR, various endocrine therapies (including megace, medroxyprogesterone acetate, tamoxifen, letrozole, and anastrozole) and immune checkpoint inhibitors. An extensive literature search was completed including but not limited to PubMed, Google Scholar, and the studies conducted by the Gynecologic Oncology Group (GOG), to identify all relevant clinical trials opened to assess clinical benefit in patients with advanced endometrial cancer. Expert commentary: Molecular characterization of tumors provides an opportunity to tailor therapy to individual patients. With continual innovation, eventually real-time changes in treatment regimens can be made for individual patients to treat the ever-changing molecular landscape of the tumor. Immunotherapy remains the most promising treatment for advanced endometrial cancers.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2020-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1732204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46020809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}