Pub Date : 2020-03-04DOI: 10.1080/23808993.2020.1735935
A. Kashou, Itzhak Z. Attia, Xiaoxi Yao, P. Friedman, P. Noseworthy
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
{"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":"5 1","pages":"119 - 121"},"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}
Pub Date : 2020-03-03DOI: 10.1080/23808993.2020.1735936
S. Sayad, Seyyed Amir Yasin Ahmadi, M. Moradi, Reza Nekouian, K. Anbari, F. Shahsavar
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.
{"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":"5 1","pages":"109 - 114"},"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}
Pub Date : 2020-02-25DOI: 10.1080/23808993.2020.1732203
M. Esposito, Ilaria Lagorio, D. Peroni, A. Bonuccelli, A. Orsini, P. Striano
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.
{"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":"5 1","pages":"101 - 108"},"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}
Pub Date : 2020-02-24DOI: 10.1080/23808993.2020.1733407
G. Aurilio, M. Santoni, A. Cimadamore, F. Massari, M. Scarpelli, A. López-Beltran, Liang Cheng, N. Battelli, F. Nolè, R. Montironi
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.
{"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":"5 1","pages":"100 - 95"},"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}
Pub Date : 2020-02-20DOI: 10.1080/23808993.2020.1732204
M. Toboni, D. Mutch
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.
{"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":"5 1","pages":"87 - 93"},"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}
Pub Date : 2020-02-12DOI: 10.1080/23808993.2020.1727739
M. Randhawa, Robert J. Jones
One of the most important advances in the management of advanced prostate cancer in recent years, has been the utilization of drugs, previously reserved for those with metastatic castration-resista...
{"title":"Can we use disease burden to predict docetaxel activity in metastatic hormone-sensitive prostate cancer?","authors":"M. Randhawa, Robert J. Jones","doi":"10.1080/23808993.2020.1727739","DOIUrl":"https://doi.org/10.1080/23808993.2020.1727739","url":null,"abstract":"One of the most important advances in the management of advanced prostate cancer in recent years, has been the utilization of drugs, previously reserved for those with metastatic castration-resista...","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"5 1","pages":"55 - 57"},"PeriodicalIF":1.2,"publicationDate":"2020-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1727739","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46354649","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}
Pub Date : 2020-01-02DOI: 10.1080/23808993.2020.1720508
S. Morganti, G. Curigliano
ABSTRACT Introduction: Hormone receptor-positive (HR+) breast cancer (BC) is the most frequent BC subtype, for which estrogen receptor (ER)-signaling blockade still represents the cornerstone of treatments. Nevertheless, almost all HR+ BC patients develop resistance to endocrine therapy, a critical therapeutic unmet need for BC patients. Recent advances in genomic medicine allowed for a more detailed identification and better characterization of the mechanisms underlining endocrine resistance and led to the development of targeted agents potentially able to restore endocrine sensitivity, thus improving disease control and potentially survival. Areas covered: New drugs in the early phase of development for HR-positive metastatic BC (MBC) treatment are here outlined. PI3K/AKT/mTOR, FGFR, and IGFRs are the main pathways addressed, and evidences about HER2 blockade in triple-positive diseases are also reported. New hormonal agents active against estrogen receptor 1 (ESR1)-mutant MBC are presented. A brief mention of biological agents not targeting intracellular signaling hubs, such as histone-deacetylase inhibitors and immunotherapy drugs, is finally provided. Expert opinion: promising results have been reported for the majority of new drugs under development. Despite this, a ‘precision medicine approach’ still has to demonstrate a benefit in this disease. Identification of reliable predictive biomarkers should be a key objective of future researches.
{"title":"Moving beyond endocrine therapy for luminal metastatic breast cancer in the precision medicine era: looking for new targets","authors":"S. Morganti, G. Curigliano","doi":"10.1080/23808993.2020.1720508","DOIUrl":"https://doi.org/10.1080/23808993.2020.1720508","url":null,"abstract":"ABSTRACT Introduction: Hormone receptor-positive (HR+) breast cancer (BC) is the most frequent BC subtype, for which estrogen receptor (ER)-signaling blockade still represents the cornerstone of treatments. Nevertheless, almost all HR+ BC patients develop resistance to endocrine therapy, a critical therapeutic unmet need for BC patients. Recent advances in genomic medicine allowed for a more detailed identification and better characterization of the mechanisms underlining endocrine resistance and led to the development of targeted agents potentially able to restore endocrine sensitivity, thus improving disease control and potentially survival. Areas covered: New drugs in the early phase of development for HR-positive metastatic BC (MBC) treatment are here outlined. PI3K/AKT/mTOR, FGFR, and IGFRs are the main pathways addressed, and evidences about HER2 blockade in triple-positive diseases are also reported. New hormonal agents active against estrogen receptor 1 (ESR1)-mutant MBC are presented. A brief mention of biological agents not targeting intracellular signaling hubs, such as histone-deacetylase inhibitors and immunotherapy drugs, is finally provided. Expert opinion: promising results have been reported for the majority of new drugs under development. Despite this, a ‘precision medicine approach’ still has to demonstrate a benefit in this disease. Identification of reliable predictive biomarkers should be a key objective of future researches.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"53 5","pages":"22 - 7"},"PeriodicalIF":1.2,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1720508","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41296997","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}
Pub Date : 2020-01-02DOI: 10.1080/23808993.2020.1724509
V. Chandran, P. Rahman
ABSTRACT Introduction: Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis for which effective targeted therapies are now available. However, despite such advances up to 40% of patients fail to meet the primary endpoint in clinical trials. Current approach to therapy does not take it account clinical or molecular heterogeneity and is based on trial-and-error. It is envisioned that choosing therapies based on appropriate molecular biomarker profiles will help choose the appropriate therapy for a patient and as such lead to better treatment outcomes with reduced costs and less exposure to less effective therapies. Areas covered: The paper introduces PsA and briefly describes the clinical phenotype, pathogenesis, and current therapies. Current literature on biomarkers relating to PsA treatment response is reviewed. Limitations of the current approach, potential solutions to issues identified, and a path forward for research and potential clinical application in this area are discussed. Expert opinion: The likelihood that the current siloed approach to biomarker discovery will lead to meaningful clinically actionable tests to facilitate precision medicine in PsA is low. We envision that with collaborative and harmonized effort by all stakeholders using an inter-omic approach will lead to the development of robust predictive biomarkers for PsA treatment response.
{"title":"Predicting therapeutic response through biomarker analysis in psoriatic arthritis, an example of precision medicine","authors":"V. Chandran, P. Rahman","doi":"10.1080/23808993.2020.1724509","DOIUrl":"https://doi.org/10.1080/23808993.2020.1724509","url":null,"abstract":"ABSTRACT Introduction: Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis for which effective targeted therapies are now available. However, despite such advances up to 40% of patients fail to meet the primary endpoint in clinical trials. Current approach to therapy does not take it account clinical or molecular heterogeneity and is based on trial-and-error. It is envisioned that choosing therapies based on appropriate molecular biomarker profiles will help choose the appropriate therapy for a patient and as such lead to better treatment outcomes with reduced costs and less exposure to less effective therapies. Areas covered: The paper introduces PsA and briefly describes the clinical phenotype, pathogenesis, and current therapies. Current literature on biomarkers relating to PsA treatment response is reviewed. Limitations of the current approach, potential solutions to issues identified, and a path forward for research and potential clinical application in this area are discussed. Expert opinion: The likelihood that the current siloed approach to biomarker discovery will lead to meaningful clinically actionable tests to facilitate precision medicine in PsA is low. We envision that with collaborative and harmonized effort by all stakeholders using an inter-omic approach will lead to the development of robust predictive biomarkers for PsA treatment response.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"5 1","pages":"35 - 42"},"PeriodicalIF":1.2,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1724509","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42580454","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}
Pub Date : 2020-01-02DOI: 10.1080/23808993.2020.1707077
H. Büning, A. Schambach, Michael A. Morgan, Axel Rossi, Helena Wichova, H. Staecker, A. Warnecke, T. Lenarz
ABSTRACT Introduction: Although sensorineural hearing loss (SNHL) is the most common neurodegenerative disease in humans, no approved pharmaceutical interventions are currently available. The progression of inherited as well as acquired forms of hearing loss can be altered by transferring single genes to distinct cell types of the ear inner. The inner ear is an attractive target for gene therapy given its small size and localized anatomic nature, which is accessible through routine surgical approaches. Areas covered: SNHL is the symptom of a diverse group of disorders with specific requirements regarding the timing of therapeutic intervention, the target cell population, the delivery system and, of course, the therapeutic active “substance’. Expert opinion: Despite these challenges, which will be discussed in the following paper, the first human gene therapy clinical trial for an inner ear disease is already initiated, making this the perfect time to translate a great variety of therapeutic approaches from the laboratory into clinical routine.
{"title":"Challenges and advances in translating gene therapy for hearing disorders","authors":"H. Büning, A. Schambach, Michael A. Morgan, Axel Rossi, Helena Wichova, H. Staecker, A. Warnecke, T. Lenarz","doi":"10.1080/23808993.2020.1707077","DOIUrl":"https://doi.org/10.1080/23808993.2020.1707077","url":null,"abstract":"ABSTRACT Introduction: Although sensorineural hearing loss (SNHL) is the most common neurodegenerative disease in humans, no approved pharmaceutical interventions are currently available. The progression of inherited as well as acquired forms of hearing loss can be altered by transferring single genes to distinct cell types of the ear inner. The inner ear is an attractive target for gene therapy given its small size and localized anatomic nature, which is accessible through routine surgical approaches. Areas covered: SNHL is the symptom of a diverse group of disorders with specific requirements regarding the timing of therapeutic intervention, the target cell population, the delivery system and, of course, the therapeutic active “substance’. Expert opinion: Despite these challenges, which will be discussed in the following paper, the first human gene therapy clinical trial for an inner ear disease is already initiated, making this the perfect time to translate a great variety of therapeutic approaches from the laboratory into clinical routine.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"5 1","pages":"23 - 34"},"PeriodicalIF":1.2,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1707077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43853547","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}
Pub Date : 2020-01-02DOI: 10.1080/23808993.2020.1715794
Amira Abugomaa, M. Elbadawy
Cancer is the main health problem with high morbidity and mortality. The worldwide annual incidence and deaths from cancers are estimated in millions [1,2]. Hence, cancer therapy must be continuously promoted and developed. Cancer study, like in other diseases, highly depends on representative and reliable models. However, the tumor is not uniform, but rather a heterogenic and highly variable and complex than other diseases, rendering its study extremely difficult, expensive [3]. The most common treatment methods for cancers are based on surgery [4], chemotherapy [5], radiotherapy [6], and immunotherapy [7]. The response of cancers to these various treatment strategies differs according to tumor subtype, clinical stage, and associated risk factors and unfortunately fails to limit the progression of cancer in various cases. Even the same tumor of the same organ or tissue differs in response to therapy among patients and the recurrence and metastasis which are associated with high resistance to therapy are main issues [8]. Also, chemotherapy affects the quality of life because of its potential side effects and therefore disfavored by many patients. Therefore, suitable models to expect the treatment response with high precision are of extreme need toward more personalized treatment of patients. Experimental models are assigned to understand the pathobiology, identify diagnostic and prognostic biomarkers of cancer progression and establish novel potent and effective therapies. To date, the available treatment protocols seem inadequate to prevent the resistance to therapy as well as the recurrence and progression of cancer. Therefore, several experimental models of to study cancer development and progression including rats and mice as well as the in vitro culture models of cell line, 2D cell, induced pluripotent stem cell (iPSCs) lines, spheroids, 3D organoids, organotypic tissue slice cultures, patient-derived tumor xenografts are developed [9–11] and certainly, they confer valuable tools for preclinical pharmacological assessment. Cancer stem cells (CSCs) are tumor-initiating cells capable of conserving cellular heterogeneity, self-renewal, epithelial to mesenchymal transition, differentiation to form all kind cells in a given tumor [12] and drive the tumor growth, metastasis and most importantly, the resistance to conventional anticancer agents [13–22]. Therefore, the total eradication of CSCs is crucial for the successful treatment of cancers. Thus, understanding the mechanism of response and resistance of CSCs to therapy and developing personalized therapy is the cornerstone for treatments of cancer in cancer patients. Currently, the selection of the correct tool to use in the laboratory to elucidate the mechanism of CSCs’ resistance to therapy can depend on the question on hand, but also on the resources (and knowledge) available. Among them, organoids constitute the more reasonable method in recapitulating the in vivo microenvironment of the tu
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