Expert Review of Precision Medicine and Drug Development最新文献

{"title":"Is there a worthwhile value in personalizing radiation therapy for breast cancer patients? Time for a new paradigm in the older adult population","authors":"V. Salvestrini, M. Mariotti, M. Banini, C. Becherini, L. Visani, V. Scotti, I. Desideri, L. Livi, I. Meattini","doi":"10.1080/23808993.2021.1897463","DOIUrl":"https://doi.org/10.1080/23808993.2021.1897463","url":null,"abstract":"Over the past few decades, the world population has increased dramatically including a large number of elderly people. This explosion in population aging comes with a rising number of older adults who have potential multiple comorbidities and chronic illnesses, including cancer. Indeed, the prevalence of multimorbidity in older patients ranges from 55 to 98% [1]. Older cancer population represents a major public health issue and tailoring of treatment for these patients represents a paradigmatic example of treatment optimization. The number of elderly living with cancer disease is high due to the possibility of early diagnosis in the last years and the recent advances in cancer treatment strategy. Breast cancer is the most common malignancy among women, and it is estimated that around 20% of newly diagnosed patients will be aged more than 70 years. It has been widely reported that breast cancer-related mortality increases with age, regardless of disease stage. A specific management for this elder population is not defined because clinical trials usually do not include this subset of patients. The International Society of Geriatric Oncology in conjunction with the European Society of Breast Cancer Specialists recommended that any decision to treat cancer in the older adult woman with cancer must be individual and based on specific evaluation of the elderly woman and cancer. Physiological age, life expectancy, treatment tolerance, patient preference, potential barriers to the proposed treatments, competitive causes of mortality, and broad geriatric evaluation must be deeply considered [2]. Many investigators are recently focusing their efforts on optimization of cancer treatment strategy in older patients. With this regard, the ongoing COVID-19 pandemic has reinforced the urgent need also to minimize exposure of our patients to virus without compromising oncological outcome [3]. Currently, the standard of care for most patients affected by early invasive breast cancer still remains whole breast irradiation (WBI) after breastconserving surgery (BCS), since WBI showed a decrease in first recurrence also in low-risk elderly patients, with a lower absolute 10-year risk reduction of any locoregional or distant relapse [4,5]. The randomized CALGB 9343 trial evaluating 636 patients aged more than 70 years affected by invasive breast cancer treated with BCS and adjuvant tamoxifen with or without postoperative WBI demonstrated a significant decrease in the local relapse rate in favor of the group of patients receiving postoperative radiation therapy (RT) [6]. Shorter courses using moderate hypofractionated schedules should currently represent the standard of care for WBI, since a level-1 evidence exists on equivalent local control and late toxicity rates [7]. A brand-new approach to optimization of RT is the ultra-hypofractionated schedule given over just oneweek, feasible option in selected low-risk patients. The FAST Forward trial compared 26 Gy or 27 Gy ","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"157 - 160"},"PeriodicalIF":1.2,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1897463","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44763778","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 value of genotyping patients for the presence of HLA-C in the personalized treatment of psoriasis","authors":"M. Galluzzo, V. Manfreda, Alessandra Petruzzellis, L. Bianchi, M. Talamonti","doi":"10.1080/23808993.2021.1878022","DOIUrl":"https://doi.org/10.1080/23808993.2021.1878022","url":null,"abstract":"ABSTRACT Introduction: Some cases of psoriasis still unfortunately do not respond, do not respond adequately or lose response to biotechnological therapies available to help control psoriasis. The common solution is to switch to other biological drugs, with a corresponding increase in pharmaceutical costs. Genetic polymorphisms have also recently been shown to influence the response of psoriasis patients to biological drugs. Areas covered: The PubMed databases were searched for articles regarding HLA-C and response to biological therapies. Additional publications were collected from references identified in articles and related citations in PubMed. Expert opinion: The clinical response to a specific biological drug may be correlated with genetic variations. Since genetic variations lead to different molecular pathways, identifying genetic markers in psoriasis patients that can predict a response to biologics is of fundamental importance. In this sense, recent evidences published in literature, suggest that HLA-C*06:02 typifies a molecularly different subtype of psoriasis whose maintenance and amplification are strongly controlled by IL12/23 signaling and therefore more responsive to the selective blockade of this signaling pathway, and it is not yet possible to exclude that this allele also influences the response to the most recent anti-IL-17 drugs.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"131 - 137"},"PeriodicalIF":1.2,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1878022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41851470","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 analysis of primary renal cell carcinoma to determine treatment approaches","authors":"V. Stühler, S. Rausch, A. Stenzl, J. Bedke","doi":"10.1080/23808993.2021.1874822","DOIUrl":"https://doi.org/10.1080/23808993.2021.1874822","url":null,"abstract":"ABSTRACT Introduction To date, there is no validated predictive biomarker available that guides treatment selection between an immune-based or an anti-VEGF-based regimen in patients with metastatic renal cell carcinoma (mRCC). Here, valid biomarkers could increase the benefit of therapy and thereby safe unnecessary toxicity. Recently, phase II and III clinical trials have shown a correlation between molecular clusters and responses to targeted therapy with tyrosine kinase inhibitors (TKIs), immune checkpoint inhibitors (ICIs) or as combination of both in patients with clear-cell mRCC. Areas covered This review discusses recent advances in the discovery of predictive biomarkers, highlighting the growing role of genetic analysis for treatment selection and its potential impact on precision medicine in mRCC. In this context, we extensively analyzed the available literature from Pubmed’s archives on this topic. Expert opinion Molecular subclassification which predicts responses to TKI, or ICI therapy is an exciting step toward personalized medicine in mRCC, but this still requires validation. However, intratumoral heterogeneity in relationship to the predictive power of molecular analysis of the primary tumor and circulating tumor DNA is challenging and requires further analysis.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"107 - 115"},"PeriodicalIF":1.2,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1874822","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44334175","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":"Global personalization of antibiotic therapy in critically ill patients","authors":"D. Lonsdale, J. Lipman","doi":"10.1080/23808993.2021.1874823","DOIUrl":"https://doi.org/10.1080/23808993.2021.1874823","url":null,"abstract":"ABSTRACT Introduction: Sepsis from bacterial infection remains a significant cause of morbidity and mortality. Antibiotic use continues to increase in the community and secondary care. This is driven by the potential benefits to the individual patient of a course of antibiotics. Far less attention is given to the potential adverse effects of antibiotic use in our view. These costs may be significant to both the individual and society. Areas covered: We review the evidence underpinning the costs and benefits of antibiotic use. We also discuss strategies to personalize medicine in this area that maximize the benefit to cost ratio for patients and society. Expert opinion: The body’s innate immune response to infection is similar to that of other inflammatory insults. Our view is as clinicians we need to differentiate these responses and hence require an accurate method to determine a diagnosis of a bacterial infection and monitor illness severity. Without this, clinicians will continue to prescribe significant volumes of unnecessary antibiotics in cases of non-bacterial inflammatory states.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"87 - 93"},"PeriodicalIF":1.2,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1874823","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45396495","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":"Initial independent validation of a genomic heart failure survival prediction algorithm","authors":"G. Bondar, I. Silacheva, T. Bao, S. Deshmukh, N. Kulkarni, T. Nakade, T. Grogan, D. Elashoff, M. Deng","doi":"10.1080/23808993.2021.1882847","DOIUrl":"https://doi.org/10.1080/23808993.2021.1882847","url":null,"abstract":"ABSTRACT Background Biological determinants of survival in advanced heart failure (AdHF) are linked to systems biological properties of disease severity including age, comorbidities, and frailty. We hypothesize that an algorithm trained to predict the survival in severely ill mechanical circulatory support (MCS) AdHF patients can be independently validated in AdHF-cohorts of varying severity undergoing etiology-specific interventions including heart transplantation (HTx), transcatheter aortic valve replacement (TAVR), and continued guidelines directed medical therapy (GDMT). Research Design & Methods We independently validated our previously published multi-dimensional algorithm, based on 4 clinical parameters and 12 transcriptomic biomarkers, and trained in AdHF patients undergoing MCS-surgery (n = 29), in AdHF patients undergoing TAVR, HTx, MCS, and GDMT-interventions (n = 48). Results In the independent validation cohort, our algorithm demonstrated 71% sensitivity, 90% specificity, 56% positive predictive value, and 95% negative predictive value, allowing for construction of a prototype survival prediction score. While prediction of 1-year survival using clinical parameters alone achieved an AUC = 0.69, addition of 12 differentially expressed genes to the clinical model improved the AUC = 0.90. Conclusions Our initial validation data suggests that the proposed multi-dimensional algorithm is applicable across various AdHF-risk groups and Surgical-Interventional Therapies (S/IT), increasing survival prediction accuracy compared to clinical data alone and warranting further study in larger cohorts.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"139 - 145"},"PeriodicalIF":1.2,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1882847","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46192690","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":"Mutation-dependent treatment approaches for patients with complex multiple myeloma","authors":"F. Theodorakakou, M. Dimopoulos, E. Kastritis","doi":"10.1080/23808993.2021.1893605","DOIUrl":"https://doi.org/10.1080/23808993.2021.1893605","url":null,"abstract":"ABSTRACT Introduction: Multiple myeloma is a complex hematologic malignancy that is considered incurable. The increasing comprehension of the genomic complexity has provided new insights into the therapeutic landscape of the disease. Next-generation sequencing studies have identified numerous driver gene mutations and alterations in signaling pathways, implicated in pathobiology and disease progression. Areas covered: Molecular tailored therapies against specific genetic alterations are under development in preclinical studies. These alterations include mutations in BRAF/KRAS/NRAS, FGFR3, overexpression of BCL2, and abberation in pathways such as MYC, JAK/STAT, NFκB, and PI3K/AKT/mTOR. Some of these novel anti-myeloma agents have entered clinical setting, as well. The question of whether these agents should be given as monotherapy or in combination with contemporary regimens is being addressed in ongoing trials. In the current review we present an up-to-date overview of targeted therapies MM. Expert opinion: Although fully personalized MM therapy is nowhere near, new technologies that allow rapid, detailed (and at a feasible cost) evaluation of the genetic content of myeloma on an individual basis may actually allow the development of therapies based on molecular profiling. These regimens may also have the potential to predict prognosis and achieve durable responses when established therapies are unable to overcome drug resistance.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"189 - 201"},"PeriodicalIF":1.2,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1893605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43391171","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 combination of encorafenib and binimetinib for the treatment of patients with BRAF-mutated advanced, unresectable, or metastatic melanoma: an update","authors":"E. McClure, Ayushi S. Patel, Michael J. Carr, James X. Sun, J. Zager","doi":"10.1080/23808993.2021.1847639","DOIUrl":"https://doi.org/10.1080/23808993.2021.1847639","url":null,"abstract":"ABSTRACT Introduction: In the treatment of advanced BRAF-mutated melanoma, selective regulation of the MAPK pathway with BRAF and MEK inhibition has emerged as one of the mainstays of therapy. Areas covered: Introduction of MAPK pathway. Current data on BRAF inhibition from phase I, II, and III trials in the setting of unresectable disease. Current data on encorafenib and binietinib, their chemistry, pharmacokinetic, and pharmacodynamic properties. Discussion on use of encorafenib therapy as a single agent as well as in combination with binimetinib and other systemic therapies. Expert opinion: BRAF inhibition with encorafenib exhibits substantial antitumor activity with less paradoxical MAPK pathway activation leading to treatment resistance. Combination therapy with binimetinib improves response rate, progression-free survival, and overall survival in patients with BRAF-mutated unresectable, metastatic melanoma. Serious adverse events, including development of cutaneous malignancies, are reported at lower rates with combination therapy, while less severe events such as pyrexia can be more common.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 1","pages":"19 - 29"},"PeriodicalIF":1.2,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1847639","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46573912","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":"How feasible is the stratification of osteoarthritis phenotypes by means of artificial intelligence?","authors":"Amanda E Nelson","doi":"10.1080/23808993.2021.1848424","DOIUrl":"https://doi.org/10.1080/23808993.2021.1848424","url":null,"abstract":"Osteoarthritis (OA) is a common and serious disease that involves all of the tissues of an affected joint (e.g., cartilage, bone, meniscus, tendon/ligament, synovium) and can affect one or multiple joints in an individual person, most often the finger joints, knees, hips, and spine [1]. OA is a major and growing contributor to disability worldwide and is associated with increased comorbidity and excess mortality [1]. Management of OA is focused on modestly effective lifestyle/behavioral interventions such as increased physical activity and weight loss, with pharmacologic therapies directed toward temporary symptomatic relief [2]. Although many clinical trials have been conducted, there are still no effective disease-modifying therapies, no proven way to prevent progression, and no cure. This is at least in part due to the lack of appreciation of, and accounting for, the heterogeneity of this complex disease in trials to date [3]. In general, most trials have enrolled all individuals with knee OA defined as the presence of symptoms (e.g., pain, aching, and stiffness) and moderate to severe radiographic change (e.g., osteophytes or joint space narrowing) in at least one knee. This does not account for the diverse mechanisms of disease development, which can be due to mechanical dysfunction, prior injury, metabolic factors, inflammation, or combinations of these. Nor does it address the diversity of presentations, burden of disease (i.e., number/severity of involved joints), chronicity, or numerous other aspects of the disease process in a given individual that may subsequently affect their response to the proposed therapy. This brief editorial review seeks to summarize recent work in the area of machine learning and osteoarthritis phenotyping.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 2","pages":"83-85"},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1848424","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25556237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Math, magnets, and medicine: enabling personalized oncology.","authors":"David A Hormuth, Angela M Jarrett, Guillermo Lorenzo, Ernesto A B F Lima, Chengyue Wu, Caroline Chung, Debra Patt, Thomas E Yankeelov","doi":"10.1080/23808993.2021.1878023","DOIUrl":"10.1080/23808993.2021.1878023","url":null,"abstract":"Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA; Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX, USA; Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy; Texas Advanced Computing Center, The University of Texas at Austin, Austin, TX, USA; Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Texas Oncology, Austin, TX, USA; Departments of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA; Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX, USA; Department of Oncology, The University of Texas at Austin, Austin, TX, USA; Departments of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 2","pages":"79-81"},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1878023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38941876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GUCY2C as a biomarker to target precision therapies for patients with colorectal cancer.","authors":"Amanda N Lisby,&nbsp;John C Flickinger,&nbsp;Babar Bashir,&nbsp;Megan Weindorfer,&nbsp;Sanjna Shelukar,&nbsp;Madison Crutcher,&nbsp;Adam E Snook,&nbsp;Scott A Waldman","doi":"10.1080/23808993.2021.1876518","DOIUrl":"https://doi.org/10.1080/23808993.2021.1876518","url":null,"abstract":"<p><strong>Introduction: </strong>Colorectal cancer (CRC) is one of the most-deadly malignancies worldwide. Current therapeutic regimens for CRC patients are relatively generic, based primarily on disease type and stage, with little variation. As the field of molecular oncology advances, so too must therapeutic management of CRC. Understanding molecular heterogeneity has led to a new-found promotion for precision therapy in CRC; underlining the diversity of molecularly targeted therapies based on individual tumor characteristics.</p><p><strong>Areas covered: </strong>We review current approaches for the treatment of CRC and discuss the potential of precision therapy in advanced CRC. We highlight the utility of the intestinal protein guanylyl cyclase C (GUCY2C), as a multi-purpose biomarker and unique therapeutic target in CRC. Here, we summarize current GUCY2C-targeted approaches for treatment of CRC.</p><p><strong>Expert opinion: </strong>The GUCY2C biomarker has multi-faceted utility in medicine. Developmental investment of GUCY2C as a diagnostic and therapeutic biomarker offers a variety of options taking the molecular characteristics of cancer into account. From GUCY2C-targeted therapies, namely cancer vaccines, CAR-T cells, and monoclonal antibodies, to GUCY2C agonists for chemoprevention in those who are at high risk for developing colorectal cancer, the utility of this protein provides many avenues for exploration with significance in the field of precision medicine.</p>","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":"6 2","pages":"117-129"},"PeriodicalIF":1.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2021.1876518","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38941879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}