Implementation Of Precision Medicine Research Articles

QPGx-CARES: Qatar pharmacogenetics clinical applications and research enhancement strategies.

Pharmacogenetic (PGx)-informed medication prescription is a cutting-edge genomic application in contemporary medicine, offering the potential to overcome the conventional "trial-and-error" approach in drug prescription. The ability to use an individual's genetic profile to predict drug responses allows for personalized drug and dosage selection, thereby enhancing the safety and efficacy of treatments. However, despite significant scientific and clinical advancements in PGx, its integration into routine healthcare practices remains limited. To address this gap, the Qatar Genome Program (QGP) has embarked on an ambitious initiative known as QPGx-CARES (Qatar Pharmacogenetics Clinical Applications and Research Enhancement Strategies), which aims to set a roadmap for optimizing PGx research and clinical implementation on a national scale. The goal of QPGx-CARES initiative is to integrate PGx testing into clinical settings with the aim of improving patient health outcomes. In 2022, QGP initiated several implementation projects in various clinical settings. These projects aimed to evaluate the clinical utility of PGx testing, gather valuable insights into the effective dissemination of PGx data to healthcare professionals and patients, and identify the gaps and the challenges for wider adoption. QPGx-CARES strategy aimed to integrate evidence-based PGx findings into clinical practice, focusing on implementing PGx testing for cardiovascular medications, supported by robust scientific evidence. The current initiative sets a precedent for the nationwide implementation of precision medicine across diverse clinical domains.

IMPRESS-Norway: improving public cancer care by implementing precision medicine in Norway; inclusion rates and preliminary results.

In Norway, comprehensive molecular tumour profiling is implemented as part of the public healthcare system. A substantial number of tumours harbour potentially targetable molecular alterations. Therapy outcomes may improve if targeted treatments are matched with actionable genomic alterations. In the IMPRESS-Norway trial (NCT04817956), patients are treated with drugs outside the labelled indication based on their tumours molecular profile. IMPRESS-Norway is a national, prospective, non-randomised, precision cancer medicine trial, offering treatment to patients with advanced-stage disease, progressing on standard treatment. Comprehensive next-generation sequencing, TruSight Oncology 500, is used for screening. Patients with tumours harbouring molecular alterations with matched targeted therapies available in IMPRESS-Norway, are offered treatment. Currently, 24 drugs are available in the study. Primary study endpoints are percentage of patients offered treatment in the trial, and disease control rate (DCR) defined as complete or partial response or stable disease in evaluable patients at 16 weeks (W16) of treatment. Secondary endpoint presented is DCR in all treated patients. Between April 2021 and October 2023, 1,167 patients were screened, and an actionable mutation with matching drug was identified for 358 patients. By the data cut off 186 patients have initiated treatment, 170 had a minimum follow-up time of 16 weeks, and 145 also had evaluable disease. In patients with evaluable disease, the DCR was 40% (58/145). Secondary endpoint analysis of DCR in all treated patients, showed DCR of 34% (58/170). Precision cancer medicine demonstrates encouraging clinical effect in a subset of patients included in the IMPRESS-Norway trial.

Precision Medicine in Congenital Heart Disease, Rheumatic Heart Disease, and Kawasaki Disease of Children: An Overview of Literature

Congenital heart disease and common acquired heart diseases like Kawasaki disease and rheumatic heart disease are prevalent cardiovascular conditions in children worldwide. Despite the availability of treatment options, they continue to be significant contributors to morbidity and mortality. Advancements in early diagnosis, improvements in treatment approaches, and overcoming resistance to available treatments are crucial to reduce morbidity. Researchers have turned to precision medicine to tackle these challenges. We aimed to analyze the existing literature concerning the utilization of precision medicine in congenital heart disease, rheumatic heart disease, and Kawasaki disease. The emphasis is placed on comprehending the key themes explored in these studies and evaluating the present state of their clinical integration. The central theme of most studies revolves around the examination of genetic factors. Despite promising research outcomes, limitations in these studies indicate that the clinical implementation of precision medicine in these conditions remains a distant prospect, necessitating additional exploration and attention to confounding factors.

Revitalizing Postoperative Pain Management in Enhanced Recovery After Surgery via Inter-departmental Collaboration Toward Precision Medicine: A Narrative Review.

This narrative review explores the crucial aspects of postoperative pain management within the framework of Enhanced Recovery After Surgery (ERAS). It emphasizes the significance of effective and secure pain management, highlighting its impact on patient well-being, surgical outcomes, and hospital stays. The inadequacy of perioperative pain relief increases the risk of persistent postoperative pain, emphasizing the need to challenge the notion that pain is expected after surgery. The goals of postoperative pain management extend beyond mere relief, encompassing comfortable sleep, pain-free rest, and liberation from pain during initial recovery. Inadequate pain management can lead to complications such as heightened postoperative bleeding and an increased risk of thrombosis. The review delves into various analgesic methods, their complications, and safety measures.ERASprograms, focused on reducing complications and medical costs, emphasize the importance of judicious postoperative pain management and active rehabilitation. The review discusses complications associated with analgesic methods like opioids, epidural analgesia, and adjuvant analgesics. Collaboration within the perioperative management team is crucial for effective postoperative pain relief. Interdepartmental collaboration is essential for evaluating surgical procedures, analgesic methods, and crisis management strategies. The review concludes by integrating precision medicine into postoperative pain management, emphasizing the potential of genetic information in assessing pain sensitivity. It underscores the importance of inter-departmental collaboration and information gathering for the successful implementation of precision medicine tailored to each facility's perioperative management systems. Additionally, the impact of artificial intelligence (AI) on preoperative risk assessment and innovative monitoring techniques is discussed, paving the way for the advancement of precision medicine in postoperative pain management.

Contextual factors influencing the equitable implementation of precision medicine in routine cancer care in Belgium.

Precision medicine represents a paradigm shift in health systems, moving from a one-size-fits-all approach to a more individualized form of care, spanning multiple scientific disciplines including drug discovery, genomics, and health communication. This study aims to explore the contextual factors influencing the equitable implementation of precision medicine in Belgium for incorporating precision medicine into routine cancer care within the Belgian health system. As part of a foresight study, our approach evaluates critical factors affecting the implementation of precision oncology. The study scrutinizes contextual, i.e. demographic, economic, societal, technological, environmental, and political/policy-related (DESTEP) factors, identified through a comprehensive literature review and validated by a multidisciplinary group at the Belgian Cancer Center, Sciensano. An expert survey further assesses the importance and likelihood of these factors, illuminating potential barriers and facilitators to implementation. Based on the expert survey, five key elements (rising cancer rates, dedicated healthcare reimbursement budgets, increasing healthcare expenditures, advanced information technology solutions for data transfer, and demand for high-quality data) are expected to influence the equitable implementation of precision medicine in routine cancer care in Belgium in the future. This work contributes to the knowledge base on precision medicine in Belgium and public health foresight, exploring the implementation challenges and suggesting solutions with an emphasis on the importance of comparative analyses of health systems, evaluation of health technology assessment methods, and the exploration of ethical issues in data privacy and equity.

The centre for health informatics: a novel approach to accelerating the field of health data science

Precision Medicine and Precision Public Health are approaches to improve population health. Achieving these goals requires innovation in health informatics. The Centre for Health Informatics (CHI) within the Cumming School of Medicine (CSM) at the University of Calgary (UC), Canada, was created to respond to this need by fostering multidisciplinary collaborations, building capacity by recruiting and training outstanding faculty and students, and harnessing Alberta's rich health data to advance health informatics. To establish CHI as a health informatics leader, CHI has struck partnerships with stakeholders, including Alberta Health Services (AHS), Alberta Health (AH), and the Alberta Strategy for Patient-Oriented Research Unit (AbSPORU) among others. Through these close relationships, the CHI intake team facilitates access to Alberta's rich health data sources and educates researchers on the available health data in Alberta. The concept of a "One Stop Shop" for CSM and UC researchers encourages multidisciplinary collaboration, helps investigators access a wide range of datasets, and receive analytical support. Population-based data sets enable the development of methods to turn raw data into health information, improve health data collection, linkage, analysis, and quality, and applied studies creating clinical decision-support tools, prognostic tools, improved health surveillance methods, and health system performance indicators. CHI's ecosystem of diverse research expertise, cutting-edge technology, and embedded AHS analysts to support data access via a wide-ranging network of partnerships allows our provincial researchers, national and international collaborators tremendous opportunities for empirical research. It paves the way for implementing Precision Medicine in the real world.

Exploring and leveraging aggregation effects on reactive oxygen species generation in photodynamic therapy

AbstractAggregate‐level photodynamic therapy (PDT) has attracted significant interest and driven substantial advances in multifunction phototheranostic platforms. As exemplified by two typical instances of aggregation‐caused quenching of reactive oxygen species (ROS) and aggregation‐induced generation of ROS, the aggregation effect plays a significant role on the ROS generation of photosensitizers (PSs), which is worthy of in‐depth exploration and full utilization. However, in contrast to the well‐developed researches on the aggregation effect on luminescence, the studies concerning the aggregation effect on ROS generation are currently in a relatively nascent and disjointed stage, lacking guidance from a firmly established research paradigm. To advance this regard, this review aims at providing a consolidated overview of the fundamental principles and research status of aggregation effects on the ROS generation. Here, the research status can be organized into two main facets. One involves the comparison between isolated state and aggregated state, which is mainly conducted by two methods of changing solvent environments and adding adjuvants into a given solvent. The other underscores the distinctions between different aggregate states, consisting of three parts, namely comparison within the same or between different categories based on the classification of single‐component and multicomponent aggregates. In this endeavor, we will present our views on current research methodologies that explore how aggregation affects ROS generation and highlight the design strategies to leverage the aggregation effect to optimize PS regiments. We aspire this review to propel the advancement of phototheranostic platforms and accelerate the clinical implementation of precision medicine, and inspire more contributions to aggregate‐level photophysics and photochemistry, pushing the aggregate science and materials forward.

Alkaptonuria.

Alkaptonuria is a rare inborn error of metabolism caused by the deficiency of homogentisate 1,2-dioxygenase activity. The consequent homogentisic acid (HGA) accumulation in body fluids and tissues leads to a multisystemic and highly debilitating disease whose main features are dark urine, ochronosis (HGA-derived pigment in collagen-rich connective tissues), and a painful and severe form of osteoarthropathy. Other clinical manifestations are extremely variable and include kidney and prostate stones, aortic stenosis, bone fractures, and tendon, ligament and/or muscle ruptures. As an autosomal recessive disorder, alkaptonuria affects men and women equally. Debilitating symptoms appear around the third decade of life, but a proper and timely diagnosis is often delayed due to their non-specific nature and a lack of knowledge among physicians. In later stages, patients' quality of life might be seriously compromised and further complicated by comorbidities. Thus, appropriate management of alkaptonuria requires a multidisciplinary approach, and periodic clinical evaluation is advised to monitor disease progression, complications and/or comorbidities, and to enable prompt intervention. Treatment options are patient-tailored and include a combination of medications, physical therapy and surgery. Current basic and clinical research focuses on improving patient management and developing innovative therapies and implementing precision medicine strategies.

Construction and optimization of multi-platform precision pathways for precision medicine

In the enduring challenge against disease, advancements in medical technology have empowered clinicians with novel diagnostic platforms. Whilst in some cases, a single test may provide a confident diagnosis, often additional tests are required. However, to strike a balance between diagnostic accuracy and cost-effectiveness, one must rigorously construct the clinical pathways. Here, we developed a framework to build multi-platform precision pathways in an automated, unbiased way, recommending the key steps a clinician would take to reach a diagnosis. We achieve this by developing a confidence score, used to simulate a clinical scenario, where at each stage, either a confident diagnosis is made, or another test is performed. Our framework provides a range of tools to interpret, visualize and compare the pathways, improving communication and enabling their evaluation on accuracy and cost, specific to different contexts. This framework will guide the development of novel diagnostic pathways for different diseases, accelerating the implementation of precision medicine into clinical practice.

Therapeutic biomarkers in acute myeloid leukemia: functional and genomic approaches.

Acute myeloid leukemia (AML) is clinically and genetically a heterogeneous disease characterized by clonal expansion of abnormal hematopoietic progenitors. Genomic approaches to precision medicine have been implemented to direct targeted therapy for subgroups of AML patients, for instance, IDH inhibitors for IDH1/2 mutated patients, and FLT3 inhibitors with FLT3 mutated patients. While next generation sequencing for genetic mutations has improved treatment outcomes, only a fraction of AML patients benefit due to the low prevalence of actionable targets. In recent years, the adoption of newer functional technologies for quantitative phenotypic analysis and patient-derived avatar models has strengthened the potential for generalized functional precision medicine approach. However, functional approach requires robust standardization for multiple variables such as functional parameters, time of drug exposure and drug concentration for making in vitro predictions. In this review, we first summarize genomic and functional therapeutic biomarkers adopted for AML therapy, followed by challenges associated with these approaches, and finally, the future strategies to enhance the implementation of precision medicine.

Multifaceted nature of young-onset diabetes - can genomic medicine improve the precision of diagnosis and management?

Young-onset type 2 diabetes (YOD), defined as diabetes diagnosis before age 40, has an aggressive clinical course with premature mortality, in part due to long disease duration and lack of evidence to guide diagnosis and management. Autoimmune type 1 diabetes, maturity-onset diabetes of the young (MODY), and latent autoimmune diabetes in adults (LADA) are subtypes of diabetes in young people, which, however, cannot fully explain their complex clinical course. Similarly, family members carrying the same rare genetic variant of monogenic diabetes can have different presentations and outcomes. Ancestral heterogeneity, ecological transition, inter-ethnic differences in genomic architecture, and variations in living environment, lifestyles, access to care, and timeliness of diagnosis and treatment can influence the age of diagnosis and exposure to these cardiometabolic-renal risk factors. Despite the wealth of literature on genetic associations with diabetes, the familial cosegregation of rare variants and their relevance to YOD remains uncertain. This perspective was motivated by decades of clinical observations and learnings from an ongoing randomized controlled trial that uses biogenetic markers to classify patients with YOD for improving outcomes. Apart from highlighting the need to use family-based studies to improve the precision of diagnosis, we discussed atypical causes for diabetic ketoacidosis and the importance of lifecourse and psychosocial-behavioral factors in patients with YOD. Apart from detailed clinical evaluation, we propose using plasma C peptide, homeostasis model of assessment (HOMA) indexes, autoantibodies, and polygenic risk scores to stratify risk, classify diabetes subtypes, and personalize treatment in YOD. To achieve these goals, we advocate changing the practice environment and team structure to enable physicians to use the insights they learn from patients and their family members to implement precision medicine and improve the outlook of these high-risk individuals.

Fast-tracking drug development with biomarkers and companion diagnostics

To fully implement precision medicine, a deeper understanding of biomarkers, companion diagnostics, and their use in clinical trials is needed. Here, we describe key events in biomarker discovery and clinical trial design, and how those stages may be streamlined to fast-track approval of companion diagnostics (CDx). We discuss crucial qualities of a successful CDx that include understanding the prevalence of the marker in the intention to treat population, careful consideration of the scoring scheme that will be used in later clinical trial stages, and reliability of the performance of the CDx, in addition to other necessary features.

Expert-based collaborative analysis of the situation and prospects of biomarker test implementation in oncology in Spain

PurposeBiomarkers as screening for precision medicine is a fundamental step. The purpose of this article is twofold. First, tohighlight the existing barriers in the implementation of Precision Medicine in Spain, with a special emphasis on barriersin access to the determination of biomarkers. Second, to provide a Roadmap that can help implement Precision Medicineequitably at the national level and optimize the use of biomarkers.MethodsA systematic review of literature (SRL) and a focus group (FG) with multidisciplinary experts has been carried out in 2023.Participants were contacted individually, and discourse analysis was processed anonymously.ResultsWe carried out a quantitative (SRL) and a qualitative approach (FG). The discourse analysis and roadmap were sentindividually to each expert for approval.ConclusionsThe potential of Precision Medicine has not been fulfilled in Spain. While several regional initiatives are in place, anational plan or strategy around Precision Medicine and use of biomarkers is lacking. In a general context of rapidprogress at a global and European level, including the 2021 Europe’s Beating Cancer Plan, it is time to define andimplement a National Plan to make the promise come true. While some comparable countries within Europe – such asthe UK or France – are mature enough to adopt such strategies, in Spain there is still a long way to go. We consider thatthe different strands of work outlined in the Roadmap can be used as basis for such purpose.

Knowledge, Attitude and Ethical Perception Towards Precision Medicine Among Healthcare Professionals- a Questionnaire Survey

Precision medicine, also known as personalized medicine, is an emerging approach in healthcare that tailors medical treatment and prevention strategies to individual patients based on their unique genetic makeup, lifestyle, and environmental factors. It represents a paradigm shift from the traditional “one size fits all” approach to a more targeted and precise form of medical care. In precision medicine, extensive genomic analysis and other high-throughput technologies are employed to identify genetic variations and molecular markers associated with specific diseases or treatment responses. This wealth of genetic information allows healthcare professionals to make more accurate diagnoses, predict disease risks, and design personalized treatment plans. The application of precision medicine spans various medical fields, including oncology, cardiovascular diseases, neurology, and infectious diseases. In oncology, for example, molecular profiling of tumors enables the identification of specific genetic alterations that guide the selection of targeted therapies, leading to improved patient outcomes and reduced adverse effects. Precision medicine also holds great promise in preventive medicine. By identifying an individual’s genetic predispositions to certain diseases, clinicians can recommend tailored lifestyle modifications or interventions to mitigate the risk. Additionally, the integration of electronic health records, wearable devices, and mobile health applications facilitates real-time monitoring and personalized interventions, enhancing patient engagement and overall healthcare outcomes. Despite its potential, several challenges need to be addressed for the widespread implementation of precision medicine. These include the high cost of genomic sequencing and data analysis, ensuring data privacy and security, and the need for interdisciplinary collaboration among researchers, clinicians, and policymakers. In conclusion, precision medicine represents a transformative approach to healthcare, enabling personalized and targeted interventions that have the potential to revolutionize patient care, improve treatment outcomes, and reduce healthcare costs. Efforts to overcome the challenges associated with precision medicine are crucial for its successful integration into routine clinical practice.

Construction of a predictive model for blood transfusion in patients undergoing total hip arthroplasty and identification of clinical heterogeneity

A precise forecast of the need for blood transfusions (BT) in patients undergoing total hip arthroplasty (THA) is a crucial step toward the implementation of precision medicine. To achieve this goal, we utilized supervised machine learning (SML) techniques to establish a predictive model for BT requirements in THA patients. Additionally, we employed unsupervised machine learning (UML) approaches to identify clinical heterogeneity among these patients. In this study, we recruited 224 patients undergoing THA. To identify factors predictive of BT during the perioperative period of THA, we employed LASSO regression and the random forest (RF) algorithm as part of supervised machine learning (SML). Using logistic regression, we developed a predictive model for BT in THA patients. Furthermore, we utilized unsupervised machine learning (UML) techniques to cluster THA patients who required BT based on similar clinical features. The resulting clusters were subsequently visualized and validated. We constructed a predictive model for THA patients who required BT based on six predictive factors: Age, Body Mass Index (BMI), Hemoglobin (HGB), Platelet (PLT), Bleeding Volume, and Urine Volume. Before surgery, 1 h after surgery, 1 day after surgery, and 1 week after surgery, significant differences were observed in HGB and PLT levels between patients who received BT and those who did not. The predictive model achieved an AUC of 0.899. Employing UML, we identified two distinct clusters with significantly heterogeneous clinical characteristics. Age, BMI, PLT, HGB, bleeding volume, and urine volume were found to be independent predictors of BT requirement in THA patients. The predictive model incorporating these six predictors demonstrated excellent predictive performance. Furthermore, employing UML enabled us to classify a heterogeneous cohort of THA patients who received BT in a meaningful and interpretable manner.

Precision Medicine in Cancer Biology: Using Genetic and Molecular Profiling to Personalize Treatment

Precision medicine is an emerging field that aims to provide personalized treatment for cancer patients by utilizing genetic and molecular profiling. By analyzing a patient’s cancer’s genetic and molecular characteristics, doctors can design tailored treatment plans targeting specific mutations or signalling pathways driving tumor growth. This approach can potentially improve patient outcomes by increasing the effectiveness of treatments and reducing the risk of side effects. However, many challenges are associated with implementing precision medicine, including the need for advanced technologies and the high cost of testing and treatment. Despite these obstacles, the promise of precision medicine is driving significant investment and research efforts in the field, and it has the potential to transform the way we treat cancer.

Future directions of lung-protective ventilation strategies in acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is characterized by the heterogeneous distribution of lung aeration along a gravitational direction due to increased lung density. Therefore, the lung available for ventilation is usually limited to ventral, nondependent lung regions and has been called the "baby" lung. In ARDS, ventilator-induced lung injury is known to occur in nondependent "baby" lungs, as ventilation is shifted to ventral, nondependent lung regions, increasing stress and strain. To protect this nondependent "baby" lung, the clinician targets and limits global parameters such as tidal volume and plateau pressure. In addition, positive end-expiratory pressure (PEEP) is used to prevent dorsal, dependent atelectasis and, if successful, increases the size of the baby lung and lessens its susceptibility to injury from inspiratory stretch. Although many clinical trials have been performed in patients with ARDS over the last two decades, there are few successfully showing benefits on mortality (ie, prone positioning and neuromuscular blocking agents). These disappointing results contrast with other medical disciplines, especially in oncology, where the heterogeneity of diseases is recognized widely and precision medicine has been promoted. Thus, lung-protective ventilation strategies need to take an innovative approach that accounts for the heterogeneity of injured lungs. This article summarizes ventilator-induced lung injury and ARDS and discusses how to implement precision medicine in the field of ARDS. Potentially useful methods to individualize PEEP with esophageal balloon manometry, lung recruitability, and electrical impedance tomography were discussed.

Precision cancer medicine and the doctor-patient relationship: a systematic review and narrative synthesis

BackgroundThe implementation of precision medicine is likely to have a huge impact on clinical cancer care, while the doctor-patient relationship is a crucial aspect of cancer care that needs to be preserved. This systematic review aimed to map out perceptions and concerns regarding how the implementation of precision medicine will impact the doctor-patient relationship in cancer care so that threats against the doctor-patient relationship can be addressed.MethodsElectronic databases (Pubmed, Scopus, Web of Science, Social Science Premium Collection) were searched for articles published from January 2010 to December 2021, including qualitative, quantitative, and theoretical methods. Two reviewers completed title and abstract screening, full-text screening, and data extraction. Findings were summarized and explained using narrative synthesis.ResultsFour themes were generated from the included articles (n = 35). Providing information addresses issues of information transmission and needs, and of complex concepts such as genetics and uncertainty. Making decisions in a trustful relationship addresses opacity issues, the role of trust, and and physicians’ attitude towards the role of precision medicine tools in decision-making. Managing negative reactions of non-eligible patients addresses patients’ unmet expectations of precision medicine. Conflicting roles in the blurry line between clinic and research addresses issues stemming from physicians’ double role as doctors and researchers.ConclusionsMany findings have previously been addressed in doctor-patient communication and clinical genetics. However, precision medicine adds complexity to these fields and further emphasizes the importance of clear communication on specific themes like the distinction between genomic and gene expression and patients’ expectations about access, eligibility, effectiveness, and side effects of targeted therapies.

A Global Survey of Precision Medicine in Emergency General Surgery

Abstract Background Since first sequencing the human genome, precision medicine has become a modern-day reality. However, translation to all areas of medicine has not been equal. This study aimed to provide a ‘status update’ of precision medicine in EGS to guide future priority setting. Methodology An observational study was conducted utilising two curated global on-line databases: 1. Pubmed publications from 2001 & 2. Clinical trials registered on ClinicalTrials.gov. The top 10 presenting conditions in EGS, Oncology, and Acute Medicine were identified from literature review. Publications/trials in these areas were identified using associated keywords: precision, personalised, genomics, genome-wide association studies, exome studies, epigenetics, transcriptomics, proteomics, metabolomics, microbiomics, and pharmacogenomics. Duplicated publications/trials were removed prior to final analysis and only active, recruiting or completed trials were included. Temporal trends were compared and annual growth rates were calculated. Results There were 209,423 EGS publications, 1807 (0.9%) being precision-focused. Oncology had 1,137,396 publications, with 127,556 precision-focused (11.2%), and Acute Medicine had 1,647,046 publications, with 80,240 (4.9%) precision-focused. The rate of rise of annual publications since 2001 (human genome project publication) was significantly (p<0.05) lower for EGS (x2.9) versus oncology (x3.5) and medicine (x6.0). Only 7 precision-focused clinical trials were identified for EGS compared to 96 for Oncology and 39 for Medicine. x10 fewer precision-focused EGS publications and trials exist over 20 years, compared to covid-19 over 2 years. Conclusion Research and implementation of precision medicine in EGS remains inadequate. Increased investment and improved global implementation are warranted to address the widening gap in translation.

Error-Corrected Next-Generation Sequencing Provides a Comprehensive Overview of the Subclonal Mutation Landscape and Its Prognostic Implications in Juvenile Myelomonocytic Leukemia

Introduction: Juvenile myelomonocytic leukemia (JMML) is a rare pediatric myelodysplastic/myeloproliferative neoplasm characterized by mutations in genes activating the RAS pathway ( PTPN11, NF1, NRAS, KRAS, and CBL). Approximately 20% of patients with JMML have secondary mutations in SETBP1 and/or JAK3, and recent droplet digital PCR (ddPCR) analyses revealed that mutations in these two genes, including very rare mutations (variant allele frequency [VAF] < 0.05) that are difficult to detect by conventional next-generation sequencing (NGS), are associated with poor prognoses. Meanwhile, the landscape of low VAF subclonal mutations of other genes in patients with JMML has not been adequately evaluated. Therefore, we utilized error-corrected NGS, which can reduce the systematic sequencing error rate of conventional NGS by incorporating molecular barcodes (MBCs). Methods: We performed error-corrected NGS in 93 patients with JMML and 11 patients with JMML-like myeloproliferative disorder with Noonan syndrome (NS/MPD) using a small panel associated with myeloid malignancies. Samples for error-corrected NGS were prepared using a SureSelect XT HS2 DNA Library Preparation Kit (Agilent Technologies), including unique dual index and duplex MBCs. A unique MBC is incorporated into each DNA fragment, and the incorporated MBC can differentiate true and false duplications, allowing for highly accurate sequencing that can detect mutations with VAF > 0.001. We used the HiSeq X platform (Illumina) and SureCall v.4.2 application (Agilent Technologies) for analysis. In addition, DNA methylation analysis was performed on the same cohort using the Infinium HumanMethylation 450K BeadChip and/or Digital Restriction Enzyme Analysis of Methylation as previously described (Murakami et al. 2018;131:1576-1586, Kitazawa et al. Blood Adv. 2021;5:5507-5518). This study was approved by the Ethics Committee of the Nagoya University Graduate School of Medicine. Results: In the cohort of 104 patients with JMML or NS/MPD, 160 mutations were identified, of which 30 (19%) had VAF < 0.05 (eight in JAK3, seven in NF1, five in ASXL1, three in NRAS, two each in PTPN11 and SOS1, and one each in SETBP1, SH2B3, and ZRSR2). Subclonal mutations in SETBP1 p.D868N and JAK3 p.R657Q identified by error-corrected NGS were confirmed using ddPCR, and consistent results were obtained for both assays (R 2 = 0.9977 and 0.9919 respectively). Of 93 patients with JMML, 30 (32%) had subclonal or clonal secondary mutations, whereas no such mutations were detected in patients with NS/MPD ( P = 0.031). Of 104 patients, 23 (22%) had secondary mutations with VAF ≥ 0.05 (Major group), 7 (7%) only had secondary mutations with VAF < 0.05 (Minor group), and the remaining 74 (71%) had no secondary mutations (Negative group). We assessed the associations of subclonal mutations detected by error-corrected NGS with the DNA methylation profile, the most important prognostic factor in JMML. Whereas 22 of 23 (96%) and 5 of 7 (71%) patients in the Major and Minor groups, respectively, had high methylation (HM) profiles, only 20 of 74 (27%) patients in the Negative group featured HM profiles ( P < 0.001). The 4-year overall survival (OS) rates were significantly lower in the Major (52.2% [95% confidence interval {CI} = 30.5%-70.0%], P = 0.01) and Minor groups (42.9% [95% CI = 9.8%-73.4%], P = 0.03) than in the Negative group (76.3% [95% CI = 64.6%-84.5%]). In a subgroup analysis of 30 patients with secondary mutations, patients with secondary mutations in RAS pathway genes (n = 18) had significantly lower 4-year OS rates than those with secondary mutations in other genes (n = 12; 32.4% [95% CI = 12.7%-54.0%] vs. 75.0% [95% CI: 40.8%-91.2%], P = 0.047). Conclusions: We successfully performed error-corrected NGS to assess comprehensive subclonal secondary mutational profiles, including very low VAF variants. The presence of subclonal mutations, particularly in RAS pathway genes, was associated with poor OS. These findings provide important information for appropriate risk stratification, which will contribute to the implementation of precision medicine for patients with JMML.