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The year 2023 marked the 60th anniversary of screening newborns in the United States for diseases that benefit from early identification and intervention. All around the world, the goal of NBS is to facilitate timely diagnosis and management to improve individual health outcomes in all newborns regardless of their place of birth, economic circumstances, ability to pay for treatment, and access to healthcare. Advances in technology to screen and treat disease have led to a rapid increase in the number of screened conditions, and innovations in genomics are expected to exponentially expand this number further. A system where all newborns are screened, coupled with rapid technological innovation, provides a unique opportunity to improve pediatric health outcomes and advance children's rights, including the unique rights of sick and disabled children. This is especially timely as we approach the 100th anniversary of the 1924 Geneva Declaration of the Rights of the Child, which includes children's right to healthcare, and the 1989 United Nations Convention on the Rights of the Child that expanded upon this aspect and affirmed each child's right to the highest attainable standard of health. In this manuscript, we provide background on the evolving recognition of the rights of children and the foundational rights to healthcare and non-discrimination, provide two examples that highlight issues to access and equity in newborn screening that may limit a child's right to healthcare and best possible outcomes, detail ways the current approach to newborn screening advances the rights of the child, and finally, propose that the incorporation of genomics into newborn screening presents a useful case study to recognize and uphold the rights of every child.
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Cardiovascular diseases (CVDs) impose a significant burden worldwide. Despite the elucidation of the etiology and underlying molecular mechanisms of CVDs by numerous studies and recent discovery of effective drugs, their morbidity, disability, and mortality are still high. Therefore, precise risk stratification and effective targeted therapies for CVDs are warranted. Recent improvements in single-cell RNA sequencing and spatial transcriptomics have improved our understanding of the mechanisms and cells involved in cardiovascular phylogeny and CVDs. Single-cell RNA sequencing can facilitate the study of the human heart at remarkably high resolution and cellular and molecular heterogeneity. However, this technique does not provide spatial information, which is essential for understanding homeostasis and disease. Spatial transcriptomics can elucidate intracellular interactions, transcription factor distribution, cell spatial localization, and molecular profiles of mRNA and identify cell populations causing the disease and their underlying mechanisms, including cell crosstalk. Herein, we introduce the main methods of RNA-seq and spatial transcriptomics analysis and highlight the latest advances in cardiovascular research. We conclude that single-cell RNA sequencing interprets disease progression in multiple dimensions, levels, perspectives, and dynamics by combining spatial and temporal characterization of the clinical phenome with multidisciplinary techniques such as spatial transcriptomics. This aligns with the dynamic evolution of CVDs (e.g., "angina-myocardial infarction-heart failure" in coronary artery disease). The study of pathways for disease onset and mechanisms (e.g., age, sex, comorbidities) in different patient subgroups should improve disease diagnosis and risk stratification. This can facilitate precise individualized treatment of CVDs.
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Background: Advances in our understanding of the genetic basis of childhood cancer, including primary central nervous system cancers, are improving the diagnosis, treatment, and clinical management of pediatric patients. To effectively translate scientific breakthroughs into enhanced clinical care, it is essential we understand and learn from the experiences of patients, families, and health professionals. Methods: This report summarizes findings from 4 Australian psychosocial substudies exploring the perspectives of patients, parents, clinicians, and scientists participating in research related to childhood cancer genetics. Specifically, these studies focus on the psychosocial impact of germline testing in children, surveillance for children with a cancer predisposition syndrome and the perspectives of healthcare professionals who deliver this testing and surveillance. Results: Data presented highlight some of the opportunities and challenges associated with the changing context of genetic predisposition testing for children, adolescents and yound adults with cancer and illustrate how embedding psychosocial data collection in clinical research can answer important questions in the field and inform the design of patient-centric models of care, resources, and workforce training. Conclusions: By embracing these perspectives, we can ensure that advances in genetic research translate into enhanced family experiences, and, ultimately, improved outcomes for children and young people with cancer, and their families.
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Introduction: Patients with cystic fibrosis (CF) experience frequent episodes of acute decline in lung function called pulmonary exacerbations (PEx). An existing clinical and place-based precision medicine algorithm that accurately predicts PEx could include racial and ethnic biases in clinical and geospatial training data, leading to unintentional exacerbation of health inequities. Methods: We estimated receiver operating characteristic curves based on predictions from a nonstationary Gaussian stochastic process model for PEx within 3, 6, and 12 months among 26,392 individuals aged 6 years and above (2003-2017) from the US CF Foundation Patient Registry. We screened predictors to identify reasons for discriminatory model performance. Results: The precision medicine algorithm performed worse predicting a PEx among Black patients when compared with White patients or to patients of another race for all three prediction horizons. There was little to no difference in prediction accuracies among Hispanic and non-Hispanic patients for the same prediction horizons. Differences in F508del, smoking households, secondhand smoke exposure, primary and secondary road densities, distance and drive time to the CF center, and average number of clinical evaluations were key factors associated with race. Conclusions: Racial differences in prediction accuracies from our PEx precision medicine algorithm exist. Misclassification of future PEx was attributable to several underlying factors that correspond to race: CF mutation, location where the patient lives, and clinical awareness. Associations of our proxies with race for CF-related health outcomes can lead to systemic racism in data collection and in prediction accuracies from precision medicine algorithms constructed from it.
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The retina-specific ABCA transporter, ABCA4, is essential for vision, and its genetic variants are associated with a wide range of inherited retinal degenerative diseases (IRDs) leading to blindness. Of the 1,630 identified missense variants in ABCA4, â¼50% are of unknown pathogenicity (variants of unknown significance, VUS). This genetic uncertainty presents three main challenges: (i) inability to predict disease-causing variants in relatives of IRD patients with multiple ABCA4 mutations; (ii) limitations in developing variant-specific treatments; and (iii) difficulty in using these variants for future disease prediction, affecting patients' life-planning and clinical trial participation. To unravel the clinical significance of ABCA4 genetic variants at the level of protein function, we have developed a virus-like particle (VLP)-based system that expresses the ABCA4 protein and its variants. We validated the efficacy of this system in the enzymatic characterization (ATPase activity) of VLPs harboring ABCA4 and two variants of established pathogenicity: p.N965S and p.C1488R. Our results were consistent with previous reports and clinical phenotypes. We also applied this platform to characterize the VUS p.Y1779F and observed a functional impairment, suggesting a potential pathogenic impact. This approach offers an efficient, high-throughput method for ABCA4 VUS characterization. Our research points to the significant promise of the VLP-based system in the functional analysis of membrane proteins, offering important perspectives on the disease-causing potential of genetic variants and shedding light on genetic conditions involving such proteins.
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BACKGROUND: Continuously improving cancer-specific survival puts a growing proportion of cancer patients at risk of major adverse cardiovascular events (MACE), but tailored tools for cardiovascular risk prediction remain unavailable. OBJECTIVES: To assess a broad panel of cardiovascular biomarkers and risk factors for the prediction of MACE and cardiovascular death in cancer patients. METHODS: In total, 2192 patients with newly diagnosed or recurrent cancer were followed prospectively for the occurrence of 2-year MACE and 5-year cardiovascular death. Univariable and multivariable risk models were fit to assess independent associations of cardiovascular risk factors and biomarkers with adverse outcomes, and a risk score was developed. RESULTS: Traditional cardiovascular risk factors and selected cancer types were linked to higher MACE risk. While levels of Lp(a), CRP, and GDF-15 did not associate with MACE, levels of ICAM-1, P-/E-/L-selectins, and NT-proBNP were independently linked to 2-year MACE risk. A clinical risk score was derived, assigning +1 point for male sex, smoking, and age of ≥60 years and +2 points for atherosclerotic disease, yielding a bootstrapped C-statistic of 0.76 (95% CI: 0.71-0.81) for the prediction of 2-year MACE. Implementation of biomarker data conferred improved performance (0.83, 95% CI: 0.78-0.88), with a simplified model showing similar performance (0.80, 95% CI: 0.74-0.86). The biomarker-enhanced and simplified prediction models achieved a C-statistic of 0.82 (95% CI: 0.71-0.93) and 0.74 (95% CI: 0.64-0.83) for the prediction of 5-year cardiovascular death. CONCLUSION: Biomarker-enhanced risk prediction strategies allow the identification of cancer patients at high risk of MACE and cardiovascular death. While external validation studies are ongoing, this first-of-its-kind risk score may provide the basis for personalized cardiovascular risk assessment across cancer entities.
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OBJECTIVE: To compare theoretical strengths and limitations of common immortal time adjustment methods, propose a new approach using multiple imputation (MI), and provide practical guidance for using MI in precision medicine evaluations centered on a real-world case study. STUDY SETTING AND DESIGN: Methods comparison, guidance, and real-world case study based on previous literature. We compared landmark analysis, time-distribution matching, time-dependent analysis, and our proposed MI application. Guidance for MI spanned (1) selecting the imputation method; (2) specifying and applying the imputation model; and (3) conducting comparative analysis and pooling estimates. Our case study used a matched cohort design to evaluate overall survival benefits of whole-genome and transcriptome analysis, a precision medicine technology, compared to usual care for advanced cancers, and applied both time-distribution matching and MI. Bootstrap simulation characterized imputation sensitivity to varying data missingness and sample sizes. DATA SOURCES AND ANALYTIC SAMPLE: Case study used population-based administrative data and single-arm precision medicine program data from British Columbia, Canada for the study period 2012 to 2015. PRINCIPAL FINDINGS: While each method described can reduce immortal time bias, MI offers theoretical advantages. Compared to alternative approaches, MI minimizes information loss and better characterizes statistical uncertainty about the true length of the immortal time period, avoiding false precision. Additionally, MI explicitly considers the impacts of patient characteristics on immortal time distributions, with inclusion criteria and follow-up period definitions that do not inadvertently risk biasing evaluations. In the real-world case study, survival analysis results did not substantively differ across MI and time distribution matching, but standard errors based on MI were higher for all point estimates. Mean imputed immortal time was stable across simulations. CONCLUSIONS: Precision medicine evaluations must employ immortal time adjustment methods for unbiased, decision-grade real-world evidence generation. MI is a promising solution to the challenge of immortal time bias.
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BACKGROUND: and aims: Cardiogenic shock (CS) remains the primary cause of in-hospital death after acute coronary syndromes (ACS), with its plateauing mortality rates approaching 50%. To test novel interventions, personalized risk prediction is essential. The ORBI (Observatoire Régional Breton sur l'Infarctus) score represents the first-of-its-kind risk score to predict in-hospital CS in ACS patients undergoing percutaneous coronary intervention (PCI). However, its sex-specific performance remains unknown, and refined risk prediction strategies are warranted. METHODS: This multinational study included a total of 53 537 ACS patients without CS on admission undergoing PCI. Following sex-specific evaluation of ORBI, regression and machine-learning models were used for variable selection and risk prediction. By combining best-performing models with highest-ranked predictors, SEX-SHOCK was developed, and internally and externally validated. RESULTS: The ORBI score showed lower discriminative performance for the prediction of CS in females than males in Swiss (AUC [95% CI]: 0.78 [0.76-0.81] vs. 0.81 [0.79-0.83]; p=0.048) and French ACS patients (0.77 [0.74-0.81] vs. 0.84 [0.81-0.86]; p=0.002). The newly developed SEX-SHOCK score, now incorporating ST-segment elevation, creatinine, C-reactive protein, and left ventricular ejection fraction, outperformed ORBI in both sexes (females: 0.81 [0.78-0.83]; males: 0.83 [0.82-0.85]; p<0.001), which prevailed following internal and external validation in RICO (females: 0.82 [0.79-0.85]; males: 0.88 [0.86-0.89]; p<0.001) and SPUM-ACS (females: 0.83 [0.77-0.90], p=0.004; males: 0.83 [0.80-0.87], p=0.001). CONCLUSIONS: The ORBI score showed modest sex-specific performance. The novel SEX-SHOCK score provides superior performance in females and males across the entire spectrum of ACS, thus providing a basis for future interventional trials and contemporary ACS management.
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OBJECTIVE: Recent randomized controlled trials have demonstrated a notable prevalence of immediate technical failures (ITFs) in percutaneous vascular interventions (PVIs) for complex arterial lesions associated with chronic limb-threatening ischemia (CLTI). Current imaging modalities present inherent limitations in identifying these lesions, making it challenging to determine the most suitable candidates for PVI. We present a novel preprocedural magnetic resonance imaging (MRI) histology protocol for identifying lesions that might present a higher rate of immediate and mid-term PVI failure. METHODS: 22 patients (13 females, average age 65.8±9.72 years) scheduled for PVI were prospectively enrolled and underwent 3T MRI using ultrashort echo time and 'Steady-State Free Precession' contrasts to characterize target lesions prior to PVI. Lesions were scored as 'hard' if >50% of the lumen was occluded by hard components (calcium/dense collagen) on MRI in the hardest cross-section. Two readers evaluated MRI datasets. TASC/GLASS/WIFi scoring was performed based on intraprocedural angiograms and chart review. The relationship between MRI scoring, TASC/GLASS scoring and procedural outcomes was investigated using univariate analysis. Mid-term follow-up (revascularization and amputation rate) was recorded at 3 months and 6 months, post-intervention. RESULTS: Our cohort of 22 patients yielded 40 target lesions. 5 lesions were excluded (2 non-diagnostic image quality, 3 PVIs were ultimately diagnostic only). 6 lesions (17%) were scored as 'hard'. MRI-scored 'hard' lesions had higher proportion of ITF ('hard' vs 'soft' 83% (n/N=5/6) vs. 3% (n/N=1/29), p<.001). 'Hard' versus 'soft' MRI scoring was the only factor significantly associated with immediate PVI technical success (p < .001), as opposed to TASC/GLASS scoring. Both at 3 months and 6 months after PVI, the re-intervention rate was significantly higher among those lesions which were scored 'hard' on MRI (3-month: hard: 80% vs. soft: 16%, p =.011 6-month: hard: 80%, soft: 27%, p=.047). CONCLUSIONS: MRI histology could be a valuable tool for optimizing PVI patient selection and treatment strategies.
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OBJECTIVE: A positivity threshold is often applied to markers or predicted risks to guide disease management. These rules are often decided exclusively by clinical experts despite being sensitive to the preferences of patients and general public as ultimate stakeholders. STUDY DESIGN AND SETTING: We propose an analytical framework for quantifying the net benefit of an evidence-based positivity threshold based on combining preference-sensitive (e.g., how individuals weight benefits and harms of treatment) and preference-agnostic (e.g., the magnitude of benefit and the risk of harm) parameters. We propose parsimonious choice experiments to elicit preference-sensitive parameters from stakeholders, and evidence synthesis to quantify the value of preference-agnostic parameters. We apply this framework to maintenance azithromycin therapy for chronic obstructive pulmonary disease (COPD) using a discrete choice experiment (DCE) to estimate preference weights for attribute level associated with treatment. We identify the positivity threshold on 12-month moderate or severe exacerbation risk that would maximize the net benefit of treatment in terms of severe exacerbations avoided. RESULTS: In the case study, the prevention of moderate and severe exacerbations (benefits) and the risk of hearing loss and gastrointestinal symptoms (harms) emerged as important attributes. 477 respondents completed the DCE survey. Relative to each percent risk of severe exacerbation, preference weights for each percent risk of moderate exacerbation, hearing loss, and gastrointestinal symptoms were 0.395 (95%CI 0.338-0.456), 1.180 (95%CI 1.071-1.201) and 0.253 (95%CI 0.207-0.299), respectively. The optimal threshold that maximized net benefit was to treat patients with a 12-month risk of moderate or severe exacerbations ≥12%. CONCLUSION: The proposed methodology can be applied to many contexts where the objective is to devise positivity thresholds that need to incorporate stakeholder preferences. Applying this framework to COPD pharmacotherapy resulted in a stakeholder-informed treatment threshold that was substantially lower than the implicit thresholds in contemporary guidelines.
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Recent advances in gene therapy, particularly for single-gene disorders (SGDs), have led to significant progress in developing innovative precision medicine approaches that hold promise for treating conditions such as primary hydrocephalus (CH), which is characterized by increased cerebrospinal fluid (CSF) volumes and cerebral ventricular dilation as a result of impaired brain development, often due to genetic causes. CH is a significant contributor to childhood morbidity and mortality and a driver of healthcare costs. In many cases, prenatal ultrasound can readily identify ventriculomegaly as early as 14-20 weeks of gestation, with severe cases showing poor neurodevelopmental outcomes. Postnatal surgical approaches, such as ventriculoperitoneal shunts, do not address the underlying genetic causes, have high complication rates, and result in a marginal improvement of neurocognitive deficits. Prenatal somatic cell gene therapy (PSCGT) promises a novel approach to conditions such as CH by targeting genetic mutations in utero, potentially improving long-term outcomes. To better understand the pathophysiology, genetic basis, and molecular pathomechanisms of CH, we conducted a scoping review of the literature that identified over 160 published genes linked to CH. Mutations in L1CAM, TRIM71, MPDZ, and CCDC88C play a critical role in neural stem cell development, subventricular zone architecture, and the maintenance of the neural stem cell niche, driving the development of CH. Early prenatal interventions targeting these genes could curb the development of the expected CH phenotype, improve neurodevelopmental outcomes, and possibly limit the need for surgical approaches. However, further research is needed to establish robust genotype-phenotype correlations and develop safe and effective PSCGT strategies for CH.
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This comprehensive review meticulously compiles data on an array of lectins and their interactions with different cancer types through specific glycans. Crucially, it establishes the link between aberrant glycosylation and cancer types. This repository of lectin-defined glycan signatures, assumes paramount importance in the realm of cancer and its dynamic nature. Cancer, known for its remarkable heterogeneity and individualized behaviour, can be better understood through these glycan signatures. The current review discusses the important lectins and their carbohydrate specificities, especially recognizing glycans of cancer origin. The review also addresses the key aspects of differentially expressed glycans on normal and cancerous cell surfaces. Specific cancer types highlighted in this review include breast cancer, colon cancer, glioblastoma, cervical cancer, lung cancer, liver cancer, and leukaemia. The glycan profiles unveiled through this review hold the key to tailor-made treatment and precise diagnostics. It opens up avenues to explore the potential of targeting glycosyltransferases and glycosidases linked with cancer advancement and metastasis. Armed with knowledge about specific glycan expressions, researchers can design targeted therapies to modulate glycan profiles, potentially hampering the advance of this relentless disease.
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Anaemia is a common health problem worldwide that disproportionately affects vulnerable groups, such as children and expectant mothers. It has a variety of underlying causes, some of which are genetic. A comprehensive strategy combining physical examination, laboratory testing (for example, a complete blood count), and molecular tools for accurate identification is required for diagnosis. With nearly 400 varieties of anaemia, accurate diagnosis remains a challenging task. Red blood cell abnormalities are largely caused by genetic factors, which means that a thorough understanding requires interpretation at the molecular level. As a result, precision medicine has become a key paradigm, utilising artificial intelligence (AI) techniques, such as deep learning and machine learning, to improve prognostic evaluation, treatment prediction, and diagnostic accuracy. Furthermore, exploring the immunomodulatory role of vitamin D along with biomarkerbased molecular techniques offers promising avenues for insight into anaemia's pathophysiology. The intricacy of aplastic anaemia makes it particularly noteworthy as a topic deserving of concentrated molecular research. Given the complexity of anaemia, an integrated strategy integrating clinical, laboratory, molecular, and AI techniques shows a great deal of promise. Such an approach holds promise for enhancing global anaemia management options in addition to advancing our understanding of the illness.
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Anemia, Aplastic , Humans , Anemia, Aplastic/diagnosis , Anemia, Aplastic/therapy , Artificial Intelligence , Anemia/diagnosis , Anemia/therapy , Biomarkers/blood , Machine Learning , Precision Medicine/methodsABSTRACT
RNA modifications have recently gained great attention due to their extensive regulatory effects in a wide range of cellular networks and signaling pathways. In cardiovascular diseases (CVDs), several RNA changes, called "epitranscriptome" alterations, are found in all RNA molecules (tRNA, rRNA, mRNA, and ncRNAs). Unlike the epigenetic process, which influences the progression of atherosclerosis (AS), its transcriptional and post-transcriptional regulatory mechanisms are still unknown. Here, we described the main epitranscriptome signs to provide new insights into AS, including m6A, m5C, m1A, m7G, Ψ, and A-to-I editing. Moreover, we also included all current known RNA-- modifier-targeting, including small molecular inhibitors or activators, mainly designed against m6A- and m5A-related enzymes, such as METTL3, FTO, and ALKBH5. Finally, since only a few drugs, such as azacitidine and tazemetostat, targeting the DNA epigenome, have been approved by the FDA, the next challenge would be to identify molecules for targeting the RNA epitranscriptome. To date, total Panax notoginseng total saponin could reduce vascular hyperplasia via Wilms' tumor-associated protein-1 m6A-dependent. Indeed, a virtual screening allowed us to individuate a phytomolecule, the rhein, which acts as an FTO inhibitor by increasing mRNA m6A levels. In this review, we highlighted the RNA epitranscriptome pathways implicated in AS, describing their biological functions and their connections to the disease. The identification of epitranscriptome- sensitive pathways could provide novel opportunities to find predictive, diagnostic, and prognostic biomarkers for precision medicine.
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BACKGROUND AND OBJECTIVE: Bladder cancer (BLCa) remains a prevalent malignancy with high recurrence rates and limited treatment options. In recent years, patient-derived organoids (PDOs) have emerged as a promising platform for studying cancer biology and therapeutic responses in a personalized manner. Using drug screening, PDOs facilitate the identification of novel therapeutic agents and translational treatment strategies. Moreover, their ability to model patient-specific responses to treatments holds promise for predicting clinical outcomes and guiding treatment decisions. This exploratory review aims to investigate the potential of PDOs in advancing BLCa research and treatment, with an emphasis on translational clinical approaches. Furthermore, we analyze the feasibility of deriving PDOs from minimally invasive blood and urine samples. METHODS: In addition to exploring hypothetical applications of PDOs for predicting patient outcomes and their ability to model different stages of BLCa, we conducted a comprehensive PubMed search on already published data as well as comprehensive screening of currently ongoing trials implementing PDOs in precision medicine in cancer patients irrespective of the tumor entity. KEY FINDINGS AND LIMITATIONS: While the research on BLCa PDOs is advancing rapidly, data on both BLCa PDO research and their clinical application are scarce. Owing to this fact, a narrative review format was chosen for this publication. CONCLUSIONS AND CLINICAL IMPLICATIONS: BLCa PDOs have the potential to influence the domain of precision medicine and enhance personalized cancer treatment strategies. However, standardized protocols for PDO generation, their ideal clinical application, as well as their impact on outcomes remain to be determined. PATIENT SUMMARY: In this review, we discuss the current state and future needs for the use of patient-derived organoids, small three-dimensional avatars of tumor cells, in bladder cancer. Patient-derived bladder cancer organoids offer a more personalized approach to studying and treating bladder cancer, providing a model that closely resembles the patient's own tumor. These organoids can help researchers identify new treatment options and predict how individual patients may respond to standard therapies. By using minimally invasive samples such as blood and urine, patients can participate in research studies more easily, potentially leading to improved outcomes in bladder cancer treatment.
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Accelerated biological aging may be associated with increased risk of esophageal adenocarcinoma (EAC). However, its relationship with genetic variation, and its effect on improving risk population stratification, remains unknown. We performed an exposome association study to determine potential associated factors associated with EAC. To quantify biological age and its difference from chronological age, we calculated the BioAge10 and Biological Age Acceleration (BioAgeAccel) based on chronological age and nine biomarkers. Multivariable Cox regression models for 362,310 participants from the UK Biobank with a median follow-up of 13.70 years were performed. We established a weighted polygenic risk score (wPRS) associated with EAC, to assess joint and interaction effects with BioAgeAccel. Four indicators were used to evaluate their interaction effects, and we fitted curves to evaluate the risk stratification ability of BioAgeAccel. Compared with biologically younger participants, those older had higher risk of EAC, with adjusted HR of 1.79 (95%CI: 1.52-2.10). Compared with low wPRS and biologically younger group, the high wPRS and biologically older group had a 4.30-fold increase in HR (95% CI: 2.78-6.66), at meanwhile, 1.15-fold relative excess risk was detected (95% CI: 0.30-2.75), and 22% of the overall EAC risk was attributable to the interactive effects (95% CI: 12%-31%). The 10-year absolute incidence risk indicates that biologically older individuals should begin screening procedures 4.18 years in advance, while youngers can postpone screening by 4.96 years, compared with general population. BioAgeAccel interacted positively with genetic variation and increased risk of EAC, it could serve as a novel indicator for predicting incidence.
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Long non-coding RNAs (lncRNAs) have been identified as important participants in several biological functions, particularly their complex interactions with the KRAS pathway, which provide insights into the significant roles lncRNAs play in cancer development. The KRAS pathway, a central signaling cascade crucial for cell proliferation, survival, and differentiation, stands out as a key therapeutic target due to its aberrant activation in many human cancers. Recent investigations have unveiled a myriad of lncRNAs, such as H19, ANRIL, and MEG3, intricately modulating the KRAS pathway, influencing both its activation and repression through various mechanisms, including epigenetic modifications, transcriptional regulation, and post-transcriptional control. These lncRNAs function as fine-tuners, delicately orchestrating the balance required for normal cellular function. Their dysregulation has been linked to the development and progression of multiple malignancies, including lung, pancreatic, and colorectal carcinomas, which frequently harbor KRAS mutations. This scrutiny delves into the functional diversity of specific lncRNAs within the KRAS pathway, elucidating their molecular mechanisms and downstream effects on cancer phenotypes. Additionally, it underscores the diagnostic and prognostic potential of these lncRNAs as indicators for cancer detection and assessment. The complex regulatory network that lncRNAs construct within the context of the KRAS pathway offers important insights for the creation of focused therapeutic approaches, opening new possibilities for precision medicine in oncology. However, challenges such as the dual roles of lncRNAs in different cancer types and the difficulty in therapeutically targeting these molecules highlight the ongoing debates and need for further research. As ongoing studies unveil the complexities of lncRNA-mediated KRAS pathway modulation, the potential for innovative cancer interventions becomes increasingly promising.
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BACKGROUND: Understanding the similarities of patients with cancer is essential to advancing personalized medicine, improving patient outcomes, and developing more effective and individualized treatments. It enables researchers to discover important patterns, biomarkers, and treatment strategies that can have a significant impact on cancer research and oncology. In addition, the identification of previously successfully treated patients supports oncologists in making treatment decisions for a new patient who is clinically or molecularly similar to the previous patient. OBJECTIVE: The planned review aims to systematically summarize, map, and describe existing evidence to understand how patient similarity is defined and used in cancer research and clinical care. METHODS: To systematically identify relevant studies and to ensure reproducibility and transparency of the review process, a comprehensive literature search will be conducted in several bibliographic databases, including Web of Science, PubMed, LIVIVIVO, and MEDLINE, covering the period from 1998 to February 2024. After the initial duplicate deletion phase, a study selection phase will be applied using Rayyan, which consists of 3 distinct steps: title and abstract screening, disagreement resolution, and full-text screening. To ensure the integrity and quality of the selection process, each of these steps is preceded by a pilot testing phase. This methodological process will culminate in the presentation of the final research results in a structured form according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) flowchart. The protocol has been registered in the Journal of Medical Internet Research. RESULTS: This protocol outlines the methodologies used in conducting the scoping review. A search of the specified electronic databases and after removing duplicates resulted in 1183 unique records. As of March 2024, the review process has moved to the full-text evaluation phase. At this stage, data extraction will be conducted using a pretested chart template. CONCLUSIONS: The scoping review protocol, centered on these main concepts, aims to systematically map the available evidence on patient similarity among patients with cancer. By defining the types of data sources, approaches, and methods used in the field, and aligning these with the research questions, the review will provide a foundation for future research and clinical application in personalized cancer care. This protocol will guide the literature search, data extraction, and synthesis of findings to achieve the review's objectives. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58705.
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Neoplasms , Humans , Neoplasms/therapy , Research Design , Precision Medicine/methods , Reproducibility of ResultsABSTRACT
Background: Hepatocellular carcinoma (HCC) surveillance is currently performed using a one-size-fits-all strategy with ultrasound plus AFP (US + AFP). There is increasing interest in risk-stratified and precision surveillance strategies incorporating individual risk and variance in surveillance test performance; however, the cost-effectiveness of these approaches has not been evaluated. Methods: We conducted a cost-effectiveness analysis to evaluate four surveillance strategies (no surveillance, universal US + AFP surveillance, risk-stratified surveillance, and precision surveillance) in a simulated cohort of 50-year-old patients with compensated cirrhosis. The most cost-effective strategy was that with the highest incremental cost-effectiveness ratio (ICER) and below the willingness-to-pay (WTP) threshold of $150,000/QALY gained. Model inputs were based on literature review, and costs were derived from the Medicare fee schedule. Findings: The precision surveillance strategy demonstrated variation in recommended surveillance test based on HCC risk category and patient factors. US + AFP, risk-stratified, and precision surveillance detected more HCC cases per 100,000 population than no surveillance, with a higher proportion of early-stage cases for precision surveillance (67.6%) than risk-stratified (63.8%), universal ultrasound (63.2%), and no surveillance (38.0%). Compared to no surveillance, precision surveillance was most cost-effective, with an ICER of $104,614/QALY gained, whereas US + AFP and risk-stratified surveillance were both dominated. Compared to US + AFP, risk-stratified surveillance was cost saving and dominated US + AFP, whereas precision surveillance was cost-effective, with an ICER of $98,103/QALY gained. Results were sensitive to survival with early-stage HCC, cost of early-stage HCC treatment, and surveillance utilization. Precision surveillance remained the most cost-effective when WTP thresholds exceeded $110,000/QALY gained. Interpretation: A precision surveillance strategy is the most cost-effective method for HCC surveillance. This approach could maximize surveillance benefits in high-risk patients, while minimizing surveillance harms in low-risk individuals. Funding: National Cancer Institute (U01 CA230694, R01 CA222900, R01 CA212008, and U24ca086368) and Cancer Prevention Research Institute of Texas (CPRIT) (RP200554).