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BACKGROUND: Hepatic lipoprotein receptor-related protein 1 (LRP-1) plays a central role in peripheral amyloid beta (Aß) clearance, but its importance in Alzheimer's disease (AD) pathology is understudied. Our previous work showed that intragastric alcohol feeding to C57BL/6 J mice reduced hepatic LRP-1 expression which correlated with significant AD-relevant brain changes. Herein, we examined the role of hepatic LRP-1 in AD pathogenesis in APP/PS1 AD mice using two approaches to modulate hepatic LRP-1, intragastric alcohol feeding to model chronic heavy drinking shown by us to reduce hepatic LRP-1, and hepato-specific LRP-1 silencing. METHODS: Eight-month-old male APP/PS1 mice were fed ethanol or control diet intragastrically for 5 weeks (n = 7-11/group). Brain and liver Aß were assessed using immunoassays. Three important mechanisms of brain amyloidosis were investigated: hepatic LRP-1 (major peripheral Aß regulator), blood-brain barrier (BBB) function (vascular Aß regulator), and microglia (major brain Aß regulator) using immunoassays. Spatial LRP-1 gene expression in the periportal versus pericentral hepatic regions was confirmed using NanoString GeoMx Digital Spatial Profiler. Further, hepatic LRP-1 was silenced by injecting LRP-1 microRNA delivered by the adeno-associated virus 8 (AAV8) and the hepato-specific thyroxine-binding globulin (TBG) promoter to 4-month-old male APP/PS1 mice (n = 6). Control male APP/PS1 mice received control AAV8 (n = 6). Spatial memory and locomotion were assessed 12 weeks after LRP-1 silencing using Y-maze and open-field test, respectively, and brain and liver Aß were measured. RESULTS: Alcohol feeding reduced plaque-associated microglia in APP/PS1 mice brains and increased aggregated Aß (p < 0.05) by ELISA and 6E10-positive Aß load by immunostaining (p < 0.05). Increased brain Aß corresponded with a significant downregulation of hepatic LRP-1 (p < 0.01) at the protein and transcript level, primarily in pericentral hepatocytes (zone 3) where alcohol-induced injury occurs. Hepato-specific LRP-1 silencing significantly increased brain Aß and locomotion hyperactivity (p < 0.05) in APP/PS1 mice. CONCLUSION: Chronic heavy alcohol intake reduced hepatic LRP-1 expression and increased brain Aß. The hepato-specific LRP-1 silencing similarly increased brain Aß which was associated with behavioral deficits in APP/PS1 mice. Collectively, our results suggest that hepatic LRP-1 is a key regulator of brain amyloidosis in alcohol-dependent AD.
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Doença de Alzheimer , Fígado , Proteína-1 Relacionada a Receptor de Lipoproteína de Baixa Densidade , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Animais , Doença de Alzheimer/metabolismo , Masculino , Camundongos , Fígado/metabolismo , Amiloidose/metabolismo , Peptídeos beta-Amiloides/metabolismo , Encéfalo/metabolismo , Encéfalo/efeitos dos fármacos , Precursor de Proteína beta-Amiloide/genética , Precursor de Proteína beta-Amiloide/metabolismo , Etanol/administração & dosagem , Modelos Animais de Doenças , Barreira Hematoencefálica/metabolismo , Barreira Hematoencefálica/efeitos dos fármacos , Proteínas Supressoras de Tumor/genética , Proteínas Supressoras de Tumor/metabolismoRESUMO
BACKGROUND: Decentralization and authentication are embedded in blockchain technology, which utilizes artificial intelligence (AI) to ensure seamless sharing of data among different health care providers while safeguarding data privacy. Although community pharmacists are highly accessible to patients and possess robust clinical knowledge, they are limited in the clinical services they can provide owing to their lack of access to patient health records. We proposed a blockchain- and AI-based conceptual framework by performing a scoping review of successful blockchain integration in health systems. OBJECTIVE: To formulate a conceptual framework based on a scoping review to improve access to health care data in the community pharmacy setting through the adoption of blockchain technology and AI. METHODS: We performed a scoping review of literature based on Preferred Reporting Items for Systematic reviews and Meta-Analyses review criteria to identify the specific areas where blockchain can be implemented in health systems. We utilized the Pharmacists' Patient Care Process (PPCP) to identify 2 critical areas for blockchain integration that can support community pharmacists to access patient electronic health records and implement patient-specific information in clinical decision-making. RESULTS: We included 7 articles out of 70 articles in our final review. The 2 areas in the PPCP identified for the use of blockchain on the basis of the literature review were "Assess" and "Implement." Our proposed model involves pharmacists using AI and blockchain technology to comprehensively assess any concerns with the prescribed medication through access to laboratory results for patients and then implement a plan based on a comprehensive assessment of the patient's health record. CONCLUSIONS: Utilizing blockchain to securely share health data with community pharmacies has the potential to improve patient outcomes, optimize medication safety, and amplify pharmacists' roles in patient care. Future research should focus on implementing the model in the real-world settings.
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Blockchain , Inteligência Artificial , Registros Eletrônicos de Saúde , Acessibilidade aos Serviços de Saúde , Humanos , Farmacêuticos , TecnologiaRESUMO
BACKGROUND: The ongoing COVID-19 outbreak has caused devastating mortality and posed a significant threat to public health worldwide. Despite the severity of this illness and 2.3 million worldwide deaths, the disease mechanism is mostly unknown. Previous studies that characterized differential gene expression due to SARS-CoV-2 infection lacked robust validation. Although vaccines are now available, effective treatment options are still out of reach. RESULTS: To characterize the transcriptional activity of SARS-CoV-2 infection, a gene signature consisting of 25 genes was generated using a publicly available RNA-Sequencing (RNA-Seq) dataset of cultured cells infected with SARS-CoV-2. The signature estimated infection level accurately in bronchoalveolar lavage fluid (BALF) cells and peripheral blood mononuclear cells (PBMCs) from healthy and infected patients (mean 0.001 vs. 0.958; P < 0.0001). These signature genes were investigated in their ability to distinguish the severity of SARS-CoV-2 infection in a single-cell RNA-Sequencing dataset. TNFAIP3, PPP1R15A, NFKBIA, and IFIT2 had shown bimodal gene expression in various immune cells from severely infected patients compared to healthy or moderate infection cases. Finally, this signature was assessed using the publicly available ConnectivityMap database to identify potential disease mechanisms and drug repurposing candidates. Pharmacological classes of tricyclic antidepressants, SRC-inhibitors, HDAC inhibitors, MEK inhibitors, and drugs such as atorvastatin, ibuprofen, and ketoconazole showed strong negative associations (connectivity score < - 90), highlighting the need for further evaluation of these candidates for their efficacy in treating SARS-CoV-2 infection. CONCLUSIONS: Thus, using the 25-gene SARS-CoV-2 infection signature, the SARS-CoV-2 infection status was captured in BALF cells, PBMCs and postmortem lung biopsies. In addition, candidate SARS-CoV-2 therapies with known safety profiles were identified. The signature genes could potentially also be used to characterize the COVID-19 disease severity in patients' expression profiles of BALF cells.
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COVID-19/genética , COVID-19/virologia , Sistemas de Liberação de Medicamentos , Perfilação da Expressão Gênica , SARS-CoV-2/fisiologia , Células A549 , COVID-19/diagnóstico , Regulação da Expressão Gênica , Humanos , Modelos Biológicos , Reprodutibilidade dos Testes , Análise de Célula ÚnicaRESUMO
The implementation of pharmacogenomics (PGx) has come a long way since the dawn of utilizing pharmacogenomic data in clinical patient care. However, the potential benefits of sharing PGx results have yet to be explored. In this paper, we explore the willingness of patients to share PGx results, as well as the inclusion of family medication history in identifying potential family members for pharmacogenomics cascade testing (PhaCT). The genetic similarities in families allow for identifying potential gene variants prior to official preemptive testing. Once a candidate patient is determined, PhaCT can be initiated. PhaCT recognizes that further cascade testing throughout a family can serve to improve precision medicine. In order to make PhaCT feasible, we propose a novel shareable HIPAA-compliant informatics platform that will enable patients to manage not only their own test results and medications but also those of their family members. The informatics platform will be an external genomics system with capabilities to integrate with patients' electronic health records. Patients will be given the tools to provide information to and work with clinicians in identifying family members for PhaCT through this platform. Offering patients the tools to share PGx results with their family members for preemptive testing could be the key to empowering patients. Clinicians can utilize PhaCT to potentially improve medication adherence, which may consequently help to distribute the burden of health management between patients, family members, providers, and payers.
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Genômica , Farmacogenética/tendências , Testes Farmacogenômicos/tendências , Registros Eletrônicos de Saúde , Humanos , Medicina de PrecisãoRESUMO
Glucocorticoids are widely used for the suppression of inflammation, but evidence is growing that they can have rapid, non-genomic actions that have been unappreciated. Diverse cell signaling effects have been reported for glucocorticoids, leading us to hypothesize that glucocorticoids alone can swiftly increase the 3',5'-cyclic adenosine monophosphate (cAMP) production. We found that prednisone, fluticasone, budesonide, and progesterone each increased cAMP levels within 3 minutes without phosphodiesterase inhibitors by measuring real-time cAMP dynamics using the cAMP difference detector in situ assay in a variety of immortalized cell lines and primary human airway smooth muscle (HASM) cells. A membrane- impermeable glucocorticoid showed similarly rapid stimulation of cAMP, implying that responses are initiated at the cell surface. siRNA knockdown of Gαs virtually eliminated glucocorticoid-stimulated cAMP responses, suggesting that these drugs activate the cAMP production via a G protein-coupled receptor. Estradiol had small effects on cAMP levels but G protein estrogen receptor antagonists had little effect on responses to any of the glucocorticoids tested. The genomic and non-genomic actions of budesonide were analyzed by RNA-Seq analysis of 24 hours treated HASM, with and without knockdown of Gαs . A 140-gene budesonide signature was identified, of which 48 genes represent a non-genomic signature that requires Gαs signaling. Collectively, this non-genomic cAMP signaling modality contributes to one-third of the gene expression changes induced by glucocorticoid treatment and shifts the view of how this important class of drugs exerts its effects.
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Cromograninas/metabolismo , AMP Cíclico/metabolismo , Subunidades alfa Gs de Proteínas de Ligação ao GTP/metabolismo , Regulação da Expressão Gênica/efeitos dos fármacos , Glucocorticoides/farmacologia , Miócitos de Músculo Liso/metabolismo , Sistema Respiratório/metabolismo , Sistemas do Segundo Mensageiro/efeitos dos fármacos , Linhagem Celular Transformada , Cromograninas/genética , AMP Cíclico/genética , Subunidades alfa Gs de Proteínas de Ligação ao GTP/genética , Técnicas de Silenciamento de Genes , Humanos , Miócitos de Músculo Liso/patologia , Sistema Respiratório/patologia , Sistemas do Segundo Mensageiro/genéticaRESUMO
Human kinases play essential and diverse roles in the cellular activities of maintaining homeostasis and growth. Genetic mutations in the genes encoding the kinases (or phosphotransferases) have been linked with various types of cancers. In this study, we cataloged mutations in 500 kinases genes in >65,000 individuals of global populations from the Human Genetic Diversity Project (HGDP) and ExAC databases, and assessed their potentially deleterious impact by using the in silico tools SIFT, Polyphen2, and CADD. The analysis highlighted 35 deleterious non-synonymous SNVs in the ExAC and 5 SNVs in the HGDP project. Notably, a higher number of deleterious mutations was observed in the Non-Finnish Europeans (26 SNVs), followed by the Africans (14 SNVs), East Asians (13 SNVs), and South Asians (12 SNVs). The gene set enrichment analysis highlighted NTRK1 and FGFR3 being most significantly enriched among the kinases. The gene expression analysis revealed over-expression of NTRK1 in liver cancer, whereas, FGFR3 was found over-expressed in lung, breast, and liver cancers compared to their expression in the respective normal tissues. Also, 13 potential drugs were identified that target the NTRK1 protein, whereas 6 potential drugs for the FGFR3 target were identified. Taken together, the study provides a framework for exploring the predisposing germline mutations in kinases to suggest the underlying pathogenic mechanisms in cancers. The potential drugs are also suggested for personalized cancer management.
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Neoplasias , Humanos , Neoplasias/genética , Mutação , Mutação em Linhagem Germinativa , Perfilação da Expressão Gênica , Fosfotransferases/genéticaRESUMO
BACKGROUND: Little progress has been made in translating nutrigenomics knowledge into clinical counseling in the past decade. Currently, clinicians are overwhelmed by nutrigenomics information without the proper scientific guidelines on patient counseling. METHODS: In this study, we conducted a scoping review of the primary literature to assess the current evidence of nutrigenomics counseling. A literature search using PRISMA guidelines identified the current challenges and opportunities facing nutrigenomics counseling in clinical practice. RESULTS: We identified four main themes: inadequate training, lack of awareness, underdeveloped nutrigenomics counseling skills, and unreliable evidence-based practice information. Many clinicians did not have the necessary knowledge to perform nutrigenomic counseling and were unaware of the available scientific information source. Moreover, there are no guidelines in the scientific community to counsel patients on nutrigenomics testing. CONCLUSION: Opportunities exist for government and non-government entities to create an evidence-based information platform using clinical guidelines to integrate nutrigenomics knowledge from bench to bedside successfully.
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Aconselhamento Genético , Nutrigenômica , HumanosRESUMO
Human airway smooth muscle (HASM) is the primary target of ßAR agonists used to control airway hypercontractility in asthma and chronic obstructive pulmonary disease (COPD). ßAR agonists induce the production of cAMP by adenylyl cyclases (ACs), activate PKA and cause bronchodilation. Several other G-protein coupled receptors (GPCR) expressed in human airway smooth muscle cells transduce extracellular signals through cAMP but these receptors elicit different cellular responses. Some G-protein coupled receptors couple to distinct adenylyl cyclases isoforms with different localization, partly explaining this compartmentation, but little is known about the downstream networks that result. We used quantitative phosphoproteomics to define the downstream signaling networks emanating from cAMP produced by two adenylyl cyclases isoforms with contrasting localization in uman airway smooth muscle. After a short stimulus of adenylyl cyclases activity using forskolin, phosphopeptides were analyzed by LC-MS/MS and differences between cells overexpressing AC2 (localized in non-raft membranes) or AC6 (localized in lipid raft membranes) were compared to control human airway smooth muscle. The degree of AC2 and AC6 overexpression was titrated to generate roughly equal forskolin-stimulated cAMP production. 14 Differentially phosphorylated proteins (DPPs) resulted from AC2 activity and 34 differentially phosphorylated proteins resulted from AC6 activity. Analysis of these hits with the STRING protein interaction tool showed that AC2 signaling is more associated with modifications in RNA/DNA binding proteins and microtubule/spindle body proteins while AC6 signaling is associated with proteins regulating autophagy, calcium-calmodulin (Ca2+/CaM) signaling, Rho GTPases and cytoskeletal regulation. One protein, OFD1, was regulated in opposite directions, with serine 899 phosphorylation increased in the AC6 condition 1.5-fold but decreased to 0.46-fold by AC2. In conclusion, quantitative phosphoproteomics is a powerful tool for deciphering the complex signaling networks resulting from discreet signaling events that occur in cAMP compartments. Our data show key differences in the cAMP pools generated from AC2 and AC6 activity and imply that distinct cellular responses are regulated by these two compartments.
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Chronic hypoxia may have a huge impact on the cardiovascular and renal systems. Advancements in microscopy, metabolomics, and bioinformatics provide opportunities to identify new biomarkers. In this study, we aimed at elucidating the metabolic alterations in kidney tissues induced by chronic hypoxia using untargeted metabolomic analyses. Reverse phase ultrahigh performance liquid chromatography-mass spectroscopy/mass spectroscopy (RP-UPLC-MS/MS) and hydrophilic interaction liquid chromatography (HILIC)-UPLC-MS/MS methods with positive and negative ion mode electrospray ionization were used for metabolic profiling. The metabolomic profiling revealed an increase in metabolites related to carnitine synthesis and purine metabolism. Additionally, there was a notable increase in bilirubin. Heme, N-acetyl-L-aspartic acid, thyroxine, and 3-beta-Hydroxy-5-cholestenoate were found to be significantly downregulated. 3-beta-Hydroxy-5-cholestenoate was downregulated more significantly in male than female kidneys. Trichome Staining also showed remarkable kidney fibrosis in mice subjected to chronic hypoxia. Our study offers potential intracellular metabolite signatures for hypoxic kidneys.
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Metabolômica , Espectrometria de Massas em Tandem , Camundongos , Masculino , Feminino , Animais , Cromatografia Líquida , Espectrometria de Massas em Tandem/métodos , Metabolômica/métodos , Rim/metabolismo , Biomarcadores/metabolismoRESUMO
Introduction: Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined. Objective: To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs. Methods: A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI therapy between 2014 and 2018. Survival analysis utilized overall survival (OS) and real-world progression free survival (rwPFS) outcomes. Model performance matrices for predicting 1-year OS and 6-month rwPFS using linear regression baseline, optimal, and machine learning modeling approaches. Results: Patients experiencing an irAE were found to have a significantly longer OS and rwPFS compared to patients who did not (median OS 25.1 vs. 11.1 months; hazard ratio [HR] 0.51, confidence interval [CI] 0.39- 0.68, P-value <0.001, median rwPFS 5.7 months vs. 2.3; HR 0.52, CI 0.41- 0.66, P-value <0.001, respectively). Patients who received TKI therapy before initiation of ICI experienced significantly shorter OS than patients without prior TKI therapy (median OS 7.6 months vs. 18.5 months; P-value < 0.01). After adjusting for other variables, irAEs and prior TKI therapy significantly impacted OS and rwPFS. Lastly, the performances of models implementing logistic regression and machine learning approaches were comparable in predicting 1-year OS and 6-month rwPFS. Conclusion: The occurrence of irAEs, the timing of the events, and prior TKI therapy were significant predictors of survival in NSCLC patients on ICI therapy. Therefore, our study supports future prospective studies to investigate the impact of irAEs, and sequence of therapy on the survival of NSCLC patients taking ICIs.
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Aim: To develop and assess an augmented reality tool for pharmacogenomics (PGx) education based on artificial intelligence. Materials & methods: A HoloLens application was developed using feedback from three clinical PGx-trained pharmacists. 15 Participants independently reviewed the application and assessed usability using the system usability scale (SUS). Results & conclusion: Eighteen different frames were developed. Each video module was 2-3 min for the education. The application included textual information and 3D structures of PGx concepts. The mean SUS score for 15 participants (11 pharmacy students and four pharmacists) was 83, with a standard deviation of 6.6. Results suggest that PGxKnow has the potential to bridge the gap in PGx education, further widespread utilization of PGx and boost its impact on precision medicine.
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Realidade Aumentada , Farmacogenética , Inteligência Artificial , Humanos , Farmacogenética/educaçãoRESUMO
INTRODUCTION: Pharmacovigilance (PV) has proven to detect post-marketing adverse drug events (ADE). Previous research used the natural language processing (NLP) tool to extract unstructured texts relevant to ADEs. However, texts without context reduce the efficiency of such algorithms. Our objective was to develop and validate an innovative NLP tool, aTarantula, using a context-aware machine-learning algorithm to detect existing ADEs from social media using an aggregated lexicon. METHOD: aTarantula utilized FastText embeddings and an aggregated lexicon to extract contextual data from three patient forums (i.e., MedHelp, MedsChat, and PatientInfo) taking warfarin. The lexicon used warfarin package inserts and synonyms of warfarin ADEs from UMLS and FAERS databases. Data was stored on SQLite and then refined and manually checked by three clinical pharmacists for validation. RESULTS: Multiple organ systems where the most frequent ADE were reported at 1.50%, followed by CNS side effects at 1.19%. Lymphatic system ADEs were the least common side effect reported at 0.09%. The overall Spearman rank correlation coefficient between patient-reported data from the forums and FAERS was 0.19. As determined by pharmacist validation, aTarantula had a sensitivity of 84.2% and a specificity of 98%. Three clinical pharmacists manually validated our results. Finally, we created an aggregated lexicon for mining ADEs from social media. CONCLUSION: We successfully developed aTarantula, a machine-learning algorithmn based on artificial intelligence to extract warfarin-related ADEs from online social discussion forums automatically. Our study shows that it is feasible to use aTarantula to detect ADEs. Future researchers can validate aTarantula on the diverse dataset.
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Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos , Mídias Sociais , Sistemas de Notificação de Reações Adversas a Medicamentos , Inteligência Artificial , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/diagnóstico , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/prevenção & controle , Humanos , Aprendizado de Máquina , Farmacovigilância , VarfarinaRESUMO
Mural cells (MCs) wrap around the endothelium, and participate in the development and homeostasis of vasculature. MCs have been reported as heterogeneous population morphologically and functionally. However, the transcriptional heterogeneity of MCs was rarely studied. In this study, we illustrated the transcriptional heterogeneity of MCs with different perspectives by using publicly available single-cell dataset GSE109774. Specifically, MCs are transcriptionally different from other cell types, and ligand-receptor interactions of different cells with MCs vary. Re-clustering of MCs identified five distinct subclusters. The heterogeneity of MCs in tissues was reflected by MC coverage, various distribution of MC subclusters, and ligand-receptor interactions of MCs and parenchymal cells. The transcriptomic diversity of MCs revealed in this article will help facilitate further research into MCs.
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Endotélio Vascular/citologia , Endotélio Vascular/metabolismo , Perfilação da Expressão Gênica/métodos , Heterogeneidade Genética , Análise de Célula Única/métodos , Animais , Conjuntos de Dados como AssuntoRESUMO
Alzheimer's Disease (AD) is one of the most prevalent neurodegenerative chronic diseases. As it progresses, patients become increasingly dependent, and their caregivers are burdened with the increasing demand for managing their care. Mobile health (mHealth) technology, such as smartphone applications, can support the need of these caregivers. This paper examines the published academic literature of mHealth applications that support the caregivers of AD patients. Following the PRISMA for scoping reviews, we searched published literature in five electronic databases between January 2014 and January 2021. Twelve articles were included in the final review. Six themes emerged based on the functionalities provided by the reviewed applications for caregivers. They are tracking, task management, monitoring, caregiver mental support, education, and caregiver communication platform. The review revealed that mHealth applications for AD patients' caregivers are inadequate. There is an opportunity for industry, government, and academia to fill the unmet need of these caregiver.
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BACKGROUND: The usefulness of circulating tumor DNA (ctDNA) in detecting mutations and monitoring treatment response has not been well studied beyond a few actionable biomarkers in non-small cell lung cancer (NSCLC). RESEARCH QUESTION: How does the usefulness of ctDNA analysis compare with that of solid tumor biopsy analysis in patients with NSCLC? METHODS: We retrospectively evaluated 370 adult patients with NSCLC treated at the City of Hope between November 2015 and August 2019 to assess the usefulness of ctDNA in mutation identification, survival, concordance with matched tissue samples in 32 genes, and tumor evolution. RESULTS: A total of 1,688 somatic mutations were detected in 473 ctDNA samples from 370 patients with NSCLC. Of the 473 samples, 177 showed at least one actionable mutation with currently available Food and Drug Administration-approved NSCLC therapies. MET and CDK6 amplifications co-occurred with BRAF amplifications (false discovery rate [FDR], < 0.01), and gene-level mutations were mutually exclusive in KRAS and EGFR (FDR, 0.0009). Low cumulative percent ctDNA levels were associated with longer progression-free survival (hazard ratio [HR], 0.56; 95% CI, 0.37-0.85; P = .006). Overall survival was shorter in patients harboring BRAF mutations (HR, 2.35; 95% CI, 1.24-4.6; P = .009), PIK3CA mutations (HR, 2.77; 95% CI, 1.56-4.9; P < .001) and KRAS mutations (HR, 2.32; 95% CI, 1.30-4.1; P = .004). Gene-level concordance was 93.8%, whereas the positive concordance rate was 41.6%. More mutations in targetable genes were found in ctDNA than in tissue biopsy samples. Treatment response and tumor evolution over time were detected in repeated ctDNA samples. INTERPRETATION: Although ctDNA analysis exhibited similar usefulness to tissue biopsy analysis, more mutations in targetable genes were missed in tissue biopsy analyses. Therefore, the evaluation of ctDNA in conjunction with tissue biopsy samples may help to detect additional targetable mutations to improve clinical outcomes in advanced NSCLC.
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Carcinoma Pulmonar de Células não Pequenas , DNA Tumoral Circulante/genética , Classe I de Fosfatidilinositol 3-Quinases/genética , Neoplasias Pulmonares , Proteínas Proto-Oncogênicas B-raf/genética , Proteínas Proto-Oncogênicas p21(ras)/genética , Idoso , Biomarcadores Tumorais/genética , Biópsia/métodos , Biópsia/estatística & dados numéricos , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Carcinoma Pulmonar de Células não Pequenas/patologia , Receptores ErbB/genética , Feminino , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/patologia , Masculino , Terapia de Alvo Molecular/métodos , Terapia de Alvo Molecular/normas , Mutação , Medicina de Precisão/métodos , Medicina de Precisão/normas , Intervalo Livre de Progressão , Melhoria de QualidadeRESUMO
Despite the potential to improve patient outcomes, the application of pharmacogenomics (PGx) is yet to be routine. A growing number of PGx implementers are leaning toward using combinatorial PGx (CPGx) tests (i.e., multigene tests) that are reusable over patients' lifetimes. However, selecting a single best available CPGx test is challenging owing to many patient- and population-specific factors, including variant frequency differences across ethnic groups. The primary objective of this study was to evaluate the detection rate of currently available CPGx tests based on the cytochrome P450 (CYP) gene variants they target. The detection rate was defined as the percentage of a given population with an "altered metabolizer" genotype predicted phenotype, where a CPGx test targeted both gene variants a prospective diplotypes. A potential genotype predicted phenotype was considered an altered metabolizer when it resulted in medication therapy modification based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Targeted variant CPGx tests found in the Genetic Testing Registry (GTR), gene selection information, and diplotype frequency data from the Pharmacogenomics Knowledge Base (PharmGKB) were used to determine the detection rate of each CPGx test. Our results indicated that the detection rate of CPGx tests covering CYP2C19, CYP2C9, CYP2D6, and CYP2B6 show significant variation across ethnic groups. Specifically, the Sub-Saharan Africans have 63.9% and 77.9% average detection rates for CYP2B6 and CYP2C19 assays analyzed, respectively. In addition, East Asians (EAs) have an average detection rate of 55.1% for CYP2C9 assays. Therefore, the patient's ethnic background should be carefully considered in selecting CPGx tests.
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Metastasis continues to be the primary cause of all cancer-related deaths despite the recent advancements in cancer treatments. To evaluate the role of mutations in overall survival (OS) and treatment outcomes, we analyzed 957 metastatic patients with seven major cancer types who had available molecular testing results with a FoundationOne CDx® panel. The most prevalent genes with somatic mutations were TP53, KRAS, APC, and LRP1B. In this analysis, these genes had mutation frequencies higher than in publicly available datasets. We identified that the somatic mutations were seven mutually exclusive gene pairs and an additional fifty-two co-occurring gene pairs. Mutations in the mutually exclusive gene pair APC and CDKN2A showed an opposite effect on the overall survival. However, patients with CDKN2A mutations showed significantly shorter OS (HR: 1.72, 95% CI: 1.34-2.21, p < 0.001) after adjusting for cancer type, age at diagnosis, and sex. Five-year post metastatic diagnosis survival analysis showed a significant improvement in OS (median survival 28 and 43 months in pre-2015 and post-2015 metastatic diagnosis, respectively, p = 0.00021) based on the year of metastatic diagnosis. Although the use of targeted therapies after metastatic diagnosis prolonged OS, the benefit was not statistically significant. However, longer five-year progression-free survival (PFS) was significantly associated with targeted therapy use (median 10.9 months (CI: 9.7-11.9 months) compared to 9.1 months (CI: 8.1-10.1 months) for non-targeted therapy, respectively, p = 0.0029). Our results provide a clinically relevant overview of the complex molecular landscape and survival mechanisms in metastatic solid cancers.
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Background: Despite potential benefits, the practice of incorporating pharmacogenomics (PGx) results in clinical decisions has yet to diffuse widely. In this study, we conducted a review of recent discussions on data standards and interoperability with a focus on sharing PGx test results among health systems. Materials & methods: We conducted a literature search for PGx clinical decision support systems between 1 January 2012 and 31 January 2020. Thirty-two out of 727 articles were included for the final review. Results: Nine of the 32 articles mentioned data standards and only four of the 32 articles provided solutions for the lack of interoperability. Discussions: Although PGx interoperability is essential for widespread implementation, a lack of focus on standardized data creates a formidable challenge for health information exchange. Conclusion: Standardization of PGx data is essential to improve health information exchange and the sharing of PGx results between disparate systems. However, PGx data standards and interoperability are often not addressed in the system-level implementation.
Assuntos
Bases de Dados Factuais/normas , Implementação de Plano de Saúde , Farmacogenética/organização & administração , Sistemas de Apoio a Decisões Clínicas , Humanos , Sistemas de Informação/normasRESUMO
BACKGROUND: Medication Guides consisting of crucial interactions and side effects are extensive and complex. Due to the exhaustive information, patients do not retain the necessary medication information, which can result in hospitalizations and medication nonadherence. A gap exists in understanding patients' cognition of managing complex medication information. However, advancements in technology and artificial intelligence (AI) allow us to understand patient cognitive processes to design an app to better provide important medication information to patients. OBJECTIVE: Our objective is to improve the design of an innovative AI- and human factor-based interface that supports patients' medication information comprehension that could potentially improve medication adherence. METHODS: This study has three aims. Aim 1 has three phases: (1) an observational study to understand patient perception of fear and biases regarding medication information, (2) an eye-tracking study to understand the attention locus for medication information, and (3) a psychological refractory period (PRP) paradigm study to understand functionalities. Observational data will be collected, such as audio and video recordings, gaze mapping, and time from PRP. A total of 50 patients, aged 18-65 years, who started at least one new medication, for which we developed visualization information, and who have a cognitive status of 34 during cognitive screening using the TICS-M test and health literacy level will be included in this aim of the study. In Aim 2, we will iteratively design and evaluate an AI-powered medication information visualization interface as a smartphone app with the knowledge gained from each component of Aim 1. The interface will be assessed through two usability surveys. A total of 300 patients, aged 18-65 years, with diabetes, cardiovascular diseases, or mental health disorders, will be recruited for the surveys. Data from the surveys will be analyzed through exploratory factor analysis. In Aim 3, in order to test the prototype, there will be a two-arm study design. This aim will include 900 patients, aged 18-65 years, with internet access, without any cognitive impairment, and with at least two medications. Patients will be sequentially randomized. Three surveys will be used to assess the primary outcome of medication information comprehension and the secondary outcome of medication adherence at 12 weeks. RESULTS: Preliminary data collection will be conducted in 2021, and results are expected to be published in 2022. CONCLUSIONS: This study will lead the future of AI-based, innovative, digital interface design and aid in improving medication comprehension, which may improve medication adherence. The results from this study will also open up future research opportunities in understanding how patients manage complex medication information and will inform the format and design for innovative, AI-powered digital interfaces for Medication Guides. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/21659.