Pharmacogenomics: Driving Personalized Medicine

Pharmacogenomic variants in the Pumi population from Yunnan, China

BACKGROUND

Pharmacogenomics is used to identify genetic factors that influence drug responses, thereby optimizing therapeutic outcomes and reducing adverse effects. The objective of this study is to identify pharmacogenomic variations and their clinical relevance to drug metabolism and toxicity within the Pumi population.

METHODS

Eighty-two genetic variants in 43 genes were genotyped in 200 unrelated Pumi individuals using the Agena MassARRAY Assay. Chi-square tests, adjusted for multiple comparisons with Bonferroni correction, were used to compare genotype frequency divergences between the Pumi population and 26 other populations. Population genetic structure diversity and pairwise F-statistics (Fst) were assessed across 27 populations using Structure v2.3.1 and Arlequin v3.5 software.

RESULTS

After Bonferroni correction, a number of single nucleotide variations (SNVs) exhibited significant differences in frequency between the Pumi population and other populations. The allele frequencies of ADH1A rs975833, ADH1B rs1229984, TPMT rs1142345, and CYP2A6 rs8192726 in the Pumi population were notably different from the East Asian population or the other 26 populations. PharmGKB data indicate that rs1229984, rs1142345, and rs8192726 are associated with the metabolic efficiency of acetaldehyde, mercaptopurine, and efavirenz, respectively. Additionally, the genetic structure analysis (K = 5) and pairwise Fst calculations revealed that the Pumi population shared a similar genetic background with CHB (Fst = 0.031), JPT (Fst = 0.033), KHV (Fst = 0.035), CHS (Fst = 0.036), and CDX (Fst = 0.037) populations.

CONCLUSION

Our findings reveal unique genetic variations and biomarkers within the Pumi population, which contributes pharmacogenomic insights and theoretical foundations for personalized medicine tailored to the Pumi population.

Translational Advances in Oncogene and Tumor-Suppressor Gene Research

Cancer, characterized by the uncontrolled proliferation of cells, is one of the leading causes of death globally, with approximately one in five people developing the disease in their lifetime. While many driver genes were identified decades ago, and most cancers can be classified based on morphology and progression, there is still a significant gap in knowledge about genetic aberrations and nuclear DNA damage. The study of two critical groups of genes-tumor suppressors, which inhibit proliferation and promote apoptosis, and oncogenes, which regulate proliferation and survival-can help to understand the genomic causes behind tumorigenesis, leading to more personalized approaches to diagnosis and treatment. Aberration of tumor suppressors, which undergo two-hit and loss-of-function mutations, and oncogenes, activated forms of proto-oncogenes that experience one-hit and gain-of-function mutations, are responsible for the dysregulation of key signaling pathways that regulate cell division, such as p53, Rb, Ras/Raf/ERK/MAPK, PI3K/AKT, and Wnt/β-catenin. Modern breakthroughs in genomics research, like next-generation sequencing, have provided efficient strategies for mapping unique genomic changes that contribute to tumor heterogeneity. Novel therapeutic approaches have enabled personalized medicine, helping address genetic variability in tumor suppressors and oncogenes. This comprehensive review examines the molecular mechanisms behind tumor-suppressor genes and oncogenes, the key signaling pathways they regulate, epigenetic modifications, tumor heterogeneity, and the drug resistance mechanisms that drive carcinogenesis. Moreover, the review explores the clinical application of sequencing techniques, multiomics, diagnostic procedures, pharmacogenomics, and personalized treatment and prevention options, discussing future directions for emerging technologies.

Synergistic Effects of Low-Frequency Ultrasound and Therapeutic Agents on Endothelial and Renal Cells: Emphasis on Cell Functionality, Oxidative Stress, and Inflammatory Markers

Background: Ischemic heart disease remains the leading cause of death worldwide, with coronary microvascular dysfunction (CMD) as a key complication after ST-elevation myocardial infarction (STEMI). Endothelial dysfunction contributes to CMD, impairing vascular tone and increasing inflammation. While angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs) aid vascular health, their efficacy may improve with therapeutic ultrasound, which enhances drug delivery and endothelial response. This study explores the combined effects of ultrasound and pharmacological treatment on the ACE axis and inflammation in endothelial and renal cells. Methods: Human umbilical vein endothelial cells (HUVECs) and human renal proximal tubular epithelial cell line RPTEC/TERT1 were treated with captopril, losartan, and dexamethasone, alone or combined with low-frequency ultrasound (LFU). Cell viability and wound-healing assays assessed cellular function, while nitric oxide (NO) and reactive oxygen species (ROS) assays were used to evaluate redox signaling. Gene expression related to the ACE axis, inflammation, and vascular and renal cell function was analyzed via qPCR. Results: Captopril and losartan combined with LFU improved endothelial cell viability, wound healing, and NO production at various concentrations, whereas only losartan with LFU enhanced cell viability and wound healing in renal cells. Dexamethasone with LFU increased ROS levels and had variable effects on RPTEC/TERT1 cell survival. Gene expression analysis showed that LFU alone reduced pro-inflammatory markers VCAM-1, ICAM-1, and PTGS2 in captopril-treated HUVECs and similarly affected CYP4F2 in losartan-treated HUVECs. LFU also decreased PTGS2 expression at higher dexamethasone concentrations. In RPTEC/TERT1 cells, LFU alone did not impact SGLT2 or GGT1 expression, but captopril with LFU downregulated GGT1, and dexamethasone with LFU upregulated SGLT2 at higher concentrations. Conclusions: This study demonstrates that LFU enhances the effects of RAS inhibitors by promoting NO synthesis and reducing oxidative stress, while its combination with dexamethasone may have variable, potentially cytotoxic effects on renal cells. Gene expression patterns suggest LFU's anti-inflammatory potential and its role in modulating drug efficacy.

Integrated Pharmacogenetic Signature for the Prediction of Prostatic Neoplasms in Men With Metabolic Disorders

BACKGROUND/AIM

Oncogenic processes are delineated by metabolic dysregulation. Drug likeness is pharmacokinetically tested through the CYP450 enzymatic system, whose genetic aberrations under epigenetic stress could shift male organisms into prostate cancer pathways. Our objective was to predict the susceptibility to prostate neoplasia, focused on benign prostatic hyperplasia (BPH) and prostate cancer (PCa), based on the pharmacoepigenetic and the metabolic profile of Caucasians.

MATERIALS AND METHODS

Two independent cohorts of 47,389 individuals in total were assessed to find risk associations of CYP450 genes with prostatic neoplasia. The metabolic profile of the first cohort was statistically evaluated and frequencies of absorption-distribution-metabolism-excretion-toxicity (ADMET) properties were calculated. Prediction of miRNA pharmacoepigenetic targeting was performed.

RESULTS

We found that prostate cancer and benign prostatic hyperplasia patients of the first cohort shared common cardiometabolic trends. Drug classes C08CA, C09AA, C09CA, C10AA, C10AX of the cardiovascular, and G04CA, G04CB of the genitourinary systems, were associated with increased prostate cancer risk, while C03CA and N06AB of the cardiovascular and nervous systems were associated with low-risk for PCa. CYP3A4*1B was the most related pharmacogenetic polymorphism associated with prostate cancer susceptibility. miRNA-200c-3p and miRNA-27b-3p seem to be associated with CYP3A4 targeting and prostate cancer predisposition. Metabolomic analysis indicated that 11β-OHT, 2β-OHT, 15β-OHT, 2α-OHT and 6β-OHT had a high risk, and 16α-OHT, and 16β-OHT had an intermediate disease-risk.

CONCLUSION

These findings constitute a novel integrated signature for prostate cancer susceptibility. Further studies are required to assess their predictive value more fully.

Relevance of proteomics and metabolomics approaches to overview the tumorigenesis and better management of cancer

Proteomics and metabolomics, integral combination of OMICs platform are gaining prominence in cancer research to enhance scientific knowledge of bio-molecular interactions occurs in the cellular processes during cancer progression. This approach designed to identify potential tools for addressing the complexities of this multifaceted disease. This analysis focussed on the intricate interplay between proteins and metabolites within cancer cells and their surrounding microenvironment. By reviewing current proteomics and metabolomics studies, we aim to gain invaluable insights into tumour biology, progression, and its implication in therapeutic responses. This study highlights the importance of proteomics and metabolomics in discovering therapeutic targets and diagnostic biomarkers for targeted cancer treatment. Proteomics facilitates the analysis of protein expression, modifications and interactions, exemplified by the identification of HER2 mutations leads to development of breast cancer hence targeted therapies like trastuzumab could be initiated. Metabolomics reveals metabolic alternations such as elevated 2-hydroxyglutarate levels in gliomas linked to cancer progression and treatment resistance. The integration of these approaches clarifies complex signalling network driving oncogenesis and paves the way for innovative cancer therapies, including immune cheque point inhibitors. Proteomics and metabolomics have revolutionised cancer biology by revealing intricate signalling networks, metabolic dysregulations, and unique molecular alterations. This information is crucial for early cancer identification and prognosis, and for designing personalized therapeutic strategies. Innovative technologies like artificial intelligence and high-throughput mass spectrometry further enhance the potential of these studies. Fostering multidisciplinary collaboration and data-sharing is essential for maximising the impact of these approaches to cure as well as better management of the cancer.

MTHFR variant links homocysteine metabolism and endothelial cell dysfunction by targeting mitophagy in human thoracic aortic dissection patient induced pluripotent stem cell (iPSC) models

AIMS

Genetics and environmental cues boost the development of human diseases. Methylenetetrahydrofolate reductase (MTHFR) is involved in the metabolism of homocysteine, and a common variant rs1801133 of MTHFR has been reported in human cardiovascular diseases. This study aims to providing a novel strategy for patient stratification with specific genetic and metabolic screening, finally for personalized healthcare for patients with thoracic aortic dissection.

METHODS AND RESULTS

We corrected the MTHFR variant to generate an isogenic control iPSC line (Isogenic-iPSC) with CRISPR/Cas9 method, and this isogenic-iPSC shared the same other genetic information with our previously established MTHFR-iPSC line, providing a promising approach for analysis the phenotype and mechanism of rs1801133. During the direct differentiation of endothelial cells from both iPSC lines, rs1801133 variant did not affect the endothelial cell fate determination. Without homocysteine, this variant has little effect on endothelial cell function. While administration of homocysteine, the MTHFR-iPSC derived endothelial cells exhibited disrupted mitophagy, increased cell apoptosis and decreased cell viability. Bulk RNA-seq data indicated LAMP3 is a target of homocysteine, activation of LAMP3 might contribute to homocysteine induced the disruption of mitochondrial structure and cell apoptosis. With chemical compounds screening, kaempferol ameliorated the homocysteine-induced cell toxicity by restoring the mitochondrial structure. The direct relationship between homocysteine metabolism and MTHFR rs1801133 variant was investigated, and the molecular target for homocysteine and translational perspective has also been demonstrated.

CONCLUSIONS

Collectively, this study provided the direct evidence of a specific genetic variant in MTHFR and homocysteine metabolism. Investigating the molecular mechanism of homocysteine activated LAMP3 on endothelial cell dysfunction and mitophagy could provide novel insights for targeted disease prevention and improving individual outcomes.

TRANSLATIONAL PERSPECTIVE

Thoracic aortic dissection (TAD) is a life-threatening cardiovascular disease with a high mortality, lacking effective medical treatment and early diagnosis. Endothelial cells dysfunction has been considered into the development of TAD. Here, we show that MTHFR variant is responsible for the elevated homocysteine in iPSC-ECs, and disrupted mitochondrial structures by homocysteine significantly impaired endothelial function. Understanding the mechanism and translational medicine of homocysteine-induced endothelial toxicity in human with MTHFR variant could benefit the novel strategy for prevention and vessel protection against metabolism injury. Meanwhile, targeting mitophagy and application of small molecule, such as kaempferol, also provide an insight for endothelial protection.

Pharmacogenomics of Chemotherapies for Childhood Cancers in Africa: A Scoping Review

Background

Pharmacogenomics holds significant promise in improving the efficacy and safety of chemotherapy for childhood cancers. However, the field remains underexplored in Africa, where high genetic diversity and substantial disease burdens, including cancers, create unique challenges. This review investigates the current state of pharmacogenomics research in childhood cancer chemotherapies across Africa, focusing on genetic variations influencing chemotherapy efficacy and adverse drug reactions. It also highlights critical gaps, such as limited infrastructure and insufficient healthcare worker knowledge, and emphasizes the importance of capacity-building initiatives in the region.

Methods

A scoping review was conducted encompassing studies published up to September 2024 that examined pharmacogenomic variations associated with chemotherapies in childhood cancer patients across Africa. The review included laboratory genetic analyses and surveys assessing healthcare workers' knowledge, attitudes, and perceptions regarding pharmacogenomics, particularly in the context of pediatric oncology.

Results

A total of 12 genes were identified across eight studies, including TPMT, CYP3A5, MDR1, MAPT, NUDT15, ITPA, IMPDH1, SLC29A1, SLC28A2, SLC28A3, ABCC4, and MTHFR. The most studied genes were TPMT and CYP3A5, which are involved in the metabolism of 6-mercaptopurine (6-MP) and vincristine, respectively. These studies spanned five African countries, including Kenya, Egypt, Zimbabwe, Nigeria, Tunisia, and Libya, and focused primarily on childhood cancers, particularly acute lymphoblastic leukemia. Chemotherapies frequently studied were 6-MP (reported in five studies), vincristine, cyclophosphamide, and methotrexate. Knowledge of pharmacogenomics among healthcare workers in Africa remains low, though a positive attitude towards its clinical applications was observed.

Conclusion

Pharmacogenomic variants, such as TPMT*3A, 3C, and CYP3A53, *6, significantly impact drug metabolism in African children with cancer. However, research remains regionally limited, and gaps in infrastructure and healthcare worker training persist. Expanding research efforts and improving pharmacogenomics capacity through pharmacist training and capacity-building initiatives are essential to advancing personalized medicine in Africa, ultimately improving treatment outcomes for pediatric cancer patients.

Artificial Intelligence-driven and technological innovations in the diagnosis and management of substance use disorders

Substance Use Disorders (SUD) lead to a collection of health challenges such as overdoses and clinical diseases. Populations that are vulnerable and lack straightforward treatment access are vulnerable to significant economic and social effects linked to SUD. The ongoing advances in technology, especially Artificial Intelligence (AI), promise new ways to reduce the effects of SUD, refine treatment standards, and minimize the risk of relapse through tailored treatment plans. Recent innovations in functional neuroimaging techniques, such as fMRI, have led to the ability to detect brain patterns associated with drug use, and biomarkers in blood testing provide crucial diagnostic support. In addition, digital platforms applied for behavioral assessment supported by AI and natural language processing improve the early recognition of substance consumption trends, allowing for targeted interventions reliant on real-time data. Using pharmacogenetics and resources like mobile apps and wearable devices makes the development of care programs that continuously track substance use, mental health, and physical changes possible. At the core of ethical issues related to the application of AI for SUD are the rights of patients to have their privacy protected to ensure that all people justly have access to these technologies. The advancement of AI models provides significant possibilities to support clinical judgment and enhance patient outcomes.

Advancements in programmed cell death research in antitumor therapy: a comprehensive overview

Cell death is a normal physiological process within cells that involves multiple pathways, such as normal DNA damage, cell cycle arrest, and programmed cell death (PCD). Cell death has been a hot spot of research in tumor-related fields, especially programmed cell death, which is a key form of cell death and is classified into different types according to the mechanism of occurrence, such as apoptosis, autophagy, necroptosis, pyroptosis, ferroptosis, and disulfidptosis. Given the important role of PCD in maintaining tissue homeostasis and inhibiting tumorigenesis and development, more and more basic and clinical studies are devoted to revealing its potential application in anti-tumor strategies. The purpose of this review is to systematically review the regulatory mechanisms of PCD and to summarize the latest research progress of anti-tumor treatment strategies based on PCD.

Discussion on the optimization of personalized medication using information systems based on pharmacogenomics: an example using colorectal cancer

Pharmacogenomics (PGx) is a powerful tool for clinical optimization of drug efficacy and safety. However, due to many factors affecting drugs in the real world, PGx still accounts for a small proportion of actual clinical application scenarios. Therefore, based on the information software, pharmacists use their professional advantages to integrate PGx into all aspects of pharmaceutical care, which is conducive to promoting the development of personalized medicine. In this paper, the establishment of an information software platform is summarized for the optimization of a personalized medication program based on PGx. Taking colorectal cancers (CRC) as an example, this paper also discusses the role of PGx in different working modes and participation in drug management of CRC patients by pharmacists with the help of information systems. Finally, we summarized the recommendations of different PGx guidelines to provide reference for the follow-up personalized pharmaceutical care.

The current landscape of personalised preventive approaches for non-communicable diseases: A scoping review

INTRODUCTION

Personalised prevention offers a promising tool to reduce the impact of non-communicable diseases, which represent a growing health burden worldwide. However, to support the adoption of this innovation it is needed to clarify the current state of available evidence in this area. This work aims to provide an overview of recent publications on personalised prevention for chronic conditions.

MATERIALS AND METHODS

A scoping review of scientific literature from Medline, Scopus, Web of Science and grey literature was conducted. Eligible articles included prospective primary studies and clinical practice directives on personalised preventive approaches for chronic diseases published between January 2017 to December 2023. The review followed Arksey-O'Malley guidelines and PRISMA-ScR checklist.

RESULTS

We identified 121 publications including 60 primary cohort studies and 61 clinical practice directives. We extracted 249 personalised preventive approaches, 27% in primary prevention, 27% in secondary prevention, and 46% in tertiary prevention. In primary prevention, 50% of the 67 approaches were from cohort studies, mainly targeting cardiovascular diseases, and 50% from directives primarily focused on cancer. Secondary prevention included 66 approaches, 73% from directives mainly concerning breast cancer. Tertiary prevention included 116 approaches, evenly distributed among the two publication types and focusing mostly on cancer and cardiovascular diseases. Lastly, tertiary prevention is the most represented level of prevention both in primary research studies and directives (54% and 41% respectively).

CONCLUSIONS

Our study highlights a significant focus on personalised prevention in oncology in the past few years, with numerous recently issued clinical practice directives. We identified substantial original research in personalised primary prevention of cardiovascular diseases, indicating growing interest in the field. However, the distribution of primary studies and directives across the three preventive levels anticipate challenges in generating evidence of clinical utility in primary and secondary prevention, with most approaches falling under tertiary prevention.

Innovation in cancer pharmacotherapy through integrative consideration of germline and tumor genomes

Precision cancer medicine is widely established, and numerous molecularly targeted drugs for various tumor entities are approved or are in development. Personalized pharmacotherapy in oncology has so far been based primarily on tumor characteristics, for example, somatic mutations. However, the response to drug treatment also depends on pharmacological processes summarized under the term ADME (absorption, distribution, metabolism, and excretion). Variations in ADME genes have been the subject of intensive research for >5 decades, considering individual patients' genetic makeup, referred to as pharmacogenomics (PGx). The combined impact of a patient's tumor and germline genome is only partially understood and often not adequately considered in cancer therapy. This may be attributed, in part, to the lack of methods for combined analysis of both data layers. Optimized personalized cancer therapies should, therefore, aim to integrate molecular information, which derives from both the tumor and the germline genome, and taking into account existing PGx guidelines for drug therapy. Moreover, such strategies should provide the opportunity to consider genetic variants of previously unknown functional significance. Bioinformatic analysis methods and corresponding algorithms for data interpretation need to be developed to integrate PGx data in cancer therapy with a special meaning for interdisciplinary molecular tumor boards, in which cancer patients are discussed to provide evidence-based recommendations for clinical management based on individual tumor profiles. SIGNIFICANCE STATEMENT: The era of personalized oncology has seen the emergence of drugs tailored to genetic variants associated with cancer biology. However, the full potential of targeted therapy remains untapped owing to the predominant focus on acquired tumor-specific alterations. Optimized cancer care must integrate tumor and patient genomes, guided by pharmacogenomic principles. An essential prerequisite for realizing truly personalized drug treatment of cancer patients is the development of bioinformatic tools for comprehensive analysis of all data layers generated in modern precision oncology programs.

Navigating Recent Changes in Dosing Information: Dynamics of FDA-Approved Monoclonal Antibodies in Post-Marketing Realities

Monoclonal antibodies (mAbs) are critical components in the therapeutic landscape, but their dosing strategies often evolve post-approval as new data emerge. This review evaluates post-marketing label changes in dosing information for FDA-approved mAbs from January 2015 to September 2024, with a focus on both initial and extended indications. We systematically analyzed dosing modifications, categorizing them into six predefined groups: Dose increases or decreases, inclusion of new patient populations by body weight or age, shifts from body weight-based dosing to fixed regimens, and adjustments in infusion rates. Among the 86 mAbs evaluated, 21% (n = 18) exhibited changes in dosing information for the initial indication, with a median time to modification of 37.5 months (range: 5-76 months). Furthermore, for mAbs with extended indications (n = 26), 19.2% (n = 5) underwent dosing changes in their first extensions, with a median time to adjustment of 31 months (range: 8-71 months). Key drivers for these adjustments included optimizing therapeutic efficacy, addressing safety concerns, accommodating special populations, and enhancing patient convenience. We also discuss the role of model-informed drug development, real-world evidence, and pharmacogenomics in refining mAb dosing strategies. These insights underscore the importance of ongoing monitoring and data integration in the post-marketing phase, providing a foundation for future precision medicine approaches in mAb therapy.

Post-transplant complications revealed by mycophenolate mofetil related transporters and metabolic enzymes gene polymorphisms in pediatric patients with hematological disorders

BACKGROUND

Haploidentical hematopoietic stem cell transplantation (Haplo-HSCT) serves as an important option for patients without an HLA matched donor in treating hematological disorders, while patients may experience various complications after transplantation. Mycophenolate mofetil (MMF), a cornerstone drug for graft-versus-host disease (GvHD) prophylaxis, effectively reduces the incidence of acute GvHD, and the efficacy of MMF varies among individuals associated with MMF-related transporters and metabolic enzymes single nucleotide polymorphisms (SNPs). However, limited studies have systematically reported the correlations between the MMF-related SNPs and post-transplant complications.

METHODS

Here, we conducted a retrospective study involving 90 pediatric patients with hematological disorders who underwent haplo-HSCT at a single center. All patients were subjected to MMF-related SNP testing, combined with common clinical characteristics, to be correlated with post-transplant complications.

RESULTS

We observed that all 15 MMF-related SNPs were in Hardy-Weinberg equilibrium. Based on multivariate Cox regression analysis of post-transplant complications, we discovered that SLCO1B1 (521T > C) variant genotype was an independent protective factor for chronic GvHD (HR = 0.25, 95% confidence interval (CI) (0.08-0.84)). For viral infection, CYP2C8 (1291 + 106T > C) variant genotype was an independent risk factor for cytomegalovirus infection (HR = 2.98, 95% CI (1.18-7.53)). As to hemorrhagic cystitis, SLCO1B1 (1865 + 4846T > C) variant genotype was an independent protective factor, while older age was considered as an independent risk factor (HR = 0.41, 95% CI (0.19-0.85); HR = 2.52, 95% CI (1.14-5.54), respectively). No statistical significance was discovered between common clinical characteristics and MMF-related SNPs with other complications, including grade II-IV/III-IV acute GvHD, Epstein-Barr virus infection, peri-engraftment syndrome, and capillary leak syndrome. We also discovered SLCO1B1 (597 C > T) and SLC29A1 (-162 + 228 A > C) variant genotypes are both independent factors for cumulative incidence of relapse after haplo-HSCT (HR = 4.02, 95% CI (1.42-11.44); HR = 0.18, 95% CI (0.07-0.43), respectively).

CONCLUSIONS

Our findings highlight the significance of MMF-related transporters and metabolic enzymes SNPs in the development of post-transplant complications, contributing to facilitating personalized risk assessment and improving the clinical management in haplo-HSCT patients.

Precision medicine advances in cystic fibrosis: Exploring genetic pathways for targeted therapies

Personalized medicine has transformed the treatment of cystic fibrosis (CF), providing customized therapeutic approaches based on individual genetic profiles. This review explores the genetic foundations of CF, focusing on mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene and their implications for the development of the disease. The advent of genetic testing has enabled the association of specific mutations to disease severity, leading to the development of CFTR modulators like Ivacaftor, Lumacaftor, and Tezacaftor. Beyond CFTR mutations, genetic modifiers, including gene replacement therapy, genetic manipulation, lentivirus, and non-viral gene therapy formulations, along with environmental factors, play critical roles in influencing disease expression and outcomes. The identification of these modifiers is essential for optimizing therapeutic strategies. Emerging biomarkers, including inflammatory markers and pulmonary function indicators, aid in early disease detection and monitoring progression. Omics technologies are uncovering novel biomarkers, enabling more precise disease management. Pharmacogenomics has become integral to CF care, allowing for personalized approaches that consider genetic variations influencing drug metabolism, especially in antibiotics and anti-inflammatory therapies. The future of CF treatment lies in precision therapies, including CFTR modulators and cutting-edge techniques like gene therapy and CRISPR-Cas9 for mutation correction. As research evolves, these advances can improve patient outcomes while minimizing adverse effects. Ethical considerations and regulatory challenges remain critical as personalized medicine advances, ensuring equitable access and the long-term effectiveness of these innovative therapies.

Revolutionizing Personalized Medicine: Synergy with Multi-Omics Data Generation, Main Hurdles, and Future Perspectives

The field of personalized medicine is undergoing a transformative shift through the integration of multi-omics data, which mainly encompasses genomics, transcriptomics, proteomics, and metabolomics. This synergy allows for a comprehensive understanding of individual health by analyzing genetic, molecular, and biochemical profiles. The generation and integration of multi-omics data enable more precise and tailored therapeutic strategies, improving the efficacy of treatments and reducing adverse effects. However, several challenges hinder the full realization of personalized medicine. Key hurdles include the complexity of data integration across different omics layers, the need for advanced computational tools, and the high cost of comprehensive data generation. Additionally, issues related to data privacy, standardization, and the need for robust validation in diverse populations remain significant obstacles. Looking ahead, the future of personalized medicine promises advancements in technology and methodologies that will address these challenges. Emerging innovations in data analytics, machine learning, and high-throughput sequencing are expected to enhance the integration of multi-omics data, making personalized medicine more accessible and effective. Collaborative efforts among researchers, clinicians, and industry stakeholders are crucial to overcoming these hurdles and fully harnessing the potential of multi-omics for individualized healthcare.

Assessment of knowledge, perceptions, and readiness of healthcare professionals towards clinical pharmacogenomics implementation in Qatar: a mixed-method study

Introduction

Pharmacogenomics implementation in clinical practice is anticipated to improve our understanding of individual variations in drug response and optimise the safety and efficacy of drug therapy. We aimed to assess the knowledge, perceptions, and readiness of physicians, pharmacists, and nurses in Qatar regarding the implementation of clinical pharmacogenomics.

Methods

A mixed-method study with an explanatory sequential design was conducted. Phase I was the quantitative phase which involved sending an online survey to physicians, pharmacists, and nurses. Phase II was the qualitative phase which involved conducting focus group discussions.

Results

A total of 802 responses were collected, with a response rate of 20%. Only 15.4% of participants had previous pharmacogenomics-related training. The median knowledge score for healthcare professionals was 4 out of 10 denoting low level of knowledge. However, compared to other professions, pharmacists had a higher knowledge score (p-value <0.001) and Doctor of Pharmacy (PharmD) holders scored higher than BSc holders (p-value <0.001). Despite the low level of knowledge, perceptions of healthcare professionals were positive. In addition, the majority believed knowledge of pharmacogenomics is necessary and that counselling patients on pharmacogenomics requires specialised training pharmacogenomic principles in practice. The main themes extracted from the focus group discussions were knowledge, outcome expectations, preparedness, facilitators, barriers, public education, and implementation planning. Regarding readiness, most healthcare professionals reported that they are not currently confident in applying.

Conclusions

Healthcare providers have a low level of knowledge of pharmacogenomics. Despite this, the majority have positive perceptions towards its implementation in practice. Compared to other professionals, pharmacists with a PharmD degree scored higher in the knowledge assessment. Most healthcare providers report low confidence regarding the readiness for the implementation of pharmacogenomics and report a lack of knowledge, specialised training, and clinical guidelines as barriers.

The Bidirectional Relationship Between Cardiovascular Medications and Oral and Gut Microbiome Health: A Comprehensive Review

Cardiovascular diseases (CVDs) are a leading cause of widespread morbidity and mortality. It has been found that the gut and oral microbiomes differ in individuals with CVDs compared to healthy individuals. Patients with CVDs often require long-term pharmacological interventions. While these medications have been extensively studied for their cardiovascular benefits, emerging research indicates that they may also impact the diversity and composition of the oral and gut microbiomes. However, our understanding of how these factors influence the compositions of the oral and gut microbiomes in individuals remains limited. Studies have shown that statins and beta-blockers, in particular, cause gut and oral microbial dysbiosis, impacting the metabolism and absorption of these medications. These alterations can lead to variations in drug responses, highlighting the need for personalized treatment approaches. The microbiome's role in drug metabolism and the impact of CVD medications on the microbiome are crucial in understanding these variations. However, there are very few studies in this area, and not all medications have been studied, emphasizing the necessity for further research to conclusively establish cause-and-effect relationships and determine the clinical significance of these interactions. This review will provide evidence of how the oral and gut microbiomes in patients with cardiovascular diseases (CVDs) interact with specific drugs used in CVD treatment.

Lipid Alterations in Chronic Nonspecific Low Back Pain in the Chinese Population: A Metabolomic and Lipidomic Study

Chronic nonspecific low back pain (cNLBP) accounts for approximately 90% of low back pain cases, affecting 65-80% of the population and significantly impacting life quality and productivity. This condition also leads to substantial financial burden. Although there have been advancements, a comprehensive understanding of the underlying etiology of cNLBP remains elusive, resulting in less than optimal treatment outcomes. This study aimed to examine the correlation between lipid variations and the development of cNLBP. The cohort consisted of 26 healthy volunteers (HV group) and 30 cNLBP patients, with an assessment of metabolites and lipid composition in both groups. Metabolomic results revealed significant alterations in lipid-associated metabolites between the HV and cNLBP groups. Subsequent lipid analysis revealed that monoacylglycerols (MAGs) increased approximately 1.2-fold (p = 0.016), diacylglycerols (DAGs) increased approximately 1.4-fold (p = 0.0003), and phosphatidylserine (PS) increased approximately 1.4-fold (p = 0.011). In contrast, triacylglycerol (TAG) decreased to about 0.7-fold (p = 0.035) in the cNLBP group compared to the HV group. The contrasting trends in MAG/DAG and TAG levels indicated that the imbalance between MAG/DAG and TAG may have an impact on the development of cNLBP. This study has provided new insights into the relationship between the progression of cNLBP and specific lipids, suggesting that these lipids could serve as therapeutic targets for cNLBP.

Analysis of the current situation of pharmacogenomics in terms of educational and healthcare needs in Egypt and Lebanon

Pharmacogenomics (PGx) is a practice that investigates the link between genetic differences and drug response in patients. This can improve treatment effectiveness and reduce harmful side effects. However, has yet to be adequately realized in developing nations. Three surveys were conducted between November 2022 to March 2023 in Egypt and Lebanon. The first survey assessed availability of PGx testing in different healthcare facilities; the second one assessed knowledge, interest and attitude toward learning about PGx among pharmacists and physicians; and the third one assessed interest in providing PGx education at academic levels. In Egypt, a few of the surveyed healthcare facilities are conducting some form of pharmacogenetic testing. In Lebanon, very few germline pharmacogenomic tests are offered in Greater Beirut's leading hospitals, and no other testing was recorded. PGx education attracts considerable interest, with 34.3% of pharmacists very interested and 48.8% interested. Similarly, 24.8% of total physicians were very interested while 44.8% were interested. Academic professionals in the surveyed institutions in both countries agreed on the need for educational programs in PGx and 78.2% agreed that there were good opportunities for implementing PGx testing. These findings clearly indicate the need to develop and implement educational programs in PGx in the Middle-East.

Serum Free Fatty Acid Concentration Predicts ARDS after Off-Pump CABG: A Prospective Observational Study

BACKGROUND

Free fatty acids (FFAs) are established risk factors for various cardiovascular and metabolic disorders. Elevated FFAs can trigger inflammatory response, which may be associated with the occurrence of acute respiratory distress syndrome (ARDS) in cardiac surgery. In this prospective study, we aimed to investigate the association between circulating FFA and the incidence of ARDS, as well as the length of ICU stay, in patients undergoing off-pump coronary artery bypass grafting (CABG).

METHODS

We conducted a single-center, prospective, observational study among patients undergoing off-pump CABG. The primary endpoint was the occurrence of ARDS within 6 days after off-pump CABG. Serum FFA were measured at baseline and 24 h post-procedure, and the difference (Δ-FFA) was calculated.

RESULTS

A total of 180 patients were included in the primary analysis. The median FFA was 2.3 mmol/L (quartile 1 [Q1]-Q3, 1.4-3.2) at baseline and 1.5 mmol/L (Q1-Q3, 0.9-2.3) 24 h after CABG, with a Δ-FFA of 0.6 mmol/L (Q1-Q3, -0.1 to 1.6). Patients with elevated Δ-FFA levels had a significantly higher ARDS occurrence (55.6% vs. 22.2%; P < 0.001). Elevated Δ-FFA after off-pump CABG correlated with a significantly lower PaO2/FiO2 ratio, prolonged mechanical ventilation, and extended length of ICU stay. The area under the curve (AUC) of Δ-FFA for predicting ARDS (AUC, 0.758; 95% confidence interval, 0.686-0.831) significantly exceeded the AUC of postoperative FFA (AUC, 0.708; 95% CI 0.628-0.788; P < 0.001).

CONCLUSIONS

Elevated Δ-FFA levels correlated with ARDS following off-pump CABG. Monitoring FFA may assist in identifying high-risk patients for ARDS, facilitating timely interventions to improve clinical outcomes.

Advances in imaging modalities for spinal tumors

The spinal cord occupies a narrow region and is tightly surrounded by osseous and ligamentous structures; spinal tumors can damage this structure and deprive patients of their ability to independently perform activities of daily living. Hence, imaging is vital for the prompt detection and accurate diagnosis of spinal tumors, as well as determining the optimal treatment and follow-up plan. However, many clinicians may not be familiar with the imaging characteristics of spinal tumors due to their rarity. In addition, spinal surgeons might not fully utilize imaging for the surgical planning and management of spinal tumors because of the complex heterogeneity of these lesions. In the present review, we focus on conventional and advanced spinal tumor imaging techniques. These imaging modalities include computed tomography, positron emission tomography, digital subtraction angiography, conventional and microstructural magnetic resonance imaging, and high-resolution ultrasound. We discuss the advantages and disadvantages of conventional and emerging imaging modalities, followed by an examination of cutting-edge medical technology to complement current needs in the field of spinal tumors. Moreover, machine learning and artificial intelligence are anticipated to impact the application of spinal imaging techniques. Through this review, we discuss the importance of conventional and advanced spinal tumor imaging, and the opportunity to combine advanced technologies with conventional modalities to better manage patients with these lesions.

Exploring the design of clinical research studies on the efficacy mechanisms in type 2 diabetes mellitus

This review examines the complexities of Type 2 Diabetes Mellitus (T2DM), focusing on the critical role of integrating omics technologies with traditional experimental methods. It underscores the advancements in understanding the genetic diversity of T2DM and emphasizes the evolution towards personalized treatment modalities. The paper analyzes a variety of omics approaches, including genomics, methylation, transcriptomics, proteomics, metabolomics, and intestinal microbiomics, delineating their substantial contributions to deciphering the multifaceted mechanisms underlying T2DM. Furthermore, the review highlights the indispensable role of non-omics experimental techniques in comprehending and managing T2DM, advocating for their integration in the development of tailored medicine and precision treatment strategies. By identifying existing research gaps and suggesting future research trajectories, the review underscores the necessity for a comprehensive, multidisciplinary approach. This approach synergistically combines clinical insights with cutting-edge biotechnologies, aiming to refine the management and therapeutic interventions of T2DM, and ultimately enhancing patient outcomes. This synthesis of knowledge and methodologies paves the way for innovative advancements in T2DM research, fostering a deeper understanding and more effective treatment of this complex condition.

Mesocorticolimbic and Cardiometabolic Diseases-Two Faces of the Same Coin?

The risk behaviors underlying the most prevalent chronic noncommunicable diseases (NCDs) encompass alcohol misuse, unhealthy diets, smoking and sedentary lifestyle behaviors. These are all linked to the altered function of the mesocorticolimbic (MCL) system. As the mesocorticolimbic circuit is central to the reward pathway and is involved in risk behaviors and mental disorders, we set out to test the hypothesis that these pathologies may be approached therapeutically as a group. To address these questions, the identification of novel targets by exploiting knowledge-based, network-based and disease similarity algorithms in two major Thomson Reuters databases (MetaBase™, a database of manually annotated protein interactions and biological pathways, and IntegritySM, a unique knowledge solution integrating biological, chemical and pharmacological data) was performed. Each approach scored proteins from a particular approach-specific standpoint, followed by integration of the scores by machine learning techniques yielding an integrated score for final target prioritization. Machine learning identified characteristic patterns of the already known targets (control targets) with high accuracy (area under curve of the receiver operator curve was ~93%). The analysis resulted in a prioritized list of 250 targets for MCL disorders, many of which are well established targets for the mesocorticolimbic circuit e.g., dopamine receptors, monoamino oxidases and serotonin receptors, whereas emerging targets included DPP4, PPARG, NOS1, ACE, ARB1, CREB1, POMC and diverse voltage-gated Ca2+ channels. Our findings support the hypothesis that disorders involving the mesocorticolimbic circuit may share key molecular pathology aspects and may be causally linked to NCDs, yielding novel targets for drug repurposing and personalized medicine.

Will Precision Medicine Meet Digital Health? A Systematic Review of Pharmacogenomics Clinical Decision Support Systems Used in Clinical Practice

Digital health, an emerging scientific domain, attracts increasing attention as artificial intelligence and relevant software proliferate. Pharmacogenomics (PGx) is a core component of precision/personalized medicine driven by the overarching motto "the right drug, for the right patient, at the right dose, and the right time." PGx takes into consideration patients' genomic variations influencing drug efficacy and side effects. Despite its potentials for individually tailored therapeutics and improved clinical outcomes, adoption of PGx in clinical practice remains slow. We suggest that e-health tools such as clinical decision support systems (CDSSs) can help accelerate the PGx, precision/personalized medicine, and digital health emergence in everyday clinical practice worldwide. Herein, we present a systematic review that examines and maps the PGx-CDSSs used in clinical practice, including their salient features in both technical and clinical dimensions. Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and research of the literature, 29 relevant journal articles were included in total, and 19 PGx-CDSSs were identified. In addition, we observed 10 technical components developed mostly as part of research initiatives, 7 of which could potentially facilitate future PGx-CDSSs implementation worldwide. Most of these initiatives are deployed in the United States, indicating a noticeable lack of, and the veritable need for, similar efforts globally, including Europe.

Cell death pathways: molecular mechanisms and therapeutic targets for cancer

Cell death regulation is essential for tissue homeostasis and its dysregulation often underlies cancer development. Understanding the different pathways of cell death can provide novel therapeutic strategies for battling cancer. This review explores several key cell death mechanisms of apoptosis, necroptosis, autophagic cell death, ferroptosis, and pyroptosis. The research gap addressed involves a thorough analysis of how these cell death pathways can be precisely targeted for cancer therapy, considering tumor heterogeneity and adaptation. It delves into genetic and epigenetic factors and signaling cascades like the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathways, which are critical for the regulation of cell death. Additionally, the interaction of the microenvironment with tumor cells, and particularly the influence of hypoxia, nutrient deprivation, and immune cellular interactions, are explored. Emphasizing therapeutic strategies, this review highlights emerging modulators and inducers such as B cell lymphoma 2 (BCL2) homology domain 3 (BH3) mimetics, tumour necrosis factor-related apoptosis-inducing ligand (TRAIL), chloroquine, and innovative approaches to induce ferroptosis and pyroptosis. This review provides insights into cancer therapy's future direction, focusing on multifaceted approaches to influence cell death pathways and circumvent drug resistance. This examination of evolving strategies underlines the considerable clinical potential and the continuous necessity for in-depth exploration within this scientific domain.

Postoperative radiotherapy with docetaxel versus cisplatin for high-risk oral squamous cell carcinoma: a randomized phase II trial with exploratory analysis of ITGB1 as a potential predictive biomarker

BACKGROUND

Oral squamous cell carcinoma (OSCC) causes significant mortality and morbidity worldwide. Surgical resection with adjuvant radiotherapy remains the standard treatment for locally advanced resectable OSCC. Results from landmark trials have established postoperative concurrent cisplatin-radiotherapy (Cis-RT) as the standard treatment for OSCC patients with high-risk pathologic features. However, cisplatin-related toxicity limits usage in clinical practice. Given the need for effective but less toxic alternatives, we previously conducted a single-arm trial showing favorable safety profiles and promising efficacy of concurrent docetaxel-radiotherapy (Doc-RT).

METHODS

In this randomized phase 2 trial, we aimed to compare Doc-RT with the standard Cis-RT in postoperative OSCC patients. Eligible patients had AJCC stage III-IV resectable OSCC with high-risk pathologic features. Two hundred twenty-four patients were enrolled and randomly assigned to receive concurrent Doc-RT or Cis-RT. The primary endpoint was 2-year disease-free survival (DFS). Secondary endpoints included overall survival (OS), locoregional-free survival (LRFS), distant metastasis-free survival (DMFS), and adverse events (AEs). Integrin β1 (ITGB1) expression was analyzed as a biomarker for efficacy.

RESULTS

After a median 28.8-month follow-up, 2-year DFS rates were 63.7% for Doc-RT arm and 56.1% for Cis-RT arm (p = 0.55). Meanwhile, Doc-RT demonstrated comparable efficacy to Cis-RT in OS, LRFS, and DMFS. Doc-RT resulted in fewer grade 3 or 4 hematological AEs. Low ITGB1 was associated with improved Doc-RT efficacy versus Cis-RT.

CONCLUSIONS

This randomized trial directly compared Doc-RT with Cis-RT for high-risk postoperative OSCC patients, with comparable efficacy and less toxicity. ITGB1 merits further validation as a predictive biomarker to identify OSCC patients most likely to benefit from Doc-RT. Findings indicate docetaxel may be considered as a concurrent chemoradiation option in this setting.

TRIAL REGISTRATION

www.

CLINICALTRIALS

gov . NCT02923258 (date of registration: October 4, 2016).

Decoding the Role of CYP450 Enzymes in Metabolism and Disease: A Comprehensive Review

Cytochrome P450 (CYP450) is a group of enzymes that play an essential role in Phase I metabolism, with 57 functional genes classified into 18 families in the human genome, of which the CYP1, CYP2, and CYP3 families are prominent. Beyond drug metabolism, CYP enzymes metabolize endogenous compounds such as lipids, proteins, and hormones to maintain physiological homeostasis. Thus, dysregulation of CYP450 enzymes can lead to different endocrine disorders. Moreover, CYP450 enzymes significantly contribute to fatty acid metabolism, cholesterol synthesis, and bile acid biosynthesis, impacting cellular physiology and disease pathogenesis. Their diverse functions emphasize their therapeutic potential in managing hypercholesterolemia and neurodegenerative diseases. Additionally, CYP450 enzymes are implicated in the onset and development of illnesses such as cancer, influencing chemotherapy outcomes. Assessment of CYP450 enzyme expression and activity aids in evaluating liver health state and differentiating between liver diseases, guiding therapeutic decisions, and optimizing drug efficacy. Understanding the roles of CYP450 enzymes and the clinical effect of their genetic polymorphisms is crucial for developing personalized therapeutic strategies and enhancing drug responses in diverse patient populations.

A small-molecule allele-selective transcriptional inhibitor of the MIF immune susceptibility locus

Functional variants of the gene for the cytokine macrophage migration inhibitory factor (MIF) are defined by a 4-nucleotide promoter microsatellite (-794 CATT5-8, rs5844572) and confer risk for autoimmune, infectious, and oncologic diseases. We describe herein the discovery of a prototypic, small molecule inhibitor of MIF transcription with selectivity for high microsatellite repeat number and correspondingly high gene expression. Utilizing a high-throughput luminescent proximity screen, we identify 1-carbomethoxy-5-formyl-4,6,8-trihydroxyphenazine (CMFT) to inhibit the functional interaction between the transcription factor ICBP90 (namely, UHRF1) and the MIF -794 CATT5-8 promoter microsatellite. CMFT inhibits MIF mRNA expression in a -794 CATT5-8 length-dependent manner with an IC50 of 470 nM, and preferentially reduces ICBP90-dependent MIF mRNA and protein expression in high-genotypic versus low-genotypic MIF-expressing macrophages. RNA expression analysis also showed CMFT to downregulate MIF-dependent, inflammatory gene expression with little evidence of off-target metabolic toxicity. These findings provide proof-of-concept for advancing the pharmacogenomic development of precision-based MIF inhibitors for diverse autoimmune and inflammatory conditions.

Efficacy of AI-Guided (GenAISTM) Dietary Supplement Prescriptions versus Traditional Methods for Lowering LDL Cholesterol: A Randomized Parallel-Group Pilot Study

Emerging evidence suggests that personalized dietary supplement regimens can significantly influence lipid metabolism and cardiovascular risk. The efficacy of AI-guided dietary supplement prescriptions, compared with standard physician-guided prescriptions, remains underexplored. In a randomized, parallel-group pilot study, 70 patients aged 40-75 years with LDL-C levels between 70 and 190 mg/dL were enrolled. Participants were randomized to receive either AI-guided dietary supplement prescriptions or standard physician-guided prescriptions for 90 days. The primary endpoint was the percent change in LDL-C levels. Secondary endpoints included changes in total cholesterol, HDL-C, triglycerides, and hsCRP. Supplement adherence and side effects were monitored. Sixty-seven participants completed the study. The AI-guided group experienced a 25.3% reduction in LDL-C levels (95% CI: -28.7% to -21.9%), significantly greater than the 15.2% reduction in the physician-guided group (95% CI: -18.5% to -11.9%; p < 0.01). Total cholesterol decreased by 15.4% (95% CI: -19.1% to -11.7%) in the AI-guided group compared with 8.1% (95% CI: -11.5% to -4.7%) in the physician-guided group (p < 0.05). Triglycerides were reduced by 22.1% (95% CI: -27.2% to -17.0%) in the AI-guided group versus 12.3% (95% CI: -16.7% to -7.9%) in the physician-guided group (p < 0.01). HDL-C and hsCRP changes were not significantly different between groups. The AI-guided group received a broader variety of supplements, including plant sterols, omega-3 fatty acids, red yeast rice, coenzyme Q10, niacin, and fiber supplements. Side effects were minimal and comparable between groups. AI-guided dietary supplement prescriptions significantly reduce LDL-C and triglycerides more effectively than standard physician-guided prescriptions, highlighting the potential for AI-driven personalization in managing hypercholesterolemia.

Haplotype Inference Using Long-Read Nanopore Sequencing: Application to GSTA1 Promoter

Recovering true haplotypes can have important clinical consequences. The laboratory process is difficult and is, therefore, most often done through inference. In this paper, we show that when using the Oxford nanopore sequencing technology, we could recover the true haplotypes of the GSTA1 promoter region. Eight LCL cell lines with potentially ambiguous haplotypes were used to characterize the efficacy of Oxford nanopore sequencing to phase the correct GSTA1 promoter haplotypes. The results were compared to Sanger sequencing and inferred haplotypes in the 1000 genomes project. The average read length was 813 bp out of a total PCR length of 1336 bp. The best coverage of sequencing was in the middle of the PCR product and decreased to 50% at the PCR ends. SNPs separated by less than 200 bp showed > 90% of correct haplotypes, while at the distance of 1089 bp, this proportion still exceeded 58%. The number of cycles influences the generation of hybrid haplotypes but not extension or annealing time. The results demonstrate that this long sequencing reads methodology, can accurately determine the haplotypes without the need for inference. The technology proved to be robust but the success of phasing nonetheless depends on the distances and frequencies of SNPs.

Deciphering the Puzzle: Literature Insights on Chlamydia trachomatis-Mediated Tumorigenesis, Paving the Way for Future Research

Some infectious agents have the potential to cause specific modifications in the cellular microenvironment that could be propitious to the carcinogenesis process. Currently, there are specific viruses and bacteria, such as human papillomavirus (HPV) and Helicobacter pylori, that are well established as risk factors for neoplasia. Chlamydia trachomatis (CT) infections are one of the most common bacterial sexually transmitted infections worldwide, and recent European data confirmed a continuous rise across Europe. The infection is often asymptomatic in both sexes, requiring a screening program for early detection. Notwithstanding, not all countries in Europe have it. Chlamydia trachomatis can cause chronic and persistent infections, resulting in inflammation, and there are plausible biological mechanisms that link the genital infection with tumorigenesis. Herein, we aimed to understand the epidemiological and biological plausibility of CT genital infections causing endometrial, ovarian, and cervical tumors. Also, we covered some of the best suitable in vitro techniques that could be used to study this potential association. In addition, we defend the point of view of a personalized medicine strategy to treat those patients through the discovery of some biomarkers that could allow it. This review supports the need for the development of further fundamental studies in this area, in order to investigate and establish the role of chlamydial genital infections in oncogenesis.

Dark local knowledge: the yet-to-be scientifically discovered and locally acknowledged aspects of local knowledge systems

This essay brings forward the idea that there is more than meets the eye in local knowledge systems than what science can show us now. To comprehend this, we need to make a conceptual jump and look for the "dark matter" (the notion borrowed from astronomy that refers to a hypothetical form of matter that does not interact with light or electromagnetic fields) that can potentially sustain local knowledge. Considering that it is a complex of knowledge, practices, and beliefs contained in TEK, knowledge in LEK does not correspond to the notion of knowledge in science. Therefore, in order to map LEK-science interactions, we will refer to the concept of peoples' knowledge of LEK as acknowledgement and the scientific recognition and awareness of information, facts, and principles as knowledge. Applying this to a Johari Window, we can observe four categories of LEK in a known-unknown/acknowledged-unacknowledged matrix. We can refer to unknown and unacknowledged as dark local knowledge. Indeed, local knowledge systems contain many aspects that modern science cannot yet explain, as a major part of its components are not even considered in scholarly research. Dark local knowledge can potentially provide us with the invaluable touch of experience of countless generations, opening different ways of seeing reality.

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Precision medicine is transforming colorectal cancer treatment through the integration of advanced technologies and biomarkers, enhancing personalized and effective disease management. Identification of key driver mutations and molecular profiling have deepened our comprehension of the genetic alterations in colorectal cancer, facilitating targeted therapy and immunotherapy selection. Biomarkers such as microsatellite instability (MSI) and DNA mismatch repair deficiency (dMMR) guide treatment decisions, opening avenues for immunotherapy. Emerging technologies such as liquid biopsies, artificial intelligence, and machine learning promise to revolutionize early detection, monitoring, and treatment selection in precision medicine. Despite these advancements, ethical and regulatory challenges, including equitable access and data privacy, emphasize the importance of responsible implementation. The dynamic nature of colorectal cancer, with its tumor heterogeneity and clonal evolution, underscores the necessity for adaptive and personalized treatment strategies. The future of precision medicine in colorectal cancer lies in its potential to enhance patient care, clinical outcomes, and our understanding of this intricate disease, marked by ongoing evolution in the field. The current reviews focus on providing in-depth knowledge on the various and diverse approaches utilized for precision medicine against colorectal cancer, at both molecular and biochemical levels.

Patient-centered precision care in anaesthesia - the PC-square (PC) 2 approach

PURPOSE OF REVIEW

This review navigates the landscape of precision anaesthesia, emphasising tailored and individualized approaches to anaesthetic administration. The aim is to elucidate precision medicine principles, applications, and potential advancements in anaesthesia. The review focuses on the current state, challenges, and transformative opportunities in precision anaesthesia.

RECENT FINDINGS

The review explores evidence supporting precision anaesthesia, drawing insights from neuroscientific fields. It probes the correlation between high-dose intraoperative opioids and increased postoperative consumption, highlighting how precision anaesthesia, especially through initiatives like Safe Brain Initiative (SBI), could address these issues. The SBI represents multidisciplinary collaboration in perioperative care. SBI fosters effective communication among surgical teams, anaesthesiologists, and other medical professionals.

SUMMARY

Precision anaesthesia tailors care to individual patients, incorporating genomic insights, personalised drug regimens, and advanced monitoring techniques. From EEG to cerebral/somatic oximetry, these methods enhance precision. Standardised reporting, patient-reported outcomes, and continuous quality improvement, alongside initiatives like SBI, contribute to improved patient outcomes. Precision anaesthesia, underpinned by collaborative programs, emerges as a promising avenue for enhancing perioperative care.

The transition from genomics to phenomics in personalized population health

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Estimating preferences and willingness to pay for pharmacogenetic testing in populations who are medically underserved: a discrete choice experiment

Background: The implementation of pharmacogenetic (PGx) testing may contribute to health disparities if access to testing is inequitable, as medically underserved patients are prescribed higher rates of drugs with PGx guidelines and often experience the benefits of emerging health technologies last. Limited research has evaluated potential implementation of PGx testing in populations who are medically underserved and none have evaluated their preferences regarding PGx test characteristics and cost. Our study endeavored to assess the willingness to pay for PGx testing and key PGx test preferences in a nationwide cohort of medically underserved respondents. Methods: A survey was developed to assess willingness to pay and preferences for PGx testing through a discrete choice experiment (DCE). Five attributes of PGx tests were included in the DCE: doctor recommendation, wait time, number of actionable results, benefit of the test (avoid a side effect or address a health problem), and out-of-pocket cost. A convenience sample of U.S. adults with an average yearly household income of $42,000 or less was collected utilizing an online survey fielded by Qualtrics Research Services (Provo, UT). For the DCE analysis, conditional logit and mixed-logit regression models were utilized to determine relative utility of attributes and levels, conditional relative importance for each attribute, and marginal willingness to pay. Results: Respondents completed the survey with an 83.1% response completion rate. Following quality control procedures, 1,060 respondents were included in the final nationwide cohort. Approximately, 82% of respondents were willing to pay less than $100 for PGx testing, and a strong price ceiling was identified at $200. Out-of-pocket cost was the attribute identified as having the greatest relative importance on choice, while wait time had the lowest importance. Greater utility was observed if the PGx test was doctor recommended, had a higher number of actionable results, and resolved major or minor health problems compared with avoiding side effects. Conclusion: This first-of-its-kind study provides important insights into the willingness to pay for PGx testing and PGx test preferences of a large medically underserved population. Applying these findings can potentially lead to improvements in the successful implementation of PGx testing in this population.

Effects of gene polymorphisms on delayed MTX clearance, toxicity, and metabolomic changes after HD-MTX treatment in children with acute lymphoblastic leukemia

This study aims to assess the role of methotrexate-related gene polymorphisms in children with acute lymphoblastic leukemia (ALL) during high-dose methotrexate (HD-MTX) therapy and to explore their effects on serum metabolites before and after HD-MTX treatment. The MTHFR 677C>T, MTHFR 1298A>C, ABCB1 3435C>T, and GSTP1 313A>G genotypes of 189 children with ALL who received chemotherapy with the CCCG-ALL-2020 regimen from January 2020 to April 2023 were analyzed, and toxic effects were reported according to the Common Terminology Criteria for Adverse Events (CTCAE, version 5.0). Fasting peripheral blood serum samples were collected from 27 children before and after HD-MTX treatment, and plasma metabolites were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS). The results of univariate and multivariate analyses showed that MTHFR 677C>T and ABCB1 3435 C>T gene polymorphisms were associated with the delayed MTX clearance (P < 0.05) and lower platelet count after treatment in children with MTHFR 677 mutation compared with wild-type ones (P < 0.05), and pure mutations in ABCB1 3435 were associated with higher serum creatinine levels (P < 0.05). No significant association was identified between MTHFR 677C>T, MTHFR 1298A>C, ABCB1 3435 C>T, and GSTP1 313A>G genes and hepatotoxicity or nephrotoxicity (P > 0.05). However, the serum metabolomic analysis indicated that the presence of the MTHFR 677C > T gene polymorphism could potentially contribute to delayed MTX clearance by influencing L-phenylalanine metabolism, leading to the occurrence of related toxic side effects.

CONCLUSION

MTHFR 677C>T and ABCB1 3435 C>T predicted the risk of delayed MTX clearance during HD-MTX treatment in children with ALL. Serum L-phenylalanine levels were significantly elevated after HD-MTX treatment in children with the MTHFR 677C>T mutation gene.

TRIAL REGISTRATION

This study was registered at the Chinese Clinical Trial Registry (registration number: ChiCTR2000035264; registration: 2020/08/05; https://www.chictr.org.cn/ ).

WHAT IS KNOWN

• MTX-related genes play an important role in MTX pharmacokinetics and toxicity, but results from different studies are inconsistent and the mechanisms involved are not clear.

WHAT IS NEW

• Characteristics, prognosis, polymorphisms of MTX-related genes, and metabolite changes were comprehensively evaluated in children treated with HD-MTX chemotherapy. • Analysis revealed that both heterozygous and pure mutations in MTHFR 677C>T resulted in a significantly increased risk of delayed MTX clearance, and that L-phenylalanine has the potential to serve as a predictive marker for the metabolic effects of the MTHFR 677C>T polymorphism.

Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication

Indiscriminate drug administration may lead to drug therapy results with varying effects on patients, and the proposal of personalized medication can help patients to receive effective drug therapy. Conventional ways of personalized medication, such as pharmacogenomics and therapeutic drug monitoring (TDM), can only be implemented from a single perspective. The development of pharmacometabolomics provides a research method for the realization of precise drug administration, which integrates the environmental and genetic factors, and applies metabolomics technology to study how to predict different drug therapeutic responses of organisms based on baseline metabolic levels. The published research on pharmacometabolomics has achieved satisfactory results in predicting the pharmacokinetics, pharmacodynamics, and the discovery of biomarkers of drugs. Among them, the pharmacokinetics related to pharmacometabolomics are used to explore individual variability in drug metabolism from the level of metabolism of the drugs in vivo and the level of endogenous metabolite changes. By searching for relevant literature with the keyword "pharmacometabolomics" on the two major literature retrieval websites, PubMed and Web of Science, from 2006 to 2023, we reviewed articles in the field of pharmacometabolomics that incorporated pharmacokinetics into their research. This review explains the therapeutic effects of drugs on the body from the perspective of endogenous metabolites and pharmacokinetic principles, and reports the latest advances in pharmacometabolomics related to pharmacokinetics to provide research ideas and methods for advancing the implementation of personalized medication.

A Comprehensive Evaluation of the Effects of RNA-Editing Proteins ADAR and ADARB1 on the Expression of the Drug-Metabolizing Enzymes in HepaRG Cells

Two RNA-editing proteins, the adenosine deaminase acting on RNA, ADAR, and ADARB1, broadly regulate gene expression in editing-dependent and editing-independent manners. Previous studies showed that the expression of the drug-metabolizing cytochrome P450s (P450s) and UDP glucuronosyltransferases (UGTs) changes upon knockdown (KD) of ADAR or ADARB1 in different hepatic cell lines. To systematically survey the effects of these two ADARs on the expression of P450s and UGTs, we used small interfering RNA in HepaRG cells and tested the association between the expression of the P450s and ADARs in a liver sample cohort (n = 246). KD of ADAR increased the expression of the CYP3As and CYP2C9 and reduced the expression of the others, whereas KD of ADARB1 reduced the expression of nearly all genes tested. ADAR KD also suppressed the induction of most P450s, whereas ADARB1 KD had mixed effects depending on the inducer/gene combination. P450 expression was positively associated with both ADARs in liver samples, consistent with the KD results. However, after adjusting for the expression of transcription factors (TFs) known to regulate P450 expression, the associations disappeared, indicating that the effects of ADAR or ADARB1 primarily occur through TFs. Moreover, we found that the expression of normally spliced CYP3A5 transcripts is increased in both KDs, indicating a direct effect of the ADARs on promoting the usage of the cryptic splice site generated by CYP3A5*3. Taken together, our results revealed the nonoverlapping regulatory effects of ADAR and ADARB1 and supported their broad roles in controlling the expression of drug-metabolizing enzymes in the liver. SIGNIFICANCE STATEMENT: Here, this study systematically surveyed the roles of ADAR and ADARB1 in both basal and induced expression of drug-metabolizing enzymes and assessed their coexpression in liver samples. This study's results support that ADAR and ADARB1 regulate the expression of the drug-metabolizing enzymes in the liver, suggesting that factors affecting ADAR expression also have the potential to impact drug metabolism.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Oxycodone: A Current Perspective on Its Pharmacology, Abuse, and Pharmacotherapeutic Developments

Oxycodone, a semisynthetic derivative of naturally occurring thebaine, an opioid alkaloid, has been available for more than 100 years. Although thebaine cannot be used therapeutically due to the occurrence of convulsions at higher doses, it has been converted to a number of other widely used compounds that include naloxone, naltrexone, buprenorphine, and oxycodone. Despite the early identification of oxycodone, it was not until the 1990s that clinical studies began to explore its analgesic efficacy. These studies were followed by the pursuit of several preclinical studies to examine the analgesic effects and abuse liability of oxycodone in laboratory animals and the subjective effects in human volunteers. For a number of years oxycodone was at the forefront of the opioid crisis, playing a significant role in contributing to opioid misuse and abuse, with suggestions that it led to transitioning to other opioids. Several concerns were expressed as early as the 1940s that oxycodone had significant abuse potential similar to heroin and morphine. Both animal and human abuse liability studies have confirmed, and in some cases amplified, these early warnings. Despite sharing a similar structure with morphine and pharmacological actions also mediated by the μ-opioid receptor, there are several differences in the pharmacology and neurobiology of oxycodone. The data that have emerged from the many efforts to analyze the pharmacological and molecular mechanism of oxycodone have generated considerable insight into its many actions, reviewed here, which, in turn, have provided new information on opioid receptor pharmacology. SIGNIFICANCE STATEMENT: Oxycodone, a μ-opioid receptor agonist, was synthesized in 1916 and introduced into clinical use in Germany in 1917. It has been studied extensively as a therapeutic analgesic for acute and chronic neuropathic pain as an alternative to morphine. Oxycodone emerged as a drug with widespread abuse. This article brings together an integrated, detailed review of the pharmacology of oxycodone, preclinical and clinical studies of pain and abuse, and recent advances to identify potential opioid analgesics without abuse liability.