Pharmacogenomics最新文献

The CYP2C19 gene encodes one of the main enzymes responsible for clopidogrel bioactivation, a widely prescribed antiplatelet prodrug. Due to its high polymorphism, clopidogrel response varies considerably, especially in carriers of nonfunctional alleles, such as CYP2C192 and  * 3. Meta-analyses have associated CYP2C19 loss-of-function alleles with worse cardiovascular outcomes, and genotype-guided strategies have demonstrated feasibility and clinical utility, supporting the rationale for locally validated implementation in Brazil. Personalized treatment strategies, based on preemptive genotyping and genotype-guided recommendations, have been proposed to improve clopidogrel efficacy and safety. However, extrapolating international guidelines to genetically diverse and underrepresented populations, such as Brazilians, poses challenges. Therefore, to discuss the clinical application of this testing in Brazil, it is also necessary to explore strategies that promote national pharmacogenomic studies, enhance infrastructure and training, and better align public policies. This study followed a contextual synthesis approach, with evidence identified through PubMed (last updated July 2025), and discusses structural and scientific barriers to implementing precision medicine in a local context of Brazil, proposing strategies for CYP2C19-clopidogrel pharmacogenetics at the Hospital de Clínicas of the Universidade Federal do Triângulo Mineiro (HC-UFTM), Minas Gerais, Brazil, considering both local realities and broader systemic limitations.

Ovarian cancers (OCs) are often defined as poorly immunogenic tumors that have low response rates to current immunotherapies and frequently develop resistance to chemotherapies. Oncolytic viruses (OVs) are an emerging therapeutic approach that is favored due to its multifactorial mechanism of action; OVs aim to enhance immune cell recovery and infiltration into the tumor, in addition to assisting the immune system to identify and target evasive tumors. While many different OVs have been studied, this review focuses on the four that have been extensively tested in preclinical models and clinical trials with OC patients: vaccinia viruses, vesicular stomatitis virus, herpes simplex 1, and adenoviruses. We will first explore how these viruses have been developed, modified and tested as monotherapies in OCs, with limited success. The various combinatorial approaches involving OVs that are currently being investigated to improve the outcomes for OC patients will then be addressed. Attention will be given to how the genetics of OC cells may influence response to OVs and how that has led to genetic modifications of OVs that improve the cancer specificity and efficacy of these therapies.

At the crossroads of genomics and pharmacology, pharmacogenomics is revolutionizing healthcare by tailoring drug therapies to individual genetic profiles thereby reducing the risk of adverse drug reactions and propelling the field of precision medicine forward. This review delves into the role of pharmacogenomics in uncovering genetic variations, including single nucleotide polymorphisms, that affects how drugs are metabolized and effective. Artificial intelligence (AI) has ameliorated the discovery of biomarkers and the drug development process; enabled real-time clinical decision-making, expanding the possibilities of personalized medicine. AI-powered models, especially in machine learning and deep learning have demonstrated potential in forecasting drug responses and enhancing the precision of genetic variant identification, exemplified by tools like DeepVariant and AlphaFold. However, the diversity of data, the clarity of model interpretations, and the ethical issues surrounding data privacy and genetic discrimination remain as major hurdles. Efforts are underway to address these challenges through multi-omics integration, federated learning, and explainable AI, all aimed at improving clinical translation and promoting fair access to personalized treatments. This review enunciates the existing applications, translational pathways, and prospects of AI in pharmacogenomics, its promise in achieving the goal of precision medicine ensuring the proper treatment of right patient at the right moment.

Aims: We compared plasma adiponectin levels between patients with preeclampsia (PE) classified as responsive and nonresponsive to antihypertensive therapy; Moreover, we examined whether ADIPOQ SNPs rs17300539, rs266729,rs2241766, and rs1501299 and their haplotypes are associated with responsiveness to antihypertensive therapy, and whether they affect plasma adiponectin levels in 215 pregnant women with PE.

Patients & methods: Genotypes for ADIPOQ SNPs were determined using TaqMan allelic discrimination assays, and circulating adiponectin concentrations were measured by ELISA.

Results: Patients with PE classified as nonresponsive to antihypertensive therapy showed higher plasma adiponectin levels than responsive patients. The TG genotype of the rs2241766 SNP was more frequent in responsive patients with PE when compared to nonresponsive patients. Nonresponsive patients with PE carrying specific genotypes of the ADIPOQ SNPs rs17300539 (GG or GA+AA), rs266729 (CC), rs2241766(TT), and rs1501299 (GT+TT), respectively, as well as the 'G,C,T,G' and 'G,C,T,T' haplotypes showed higher plasma adiponectin levels than responsive patients with PE carrying the same genotypes/haplotypes.

Conclusions: Nonresponsive patients with PE showed higher plasma adiponectin levels than responsive patients, the TG genotype of the rs2241766 SNP was more frequent in the responsive patients with PE when compared to nonresponsive patients. Genotypes of rs17300539, rs266729, rs2241766, and rs1501299 SNPs and haplotypes may affect adiponectin levels in patients with PE classified as nonresponsive to antihypertensive therapy.

Aim: This study aimed to assess the impact of GSTP1, GSTM1, and GSTT1 polymorphisms on the response to oxaliplatin-based chemotherapy and survival outcomes in gastric cancer patients from Northwest China.

Patients and methods: Genotypes of GSTP1, GSTM1, and GSTT1 were analyzed in 185 gastric cancer patients receiving SOX/XELOX regimens. The associations of these genotypes with the objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were evaluated through logistic regression and Kaplan-Meier/Cox model analyses.

Results: Patients carrying the GSTP1(AG+GG) genotype exhibited a significantly better chemotherapy response (OR = 0.301, p = 0.022) compared to those with the AA genotype. Additionally, the GSTP1 (AG+GG) genotype conferred a reduced risk of disease progression (HR = 1.645, log-rank p = 0.003) and mortality (HR = 1.705, log-rank p = 0.007) relative to the AA genotype. No significant associations were observed for GSTM1 or GSTT1 individually. However, the combined GSTP1(AG+GG)/GSTM1- genotype was linked to an improved chemotherapy response and significantly better overall and progression-free survival.

Conclusion: The GSTP1 genotype status could be a valuable predictive biomarker for treatment response and survival, potentially facilitating more personalized therapeutic approaches for gastric cancer.

Purpose: Sunitinib is a multikinase inhibitor used to treat metastatic renal cell carcinoma (mRCC), with an inter-individual variability of pharmacokinetics and toxicity. Our goal was to assess associations between the pharmacogenetics, pharmacokinetics and toxicity of sunitinib.

Methods: In this multi-center prospective study, 42 patients with mRCC were included. An NGS panel was used to identify variations in 19 genes involved in sunitinib pharmacokinetics and pharmacodynamics. Residual concentration of sunitinib and N-desethyl-sunitinib were used to estimate a composite AUC at steady-state.

Results: Fifty-seven percent of patients had a plasma exposure within the optimal therapeutic range. A higher composite AUC led to significantly greater risk of endocrine toxicity (p = 0.008) and neurologic toxicity (p = 0.024), and to a non-significantly greater risk of cardiovascular toxicity (p = 0.11). A alleles of FGFR2-rs2981582 and VEFGFR2-rs1870377 were associated with a lower risk of cardiovascular toxicity (OR = 0.22 [0.05-0.97], p = 0.04 and OR = 0.17 [0.04- 0.73], p = 0.01 respectively) and with a lower composite AUC (p = 0.02 and p = 0.0002 respectively).

Conclusion: We demonstrated for the first time, an association between genetics polymorphisms in sunitinib targets and extent of exposure to this molecule as well as their association associated with the risk of cardiovascular toxicity. We described the concentration dependence of neurological and endocrine toxicity.

Trial registration: NCT02404584, registered 26 March 2015.

Pharmacogenomic (PGx) testing can help guide medication prescribing for a wide range of health indications. The objective of this scoping review was to understand how PGx testing has been clinically implemented and learn from these experiences. Research questions guiding this work were: (1) what different models for delivery of PGx testing have been employed? (2) what are the characteristics of each delivery model? and (3) what are the reported facilitators and barriers associated with each delivery model? A total of 134 articles reported on 125 PGx initiatives spanning 19 countries. Four unique delivery models were identified: sole prescriber-led (n = 45), prescriber-led within an interdisciplinary care team (n = 34), community pharmacist-led (n = 16), and PGx consultation service (n = 30). The unique combination of characteristics, and reported facilitators and barriers yielded distinct strengths and challenges for each identified delivery model. Findings from this review can help inform future implementation planning or expansion of PGx initiatives by presenting different delivery models that may be employed and the corresponding considerations for each approach. This information can help inform future implementers in the selection of one or more approaches that may be most suitable based on their unique contextual needs, and available infrastructures or resources.

Aims: Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer. Although PEG-asparaginase (PEG-ASNase) is a key drug in treatment, hypersensitivity reactions, pancreatitis, and silent inactivation remain major challenges. Interindividual genetic variability influences drug metabolism and toxicity, and pharmacogenetic research aims to identify these variants early to predict specific responses effectively.

Methods: We investigated the association between variants in NFATC2, GRIA1, CNOT3, MYBBP1A, ARHGAP28, ULK2, and RGS6 and PEG-ASNase - induced toxicities in a prospective multicenter study of 441 children with ALL. Genotyping was performed using TaqMan probes on saliva-extracted DNA.

Results: Among patients, 9.7% developed allergies, 3.4% pancreatitis, and 10.1% silent inactivation, which was significantly associated with allergic reactions (p < 0.05). No significant associations were found between the genetic variants and hypersensitivity or pancreatitis (p > 0.05).

Conclusions: No statistically significant associations were observed between the selected variants and PEG-ASNase-related hypersensitivity or pancreatitis in this cohort.This study highlights the importance of ancestry-informed approaches in pharmacogenomic research for ALL.

Aim: This study investigated the impact of ABCB1 gene polymorphisms on clopidogrel absorption and therapeutic response by analyzing plasma levels of the clopidogrel carboxylic acid metabolite (CAM), and cardiovascular events (CVEs) in patients undergoing percutaneous coronary intervention (PCI).

Methods: A prospective cohort study of 264 post-PCI patients was conducted in Peshawar, Pakistan. CVEs over 12 months were recorded. Plasma concentrations of CAM were measured by high-performance liquid chromatography (HPLC), while the ABCB1 gene (rs1045642) was genotyped by Sanger sequencing to determine associations between genetic variants, CAM levels, and clinical outcomes.

Results: The study documented 54 CVEs, including 13 deaths, 6 stent thromboses, 10 recurrent myocardial infarctions, 23 ischemic events requiring hospitalization, and 2 strokes. The analysis showed that 31.1% of patients had subtherapeutic CAM levels ( <2000 ng/ml), while 68.9% had therapeutic levels. Genetic analysis identified 65% as poor absorbers (CT/TT genotypes) and 35% as good absorbers (CC genotype), while CAM levels were significantly associated with the CT/TT genotype (p < 0.005).

Conclusion: This study linking ABCB1 variation to CAM concentration and therapeutic outcomes. There was a significant association between ABCB1 variants and CAM concentrations. However, no association was found between ABCB1 polymorphisms and CVEs.

Background: Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic enzyme responsible for metabolizing approximately 20% of commonly prescribed drugs. Its genetic variability contributes to interindividual and interethnic differences in drug response. However, large-scale studies on CYP2D6 allele distributions in the Korean population remain limited.

Methods: We conducted CYP2D6 genotyping, including copy number variation analysis, in 3,874 unrelated Korean individuals recruited from five university hospitals. Genotypes were assigned diplotypes and phenotypes using the CPIC activity score system.

Results: The most frequent allele was the decreased-function *10 (44.9%), followed by normal-function *1 (32.8%) and 2 (11.0%). The gene deletion five accounted for 5.7%. Among phenotypes, 62.2% were extensive metabolizers, 36.1% intermediate metabolizers, 0.9% ultrarapid metabolizers, and 0.4% poor metabolizers. We also identified CYP2D6 × 65, previously unreported in Koreans, and a novel duplication variant, CYP2D6 × 49x2.

Conclusion: This is the largest study of CYP2D6 polymorphisms in a Korean population to date. It provides a comprehensive reference for Korean pharmacogenomics and highlights important interethnic differences. The findings support the development of personalized medicine strategies based on population-specific pharmacogenetic data.