An updated examination of the perception of barriers for pharmacogenomics implementation and the usefulness of drug/gene pairs in Latin America and the Caribbean

Impact of CYP3A5 1* and 3* single nucleotide variants on tacrolimus pharmacokinetics and graft rejection risk in pediatric kidney transplant patients

Tacrolimus, a calcineurin inhibitor, is widely used to prevent allograft rejection in kidney transplant recipients. Its metabolism is predominantly mediated by the cytochrome P450 3A5 (CYP3A5) enzyme, and single nucleotide variants (SNVs) within intron 3 of the CYP3A5 gene are strongly associated with interindividual variability in enzyme expression and activity. These SNVs can generate a cryptic splice site, resulting in either preserved enzymatic function classified as expressers (CYP3A5 *1/*1 and *1/*3) or loss of function, classified as non-expressers (CYP3A5 *3/*3). Differential expression of CYP3A5 contributes to variability in tacrolimus pharmacokinetics and clinical outcomes, including graft rejection and therapeutic efficacy. In this study, we evaluated three pharmacokinetic parameters: trough concentration (TAC-C0), weight-adjusted daily dose (TAC-D, mg/kg), and dose-normalized trough concentration (TAC-C0/D). One-way ANOVA was used to assess differences in these parameters between CYP3A5 expressers and non-expressers. Additionally, Poisson regression was performed to examine associations between clinical/genetic variables and the incidence rate of acute rejection events. Genotyping was conducted in 45 pediatric kidney transplant recipients. The CYP3A5 *3/*3 genotype was most prevalent (66.7%), followed by *1/*3 (26.7%) and *1/*1 (6.7%). During the 6-month post-transplant period, CYP3A5 expressers required significantly higher tacrolimus doses to achieve target trough levels. Increased drug exposure was associated with a higher incidence of rejection events, whereas CYP3A5 expression correlated with a reduced rate of rejection. These findings underscore the clinical utility of CYP3A5 genotyping for optimizing tacrolimus dosing strategies. Carriers of functional CYP3A5 alleles (*1/*3 or *1/*1) benefit from individualized dose adjustments to achieve therapeutic concentrations and reduce the risk of graft rejection.

Global analysis of actionable genomic alterations in thyroid cancer and precision-based pharmacogenomic strategies

Introduction

Thyroid cancer, a prevalent endocrine malignancy, has an age-standardized incidence rate of 9.1 per 100,000 people and a mortality rate of 0.44 per 100,000 as of 2024. Despite significant advances in precision oncology driven by large-scale international consortia, gaps persist in understanding the genomic landscape of thyroid cancer and its impact on therapeutic efficacy across diverse populations.

Methods

To address this gap, we performed comprehensive data mining and in silico analyses to identify pathogenic variants in thyroid cancer driver genes, calculate allele frequencies, and assess deleteriousness scores across global populations, including African, Amish, Ashkenazi Jewish, East and South Asian, Finnish and non-Finnish European, Latino, and Middle Eastern groups. Additionally, pharmacogenomic profiling, in silico drug prescription, and clinical trial data were analyzed to prioritize targeted therapeutic strategies.

Results

Our analysis examined 56,622 variants in 40 thyroid cancer-driver genes across 76,156 human genomes, identifying 5,001 known and predicted oncogenic variants. Enrichment analysis revealed critical pathways such as MAPK, PI3K-AKT-mTOR, and p53 signaling, underscoring their roles in thyroid cancer pathogenesis. High-throughput validation strategies confirmed actionable genomic alterations in RET, BRAF, NRAS, KRAS, and EPHA7. Ligandability assessments identified these proteins as promising therapeutic targets. Furthermore, our findings highlight the clinical potential of targeted drug inhibitors, including vandetanib, dabrafenib, and selumetinib, for improving treatment outcomes.

Discussion

This study underscores the significance of integrating genomic insights with pharmacogenomic strategies to address disparities in thyroid cancer treatment. The identification of population-specific oncogenic variants and actionable therapeutic targets provides a foundation for advancing precision oncology. Future efforts should focus on including underrepresented populations, developing population-specific prevention strategies, and fostering global collaboration to ensure equitable access to pharmacogenomic testing and innovative therapies. These initiatives have the potential to transform thyroid cancer care and align with the broader goals of personalized medicine.

Return of Clinically Actionable Pharmacogenetic Results From Molecular Tumor Board DNA Sequencing Data: Workflow and Estimated Costs

Pharmacogenetic testing can prevent severe toxicities from several oncology drug therapies; it also has the potential to improve the outcomes from supportive care drugs. Paired tumor and germline sequencing is increasingly common in oncology practice; these include sequencing of pharmacogenes, but the germline pharmacogenetic variants are rarely included in the clinical reports, despite many being clinically actionable. We established an informatics workflow to evaluate the clinical sequencing results for pharmacogenetic variants. We used the Aldy computational tool, which we have previously shown to determine the variant alleles in 14 pharmacogenes in clinical sequencing data with >99% accuracy, to identify pharmacogenetic variants in the clinical whole exome sequencing from our molecular tumor board. Patients with genetic variants that are clinically actionable for their individual therapy programs, including both treatment and supportive care, are referred to a clinical pharmacogenetics testing laboratory for confirmation. Through an evaluation of our weekly informatics workflow, we determined it took approximately 3.25 hours to complete the analysis of the sequencing data from approximately 20 patients. Using a United States pharmacist's median salary, we estimated the incremental added cost of the process to be only ~$15 per patient. This adds only a minor increase to the patient's cost of testing and has the potential to improve the safety and efficacy of their treatment.

Allele and genotype frequencies of variants in P450 cytochromes, transports, and DNA repair enzymes in the Dominican Republic population

Introduction

Single-nucleotide variants (SNVs) give rise to important inter-individual and inter-ethnic variabilities in the metabolism and disposition of several therapeutic agents and may cause differences in the treatment response to clinically important drugs like antiarrhythmics, antidepressants, antihistamines, and antipsychotics, among others. Information about the prevalence of variants in the Dominican Republic population is still limited. The aim of this study was to describe the frequency distribution of 32 SNVs from 14 genes with pharmacogenetic interest within a sample of 150 unrelated healthy individuals.

Methods

Genotype and allele frequencies were determined, and pairwise Wright's FST statistic was evaluated.

Results

Hardy-Weinberg equilibrium deviations were found in seven loci from CYP2D6 (rs16947, rs3892097, rs1058164, rs1135840, and rs28371725) and CYP2C19 (rs12769205 and rs4244285) genes. The minor allele frequencies ranged from 0.01 to 0.50 values in the xenobiotic biotransformation enzymes and transporter genes. The average admixture estimates were 51.6%, 39.5%, and 8.9% for European, African, and Amerindian ancestries, respectively. Pairwise FST analysis revealed that Dominicans displayed genetic similarity to Latin American populations, especially those with Afro-Caribbean ancestry, given the selected variants. Higher differences were identified from East and South Asians, Europeans, and Africans, in which several values above the FST threshold for moderate differentiation were identified within variants in CYP2C, CYP3A, CYP1A1, ABCB1, SLC45A2, XRCC1, and XRCC3 genes.

Conclusions

These results should allow establishing the clinical relevance of pharmacogenetic testing in variant alleles related to drug transport and metabolism genes in this population.

Genotype-driven asthma prescribing of inhaled corticosteroids and long-acting β2-agonist: A cost-effectiveness analysis

INTRODUCTION

Predicting response to inhaled corticosteroids (ICSs) + long-acting β2-agonist (LABA) by previously detecting the presence of Arg16Gly ADRB2 genotype is a strategy that could reduce and optimize the management of asthmatic patients. There is a need for economic evaluations to facilitate the implementation of such tests. This research aims to evaluate the cost-effectiveness of Arg16Gly ADRB2 screening in children with asthma in Colombia.

METHODS

From the perspective of a third-party payer, we conducted a cost-effectiveness analysis to determine the cost and quality-adjusted life-years (QALYs) of genotype-driven asthma prescribing based on the Arg16Gly ADRB2 genotype versus current treatment based on no genetic testing. Using four state-transition models, we estimate cost and QALYs employing micro-simulation modeling with a time horizon of 10 years and a cycle length of 1 week. Cost-effectiveness was assessed at a willingness-to-pay (WTP) value of US$5180.

RESULTS

The mean incremental cost of strategy genetic testing versus no genetic testing is US$ -6809. The mean incremental benefit of strategy genetic testing is 16 QALYs. The incremental net monetary benefit of strategic genetic testing versus no genetic testing is US$ 88,893. Genetic testing is the strategy with the highest expected net benefit. The outcomes derived from our primary analysis remained robust when subjected to variations in all underlying assumptions and parameter values.

CONCLUSION

Genetic testing of Arg16Gly ADRB2 is a cost-effective strategy to address asthma management in asthmatic children requiring ICS+LABA. This result should encourage the generation of more evidence and the incorporation of such evidence into clinical practice guidelines for pediatric asthma.

Worldwide analysis of actionable genomic alterations in lung cancer and targeted pharmacogenomic strategies

Based on data from the Global Cancer Statistics 2022, lung cancer stands as the most lethal cancer worldwide, with age-adjusted incidence and mortality rates of 23.6 and 16.9 per 100,000 people, respectively. Despite significant strides in precision oncology driven by large-scale international research consortia, there remains a critical need to deepen our understanding of the genomic landscape across diverse racial and ethnic groups. To address this challenge, we performed comprehensive in silico analyses and data mining to identify pathogenic variants in genes that drive lung cancer. We subsequently calculated the allele frequencies and assessed the deleteriousness of these oncogenic variants among populations such as African, Amish, Ashkenazi Jewish, East and South Asian, Finnish and non-Finnish European, Latino, and Middle Eastern. Our analysis examined 117,707 variants within 86 lung cancer-associated genes across 75,109 human genomes, uncovering 8042 variants that are known or predicted to be pathogenic. We prioritized variants based on their allele frequencies and deleterious scores, and identified those with potential significance for response to anti-cancer therapies through in silico drug simulations, current clinical pharmacogenomic guidelines, and ongoing late-stage clinical trials targeting lung cancer-driving proteins. In conclusion, it is crucial to unite global efforts to create public health policies that emphasize prevention strategies and ensure access to clinical trials, pharmacogenomic testing, and cancer research for these groups in developed nations.

Influence of IL-β, IL-1RN, and TNF-α variants on the risk of acetylsalicylic acid-induced upper gastrointestinal bleeding: a case-control study

OBJECTIVE

Forgerini et al. investigated the role of seven genetic variants in the risk of upper gastrointestinal bleeding as an adverse drug reaction. In 289 participants (50 cases and 189 controls), the presence of seven variants in the IL-1β, IL-1RN, and TNF-α genes was not associated with susceptibility to acetylsalicylic acid-induced upper gastrointestinal bleeding. The use of acetylsalicylic acid, even in low doses, may be associated with the onset of upper gastrointestinal bleeding as an idiosyncratic response. Considering the role of the genetic background in inter-individual responses to pharmacotherapy, we aimed to investigate the role of seven variants in the TNF-α, IL-β, and IL-1RN genes in association with the risk of upper gastrointestinal bleeding in users of low-dose acetylsalicylic acid for the prevention of cardiovascular events.

METHODS

A case-control study was conducted in a Brazilian hospital complex. The Case Group comprised patients diagnosed with upper gastrointestinal bleeding who were administered a low dose of acetylsalicylic acid (n=50). Two Control Groups were recruited: 1) low-dose acetylsalicylic acid users without gastrointestinal complaints and under the supervision of a cardiologist (n=50) and 2) healthy controls (n=189). Sociodemographic, clinical, pharmacotherapeutic, and lifestyle data were recorded through face-to-face interviews. Genomic DNA from all participants was genotyped for rs16944 and rs1143634 (IL-β gene), rs4251961 (IL-1RN gene), and rs1799964, rs1799724, rs361525, and rs1800629 (TNF-α gene).

RESULTS

No significant difference was noted in the genotypic frequencies of TNF-α, IL-β, and IL-1RN variants between the Case and Control Groups of low-dose acetylsalicylic acid users (p>0.05). The frequency of rs1800629 genotypes (TNF-α gene) differed significantly between the Case Group and healthy controls (p=0.003). None of the evaluated variants were associated with a risk of upper gastrointestinal bleeding.

CONCLUSION

This study aimed to explore pharmacogenomics biomarkers in low-dose acetylsalicylic acid users. Our data suggest that the presence of IL-1β, IL-1RN, and TNF-α variants was not associated with an increased risk of upper gastrointestinal bleeding.

Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses

The druggable proteome refers to proteins that can bind to small molecules with appropriate chemical affinity, inducing a favorable clinical response. Predicting druggable proteins through screening and in silico modeling is imperative for drug design. To contribute to this field, we developed an accurate predictive classifier for druggable cancer-driving proteins using amino acid composition descriptors of protein sequences and 13 machine learning linear and non-linear classifiers. The optimal classifier was achieved with the support vector machine method, utilizing 200 tri-amino acid composition descriptors. The high performance of the model is evident from an area under the receiver operating characteristics (AUROC) of 0.975 ± 0.003 and an accuracy of 0.929 ± 0.006 (threefold cross-validation). The machine learning prediction model was enhanced with multi-omics approaches, including the target-disease evidence score, the shortest pathways to cancer hallmarks, structure-based ligandability assessment, unfavorable prognostic protein analysis, and the oncogenic variome. Additionally, we performed a drug repurposing analysis to identify drugs with the highest affinity capable of targeting the best predicted proteins. As a result, we identified 79 key druggable cancer-driving proteins with the highest ligandability, and 23 of them demonstrated unfavorable prognostic significance across 16 TCGA PanCancer types: CDKN2A, BCL10, ACVR1, CASP8, JAG1, TSC1, NBN, PREX2, PPP2R1A, DNM2, VAV1, ASXL1, TPR, HRAS, BUB1B, ATG7, MARK3, SETD2, CCNE1, MUTYH, CDKN2C, RB1, and SMARCA4. Moreover, we prioritized 11 clinically relevant drugs targeting these proteins. This strategy effectively predicts and prioritizes biomarkers, therapeutic targets, and drugs for in-depth studies in clinical trials. Scripts are available at https://github.com/muntisa/machine-learning-for-druggable-proteins .

Association of CHAT Gene Polymorphism rs3793790 and rs2177370 with Donepezil Response and the Risk of Alzheimer's Disease Continuum

Background

Genetic variation plays an important role in drug response, there are few relevant studies on patients with Alzheimer's disease continuum (ADC).

Objective

This study focused on the associations between two single nucleotide polymorphisms (SNPs) (rs3793790 and rs2177370) located in the CHAT gene and donepezil response in ADC patients, and further evaluated the associations between the two SNPs and ADC.

Material and Methods

According to 2018 National Institute on Aging and Alzheimer's Association (NIA-AA) standard, amyloid β-protein positive (Aβ+) and negative (Aβ-) patients were recruited according to the Aβ-PET/CT standard. rs3793790 and rs2177370 were genotyped in buccal swab samples by using the MassARRAY system. We used the Mini Mental State Examination (MMSE) in Chinese version, caregiver evaluation, and prescribing behavior to assess therapeutic response during the 9-month period. Using logistic regression models, we analyzed the relationship between the two SNPs and donepezil response in 58 Aβ+ patients treated with donepezil alone at the initial diagnosis of ADC. We also explored a probable link between the two SNPs and ADC in 147 Aβ+ and 73 Aβ- patients using a logistic regression analysis.

Results

The chance of donepezil response was higher in patients with the G allele of rs3793790 and/or the A allele of rs2177370 than in those without (odds ratio (OR) 6.83, 95% confidence interval (CI): 1.64-28.49). Additionally, the rs3793790 variant was not associated with ADC, whereas the A allele in rs2177370 increased 1.51-fold the ADC risk (OR 2.51, 95% CI: 1.28-4.95).

Conclusion

The genetic variants of rs3793790 and rs2177370 were associated with the donepezil response, and rs2177370 may have a moderate relationship with the risk of ADC.

Gastric cancer actionable genomic alterations across diverse populations worldwide and pharmacogenomics strategies based on precision oncology

Introduction: Gastric cancer is one of the most prevalent types of cancer worldwide. The World Health Organization (WHO), the International Agency for Research on Cancer (IARC), and the Global Cancer Statistics (GLOBOCAN) reported an age standardized global incidence rate of 9.2 per 100,000 individuals for gastric cancer in 2022, with a mortality rate of 6.1. Despite considerable progress in precision oncology through the efforts of international consortia, understanding the genomic features and their influence on the effectiveness of anti-cancer treatments across diverse ethnic groups remains essential. Methods: Our study aimed to address this need by conducting integrated in silico analyses to identify actionable genomic alterations in gastric cancer driver genes, assess their impact using deleteriousness scores, and determine allele frequencies across nine global populations: European Finnish, European non-Finnish, Latino, East Asian, South Asian, African, Middle Eastern, Ashkenazi Jewish, and Amish. Furthermore, our goal was to prioritize targeted therapeutic strategies based on pharmacogenomics clinical guidelines, in silico drug prescriptions, and clinical trial data. Results: Our comprehensive analysis examined 275,634 variants within 60 gastric cancer driver genes from 730,947 exome sequences and 76,215 whole-genome sequences from unrelated individuals, identifying 13,542 annotated and predicted oncogenic variants. We prioritized the most prevalent and deleterious oncogenic variants for subsequent pharmacogenomics testing. Additionally, we discovered actionable genomic alterations in the ARID1A, ATM, BCOR, ERBB2, ERBB3, CDKN2A, KIT, PIK3CA, PTEN, NTRK3, TP53, and CDKN2A genes that could enhance the efficacy of anti-cancer therapies, as suggested by in silico drug prescription analyses, reviews of current pharmacogenomics clinical guidelines, and evaluations of phase III and IV clinical trials targeting gastric cancer driver proteins. Discussion: These findings underline the urgency of consolidating efforts to devise effective prevention measures, invest in genomic profiling for underrepresented populations, and ensure the inclusion of ethnic minorities in future clinical trials and cancer research in developed countries.

The pharmacoepigenetic paradigm in cancer treatment

Epigenetic modifications, characterized by changes in gene expression without altering the DNA sequence, play a crucial role in the development and progression of cancer by significantly influencing gene activity and cellular function. This insight has led to the development of a novel class of therapeutic agents, known as epigenetic drugs. These drugs, including histone deacetylase inhibitors, histone acetyltransferase inhibitors, histone methyltransferase inhibitors, and DNA methyltransferase inhibitors, aim to modulate gene expression to curb cancer growth by uniquely altering the epigenetic landscape of cancer cells. Ongoing research and clinical trials are rigorously evaluating the efficacy of these drugs, particularly their ability to improve therapeutic outcomes when used in combination with other treatments. Such combination therapies may more effectively target cancer and potentially overcome the challenge of drug resistance, a significant hurdle in cancer therapy. Additionally, the importance of nutrition, inflammation control, and circadian rhythm regulation in modulating drug responses has been increasingly recognized, highlighting their role as critical modifiers of the epigenetic landscape and thereby influencing the effectiveness of pharmacological interventions and patient outcomes. Epigenetic drugs represent a paradigm shift in cancer treatment, offering targeted therapies that promise a more precise approach to treating a wide spectrum of tumors, potentially with fewer side effects compared to traditional chemotherapy. This progress marks a step towards more personalized and precise interventions, leveraging the unique epigenetic profiles of individual tumors to optimize treatment strategies.

Assessing the Occurrence and Influence of Cancer Chemotherapy-Related Pharmacogenetic Alleles in the Chilean Population

BACKGROUND

Pharmacogenomic knowledge as a biomarker for cancer care has transformed clinical practice, however, as current guidelines are primarily derived from Eurocentric populations, this limits their application in Latin America, particularly among Hispanic or Latino groups. Despite advancements, systemic chemotherapy still poses challenges in drug toxicity and suboptimal response. This study explores pharmacogenetic markers related to anticancer drugs in a Chilean cohort, filling a gap in Latin American research. Notably, the influence of native South American Mapuche-Huilliche ancestry.

METHODS

To explore pharmacogenetic markers related to anticancer drugs, we utilized an ethnically Admixed Chilean genome-wide association studies (GWAS) dataset of 1095 unrelated individuals. Pharmacogenomic markers were selected from PharmGKB, totaling 36 level 1 and 2 evidence single nucleotide polymorphisms (SNPs) and 571 level 3 SNPs. Comparative analyses involved assessing SNP frequencies across diverse populations from the 1000 Genomes Project. Haplotypes were estimated, and linkage disequilibrium was examined. Ancestry-based association analyses explored relationships between SNPs and Mapuche-Huilliche and European ancestries. Chi-square distribution with p ≤ 0.05 and Bonferroni's multiple adjustment tests determined statistical differences between allele frequencies.

RESULTS

Our study reveals significant disparities in SNP frequency within the Chilean population. Notably, dihydropyrimidine dehydrogenase (DPYD) variants (rs75017182 and rs67376798), linked to an increased risk of severe fluoropyrimidine toxicity, exhibit an exceptionally low frequency (minor allele frequency (MAF) < 0.005). Nudix hydrolase 15 (NUDT15) rs116855232, associated with hematological mercaptopurine toxicity, is relatively common (MAF = 0.062), and is further linked to Mapuche-Huilliche ancestry. Thiopurine methyltransferase enzyme (TPMT), implicated in severe toxicity to mercaptopurines, SNPs rs1142345 and rs1800460 of TMPT gene demonstrate higher MAFs in Admixed Americans and the Chilean population (MAF range 0.031-0.057). Finally, the variant in the UDP-glucuronosyltransferase 1 gene (UGT1A1) rs4148323, correlated with irinotecan neutropenia, exhibits the highest MAF in East Asian (MAF = 0.136) and Chilean (MAF = 0.025) populations, distinguishing them from other investigated populations.

CONCLUSIONS

This study provides the first comprehensive pharmacogenetic characterization of cancer therapy-related SNPs and highlights significant disparities in SNP frequencies within the Chilean population. Our findings underscore the necessity for inclusive research and personalized therapeutic strategies to ensure the equitable and effective application of precision medicine across diverse global communities.