Front Pharmacol. 2024 Mar 8;15:1274442. doi: 10.3389/fphar.2024.1274442. eCollection 2024.

ABSTRACT

Background: Response to antipsychotics is subject to a wide interindividual variability, due to genetic and non-genetic factors. Several single nucleotide polymorphisms (SNPs) have been associated with response to antipsychotics in genome-wide association studies (GWAS). Polygenic risk scores (PRS) are a powerful tool to aggregate into a single measure the small effects of multiple risk alleles. Materials and methods: We studied the association between a PRS composed of SNPs associated with response to antipsychotics in GWAS studies (PRSresponse) in a real-world sample of patients (N = 460) with different diagnoses (schizophrenia spectrum, bipolar, depressive, neurocognitive, substance use disorders and miscellaneous). Two other PRSs composed of SNPs previously associated with risk of schizophrenia (PRSschizophrenia1 and PRSschizophrenia2) were also tested for their association with response to treatment. Results: PRSresponse was significantly associated with response to antipsychotics considering the whole cohort (OR = 1.14, CI = 1.03-1.26, p = 0.010), the subgroup of patients with schizophrenia, schizoaffective disorder or bipolar disorder (OR = 1.18, CI = 1.02-1.37, p = 0.022, N = 235), with schizophrenia or schizoaffective disorder (OR = 1.24, CI = 1.04-1.47, p = 0.01, N = 176) and with schizophrenia (OR = 1.27, CI = 1.04-1.55, p = 0.01, N = 149). Sensitivity and specificity were sub-optimal (schizophrenia 62%, 61%; schizophrenia spectrum 56%, 55%; schizophrenia spectrum plus bipolar disorder 60%, 56%; all patients 63%, 58%, respectively). PRSschizophrenia1 and PRSschizophrenia2 were not significantly associated with response to treatment. Conclusion: PRSresponse defined from GWAS studies is significantly associated with response to antipsychotics in a real-world cohort; however, the results of the sensitivity-specificity analysis preclude its use as a predictive tool in clinical practice.

PMID:38523642 | PMC:PMC10958197 | DOI:10.3389/fphar.2024.1274442

Hum Genomics. 2024 Mar 25;18(1):30. doi: 10.1186/s40246-024-00594-9.

ABSTRACT

BACKGROUND: SLCO1B1 plays an important role in mediating hepatic clearance of many different drugs including statins, angiotensin-converting enzyme inhibitors, chemotherapeutic agents and antibiotics. Several variants in SLCO1B1 have been shown to have a clinically significant impact, in relation to efficacy of these medications. This study provides a comprehensive overview of SLCO1B1 variation in Saudi individuals, one of the largest Arab populations in the Middle East.

METHODS: The dataset of 11,889 (9,961 exomes and 1,928 pharmacogenetic gene panel) Saudi nationals, was used to determine the presence and frequencies of SLCO1B1 variants, as described by the Clinical Pharmacogenetic Implementation Consortium (CPIC).

RESULTS: We identified 141 previously described SNPs, of which rs2306283 (50%) and rs4149056 (28%), were the most common. In addition, we observed six alleles [*15 (24.7%) followed by *20 (8.04%), *14 (5.86%), *5 (3.84%), *31 (0.21%) and *9 (0.03%)] predicted to be clinically actionable. Allele diplotype to phenotype conversion revealed 41 OATP1B1 diplotypes. We estimated the burden of rare, and novel predicted deleterious variants, resulting from 17 such alterations.

CONCLUSIONS: The data we present, from one of the largest Arab cohorts studied to date, provides the most comprehensive overview of SLCO1B1 variants, and the subsequent OATP1B1 activity of this ethnic group, which thus far remains relatively underrepresented in available international genomic databases. We believe that the presented data provides a basis for further clinical investigations and the application of personalized statin drug therapy guidance in Arabs.

PMID:38523294 | DOI:10.1186/s40246-024-00594-9

Br J Clin Pharmacol. 2024 Mar 24. doi: 10.1111/bcp.16048. Online ahead of print.

ABSTRACT

Pharmacokinetics plays a central role in understanding the significant interindividual differences that exist in drug metabolism and response. Effectively addressing these differences requires a multi-faceted approach that encompasses a variety of tools and methods. In this review, we examine three key strategies to achieve this goal, namely pharmacogenomics, therapeutic drug monitoring (TDM) and liquid biopsy-based monitoring of hepatic ADME gene expression and highlight their advantages and limitations. We note that larger cohort studies are needed to validate the utility of liquid biopsy-based assessment of hepatic ADME gene expression, which includes prediction of drug metabolism in the clinical setting. Modern mass spectrometers have improved traditional TDM methods, offering versatility and sensitivity. In addition, the identification of endogenous or dietary markers for CYP metabolic traits offers simpler and more cost-effective alternatives to determine the phenotype. We believe that future pharmacogenomic applications in clinical practice should prioritize the identification of missing heritable factors, using larger, well-characterized patient studies and controlling for confounding factors such as diet, concomitant medication and physical health. The intricate regulation of ADME gene expression implies that large-scale studies combining long-read next-generation sequencing (NGS) of complete genomes with phenotyping of patients taking different medications are essential to identify these missing heritabilities. The continuous integration of such data into AI-driven analytical systems could provide a comprehensive and useful framework. This could lead to the development of highly effective algorithms to improve genetics-based precision treatment by predicting drug metabolism and response, significantly improving clinical outcomes.

PMID:38523083 | DOI:10.1111/bcp.16048

Comput Biol Chem. 2024 Mar 19;110:108054. doi: 10.1016/j.compbiolchem.2024.108054. Online ahead of print.

ABSTRACT

The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predicting drug synergy, but high computational cost for training models as well as great diversity and limited size in screening data escalate the difficulty of prediction. To address this challenge, we propose a simple machine learning framework, namely Similarity Network-based Synergy prediction (SNSynergy), for predicting synergistic effects towards new cell lines and new drug combinations by two locally weighted models CLSN and DCSN. This framework only requires a small amount of auxiliary data, like genomics information of cell lines and the molecular fingerprints or targets of drugs. Based on the assumption that similar cell lines and similar drug combinations have similar synergistic effects, CLSN and DCSN predict synergy scores through capturing individual synergy contributions of nearest cell line and drug combination neighbors, respectively. High correlations between predicted and measured synergy scores on two leading cancer cell line pharmacogenomic screening datasets (the O'Neil dataset and the NCI-ALMANAC dataset) demonstrate the effectiveness and robustness of SNSynergy. Many of the identified drug combinations are consistent with previous studies, or have been explored in clinical settings against the specific cancer type, showing that SNSynergy has the potential to supply cost-saving and effective high-throughput screening for prioritizing the most applicable cell lines and the most promising drug combinations.

PMID:38522389 | DOI:10.1016/j.compbiolchem.2024.108054

BMC Complement Med Ther. 2024 Mar 23;24(1):130. doi: 10.1186/s12906-024-04426-0.

ABSTRACT

BACKGROUND: In a pilot study using both cannabidiol (CBD) and tetrahydrocannabinol (THC) as single agents in advanced cancer patients undergoing palliative care in Thailand, the doses were generally well tolerated, and the outcome measure of total symptom distress scores showed overall symptom benefit. The current study aims to determine the intensity of the symptoms experienced by breast cancer patients, to explore the microbiome profile, cytokines, and bacterial metabolites before and after the treatment with cannabis oil or no cannabis oil, and to study the pharmacokinetics parameters and pharmacogenetics profile of the doses.

METHODS: A randomized, double-blinded, placebo-controlled trial will be conducted on the breast cancer cases who were diagnosed with breast cancer and currently receiving chemotherapy at King Chulalongkorn Memorial Hospital (KCMH), Bangkok, Thailand. Block randomization will be used to allocate the patients into three groups: Ganja Oil (THC 2 mg/ml; THC 0.08 mg/drop, and CBD 0.02 mg/drop), Metta Osot (THC 81 mg/ml; THC 3 mg/drop), and placebo oil. The Edmonton Symptom Assessment System (ESAS), Food Frequency Questionnaires (FFQ), microbiome profile, cytokines, and bacterial metabolites will be assessed before and after the interventions, along with pharmacokinetic and pharmacogenetic profile of the treatment during the intervention.

TRIAL REGISTRATION: TCTR20220809001.

PMID:38521934 | DOI:10.1186/s12906-024-04426-0

Nat Biotechnol. 2024 Mar 21. doi: 10.1038/s41587-024-02173-8. Online ahead of print.

ABSTRACT

Spatially resolved gene expression profiling provides insight into tissue organization and cell-cell crosstalk; however, sequencing-based spatial transcriptomics (ST) lacks single-cell resolution. Current ST analysis methods require single-cell RNA sequencing data as a reference for rigorous interpretation of cell states, mostly do not use associated histology images and are not capable of inferring shared neighborhoods across multiple tissues. Here we present Starfysh, a computational toolbox using a deep generative model that incorporates archetypal analysis and any known cell type markers to characterize known or new tissue-specific cell states without a single-cell reference. Starfysh improves the characterization of spatial dynamics in complex tissues using histology images and enables the comparison of niches as spatial hubs across tissues. Integrative analysis of primary estrogen receptor (ER)-positive breast cancer, triple-negative breast cancer (TNBC) and metaplastic breast cancer (MBC) tissues led to the identification of spatial hubs with patient- and disease-specific cell type compositions and revealed metabolic reprogramming shaping immunosuppressive hubs in aggressive MBC.

PMID:38514799 | DOI:10.1038/s41587-024-02173-8

Pharmacogenomics. 2024 Mar 21. doi: 10.2217/pgs-2023-0243. Online ahead of print.

ABSTRACT

Whole-exome sequencing (WES) is widely used in clinical settings; however, the exploration of its use in pharmacogenomic analysis remains limited. Our study compared the variant callings for 28 core absorption, distribution, metabolism and elimination genes by WES and array-based technology using clinical trials samples. The results revealed that WES had a positive predictive value of 0.71-0.92 and a sensitivity of single-nucleotide variants between 0.68 and 0.95, compared with array-based technology, for the variants in the commonly targeted regions of the WES and PhamacoScan™ assay. Besides the common variants detected by both assays, WES identified 200-300 exclusive variants per sample, totalling 55 annotated exclusive variants, including important modulators of metabolism such as rs2032582 (ABCB1) and rs72547527 (SULT1A1). This study highlights the potential clinical advantages of using WES to identify a wider range of genetic variations and enabling precision medicine.

PMID:38511470 | DOI:10.2217/pgs-2023-0243

Pharmacogenomics. 2024 Mar 21. doi: 10.2217/pgs-2024-0026. Online ahead of print.

NO ABSTRACT

PMID:38511426 | DOI:10.2217/pgs-2024-0026

J Chemother. 2024 Mar 21:1-15. doi: 10.1080/1120009X.2024.2330241. Online ahead of print.

ABSTRACT

Chemoresistance leads to treatment failure, which can arise through different mechanisms including patients' characteristics. Searching for genetic profiles as a predictor for drug response and toxicity has been extensively studied in pharmacogenomics, thus contributing to personalized medicine and providing alternative treatments. Numerous studies have demonstrated significant evidence of association between genetic polymorphisms and response to neoadjuvant chemotherapy (NAC) in breast cancer. In this review, we explored the potential impact of genetic polymorphisms in NAC primary resistance through selecting a specific clinical profile. The genetic variability within pharmacokinetics, pharmacodynamics, DNA synthesis and repair, and oncogenic signaling pathways genes could be predictive or prognostic markers for NAC resistance. The clinical implication of these results can help provide individualized treatment plans in the early stages of breast cancer treatment. Further studies are needed to determine the genetic hosts of primary chemoresistance mechanisms in order to further emphasize the implementation of genotypic approaches in personalized medicine.

PMID:38511398 | DOI:10.1080/1120009X.2024.2330241

Am Heart J Plus. 2023 Nov 25;37:100348. doi: 10.1016/j.ahjo.2023.100348. eCollection 2024 Jan.

NO ABSTRACT

PMID:38510509 | PMC:PMC10945887 | DOI:10.1016/j.ahjo.2023.100348

JACC CardioOncol. 2024 Jan 23;6(1):38-50. doi: 10.1016/j.jaccao.2023.11.008. eCollection 2024 Feb.

ABSTRACT

BACKGROUND: Genome-wide association studies and candidate gene association studies have identified more than 180 genetic variants statistically associated with anthracycline-induced cardiotoxicity (AIC). However, the lack of functional validation has hindered the clinical translation of these findings.

OBJECTIVES: The aim of this study was to functionally validate all genes associated with AIC using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).

METHODS: Through a systemic literature search, 80 genes containing variants significantly associated with AIC were identified. Additionally, 3 more genes with potential roles in AIC (GSTM1, CBR1, and ERBB2) were included. Of these, 38 genes exhibited expression in human fetal heart, adult heart, and hiPSC-CMs. Using clustered regularly interspaced short palindromic repeats/Cas9-based genome editing, each of these 38 genes was systematically knocked out in control hiPSC-CMs, and the resulting doxorubicin-induced cardiotoxicity (DIC) phenotype was assessed using hiPSC-CMs. Subsequently, functional assays were conducted for each gene knockout on the basis of hypothesized mechanistic implications in DIC.

RESULTS: Knockout of 26 genes increased the susceptibility of hiPSC-CMs to DIC. Notable genes included efflux transporters (ABCC10, ABCC2, ABCB4, ABCC5, and ABCC9), well-established DIC-associated genes (CBR1, CBR3, and RAC2), and genome-wide association study-discovered genes (RARG and CELF4). Conversely, knockout of ATP2B1, HNMT, POR, CYBA, WDR4, and COL1A2 had no significant effect on the in vitro DIC phenotype of hiPSC-CMs. Furthermore, knockout of the uptake transporters (SLC28A3, SLC22A17, and SLC28A1) demonstrated a protective effect against DIC.

CONCLUSIONS: The present findings establish a comprehensive platform for the functional validation of DIC-associated genes, providing insights for future studies in DIC variant associations and potential mechanistic targets for the development of cardioprotective drugs.

PMID:38510289 | PMC:PMC10950437 | DOI:10.1016/j.jaccao.2023.11.008

Heliyon. 2024 Mar 5;10(6):e27043. doi: 10.1016/j.heliyon.2024.e27043. eCollection 2024 Mar 30.

ABSTRACT

Despite the raised awareness of the role of pharmacogenomic (PGx) in personalized medicines for COVID-19, data for COVID-19 drugs is extremely scarce and not even a publication on this topic for post-COVID-19 medications to date. In the current study, we investigated the genetic variations associated with COVID-19 and post-COVID-19 therapies by using whole genome sequencing data of the 1000 Vietnamese Genomes Project (1KVG) in comparison with other populations retrieved from the 1000 Genomes Project Phase 3 (1KGP3) and the Genome Aggregation Database (gnomAD). Moreover, we also evaluated the risk of drug interactions in comorbid COVID-19 and post-COVID-19 patients based on pharmacogenomic profiles of drugs using a computational approach. For COVID-19 therapies, variants related to the response of two causal treatment agents (tolicizumab and ritonavir) and antithrombotic drugs are common in the Vietnamese cohort. Regarding post-COVID-19, drugs for mental manipulations possess the highest number of clinical annotated variants carried by Vietnamese individuals. Among the superpopulations, East Asian populations shared the most similar genetic structure with the Vietnamese population, whereas the African population showed the most difference. Comorbid patients are at an increased drug-drug interaction (DDI) risk when suffering from COVID-19 and after recovering as well due to a large number of potential DDIs which have been identified. Our results presented the population-specific understanding of the pharmacogenomic aspect of COVID-19 and post-COVID-19 therapy to optimize therapeutic outcomes and promote personalized medicine strategy. We also partly clarified the higher risk in COVID-19 patients with underlying conditions by assessing the potential drug interactions.

PMID:38509882 | PMC:PMC10950508 | DOI:10.1016/j.heliyon.2024.e27043

Int J Antimicrob Agents. 2024 Mar 18:107137. doi: 10.1016/j.ijantimicag.2024.107137. Online ahead of print.

ABSTRACT

BACKGROUND: Blood brain barrier impairment is frequent in people living with HIV (PLWH), affecting the penetration of target cells and antiretrovirals into the central nervous system, through transporters (e.g. ABCB1), leading to neuroinflammation.

OBJECTIVES: The aim of this study was to identify variants of genes encoding transporters able to predict neuroinflammation biomarker levels.

MATERIALS AND METHODS: Cerebrospinal fluid (CSF) and plasma samples were obtained from PLWH. CSF biomarkers were quantified by commercial assays. Genetic variants were evaluated through real-time polymerase chain reaction (PCR).

RESULTS: 107 PLWH (163 samples) were included in the study: 79% were male, median age was 48.5 years, CD4% was 25%, HIV-associated neurolocognitive disorder (HAND) was observed in 17.8% of patients. ABCB1 2677G>T genetic variant showed a different allelic distribution according to the clinical group (p=0.026). In linear regression analyses, HIV-related central nervous system disorders, ABCG2 1194+928CC genotype, log viral load, CSAR, β-1,42 levels and CSF proteins were retained in the final model as factors independently associated with CSF neopterin levels; CSF proteins and integrase inhibitors use were associated with CSF tau level in the multivariate model. Phospho-tau regression analysis reported ABCB1 2677GT/TT genotype and CSF proteins as predictors in the final model; gender and protease inhibitors, neopterin, ABCB1 2677 GT/ TT genotype resulted predictors in the multivariate regression for β-1,42.

CONCLUSIONS: For the first time, pharmacogenetic and clinical features were predictors of neuro-inflammation biomarkers.

PMID:38508536 | DOI:10.1016/j.ijantimicag.2024.107137

Paediatr Drugs. 2024 Mar 20. doi: 10.1007/s40272-024-00621-1. Online ahead of print.

ABSTRACT

BACKGROUND: Therapeutic drug monitoring (TDM) of infliximab has been shown to be a effective strategy for inflammatory bowel disease (IBD). Population pharmacokinetic (PopPK) modeling can predict trough concentrations for individualized dosing.

OBJECTIVE: The aim of this study was to develop a PopPK model of infliximab in a paediatric population with IBD, assessing the effect of single nucleotide polymorphisms (SNPs) and other biomarkers on infliximab clearance.

METHODS: This observational and ambispective single-centre study was conducted in paediatric patients with IBD treated with infliximab between July 2016 and July 2022 in the Paediatric Gastroenterology Service of the Hospital Universitari Vall d'Hebron (HUVH) (Spain). Demographic, clinical, and analytical variables were collected. Twenty SNPs potentially associated with variations in the response to infliximab plasma concentrations were analysed. infliximab serum concentrations and antibodies to infliximab (ATI) were determined by ELISA. PopPK modelling was performed using nonlinear mixed-effects analysis (NONMEM).

RESULTS: Thirty patients (21 males) were included. The median age (range) at the start of infliximab treatment was 13 years (16 months to 16 years). A total of 190 samples were obtained for model development (49 [25.8%] during the induction phase). The pharmacokinetics (PK) of infliximab were described using a two-compartment model. Weight, erythrocyte sedimentation rate (ESR), faecal calprotectin (FC), and the SNP rs1048610 (ADAM17) showed statistical significance for clearance (CL), and albumin for inter-compartmental clearance (Q). Estimates of CL1 (genotype 1-AA), CL2 (genotype 2-AG), CL3 (genotype 3-GG), Q, Vc, and Vp (central and peripheral distribution volumes) were 0.0066 L/h/46.4 kg, 0.0055 L/h/46.4 kg, 0.0081 L/h/46.4 kg, 0.0029 L/h/46.4 kg, 0.6750 L/46.4 kg, and 1.19 L/46.4 kg, respectively. The interindividual variability (IIV) estimates for clearance, Vc, and Vp were 19.33, 16.42, and 36.02%, respectively.

CONCLUSIONS: A popPK model utilising weight, albumin, FC, ESR, and the SNP rs1048610 accurately predicted infliximab trough concentrations in children with IBD.

PMID:38507036 | DOI:10.1007/s40272-024-00621-1

Pharmacogenomics. 2024 Mar 20. doi: 10.2217/pgs-2024-0013. Online ahead of print.

ABSTRACT

Objective: This work was designed to describe the knowledge and perceptions of pharmacogenomics (PGx) among pharmacists in the Canadian province of Manitoba. Methods: A 40-item, web-based survey was distributed to pharmacists in Manitoba. Results: Of 74 participants, one third had some education or training in PGx, and 12.2% had used PGx test results in their practice. Participants' self-rated knowledge of PGx testing and common PGx resources (e.g., Pharmacogenomics Knowledge Base, Clinical Pharmacogenetics Implementation Consortium) was low. Most pharmacists surveyed believe that PGx can improve medication efficacy (82.4%) or prevent adverse drug reactions (81.1%). Most (91%) desired more education on PGx. Conclusion: Manitoba pharmacists reported positive perceptions toward PGx. However, they are currently underprepared to implement PGx into practice.

PMID:38506345 | DOI:10.2217/pgs-2024-0013

Pharmacogenomics. 2024 Mar 20. doi: 10.2217/pgs-2023-0189. Online ahead of print.

ABSTRACT

Aim: The study aim was to determine caregiver interest and planned utilization of pharmacogenomic (PGx) results for their child with Prader-Willi syndrome. Methods: Caregivers consented to PGx testing for their child and completed a survey before receiving results. Results: Of all caregivers (n = 48), 93.8% were highly interested in their child's upcoming PGx results. Most (97.9%) planned to share results with their child's medical providers. However, only 47.9% of caregivers were confident providers would utilize the PGx results. Conclusion: Caregivers are interested in utilizing PGx but are uncertain providers will use these results in their child's care. More information about provider comfort with PGx utilization is needed to understand how PGx education would benefit providers and ultimately patients with PGx results.

PMID:38506331 | DOI:10.2217/pgs-2023-0189

Pharmacogenomics. 2024 Mar 20. doi: 10.2217/pgs-2024-0009. Online ahead of print.

ABSTRACT

This study shows that the distribution of CYP3A5 alleles (*1, *3, *6 and *7) and genotype-predicted CYP3A5 phenotypes vary significantly across Latin American cohorts (Brazilians and the One Thousand Genomes Admixed American superpopulation), as well as among subcohorts comprising individuals with the highest proportions of Native, European or sub-Saharan African ancestry. Differences in biogeographical ancestry across the study groups are the likely explanation for these results. The differential distribution of CYP3A5 phenotypes has major pharmacogenomic implications, affecting the proportion of individuals carrying high risk CYP3A5 phenotypes for the immunosuppressant tacrolimus and the number of patients that would need to be genotyped to prevent acute rejection in kidney transplant recipients under tacrolimus treatment.

PMID:38506326 | DOI:10.2217/pgs-2024-0009

Pharmacogenomics. 2024 Mar 20. doi: 10.2217/pgs-2023-0229. Online ahead of print.

ABSTRACT

Aim: Drug-induced long QT syndrome (diLQTS), an adverse effect of many drugs, can lead to sudden cardiac death. Candidate genetic variants in cardiac ion channels have been associated with diLQTS, but several limitations of previous studies hamper clinical utility. Materials & methods: Thus, the purpose of this study was to assess the associations of KCNE1-D85N, KCNE2-I57T and SCN5A-G615E with diLQTS in a large observational case-control study (6,083 self-reported white patients treated with 27 different high-risk QT-prolonging medications; 12.0% with diLQTS). Results: KCNE1-D85N significantly associated with diLQTS (adjusted odds ratio: 2.24 [95% CI: 1.35-3.58]; p = 0.001). Given low minor allele frequencies, the study had insufficient power to analyze KCNE2-I57T and SCN5A-G615E. Conclusion: KCNE1-D85N is a risk factor for diLQTS that should be considered in future clinical practice guidelines.

PMID:38506312 | DOI:10.2217/pgs-2023-0229

Int Med Case Rep J. 2024 Mar 15;17:167-175. doi: 10.2147/IMCRJ.S446184. eCollection 2024.

ABSTRACT

INTRODUCTION: Pancreatic cancer (PC) is among the deadliest malignancies. Kidney cancer (KC) is a common malignancy globally. Chemo- or radio-therapies are not very effective to control PC or KC, and overdoses often cause severe site reactions to the patients. As a result, novel treatment strategies with high efficacy but without toxic side effects are urgently desired. Secoisolariciresinol diglucoside (SDG) belongs to plant lignans with potential anticancer activities, but clinical evidence is not available in PC or KC treatment.

PATIENT CONCERNS: We report a rare case of an 83-year-old female patient with pancreatic and kidney occupying lesions that lacked the conditions to receive surgery or chemo- or radiotherapy.

DIAGNOSIS: Pancreatic and kidney cancers.

INTERVENTIONS: We gave dietary SDG to the patient as the only therapeutics.

OUTCOMES: SDG effectively halted progression of both PC and KC. All clinical manifestations, including bad insomnia, loss of appetite, stomach symptoms, and skin itching over the whole body, all disappeared. The initial massive macroscopic hematuria became microscopic and infrequent, and other laboratory results also gradually returned to normal. Most of the cancer biomarkers, initially high such as CEA, CA199, CA724, CA125, came down rapidly, among which CA199 changed most radically. This patient has had progression-free survival of one year so far.

CONCLUSION: These results demonstrate the potent inhibitory effects of SDG on PC and KC of this patient and provide promising novel therapeutics for refractory malignant tumors.

PMID:38504721 | PMC:PMC10949998 | DOI:10.2147/IMCRJ.S446184

Clin Transl Sci. 2024 Mar;17(3):e13772. doi: 10.1111/cts.13772.

ABSTRACT

Genetic variants affect drug responses, making pre-emptive genotyping crucial for averting serious adverse events (SAEs) and treatment failure. However, assessing the benefits of pre-emptive genotyping based on genetic distribution, drug exposure, and demographics is challenging. This study aimed to estimate the population-level benefits of pre-emptive genotyping in the Korean population using nationwide cohort data. We reviewed actionable gene-drug combinations recommended by both the Clinical Pharmacogenomics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG) as of February 2022, identifying high-risk phenotypes. We collected reported risk reduction from genotyping and standardized it into population attributable risks. Healthcare reimbursement costs for SAEs and treatment failures were obtained from the Health Insurance Review and Assessment Service Statistics in 2021. The benefits of pre-emptive genotyping for a specific group were determined by multiplying drug exposure from nationwide cohort data by individual genotyping benefits. We identified 31 gene-drug-event pairs, with CYP2D6 and CYP2C19 demonstrating the greatest benefits for both male and female patients. Individuals aged 65-70 years had the highest individual benefit from pre-emptive genotyping, with $84.40 for men and $100.90 for women. Pre-emptive genotyping, particularly for CYP2D6 and CYP2C19, can provide substantial benefits.

PMID:38501281 | DOI:10.1111/cts.13772