Biochem Biophys Res Commun. 2021 Aug 31;576:59-65. doi: 10.1016/j.bbrc.2021.08.091. Online ahead of print.

ABSTRACT

HER1-and HER2-targeted drugs are effective in cancer therapy, especially against lung, breast and colon malignancies; however, resistance of cancer cells to HER1-and HER2-targeted therapies is becoming a serious problem. The avidity/affinity constant (KA) and growth inhibitory effect of anti-HER3 rat monoclonal antibodies (mAb, Ab1∼Ab6) in the presence of therapeutic mAb or low-molecular-weight inhibitors against HER family proteins were analyzed by flow cytometry-based Scatchard plots (Splot) and cell proliferation assay. The KA of Ab3 and Ab6, but not Ab1 or Ab4, split into dual (high and low) modes of KA, and Ab6 exhibited greater anti-proliferative effects against LS-174T colon cancer cells in the presence of Pertuzumab (anti-HER2 mAb). A high KA by Ab6 and Ab6-mediated increased growth inhibition were observed against NCI-H1838 lung or BT474 breast cancer cells, respectively, in the presence of Panitumumab (anti-HER1 mAb) or Perutuzumab. A high KA by Ab6 and Ab6-mediated increased anti-proliferative effects against NCI-H1838 or BT474 were also respectively observed in the presence of Erlotinib (HER1 inhibitor) or Lapatinib (HER1/HER2 inhibitor). In HER1-knockout (KO) NCI-H1838, the reactivity and KA of Ab4 increased compared with in parent NCI-H1838. In HER1-KO or HER3-KO SW1116 colon cancer cells, dual modes of KA with Pertuzumab were noted, and the combination Ab6 and Pertuzumab promoted growth inhibition of HER1-KO, but not of parent SW1116.

PMID:34482024 | DOI:10.1016/j.bbrc.2021.08.091

Basic Clin Pharmacol Toxicol. 2021 Sep 4. doi: 10.1111/bcpt.13654. Online ahead of print.

ABSTRACT

Chemotherapy-induced peripheral neuropathy (CIPN) is a common dose-limiting toxicity that affects 30-40% of patients undergoing cancer treatment. Although multiple mechanisms of chemotherapy-induced neurotoxicity have been described in preclinical models, these have not been translated into widely effective strategies for the prevention or treatment of CIPN. Predictive biomarkers to inform therapeutic approaches are also lacking. Recent studies have examined genetic risk factors associated with CIPN susceptibility. This review provides an overview of the clinical and pathologic features of CIPN and summarizes efforts to identify target pathways through genetic and functional studies. Structurally and mechanistically diverse chemotherapeutics are associated with CIPN; however, the current review is focused on microtubule targeting agents since these are the focus of most pharmacogenetic association and functional studies of CIPN. Genome-wide pharmacogenetic association studies are useful tools to identify not only causative genes and genetic variants but also genetic networks implicated in drug response or toxicity and have been increasingly applied to investigations of CIPN. Induced pluripotent stem cell-derived models of human sensory neurons are especially useful to understand the mechanistic significance of genomic findings. Combined genetic and functional genomic efforts to understand CIPN hold great promise for developing therapeutic approaches for its prevention and treatment.

PMID:34481421 | DOI:10.1111/bcpt.13654

J Anal Toxicol. 2021 Sep 5:bkab096. doi: 10.1093/jat/bkab096. Online ahead of print.

ABSTRACT

Tramadol (TR) metabolism is mainly dependent on the enzymatic activity of CYP2D6, which is controlled by genetic polymorphisms. Individuals are classified as poor (PMs), intermediate (IMs), extensive (EMs) or ultrarapid metabolizers (UMs) according to their genotype or phenotype. The determination of the metabolic phenotype for CYP2D6 can be of utmost importance in forensic and clinical contexts that involve TR intake. The present study aimed to describe CYP2D6 genetic variants in cases of TR-related deaths and to assess which metabolic ratio(s) (MRs) would allow to determine CYP2D6 phenotype without having to perform genetic analyses. Forty-eight postmortem blood samples were selected from TR-related death cases previously analyzed in a forensic context in North of France between 2013 and 2019. Initial available data included blood concentrations of TR and its two main metabolites (M1& M2) determined using a LC-MS/MS method. TR metabolism was expressed as various MRs comprising TR/M1, TR/M2 and M2/M1. After DNA extraction, sequencing was used for genetic variant detections that affect CYP2D6 activity/expression. In the present study, the allelic variants with the higher frequency were CYP2D6*1 (68%), followed by *4 (21%). The most frequent phenotype is EMs (59.6%), followed by IMs (23.4%), PMs (12.8%), and UMs (6.4%). There was no significant correlation between each calculated MR and the genotypically-predicted phenotypes, except for M2/M1 which appears related to the PM phenotype. The observed distribution of CYP2D6 genetic variants in this TR-related death population was similar to that found in the general Caucasian population. The present study displayed that the blood M2/M1 ratio could be the best-correlated tramadol MR to the PM phenotype, and could thus be used in forensic contexts where genetic analyses are not possible or poorly informative. For the other phenotypes, especially the UM phenotype, genetic analysis appears to be the only reliable method to predict the CYP2D6 phenotype.

PMID:34480795 | DOI:10.1093/jat/bkab096

Eur J Clin Pharmacol. 2021 Sep 4. doi: 10.1007/s00228-021-03206-w. Online ahead of print.

ABSTRACT

BACKGROUND: Body surface area (BSA)-based dosing of irinotecan (IR) does not account for its pharmacokinetic (PK) and pharmacodynamic (PD) variabilities. Functional hepatic nuclear imaging (HNI) and excretory/metabolic/PD pharmacogenomics have shown correlations with IR disposition and toxicity/efficacy. This study reports the development of a nonlinear mixed-effect population model to identify pharmacogenomic and HNI-related covariates that impact on IR disposition to support dosage optimization.

METHODS: Patients had advanced colorectal cancer treated with IR combination therapy. Baseline blood was analysed by Affymetrix DMET™ Plus Array and, for PD, single nucleotide polymorphisms (SNPs) by Sanger sequencing. For HNI, patients underwent 99mTc-IDA hepatic imaging, and data was analysed for hepatic extraction/excretion parameters. Blood was taken for IR and metabolite (SN38, SN38G) analysis on day 1 cycle 1. Population modelling utilised NONMEM version 7.2.0, with structural PK models developed for each moiety. Covariates include patient demographics, HNI parameters and pharmacogenomic variants.

RESULTS: Analysis included (i) PK data: 32 patients; (ii) pharmacogenomic data: 31 patients: 750 DMET and 22 PD variants; and (iii) HNI data: 32 patients. On initial analysis, overall five SNPs were identified as significant covariates for CLSN38. Only UGT1A3_c.31 T > C and ABCB1_c.3435C > T were included in the final model, whereby CLSN38 reduced from 76.8 to 55.1%.

CONCLUSION: The identified UGT1A3_c.31 T > C and ABCB1_c.3435C > T variants, from wild type to homozygous, were included in the final model for SN38 clearance.

PMID:34480602 | DOI:10.1007/s00228-021-03206-w

Pharmacogenomics J. 2021 Sep 3. doi: 10.1038/s41397-021-00253-5. Online ahead of print.

ABSTRACT

Urine drug testing (UDT) is a tool for monitoring drug use, including oxycodone. While variation in cytochrome P450 (CYP) genes is known to alter oxycodone metabolism, its impact on UDT results of oxycodone and its metabolites has not been well-studied. Here, multivariate analysis was performed on retrospective UDT results of 90,379 specimens collected from 14,684 genotyped patients prescribed oxycodone. Genetic variation in CYP2D6 and CYP2C19 had a significant impact on oxymorphone/oxycodone ratios, with a 6.9-fold difference between CYP2D6 ultrarapid metabolizers (UMs) and poor metabolizers (PMs; p < 10-300) and a 1.6-fold difference between CYP2C19 UMs and PMs (p = 1.50 × 10-4). CYP2D6 variation also significantly impacted noroxycodone/oxycodone ratios (p = 6.95 × 10-38). Oxycodone-positive specimens from CYP2D6 PMs were ~5-fold more likely to be oxymorphone-negative compared to normal metabolizers. These findings indicate that multivariate analysis of UDT data may be used to reveal the real-world impact of genetic and non-genetic factors on drug metabolism.

PMID:34480108 | DOI:10.1038/s41397-021-00253-5

Cancer Genomics Proteomics. 2021 Sep-Oct;18(5):605-626. doi: 10.21873/cgp.20284.

ABSTRACT

In this review, the fundamental basis of machine learning (ML) and data mining (DM) are summarized together with the techniques for distilling knowledge from state-of-the-art omics experiments. This includes an introduction to the basic mathematical principles of unsupervised/supervised learning methods, dimensionality reduction techniques, deep neural networks architectures and the applications of these in bioinformatics. Several case studies under evaluation mainly involve next generation sequencing (NGS) experiments, like deciphering gene expression from total and single cell (scRNA-seq) analysis; for the latter, a description of all recent artificial intelligence (AI) methods for the investigation of cell sub-types, biomarkers and imputation techniques are described. Other areas of interest where various ML schemes have been investigated are for providing information regarding transcription factors (TF) binding sites, chromatin organization patterns and RNA binding proteins (RBPs), while analyses on RNA sequence and structure as well as 3D dimensional protein structure predictions with the use of ML are described. Furthermore, we summarize the recent methods of using ML in clinical oncology, when taking into consideration the current omics data with pharmacogenomics to determine personalized treatments. With this review we wish to provide the scientific community with a thorough investigation of main novel ML applications which take into consideration the latest achievements in genomics, thus, unraveling the fundamental mechanisms of biology towards the understanding and cure of diseases.

PMID:34479914 | DOI:10.21873/cgp.20284

Medicine (Baltimore). 2021 Sep 3;100(35):e27130. doi: 10.1097/MD.0000000000027130.

ABSTRACT

Bevacizumab (BV) plus chemotherapy is broadly used in advanced ovarian cancer (OC). However, the efficacy of BV-based regimens for advanced OC patients is not satisfactory. Therefore, it is urgent to explore the predictive genetic biomarkers for BV.Tumor tissues from advanced OC patients receiving BV-based regimens were analyzed with a 150-gene targeted panel for next generation sequencing. The associations between gene alterations or clinicopathology features and progression-free survival (PFS) were analyzed by Kaplan-Meier curves or Cox regression. The association of the genetic alteration in potential predictive genes and expressions of 11 vascular endothelial growth factor-related genes were analyzed in The Cancer Genome Atlas cohort using 292 OC cases.Sixty two Chinese advanced OC patients treated with BV-based therapy were included. The median PFS of was 6.9 months, and objective response rate was 14.5%. In multivariate Cox regression analysis, the status of endothelial growth factor receptor (EGFR) (hazard ratio = 6.39, 95% confidence interval [CI] 2.25-18.13, P < .001) and human epidermal growth factor receptor 2 (HER2) (hazard ratio = 3.58, 95% CI 1.27-10.08, P = .016) were significantly correlated with PFS. MYC Proto-Oncogene amplification seemed to have a positive trend (hazard ratio = 0.21, 95% CI 0.05-1.02, P = .052). Moreover, EGFR and HER2 alterations were not prognostic factors of overall survival for OC in The Cancer Genome Atlas OC cohort. The vascular endothelial growth factor-related signature analysis indicated vascular endothelial factor A expression was upregulated with EGFR alterations (P = .034) which may be involved in BV resistance, and HER2 alterations were associated with hypoxia inducible factor 1 subunit alpha overexpression significantly (P = .029).EGFR or HER2 alterations are negative predictors of PFS for OC patient treated with BV plus chemotherapy. Therefore, the clinicians may consider to use alternative regimens such as anti-EGFR or anti-HER2 targeted therapy instead of BV-based regimens on these patients when standard care fail.

PMID:34477158 | PMC:PMC8415939 | DOI:10.1097/MD.0000000000027130

Clin Transl Sci. 2021 Sep 3. doi: 10.1111/cts.13135. Online ahead of print.

ABSTRACT

CYP2A6 activity, phenotyped by the nicotine metabolite ratio (NMR), is a predictor of several smoking behaviours, including cessation and smoking-related disease risk. The heritability of the NMR is 60-80%, yet weighted genetic risk scores (wGRSs) based on common variants explain only 30-35%. Rare variants (minor allele frequency <1%) are hypothesized to explain some of this missing heritability. We present two targeted sequencing studies where rare protein-coding variants are functionally characterized in vivo, in silico, and in vitro to examine this hypothesis. In a smoking cessation trial, 1687 individuals were sequenced; characterization measures included the in vivo NMR, in vitro protein expression, and metabolic activity measured from recombinant proteins. In a human liver bank, 312 human liver samples were sequenced; measures included RNA expression, protein expression, and metabolic activity from extracted liver tissue. In total, 38 of 47 rare coding variants identified were novel; characterizations ranged from gain-of-function to loss-of-function. On a population level, the portion of NMR variation explained by the rare coding variants was small (~1%). However, upon incorporation, the accuracy of the wGRS was improved for individuals with rare protein-coding variants (i.e. the residuals were reduced), and approximately one-third of these individuals (12/39) were reassigned from normal to slow metabolizer status. Rare coding variants can alter an individual's CYP2A6 activity; their integration into wGRSs through precise functional characterization is necessary to accurately assess clinical outcomes and achieve precision medicine for all. Investigation into non-coding variants is warranted to further explain the missing heritability in the NMR.

PMID:34476898 | DOI:10.1111/cts.13135

Res Social Adm Pharm. 2021 Aug 20:S1551-7411(21)00313-2. doi: 10.1016/j.sapharm.2021.08.009. Online ahead of print.

ABSTRACT

BACKGROUND: Pharmacogenomics (PGx) can provide valuable pharmacokinetic and pharmacodynamic information for the pharmacist's assessment of drug therapy, especially within medication therapy management (MTM) services. However, no review has comprehensively mapped the pharmacists' use of PGx in practice-based research. Doing so would allow future researchers, practitioners, and policy-makers to identify the ideal populations and settings for PGx implementation within the pharmacy.

OBJECTIVE: The purpose of this review is to identify the evidence to date of PGx use in pharmacy practice.

METHODS: A scoping review was conducted to find all studied non-oncologic pharmacy practices incorporating PGx testing. Search terms were applied to 5 databases and relevant journals. Characteristics of patients, pharmacy settings, genetic tests, and outcomes were summarized to determine models most likely to benefit patients.

RESULTS: The search identified 43 studies on the use of PGx by pharmacists published between 2007 and 2020. CYP2C19 testing with antiplatelets was the most studied model, found in both community and institutional settings. It also was the most actionable test: approximately 30% of patients have polymorphisms indicating a need for alternative antiplatelets, and identifying these patients can reduce morbidity and mortality by more than 50%. As technology shifts, broader studies using multi-gene panel tests within MTM demonstrate an approximate 50% decrease in emergency visits and hospitalizations in elderly polypharmacy patients. Clinical benefit or drug-gene interactions are also found in other cardiovascular, psychiatric, analgesic, and gastrointestinal indications. No evaluations of actual costs or of pharmacist prescribing within pharmacy-based PGx have been performed. Facilitators towards successful PGx implementation included pharmacist education, collaboration with other healthcare providers, and the use of clinical decision software.

CONCLUSIONS: Pharmacogenomic testing has demonstrated feasibility and improved medication outcomes in pharmacy practice, including in the community pharmacy. Further PGx research should be directed towards pharmacist prescribing, pharmacist education, and pharmacoeconomics.

PMID:34474980 | DOI:10.1016/j.sapharm.2021.08.009

Int J Med Inform. 2021 Aug 18;154:104559. doi: 10.1016/j.ijmedinf.2021.104559. Online ahead of print.

ABSTRACT

BACKGROUND: Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine.

BASIC PROCEDURES: We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing.

MAIN FINDINGS: We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.

PRINCIPAL CONCLUSIONS: We show the benchmarking results of novel blockchain-based methods for institutions to share patient outcomes related to gene-drug interactions. Our findings support blockchain utilization in healthcare, genomic and biomedical applications. The source code is publicly available at https://github.com/tsungtingkuo/genedrug.

PMID:34474309 | DOI:10.1016/j.ijmedinf.2021.104559

J Pharmacol Toxicol Methods. 2021 Aug 30:107117. doi: 10.1016/j.vascn.2021.107117. Online ahead of print.

ABSTRACT

The western blot (WB) is the predominate method for protein quantification, frequently used in pharmacological and toxicological studies. To control for technical variation, WB signals are normalized through immunodetection of an internal standard "house-keeping" gene or total protein quantification via staining of the same blot or a duplicate, sister blot. Increasing evidence suggests that house-keeping genes are subject to change after drug treatment or under disease states, causing protein quantification errors in WB. Recent advances in automated capillary-based WB technologies enable measurement of the protein of interest, internal standards, and total protein in a single capillary. Using this approach, we quantified cytochrome P450 3A4 (CYP3A4) across 179 liver samples and compared normalization by both β-actin and total protein to determine which better functions as an internal standard. CYP3A4 is responsible for metabolism of a wide array of xenobiotics and is known to exhibit large inter-person variation, making it a good candidate to evaluate protein quantification. We observed significant differences in β-actin protein levels between liver samples (~20-fold) and found better correlation between CYP3A4 protein and mRNA using total protein normalization than β-actin, indicating total protein normalization to be less error prone for estimation of CYP3A4. Furthermore, by using total protein normalization, we confirmed significant association between CYP3A4 protein expression and the functional CYP3A4 variant CYP3A4*22, which contains two linked SNPs rs35599367 and rs62471956. Our results indicate that the automatic capillary WB instrument combined with total protein normalization provides a high throughput and robust approach for protein quantification.

PMID:34474151 | DOI:10.1016/j.vascn.2021.107117

Eur J Pharm Sci. 2021 Aug 30:105986. doi: 10.1016/j.ejps.2021.105986. Online ahead of print.

ABSTRACT

BACKGROUND: Efavirenz is a vital component used to treat HIV-1 infection. Nevertheless, it shows large between-subject variability, which affects both its therapeutic response and adverse effects.

OBJECTIVE: To investigate the impact of gene polymorphisms and non-genetic factors on the variability of efavirenz pharmacokinetics and to propose the optimal dose regimens.

METHODS: A total of 769 plasma samples from 376 HIV-infected Han Chinese outpatients were collected to develop a population pharmacokinetic model using NONMEM software. The impact of patient demographics, laboratory tests, concomitant medication, and genetic polymorphisms of CYP2B6 and ABCB1 on efavirenz pharmacokinetics were explored. According to the final model, the model-informed dose optimization was conducted.

RESULTS: The pharmacokinetics of efavirenz was characterized by a one-compartment model with first-order absorption and elimination. The typical values of the estimated apparent oral clearance, volume of distribution, and absorption rate constant in the final model were 9.44 L/h, 200 L, and 0.727 h-1, respectively. Efavirenz clearance was significantly influenced by CYP2B6 variants, including rs2099361, rs3745274, and rs2279343, along with albumin and weight. The volume of distribution was affected by albumin and weight. Based on the CYP2B6 polymorphisms of patients, the recommended daily doses of efavirenz were 100 mg for CYP2B6 slow metabolizers, 400 or 600 mg for intermediate metabolizers, and 800 or 1000 mg for extensive metabolizers.

CONCLUSIONS: Polymorphisms of CYP2B6, along with albumin and weight, resulted as the predictors of efavirenz pharmacokinetic variability, which could be used in prescribing optimal efavirenz doses.

PMID:34474119 | DOI:10.1016/j.ejps.2021.105986

J Crohns Colitis. 2021 Sep 2:jjab153. doi: 10.1093/ecco-jcc/jjab153. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Infliximab attenuates serological responses to SARS-CoV-2 infection. Whether this is a class effect, or if anti-TNF level influences serological responses, remains unknown.

METHODS: Seroprevalence and the magnitude of SARS-CoV-2 nucleocapsid antibody responses were measured in surplus serum from 11422 (53.3% (6084) male; median age 36.8 years) patients with immune-mediated inflammatory diseases, stored at six therapeutic drug monitoring laboratories between 29 th January and 30 th September 2020. Data were linked to nationally-held SARS-CoV-2 PCR results to 4 th May 2021.

RESULTS: Rates of PCR confirmed SARS-CoV-2 infection were similar across treatment groups. Seroprevalence rates were lower in infliximab- and adalimumab- than vedolizumab-treated patients (infliximab: 3.0% (178/5893), adalimumab: 3.0% (152/5074), vedolizumab: 6.7% (25/375), p = 0.003). The magnitude of SARS-CoV-2 reactivity was similar in infliximab- vs adalimumab-treated patients (median 4.30 cut-off index (COI) (1.94 - 9.96) vs 5.02 (2.18 - 18.70), p = 0.164), but higher in vedolizumab-treated patients (median 21.60 COI (4.39 - 68.10, p< 0.004). Compared to patients with detectable infliximab and adalimumab drug levels, patients with undetectable drug levels (<0.8 mg/L) were more likely to be seropositive for SARS-CoV-2 antibodies. One-third of patients who had PCR testing prior to antibody testing failed to seroconvert, all were anti-TNF treated. Subsequent positive PCR-confirmed SARS-CoV-2 was seen in 7.9% (12/152) patients after a median time of 183.5 days (129.8 - 235.3), without differences between drugs.

CONCLUSION: Anti-TNF treatment is associated with lower SARS-CoV-2 nucleocapsid seroprevalence and antibody reactivity when compared to vedolizumab-treated patients. Higher seropositivity rates in patients with undetectable anti-TNF levels supports a causal relationship, although confounding factors, such as combination therapy with immunomodulator, may have influenced the results.

PMID:34473254 | DOI:10.1093/ecco-jcc/jjab153

SAGE Open Med. 2021 Aug 26;9:20503121211042209. doi: 10.1177/20503121211042209. eCollection 2021.

ABSTRACT

INTRODUCTION: Antithrombotic agents are the basic therapeutic option for patients with arterial thrombosis who underwent percutaneous coronary intervention (PCI). In Bangladesh, aspirin and clopidogrel are frequently prescribed as antithrombotics or platelet inhibitors. Studies reported the genetic polymorphisms of CYP2C19*2, CYP2C19*17, and ITGB3 cause an alteration of the pharmacodynamic and pharmacokinetic profile of aspirin and clopidogrel. Therefore, we aimed to assess the prevalence of CYP2C19*2, CYP2C19*17, and ITGB3 polymorphisms among Bangladeshi patients with cardiovascular disease (CVD) who underwent PCI.

METHODS: Here we assessed a total of 1,000 CVD patients (male 782 and female 218) who underwent PCI and were treated with clopidogrel and/or aspirin. We performed genotyping of patients treated with clopidogrel and aspirin by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and tetra-primer amplification refractory mutation system PCR (T-ARMS-PCR) methods. The PCR products of clopidogrel-treated patients were screened with agarose gel electrophoresis and then digested with SmaI and NsiI-HF for CYP2C19*2 and CYP2C19*17, respectively. We genotyped aspirin-treated patients with T-ARMS-PCR for missense rs5918 (PlA1/A1) polymorphism of the ITGB3 gene. Then we ran the digested PCR products on 2% agarose gel electrophoresis to detect the mentioned polymorphisms.

RESULTS: Among the clopidogrel-treated patients, we observed 64.1% polymorphism (hetero + mutant) of CYP2C19*2 (loss-of-function allele) and 22.7% (hetero + mutant) of CYP2C19*17 (gain-of-function allele). On the other hand, among the aspirin-treated patients, polymorphisms of ITGB3 were 84.1% homozygous (PlA1/A1), 15.6% heterozygous (PlA1/A2), and 0.3% mutant homozygous.

CONCLUSION: In the present study, we observed a high prevalence of genetic polymorphisms of CYP2C19 and ITGB3 genes. Therefore, we recommend genotyping of CVD patients before prescribing clopidogrel or aspirin to prevent coagulation. Based on the genotyping study, the adjustment of doses or alternative generics might require to avoid therapeutic failure or toxicity in some cases.

PMID:34471538 | PMC:PMC8404630 | DOI:10.1177/20503121211042209

Comput Struct Biotechnol J. 2021 Aug 10;19:4435-4446. doi: 10.1016/j.csbj.2021.08.007. eCollection 2021.

ABSTRACT

Poly (ADPribose) polymerase inhibitors (PARPis) are clinically approved drugs designed according to the concept of synthetic lethality (SL) interaction. It is crucial to expand the scale of patients who can benefit from PARPis, and overcome drug resistance associated with it. Genetic interactions (GIs) include SL and synthetic viability (SV) that participate in drug response in cancer cells. Based on the hypothesis that mutated genes with SL or SV interactions with PARP1/2/3 are potential sensitive or resistant PARPis biomarkers, respectively, we developed a novel computational method to identify them. We analyzed fitness variation of cell lines to identify PARP1/2/3-related GIs according to CRISPR/Cas9 and RNA interference functional screens. Potential resistant/sensitive mutated genes were identified using pharmacogenomic datasets. We identified 41 candidate resistant and 130 candidate sensitive PARPi-response related genes, and observed that EGFR with gain-of-function mutation induced PARPi resistance, and predicted a combination therapy with PARP inhibitor (veliparib) and EGFR inhibitor (erlotinib) for lung cancer. We also revealed that a resistant gene set (TNN, PLEC, and TRIP12) in lower grade glioma and a sensitive gene set (BRCA2, TOP3A, and ASCC3) in ovarian cancer, which were associated with prognosis. Thus, cancer genome-derived GIs provide new insights for identifying PARPi biomarkers and a new avenue for precision therapeutics.

PMID:34471490 | PMC:PMC8379270 | DOI:10.1016/j.csbj.2021.08.007

Genome Med. 2021 Sep 1;13(1):142. doi: 10.1186/s13073-021-00955-2.

ABSTRACT

BACKGROUND: Colorectal cancer is the 2nd leading cause of cancer-related deaths with few patients benefiting from biomarker-guided therapy. Mutation expression is essential for accurate interpretation of mutations as biomarkers, but surprisingly, little has been done to analyze somatic cancer mutations on the expression level. We report a large-scale analysis of allele-specific mutation expression.

METHODS: Whole-exome and total RNA sequencing was performed on 137 samples from 121 microsatellite stable colorectal cancers, including multiregional samples of primary and metastatic tumors from 4 patients. Data were integrated with allele-specific resolution. Results were validated in an independent set of 241 colon cancers. Therapeutic associations were explored by pharmacogenomic profiling of 15 cell lines or patient-derived organoids.

RESULTS: The median proportion of expressed mutations per tumor was 34%. Cancer-critical mutations had the highest expression frequency (gene-wise mean of 58%), independent of frequent allelic imbalance. Systematic deviation from the general pattern of expression levels according to allelic frequencies was detected, including preferential expression of mutated alleles dependent on the mutation type and target gene. Translational relevance was suggested by correlations of KRAS/NRAS or TP53 mutation expression levels with downstream oncogenic signatures (p < 0.03), overall survival among patients with stage II and III cancer (KRAS/NRAS: hazard ratio 6.1, p = 0.0070), and targeted drug sensitivity. The latter was demonstrated for EGFR and MDM2 inhibition in pre-clinical models.

CONCLUSIONS: Only a subset of mutations in microsatellite stable colorectal cancers were expressed, and the "expressed mutation dose" may provide an opportunity for more fine-tuned biomarker interpretations.

PMID:34470667 | DOI:10.1186/s13073-021-00955-2

Pharmacogenomics. 2021 Sep 1. doi: 10.2217/pgs-2021-0032. Online ahead of print.

ABSTRACT

The application of pharmacogenomics could meaningfully contribute toward medicines optimization within primary care. This review identified 13 studies describing eight implementation models utilizing a multi-gene pharmacogenomic panel within a primary care or community setting. These were small feasibility studies (n <200). They demonstrated importance and feasibility of pre-test counseling, the role of the pharmacist, data integration into the electronic medical record and point-of-care clinical decision support systems (CDSS). Findings were considered alongside existing primary care prescribing practices and implementation frameworks to demonstrate how issues may be addressed by existing nationalized healthcare and primary care infrastructure. Development of point-of-care CDSS should be prioritized; establishing clinical leadership, education programs, defining practitioner roles and responsibilities and addressing commissioning issues will also be crucial.

PMID:34467776 | DOI:10.2217/pgs-2021-0032

Cell Rep Med. 2021 Aug 17;2(8):100373. doi: 10.1016/j.xcrm.2021.100373. eCollection 2021 Aug 17.

ABSTRACT

Functional profiling of a cancer patient's tumor cells holds potential to tailor personalized cancer treatment. Here, we report the utility of fresh uncultured tumor-derived EpCAM+ epithelial cells (FUTCs) for ex vivo drug-response interrogation. Analysis of murine Kras mutant FUTCs demonstrates pharmacological and adaptive signaling profiles comparable to subtype-matched cultured cells. By applying FUTC profiling on non-small-cell lung cancer patient samples, we report robust drug-response data in 19 of 20 cases, with cells exhibiting targeted drug sensitivities corresponding to their oncogenic drivers. In one of these cases, an EGFR mutant lung adenocarcinoma patient refractory to osimertinib, FUTC profiling is used to guide compassionate treatment. FUTC profiling identifies selective sensitivity to disulfiram and the combination of carboplatin plus etoposide, and the patient receives substantial clinical benefit from treatment with these agents. We conclude that FUTC profiling provides a robust, rapid, and actionable assessment of personalized cancer treatment options.

PMID:34467250 | PMC:PMC8385325 | DOI:10.1016/j.xcrm.2021.100373

Clin Pharmacol Ther. 2021 Aug 31. doi: 10.1002/cpt.2408. Online ahead of print.

ABSTRACT

In patients with treatment-resistant epilepsy (TRE), cannabidiol (CBD) produces variable improvement in seizure control. Patients in the University of Alabama at Birmingham CBD Expanded Access Program (EAP) were enrolled in the genomic study and genotyped using the Affymetrix Drug Metabolizing Enzymes and Transporters plus array. Associations between variants and CBD response (≥50% seizure reduction) and tolerability (diarrhea, sedation, abnormal liver function) was evaluated under dominant and recessive models. Expression quantitative trait loci (eQTL) influencing potential CBD targets was evaluated in Braineac, and genetic co-expression examined. Of 169 EAP patients, 112 (54.5% pediatric; 50.0% female) were included in the genetic analyses. Patients with AOX1 rs6729738 CC (aldehyde oxidase; OR 6.69, 95%CI 2.19-20.41; p=0.001) or ABP1 rs12539 (diamine oxidase; OR 3.96, 95%CI 1.62-9.73; p=0.002) were more likely to respond. Conversely, patients with SLC15A1 rs1339067 TT had lower odds of response (OR 0.06, 95%CI 0.01-0.56; p=0.001). ABCC5 rs3749442 was associated with lower likelihood of response and abnormal LFTs, and higher likelihood of sedation. EQTL revealed that rs1339067 decreased GPR18 expression (endocannabinoid receptor) in white matter (p=5.6x10-3 ), and rs3749442 decreased hippocampal HTR3E expression (serotonin 5-HT3E ; p=8.5x10-5 ). Furthermore, 75% of genes associated with lower likelihood of response were co-expressed. Pharmacogenetic variation is associated with CBD response and influences expression of CBD targets in TRE. Implicated pathways, including cholesterol metabolism and glutathione conjugation, demonstrate potential interactions between CBD and common medications (e.g. statins, acetaminophen) that may require closer monitoring. These results highlight the role of pharmacogenes in fundamental biologic processes and potential genetic underpinnings of treatment-resistance.

PMID:34464454 | DOI:10.1002/cpt.2408

Eur Heart J Cardiovasc Pharmacother. 2021 Aug 31:pvab063. doi: 10.1093/ehjcvp/pvab063. Online ahead of print.

ABSTRACT

Pharmacogenomics promises to advance cardiovascular therapy, but there remain pragmatic barriers to implementation. These are particularly important to explore within Europe, as there are differences in the populations, availability of resources and expertise, as well as in ethico-legal frameworks. Differences in healthcare delivery across Europe present a challenge, but also opportunities to collaborate on PGx implementation. Clinical work force upskilling is already in progress but will require substantial input. Digital infrastructure and clinical support tools are likely to prove crucial. It is important that widespread implementation serves to narrow rather than widen any existing gaps in health equality between populations. This viewpoint supplements the working group position paper on cardiovascular pharmacogenomics to address these important themes.

PMID:34463331 | DOI:10.1093/ehjcvp/pvab063