A systematic review and meta-analysis of the impacts of germline pharmacogenomics on severe toxicity and symptom burden in adult patients with cancer.

The clinical application of Pharmacogenomics (PGx) has improved patient safety. However, comprehensive PGx testing has not been widely adopted in clinical practice, and significant opportunities exist to further optimize PGx in cancer care. This systematic review and meta-analysis aim to evaluate the safety outcomes of reported PGx-guided strategies (Analysis 1) and identify well-studied emerging pharmacogenomic variants that predict severe toxicity and symptom burden (Analysis 2) in patients with cancer. We searched MEDLINE, EMBASE, CENTRAL, clinicaltrials.gov, and International Clinical Trials Registry Platform from inception to January 2023 for clinical trials or comparative studies evaluating PGx strategies or unconfirmed pharmacogenomic variants. The primary outcomes were severe adverse events (SAE; ≥ grade 3) or symptom burden with pain and vomiting as defined by trial protocols and assessed by trial investigators. We calculated pooled overall relative risk (RR) and 95% confidence interval (95%CI) using random effects models. PROSPERO, registration number CRD42023421277. Of 6811 records screened, six studies were included for Analysis 1, 55 studies for Analysis 2. Meta-analysis 1 (five trials, 1892 participants) showed a lower absolute incidence of SAEs with PGx-guided strategies compared to usual therapy, 16.1% versus 34.0% (RR = 0.72, 95%CI 0.57-0.91, p = 0.006, I2 = 34%). Meta-analyses 2 identified nine medicine(class)-variant pairs of interest across the TYMS, ABCB1, UGT1A1, HLA-DRB1, and OPRM1 genes. Application of PGx significantly reduced rates of SAEs in patients with cancer. Emergent medicine-variant pairs herald further research into the expansion and optimization of PGx to improve systemic anti-cancer and supportive care medicine safety and efficacy.

Influence of pharmacogenomic polymorphisms on allopurinol-induced cutaneous adverse drug reactions in Thai patients.

BACKGROUND: Allopurinol has been causing substantial morbidity and mortality particularly in Asian population by producing cutaneous adverse drug reactions (cADRs). Nonetheless, there are no data describing whether other genetics are a valid marker for prediction of allopurinol-induced cADRs patients in addition to HLA-B*58:01 allele. The goal of this study was to identify suitable single nucleotide polymorphisms (SNPs) for allopurinol induced cADRs among Thai patients. METHODS: We conducted a case-control association study after enrolling 57 Thai patients with allopurinol induced cADRs and 101 allopurinol-tolerant controls. The genetic biomarkers and associated SNPs located on chromosome 6p21 were examined by TaqMan® SNP genotyping assays in both the cases and the controls. RESULTS: Out of fifteen SNPs in nine genes, we found four combined SNPs (rs3099844 of HCP5, rs9263726 of PSORS1C1, rs9263733 of POLR2LP, and rs9263745 of CCHCR1) were significantly associated with allopurinol-induced cADRs compared to the tolerant controls (OR 73.2; 95% CI 24.2-266.8; P = 1.9 × 10- 24). The overall sensitivity, specificity, positive predictive value and negative predictive value of these combinations were 84%, 94%, 9%, and 100%, respectively. However, the variant alleles of these SNP combinations were detected in 89.5% (51/57) of the cases. Moreover, the HLA-B*58:01 allele was observed in 86.0% of patients with allopurinol-induced cADRs, but only in 4.0% of tolerant controls (OR: 137.2; 95% CI: 38.3-670.5 and p-value = 1.7 × 10- 27). CONCLUSIONS: Thus, this research confirms the association between the specific HLA-B*58:01 allele and all phenotypes of allopurinol-induced cADRs in Thais. Furthermore, there was found the combined four SNPs (rs3099844, rs9263726, rs9263733, and rs9263745) could be used as alternative novel biomarkers for predicting cADRs in patients taking allopurinol.

Genome-Wide Association Study of Atorvastatin Pharmacokinetics: Associations With SLCO1B1, UGT1A3, and LPP.

In a genome-wide association study of atorvastatin pharmacokinetics in 158 healthy volunteers, the SLCO1B1 c.521T>C (rs4149056) variant associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC0-∞) of atorvastatin (P = 1.2 × 10-10), 2-hydroxy atorvastatin (P = 4.0 × 10-8), and 4-hydroxy atorvastatin (P = 2.9 × 10-8). An intronic LPP variant, rs1975991, associated with reduced atorvastatin lactone AUC0-∞ (P = 3.8 × 10-8). Three UGT1A variants linked with UGT1A3*2 associated with increased 2-hydroxy atorvastatin lactone AUC0-∞ (P = 3.9 × 10-8). Furthermore, a candidate gene analysis including 243 participants suggested that increased function SLCO1B1 variants and decreased activity CYP3A4 variants affect atorvastatin pharmacokinetics. Compared with individuals with normal function SLCO1B1 genotype, atorvastatin AUC0-∞ was 145% (90% confidence interval: 98-203%; P = 5.6 × 10-11) larger in individuals with poor function, 24% (9-41%; P = 0.0053) larger in those with decreased function, and 41% (16-59%; P = 0.016) smaller in those with highly increased function SLCO1B1 genotype. Individuals with intermediate metabolizer CYP3A4 genotype (CYP3A4*2 or CYP3A4*22 heterozygotes) had 33% (14-55%; P = 0.022) larger atorvastatin AUC0-∞ than those with normal metabolizer genotype. UGT1A3*2 heterozygotes had 16% (5-25%; P = 0.017) smaller and LPP rs1975991 homozygotes had 34% (22-44%; P = 4.8 × 10-5) smaller atorvastatin AUC0-∞ than noncarriers. These data demonstrate that genetic variation in SLCO1B1, UGT1A3, LPP, and CYP3A4 affects atorvastatin pharmacokinetics. This is the first study to suggest that LPP rs1975991 may reduce atorvastatin exposure. [Correction added on 6 April, after first online publication: An incomplete sentence ("= 0.017) smaller in heterozygotes for UGT1A3*2 and 34% (22%, 44%; P × 10-5) smaller in homozygotes for LPP noncarriers.") has been corrected in this version.].

Factors associated with clopidogrel resistance and clinical outcomes in ischemic cerebrovascular disease: A retrospective study.

OBJECTIVE: Clopidogrel resistance may lead to the recurrence of cerebrovascular diseases. We aimed to identify potential factors associated with clopidogrel resistance and evaluate the clinical outcomes of the patients. MATERIALS AND METHODS: In this retrospective study, patients with ischemic cerebrovascular disease treated with clopidogrel were included and classified into 2 groups according to the adenosine diphosphate (ADP)-induced platelet aggregation. Patients with the ADP inhibition rate of <30 % were included in clopidogrel resistance group, otherwise were included in clopidogrel sensitive group. CYP2C19 genotype and other clinical data were analyzed to identify factors and clinical features in the multivariate analysis. The outcomes were vascular events in 6 months. RESULTS: In total, 139 patients were enrolled with 81 (58.27 %) in clopidogrel sensitive group and 58 (41.73 %) in clopidogrel resistance group. Female and CYP2C19 *2*3 carrying were risk factors for clopidogrel resistance, and female was an independent risk factor (OR 2.481, 95 % CI 1.066-5.771, P=0.035). The clopidogrel resistance group showed a higher use rate of argatroban (P=0.030) and a lower arachidonic acid-induced inhibition of platelet aggregation (P=0.036). Clopidogrel resistance was related to the progressing stroke (HR 3.521, 95 % CI 1.352-9.170, P=0.010), but had no influence on the bleeding events (P>0.05). CONCLUSIONS: The risk of clopidogrel resistance increased significantly in female patients. Patients with clopidogrel resistance may have an increased incidence of stroke progression in the acute phase.

The landscape of very important pharmacogenes variants and potential clinical relevance in the Chinese Jingpo population: a comparative study with worldwide populations.

BACKGROUND: Pharmacogenomics is a facet of personalized medicine that explores how genetic variants affect drug metabolism and adverse drug reactions. Therefore, this study aims to detect distinct pharmacogenomic variations among the Jingpo population and explore their clinical correlation with drug metabolism and toxicity. METHODS: Agena MassARRAY Assay was used to genotype 57 VIP variants in 28 genes from 159 unrelated Jingpo participants. Subsequently, the chi-squared test and Bonferroni's statistical tests were utilized to conduct a comparative analysis of genotypes and allele frequencies between the Jingpo population and the other 26 populations from the 1000 Genome Project. RESULTS: We discovered that the KHV (Kinh in Ho ChiMinh City, Vietnam), CHS (Southern Han Chi-nese, China) and JPT (Japanese in Tokyo, Japan) exhibited the smallest differences from the Jingpo with only 4 variants, while ESN (Esan in Nigeria) exhibited the largest differences with 30 variants. Besides, a total of six considerably different loci (rs4291 in ACE, rs20417 in PTGS2, rs1801280 and rs1799929 in NAT2, rs2115819 in ALOX5, rs1065852 in CYP2D6, p < 3.37 × 10-5) were identified in this study. According to PharmGKB, rs20417 (PTGS2), rs4291 (ACE), rs2115819 (ALOX5) and rs1065852 (CYP2D6) were found to be associated with the metabolism efficiency of non-steroidal anti-inflammatory drugs (NSAIDs), aspirin, montelukast and tamoxifen, respectively. Meanwhile, rs1801280 and rs1799929 (NAT2) were found to be related to drug poisoning with slow acetylation. CONCLUSION: Our study unveils distinct pharmacogenomic variants in the Jingpo population and discovers their association with the metabolic efficiency of NSAIDs, montelukast, and tamoxifen.

Attempted replication of pharmacogenetic association of variants in PPP1R14C and CCDC148 with aromatase inhibitor-induced musculoskeletal symptoms.

Third-generation aromatase inhibitors (AI) are the standard treatment for patients with hormone receptor positive (HR+) breast cancer. While effective, AI can lead to severe adverse events, including AI-induced musculoskeletal syndrome (AIMSS). Genetic predictors of AIMSS have the potential to personalize AI treatment and improve outcomes. We attempted to replicate results from a previous genome-wide association study that found a lower risk of AIMSS in patients carrying PPP1R14C rs912571 and a higher risk in patients carrying CCDC148 rs79048288. AIMSS data were collected prospectively from patients with HR+ breast cancer prior to starting and after 3 and 6 months of adjuvant AI via the Patient-Reported Outcome Measurement Information System and Functional Assessment of Cancer Therapy-Endocrine Symptom. Germline genotypes for PPP1R14C rs912571 and CCDC148 rs79048288 were tested for a similar association with AIMSS as previously reported via $2 tests. Of the 143 patients with AIMSS and genetics data were included in the analysis. There was no association identified between PPP1R14C rs912571 and AIMSS risk ( P  > 0.05). Patients carrying CCDC148 rs79048288 variant alleles had lower AIMSS incidence in a secondary analysis ( P  = 0.04); however, this was in the opposite direction of the previous finding. The study did not replicate previously reported associations with AIMSS risk for genetic variants in PPP1R14C and CCDC148 and AIMSS risk. Further research is needed to discover and validate genetic predictors of AIMSS that can be used to personalize treatment in patients with HR+ breast cancer.

Pharmacogenomic variants affecting efficacy and toxicity of statins in a south Asian population from Sri Lanka.

Aim: To describe the diversity of pharmacogenetic variants of statins among Sri Lankans. Materials & methods: Variant data of relevant genes were obtained from an anonymized database of 426 Sri Lankans. Minor allele frequencies (MAFs) were compared with published data from other populations. Results: The MAF of SLCO1B1*5 (rs4149056 [T>C]) was 18.19% (95% CI: 14.53-21.85). MAFs of CYP2C9*2 (rs1799853 [C>T]) and CYP2C9*3 (rs1057910 [A>C]) were 2.58% (95% CI: 1.08-4.08) and 10.30% (95% CI: 7.75-13.61), respectively. MAFs of rs2231142 (G>T) (ABCG2), rs7412 (C>T) (APOE) and rs20455 (A>G) (KIF6) variants were 10.68% (95% CI: 7.76-13.60), 3.52% (95% CI: 1.77-5.27) and 50.7% (95% CI: 45.96-55.45), respectively. Compared with western/other Asian populations, rs20455 (A>G), CYP2C9*3 (A>C) and SLCO1B1*5 (T>C) variants were significantly higher in Sri Lankans. Conclusion: Variants that affect efficacy of statins (KIF6 [rs20455], CYP2C9*3) and increase risk of statin-induced myotoxicity (SLCO1B1*5 and CYP2C9*3) were prevalent in higher frequencies among Sri Lankans compared with western populations.

Can Pharmacogenetic Variants in TPMT, MTHFR and SLCO1B1 Genes Be Used as Potential Markers of Outcome Prediction in Systemic Sclerosis Patients?

Systemic sclerosis (SSc) is a rare connective tissue disorder with highest morbidity and mortality among rheumatologic diseases. Disease progression is highly heterogeneous between patients, implying a strong need for individualization of therapy. Four pharmacogenetic variants, namely TPMT rs1800460, TPMT rs1142345, MTHFR rs1801133 and SLCO1B1 rs4149056 were tested for association with severe disease outcomes in 102 patients with SSc from Serbia treated either with immunosuppressants azathioprine (AZA) and methotrexate (MTX) or with other types of medications. Genotyping was performed using PCR-RFLP and direct Sanger sequencing. R software was used for statistical analysis and development of polygenic risk score (PRS) model. Association was found between MTHFR rs1801133 and higher risk for elevated systolic pressure in all patients except those prescribed with MTX, and higher risk for kidney insufficiency in patients prescribed with other types of drugs. In patients treated with MTX, variant SLCO1B1 rs4149056 was protective against kidney insufficiency. For patients receiving MTX a trend was shown for having a higher PRS rank and elevated systolic pressure. Our results open a door wide for more extensive research on pharmacogenomics markers in patients with SSc. Altogether, pharmacogenomics markers could predict the outcome of patients with SSc and help in prevention of adverse drug reactions.

Profiling of pharmacogenomic variants in CYP2D6 and DPYD in indigenous Arab breast cancer patients.

Aim: The indigenous Arab population is underrepresented in genomic studies and the landscape of actionable pharmacogenomic variants among Arab breast cancer patients remains unclear. Materials & methods: Exome sequencing was performed on 220 unselected Arab female breast cancer patients and germline variants in CYP2D6 and DPYD were profiled using a deep learning method. Results: In total, 13 (5.9%) patients had clinically actionable results and 56 (25.5%) carried an allele in DYPD or CYP2D6 with unknown impact on drug metabolism. In addition, four unique novel missense variants were discovered, including one in CYP2D6 (p.Arg64Leu) with high predicted pathogenicity. Conclusion: A nontrivial subset of Arab breast cancer patients can potentially benefit from pretreatment molecular profiling, and further study is needed to improve characterization of the pharmacogenomic landscape.

DPYD genotyping and predicting fluoropyrimidine toxicity: where do we stand?

Fluoropyrimidines (FPs) are antineoplastic drugs widely used in the treatment of various solid tumors. Nearly 30% of patients treated with FP chemotherapy experience severe FP-related toxicity, and in some cases, toxicity can be fatal. Patients with reduced activity of DPD, the main enzyme responsible for the breakdown of FP, are at an increased risk of experiencing severe FP-related toxicity. While European regulatory agencies and clinical societies recommend pre-treatment DPD deficiency screening for patients starting treatment with FPs, this is not the case with American ones. Pharmacogenomic guidelines issued by several pharmacogenetic organizations worldwide recommend testing four DPD gene (DPYD) risk variants, but these can predict only a proportion of toxicity cases. New evidence on additional common DPYD polymorphisms, as well as identification and functional characterization of rare DPYD variants, could partially address the missing heritability of DPD deficiency and FP-related toxicity.

Pharmacogenetic variants and risk of remdesivir-associated liver enzyme elevations in Million Veteran Program participants hospitalized with COVID-19.

Remdesivir is the first US Food and Drug Administration (FDA)-approved drug for the treatment of coronavirus disease 2019 (COVID-19). We conducted a retrospective pharmacogenetic study to examine remdesivir-associated liver enzyme elevation among Million Veteran Program participants hospitalized with COVID-19 between March 15, 2020, and June 30, 2021. Pharmacogene phenotypes were assigned using Stargazer. Linear regression was performed on peak log-transformed enzyme values, stratified by population, adjusted for age, sex, baseline liver enzymes, comorbidities, and 10 population-specific principal components. Patients on remdesivir had higher peak alanine aminotransferase (ALT) values following treatment initiation compared with patients not receiving remdesivir. Remdesivir administration was associated with a 33% and 24% higher peak ALT in non-Hispanic White (NHW) and non-Hispanic Black (NHB) participants (p < 0.001), respectively. In a multivariable model, NHW CYP2C19 intermediate/poor metabolizers had a 9% increased peak ALT compared with NHW normal/rapid/ultrarapid metabolizers (p = 0.015); this association was not observed in NHB participants. In summary, remdesivir-associated ALT elevations appear to be multifactorial, and further studies are needed.

Implementation of CYP2D6 copy-number imputation panel and frequency of key pharmacogenetic variants in Finnish individuals with a psychotic disorder.

We demonstrate that CYP2D6 copy-number variation (CNV) can be imputed using existing imputation algorithms. Additionally, we report frequencies of key pharmacogenetic variants in individuals with a psychotic disorder from the genetically bottle-necked population of Finland. We combined GWAS chip and CYP2D6 CNV data from the Breast Cancer Pain Genetics study to construct an imputation panel (n = 902) for CYP2D6 CNV. The resulting data set was used as a CYP2D6 CNV imputation panel in 9262 non-related individuals from the SUPER-Finland study. Based on imputation of 9262 individuals we confirm the higher frequency of CYP2D6 ultrarapid metabolizers and a 22-fold enrichment of the UGT1A1 decreased function variant rs4148323 (UGT1A1*6) in Finland compared with non-Finnish Europeans. Similarly, the NUDT15 variant rs116855232 was highly enriched in Finland. We demonstrate that imputation of CYP2D6 CNV is possible and the methodology enables studying CYP2D6 in large biobanks with genome-wide data.

Flat Pattern Peaks of Tacrolimus Absorption and Associated Pharmacogenomic Variants in Kidney Transplantation Recipients.

BACKGROUND: Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours. A group of patients showed different early absorption phase of tacrolimus after kidney transplantation. METHODS: Trough(C0) and 1.5-hour blood levels (C1.5) of tacrolimus were measured in 95 kidney transplantation recipients. Patients with a C1.5/C0 < 1.5 and > 1.5 were defined as those having flat pattern peaks and as controls, respectively. Transplantation outcomes were compared between the groups. Whole exome sequencing was performed to investigate the genetic susceptibility to flat pattern peaks. RESULTS: Twenty-eight patients showed flat pattern peaks. The mean C1.5/C0 values were 1.13 ± 0.22 and 3.78 ± 1.25 in the flat pattern peak and control groups, respectively. In multivariate analysis, flat pattern peak was an independent risk factor for biopsy-proven acute rejection (BPAR) and/or borderline change (P = 0.014). Patients having flat pattern peaks showed significantly lower post-transplant 36-month estimated glomerular filtration rate (P = 0.001). Two single nucleotide variants in ABCB1 genes, rs1922242 and rs2235035, were associated with flat pattern peaks (P = 0.019 and P = 0.027, respectively). CONCLUSION: Both of C1.5 and C0 should be measured to distinguish the patients showing unique initial absorption. A C1.5/C0 ratio lower than 1.5 was associated with an increased risk of BPAR and/or borderline change. Single nucleotide variants s in ABCB1 gene might influence the flat pattern peaks of tacrolimus absorption.

VEGF-A, VEGFR1 and VEGFR2 single nucleotide polymorphisms and outcomes from the AGITG MAX trial of capecitabine, bevacizumab and mitomycin C in metastatic colorectal cancer.

The phase III MAX clinical trial randomised patients with metastatic colorectal cancer (mCRC) to receive first-line capecitabine chemotherapy alone or in combination with the anti-VEGF-A antibody bevacizumab (± mitomycin C). We utilised this cohort to examine whether single nucleotide polymorphisms (SNPs) in VEGF-A, VEGFR1, and VEGFR2 are predictive of efficacy outcomes with bevacizumab or the development of hypertension. Genomic DNA extracted from archival FFPE tissue for 325 patients (69% of the MAX trial population) was used to genotype 16 candidate SNPs in VEGF-A, VEGFR1, and VEGFR2, which were analysed for associations with efficacy outcomes and hypertension. The VEGF-A rs25648 'CC' genotype was prognostic for improved PFS (HR 0.65, 95% CI 0.49 to 0.85; P = 0.002) and OS (HR 0.70, 95% CI 0.52 to 0.94; P = 0.019). The VEGF-A rs699947 'AA' genotype was prognostic for shorter PFS (HR 1.32, 95% CI 1.002 to 1.74; P = 0.048). None of the analysed SNPs were predictive of bevacizumab efficacy outcomes. VEGFR2 rs11133360 'TT' was associated with a lower risk of grade ≥ 3 hypertension (P = 0.028). SNPs in VEGF-A, VEGFR1 and VEGFR2 did not predict bevacizumab benefit. However, VEGF-A rs25648 and rs699947 were identified as novel prognostic biomarkers and VEGFR2 rs11133360 was associated with less grade ≥ 3 hypertension.

Fatigue in breast cancer patients on chemotherapy: a cross-sectional study exploring clinical, biological, and genetic factors.

BACKGROUND: Cancer-related fatigue (CRF) is one of the most common and distressing complaints reported by cancer patients during chemotherapy considerably impacting all aspects of a patient's life (physical, psychosocial, professional, and socioeconomic). The aim of this study was to assess the severity of cancer-related fatigue in a group of breast cancer patients undergoing chemotherapy and explore the association between fatigue scores and sociodemographic, clinical, biological, psychiatric, and genetic factors. METHODS: A cross-sectional pilot study carried out at the oncology outpatient unit of Hôtel-Dieu de France University Hospital recruited 67 breast cancer patients undergoing chemotherapy between November 2017 and June 2019 to evaluate fatigue using the EORTC QLQ-C30 scale (European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire). Genotyping for seven gene polymorphisms (COMT, DRD2, OPRM1, CLOCK, PER2, CRY2, ABCB1) was performed using the Lightcycler® (Roche). RESULTS: The prevalence of fatigue was 46.3%. Multivariable analysis taking the fatigue score as the dependent variable showed that a higher number of cycles and a lower hemoglobin level were significantly associated with higher odds of exhibiting fatigue. Moreover, having at least one C allele for DRD2 SNP (vs. TT) was significantly associated with a 4.09 higher odds of expressing fatigue compared to TT patients. Finally, patients with at least one C allele for CLOCK SNP tended to display higher fatigue levels than TT patients. CONCLUSIONS: Our study showed that anemic breast cancer patients with a high number of chemotherapy cycles and those carrying at least one C allele for DRD2 and CLOCK SNPs are at greater risk of exhibiting fatigue. Since no previous research has reported such genetic results, future studies are necessary to confirm our findings.

Prognostic gene expression analysis in a retrospective, multinational cohort of 155 multiple myeloma patients treated outside clinical trials.

OBJECTIVES: Typically, prognostic capability of gene expression profiling (GEP) is studied in the context of clinical trials, for which 50%-80% of patients are not eligible, possibly limiting the generalizability of findings to routine practice. Here, we evaluate GEP analysis outside clinical trials, aiming to improve clinical risk assessment of multiple myeloma (MM) patients. METHODS: A total of 155 bone marrow samples from MM patients were collected from which RNA was analyzed by microarray. Sixteen previously developed GEP-based markers were evaluated, combined with survival data, and studied using Cox proportional hazard regression. RESULTS: Gene expression profiling-based markers SKY92 and the PR-cluster were shown to be independent prognostic factors for survival, with hazard ratios and 95% confidence interval of 3.6 [2.0-6.8] (P < .001) and 5.8 [2.7-12.7] (P < .01) for overall survival (OS). A multivariate model proved only SKY92 and the PR-cluster to be independent prognostic factors compared to cytogenetic high-risk patients, the International Staging System (ISS), and revised ISS. A substantial number of high-risk individuals could be further identified when SKY92 was added to the cytogenetic, ISS, or R-ISS. In the cytogenetic standard-risk group, ISS I/II, and R-ISS I/II, 13%, 23%, and 23% of patients with adverse survivals were identified. CONCLUSIONS: For the first time, this study confirmed the prognostic value of GEP markers outside clinical trials. Conventional prognostic models to define high-risk MM are improved by the incorporation of GEP markers.

The reference liver-CYP450 and UGT enzymes in healthy donor and metastatic livers: the impact of genotype.

BACKGROUND: Hepatic enzymes involved in drug metabolism vary markedly in expression, abundance and activity, which affects individual susceptibility to drugs and toxicants. The present study aimed to compare mRNA expression and protein abundance of the most pharmacologically relevant drug-metabolizing enzymes in two main sources of the control liver samples that are used as the reference, i.e. organ donor livers and non-tumorous tissue from metastatic livers. An association analysis of the most common genetic variants with mRNA and protein levels was also performed. METHODS: The CYP450 and UGT enzymes (CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, UGT1A1, UGT1A3, UGT2B7 and UGT2B15) were analyzed for mRNA (qPCR) and protein abundance (LC-MS/MS) in healthy donors (n = 11) and metastatic (n = 13) livers. Genotyping was performed by means of TaqMan assays and pyrosequencing. RESULTS: Significantly higher protein abundance in the metastatic livers was observed in case of CYP2C9, CYP2D6, and UGT2B7, and for UGT1A3 the difference was only significant at mRNA level. For all the enzymes except CYP2E1 some significant correlation between mRNA and protein content was observed, and for UGT1A1 an inverse correlation with age was noted. CYP2C19, CYP3A5 and CYP2D6 were significantly affected by genotype. CONCLUSION: The selection of a control group for the study on drug-metabolizing enzymes (e.g. in pathological states) may possibly affect its conclusions on differences in mRNA and protein content. Genotyping for common functional variants of CYP450 enzymes should be performed in all studies on drug-metabolizing enzymes.

Integration of DNA sequencing with population pharmacokinetics to improve the prediction of irinotecan exposure in cancer patients.

BACKGROUND: Irinotecan (CPT-11) is an anticancer agent widely used to treat adult solid tumours. Large interindividual variability in the clearance of irinotecan and SN-38, its active and toxic metabolite, results in highly unpredictable toxicity. METHODS: In 217 cancer patients treated with intravenous irinotecan single agent or in combination, germline DNA was used to interrogate the variation in 84 genes by next-generation sequencing. A stepwise analytical framework including a population pharmacokinetic model with SNP- and gene-based testing was used to identify demographic/clinical/genetic factors that influence the clearance of irinotecan and SN-38. RESULTS: Irinotecan clearance was influenced by rs4149057 in SLCO1B1, body surface area, and co-administration of 5-fluorouracil/leucovorin/bevacizumab. SN-38 clearance was influenced by rs887829 in UGT1A1, pre-treatment total bilirubin, and EGFR rare variant burden. Within each UGT1A1 genotype group, elevated pre-treatment total bilirubin and/or presence of at least one rare variant in EGFR resulted in significantly lower SN-38 clearance. The model reduced the interindividual variability in irinotecan clearance from 38 to 34% and SN-38 clearance from 49 to 32%. CONCLUSIONS: This new model significantly reduced the interindividual variability in the clearance of irinotecan and SN-38. New genetic factors of variability in clearance have been identified.

Glutathione-S-transferase genetic polymorphism and risk of hepatotoxicity to antitubercular drugs in a North-African population: A case-control study.

INTRODUCTION: GST non-functional genotypes can lead to the accumulation of toxic intermediates, resulting in liver damage and increasing susceptibility to ATDH. AIM: To investigate the impact of GST Mu (GSTM1), GST Theta (GSTT1) null genotypes, and GST Pi (GSTP1; adenosine (A) > guanine (G), rs1695) variant allele on the development of ATDH in Tunisian patients treated with anti-tuberculosis therapy. METHODS: This was a case-control study including patients receiving anti-tuberculosis regimen. Cases (n = 23) were tuberculosis patients presenting ATDH during two months of anti-tuberculosis drug therapy. Controls (n = 30) were patients treated for tuberculosis, but presenting no ATDH. Genotyping was performed using a polymerase chain reaction-restriction fragment length polymorphism. RESULTS: No statistically significant association was observed between GSTM1 and GSTT1 homozygous null genotypes, and the risk of ATDH. A statistically significant association between GSTM1 and GSTT1 double null genotypes, and the risk of ATDH was found (p = 0.033) between cases and controls. For GSTP1, the distribution of GG homozygous mutant genotype was significantly associated with ATDH compared with the wild and the transition A to G (AA + AG) genotypes. CONCLUSION: Double deletion of GSTM1 and GSTT1 may predispose to ATDH in a Tunisian population. Moreover, GSTP1 rs1695 (A > G) genotyping can predict susceptibility to developing ATDH.

TPMT and NUDT15 Variants Predict Discontinuation of Azathioprine for Myelotoxicity in Patients with Inflammatory Disease: Real-World Clinical Results.

Azathioprine is used frequently to treat several inflammatory conditions. However, treatment is limited by adverse events-in particular, myelotoxicity. Thiopurine-S-methyltransferase (TPMT) and nudix hydrolase-15 (NUDT15) are enzymes involved in azathioprine metabolism; variants in the genes encoding these enzymes increase the risk for azathioprine myelotoxicity. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has recommended dose adjustments based on the results of TPMT and NUDT15 genotyping. However, little is known about the importance of this genetic information in routine clinical care. We hypothesized that in patients with inflammatory diseases, TPMT and NUDT15 genotype data predict the risk of discontinuing azathioprine due to myelotoxicity. This was a retrospective cohort study in 1,403 new adult azathioprine users for the management of inflammatory conditions for whom we had genetic information and clinical data. Among patients who discontinued azathioprine, we adjudicated the reason(s). Genotyping was performed using the Illumina Infinium Expanded Multi-Ethnic Genotyping Array plus custom content. We used CPIC guidelines to determine TPMT and NUDT15 metabolizer status; patients were grouped as either: (i) poor/intermediate, or (ii) normal/indeterminate metabolizers. We classified 110 patients as poor/intermediate, and 1,293 patients as normal/indeterminate metabolizers. Poor/intermediate status was associated with a higher risk for azathioprine discontinuation due to myelotoxicity compared to normal/indeterminate metabolizers (hazard ratio (HR) = 2.90, 95% confidence interval (CI): 1.58-5.31, P = 0.001). This association remained significant after adjustment for race, age at initiation, sex, primary indication, and initial daily dose of azathioprine (adjusted HR (aHR) = 2.67, 95% CI: 1.44-4.94, P = 0.002). In conclusion, TPMT and NUDT15 metabolizer status predicts discontinuation due to myelotoxicity for patients taking azathioprine for inflammatory conditions.