D-Methionine and 2-hydroxy-4-methylthiobutanoic acid i alter beta-casein, proteins and metabolites linked in milk protein synthesis in bovine mammary epithelial cells.

This study aims to determine the effects of D-methionine (D-Met) isomer and the methionine precursor 2-hydroxy-4-methylthiobutanoic acid i (HMBi) supplementation on milk protein synthesis on immortalized bovine mammary epithelial cell (MAC-T). MAC-T cells were seeded using 10-cm dishes and cultured in Dulbecco's modified Eagle's medium/F12 (DMEM/F12) basic medium. The basic medium of DMEM/F12 was replaced with the lactogenic DMEM/F12 differentiation medium when 90% of MAC-T cells reached confluency. The best dosage at 0.6 mM of D-Met and HMBi and incubation time at 72 h were used uniformly for all treatments. Each treatment was replicated six times wherein treatments were randomly assigned in a 6-well plate. Cell, medium, and total protein were determined using a bicinchoninic acid protein assay kit. Genes, proteomics and metabolomics analyses were also done to determine the mechanism of the milk protein synthesis pathway. Data were analyzed by two-way analysis of variance (ANOVA) with supplement type and plate as fixed effects. The least significant difference test was used to evaluate the differences among treatments. The HMBi treatment group had the highest beta-casein and S6 kinase beta-1 (S6K1) mRNA gene expression levels. HMBi and D-Met treatments have higher gene expressions compared to the control group. In terms of medium protein content, HMBi had a higher medium protein quantity than the control although not significantly different from the D-Met group. HMBi supplementation stimulated the production of eukaryotic translation initiation factor 3 subunit protein essential for protein translation initiation resulting in higher medium protein synthesis in the HMBi group than in the control group. The protein pathway analysis results showed that the D-Met group stimulated fructose-galactose metabolism, glycolysis pathway, phosphoinositide 3 kinase, and pyruvate metabolism. The HMBi group stimulated the pentose phosphate and glycolysis pathways. Metabolite analysis revealed that the D-Met treatment group increased seven metabolites and decreased uridine monophosphate (UMP) production. HMBi supplementation increased the production of three metabolites and decreased UMP and N-acetyl-L-glutamate production. Taken together, D-Met and HMBi supplementation are effective in stimulating milk protein synthesis in MAC-T cells by genes, proteins, and metabolites stimulation linked to milk protein synthesis.

A Prognostic and Carboplatin Response Predictive Model in Ovarian Cancer: A Mono-Institutional Retrospective Study Based on Clinics and Pharmacogenomics.

Carboplatin is the cornerstone of ovarian cancer (OC) treatment, while platinum-response, dependent on interindividual variability, is the major prognostic factor for long-term outcomes. This retrospective study was focused on explorative search of genetic polymorphisms in the Absorption, Distribution, Metabolism, Excretion (ADME) genes for the identification of biomarkers prognostic/predictive of platinum-response in OC patients. Ninety-two advanced OC patients treated with carboplatin-based therapy were enrolled at our institution. Of these, we showed that 72% of patients were platinum-sensitive, with a significant benefit in terms of OS (p = 0.001). We identified an inflammatory-score with a longer OS in patients with lower scores as compared to patients with the maximum score (p = 0.001). Thirty-two patients were genotyped for 1931 single nucleotide polymorphisms (SNPs) and five copy number variations (CNVs) by the DMET Plus array platform. Among prognostic polymorphisms, we found a potential role of UGT2A1 both as a predictor of platinum-response (p = 0.01) and as prognostic of survival (p = 0.05). Finally, we identified 24 SNPs related to OS. UGT2A1 correlates to an "inflammatory-score" and retains a potential prognostic role in advanced OC. These data provide a proof of concept that warrants further validation in follow-up studies for the definition of novel biomarkers in this aggressive disease.

Risk Alleles for Multiple Myeloma Susceptibility in ADME Genes.

The cause of multiple myeloma (MM) remains largely unknown. Several pieces of evidence support the involvement of genetic and multiple environmental factors (i.e., chemical agents) in MM onset. The inter-individual variability in the bioactivation, detoxification, and clearance of chemical carcinogens such as asbestos, benzene, and pesticides might increase the MM risk. This inter-individual variability can be explained by the presence of polymorphic variants in absorption, distribution, metabolism, and excretion (ADME) genes. Despite the high relevance of this issue, few studies have focused on the inter-individual variability in ADME genes in MM risk. To identify new MM susceptibility loci, we performed an extended candidate gene approach by comparing high-throughput genotyping data of 1936 markers in 231 ADME genes on 64 MM patients and 59 controls from the CEU population. Differences in genotype and allele frequencies were validated using an internal control group of 35 non-cancer samples from the same geographic area as the patient group. We detected an association between MM risk and ADH1B rs1229984 (OR = 3.78; 95% CI, 1.18-12.13; p = 0.0282), PPARD rs6937483 (OR = 3.27; 95% CI, 1.01-10.56; p = 0.0479), SLC28A1 rs8187737 (OR = 11.33; 95% CI, 1.43-89.59; p = 0.005), SLC28A2 rs1060896 (OR = 6.58; 95% CI, 1.42-30.43; p = 0.0072), SLC29A1 rs8187630 (OR = 3.27; 95% CI, 1.01-10.56; p = 0.0479), and ALDH3A2 rs72547554 (OR = 2.46; 95% CI, 0.64-9.40; p = 0.0293). The prognostic value of these genes in MM was investigated in two public datasets showing that shorter overall survival was associated with low expression of ADH1B and SLC28A1. In conclusion, our proof-of-concept findings provide novel insights into the genetic bases of MM susceptibility.

Evaluation of pharmacogenomics and hepatic nuclear imaging-related covariates by population pharmacokinetic models of irinotecan and its metabolites.

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.

Pharmacogenomics and functional imaging to predict irinotecan pharmacokinetics and pharmacodynamics: the predict IR study.

PURPOSE: Irinotecan (IR) displays significant PK/PD variability. This study evaluated functional hepatic imaging (HNI) and extensive pharmacogenomics (PGs) to explore associations with IR PK and PD (toxicity and response). METHODS: Eligible patients (pts) suitable for Irinotecan-based therapy. At baseline: (i) PGs: blood analyzed by the Affymetrix-DMET™-Plus-Array (1936 variants: 1931 single nucleotide polymorphisms [SNPs] and 5 copy number variants in 225 genes, including 47 phase I, 80 phase II enzymes, and membrane transporters) and Sanger sequencing (variants in HNF1A, Topo-1, XRCC1, PARP1, TDP, CDC45L, NKFB1, and MTHFR), (ii) HNI: pts given IV 250 MBq-99mTc-IDA, data derived for hepatic extraction/excretion parameters (CLHNI, T1/2-HNI, 1hRET, HEF, Td1/2). In cycle 1, blood was taken for IR analysis and PK parameters were derived by non-compartmental methods. Associations were evaluated between HNI and PGs, with IR PK, toxicity, objective response rate (ORR) and progression-free survival (PFS). RESULTS: N = 31 pts. The two most significant associations between PK and PD with gene variants or HNI parameters (P < 0.05) included: (1) PK: SN38-Metabolic Ratio with CLHNI, 1hRET, (2) Grade 3+ diarrhea with SLC22A2 (rs 316019), GSTM5 (rs 1296954), (3) Grade 3+ neutropenia with CLHNI, 1hRET, SLC22A2 (rs 316019), CYP4F2 (rs2074900) (4) ORR with ALDH2 (rs 886205), MTHFR (rs 1801133). (5) PFS with T1/2-HNI, XDH (rs 207440), and ABCB11 (rs 4148777). CONCLUSIONS: Exploratory associations were observed between Irinotecan PK/PD with hepatic functional imaging and extensive pharmacogenomics. Further work is required to confirm and validate these findings in a larger cohort of patients. AUSTRALIAN NEW ZEALAND CLINICAL TRIALS REGISTRY (ANZCTR) NUMBER: ACTRN12610000897066, Date registered: 21/10/2010.

Pharmacogenomics with red cells: a model to study protein variants of drug transporter genes.

The PharmacoScan pharmacogenomics platform screens for variation in genes that affect drug absorption, distribution, metabolism, elimination, immune adverse reactions and targets. Among the 1,191 genes tested on the platform, 12 genes are expressed in the red cell membrane: ABCC1, ABCC4, ABCC5, ABCG2, CFTR, SLC16A1, SLC19A1, SLC29A1, ATP7A, CYP4F3, EPHX1 and FLOT1. These genes represent 5 ATP-binding cassette proteins, 3 solute carrier proteins, 1 ATP transport protein and 3 genes associated with drug metabolism and adverse drug reactions. Only ABCG2 and SLC29A1 encode blood group systems, JR and AUG, respectively. We propose red cells as an ex vivo model system to study the effect of heritable variants in genes encoding the transport proteins on the pharmacokinetics of drugs. Altered pharmacodynamics in red cells could also cause adverse reactions, such as haemolysis, hitherto unexplained by other mechanisms.

D-amino Acids in Plants: Sources, Metabolism, and Functions.

Although plants are permanently exposed to D-amino acids (D-AAs) in the rhizosphere, these compounds were for a long time regarded as generally detrimental, due to their inhibitory effects on plant growth. Recent studies showed that this statement needs a critical revision. There were several reports of active uptake by and transport of D-AAs in plants, leading to the question whether these processes happened just as side reactions or even on purpose. The identification and characterization of various transporter proteins and enzymes in plants with considerable affinities or specificities for D-AAs also pointed in the direction of their targeted uptake and utilization. This attracted more interest, as D-AAs were shown to be involved in different physiological processes in plants. Especially, the recent characterization of D-AA stimulated ethylene production in Arabidopsis thaliana revealed for the first time a physiological function for a specific D-AA and its metabolizing enzyme in plants. This finding opened the question regarding the physiological or developmental contexts in which D-AA stimulated ethylene synthesis are involved in. This question and the ones about the transport characteristics of D-AAs, their metabolism, and their different physiological effects, are the focus of this review.

Identification of host variants associated with overall survival of esophageal cancer patients receiving platinum-based therapy.

Aim: Clinical features of esophageal cancer (EC) patients have poor prognostic power. Thus, it is paramount to discover biomarkers that can allow a more accurate survival prediction. Methods: To detect genetic variants associated with survival, DNA from 120 patients treated with cisplatin-based neoadjuvant therapy were genotyped using drug metabolism enzymes and transporters array. Results: We identified two variants: the rs2038067 in PPARD (p = 0.0004) and the rs683369 (F160L) in SLC22A1 (p = 0.001). Their prognostic power was greater than that of clinical stage alone (p = 0.017) and comparable to that of response to neoadjuvant therapy (p = 0.71). Interestingly, the prognostic accuracy of response models increased significantly when genetic variables were included (p = 0.003). Conclusion: Our data, though preliminary, strengthen the potential utility of germline variants for a better-tailored management of EC patients.

Transition of the Bacterial Community and Culturable Chitinolytic Bacteria in Chitin-treated Upland Soil: From Streptomyces to Methionine-auxotrophic Lysobacter and Other Genera.

Chitin amendment is an agricultural management strategy for controlling soil-borne plant disease. We previously reported an exponential decrease in chitin added to incubated upland soil. We herein investigated the transition of the bacterial community structure in chitin-degrading soil samples over time and the characteristics of chitinolytic bacteria in order to elucidate changes in the chitinolytic bacterial community structure during chitin degradation. The addition of chitin to soil immediately increased the population of bacteria in the genus Streptomyces, which is the main decomposer of chitin in soil environments. Lysobacter, Pseudoxanthomonas, Cellulosimicrobium, Streptosporangium, and Nonomuraea populations increased over time with decreases in that of Streptomyces. We isolated 104 strains of chitinolytic bacteria, among which six strains were classified as Lysobacter, from chitin-treated soils. These results suggested the involvement of Lysobacter as well as Streptomyces as chitin decomposers in the degradation of chitin added to soil. Lysobacter isolates required yeast extract or casamino acid for significant growth on minimal agar medium supplemented with glucose. Further nutritional analyses demonstrated that the six chitinolytic Lysobacter isolates required methionine (Met) to grow, but not cysteine or homocysteine, indicating Met auxotrophy. Met auxotrophy was also observed in two of the five type strains of Lysobacter spp. tested, and these Met auxotrophs used d-Met as well as l-Met. The addition of Met to incubated upland soil increased the population of Lysobacter. Met may be a factor increasing the population of Lysobacter in chitin-treated upland soil.

Unusual complications and corneal clearance after Descemet Membrane Endothelial Transfer in Pseudophakic Bullous Keratopathy.

Purpose. to report malignant glaucoma and infectious crystalline keratopathy as complications after an uneventful Descemet Membrane Endothelial Keratoplasty (DMEK), and corneal clearance despite graft detachment after the surgery in a patient with pseudophakic bullous keratopathy. Method. A 81-year-old patient with high Intraocular Pressure (IOP) and flat anterior chamber with patent iridotomies after DMEK was diagnosed of malignant glaucoma. The medical approach being insufficient, the patient required a pars-plana vitrectomy, capsulo-hyaloidectomy, and surgical iridectomy. Results. The IOP was reduced and anterior chamber was repositioned after surgical management. Corneal clearance was observed despite graft detachment. The patient developed an infectious crystalline keratopathy after the resolution of malignant glaucoma. Conclusions. malignant glaucoma is a rare complication following DMEK. Corneal clearance can be attained despite graft detachment after DMEK probably due to an unintentional Descemet Membrane Endothelial Transfer (DMET). However, in low dosage, steroid treatment remains a risk factor for developing ICK. Abbreviations: PBK = Pseudophakic Bullous Keratopathy, DMEK = Descemet Membrane Endothelial Keratoplasty, DMET = Descemet Membrane Endothelial Transfer, IOP = Intraocular Pressure, BCVA = Best Corrected Visual Acuity, AC = Anterior Chamber, MG = Malignant Glaucoma, ICK = Infectious Crystalline Keratopathy.

CHST3 and CHST13 polymorphisms as predictors of bosentan-induced liver toxicity in Japanese patients with pulmonary arterial hypertension.

Bosentan, an endothelin receptor antagonist, has been widely used as a first-line drug for the treatment of pulmonary arterial hypertension (PAH). In addition, bosentan is approved for patients with digital ulcers related to systemic sclerosis. Liver dysfunction is a major adverse effect of bosentan and may lead to discontinuation of therapy. The purpose of this study was to identify genomic biomarkers to predict bosentan-induced liver injury. A total of 69 PAH patients were recruited into the study. An exploratory analysis of 1936 single-nucleotide polymorphisms (SNPs) in 231 genes involved in absorption, distribution, metabolism, and elimination of multiple medications using Affimetrix DMET™ (Drug Metabolism Enzymes and Transporters) chips was performed. We extracted 16 SNPs (P < 0.05) using the Jonckheere-Terpstra trend test and multiplex logistic analysis; we identified two SNPs in two genes, CHST3 and CHST13, which are responsible for proteoglycan sulfation and were significantly associated with bosentan-induced liver injury. We constructed a predictive model for bosentan-induced liver injury (area under the curve [AUC]: 0.89, sensitivity: 82.61%, specificity: 86.05%) via receiver operating curve (ROC) analysis using 2 SNPs and 2 non-genetic factors. Two SNPs were identified as potential predictive markers for bosentan-induced liver injury in Japanese patients with pulmonary arterial hypertension. This is the first pharmacogenomics study linking proteoglycan sulfating genes to drug-induced liver dysfunction, a frequently observed clinical adverse effect of bosentan therapy. These results may provide a way to personalize PAH medicine as well as provide novel mechanistic insights to drug-induced liver dysfunction.

Epigenetics and MicroRNAs in Pharmacogenetics.

Germline pharmacogenetics has so far mainly studied common variants in "pharmacogenes," i.e., genes encoding drug metabolizing enzymes and transporters (DMET genes), certain auxiliary and regulatory genes, and drug target genes. Despite remarkable progress in understanding genetically determined differences in pharmacokinetics and pharmacodynamics of drugs, currently known common variants even in important pharmacogenes explain genetic variability only partially. This suggests "missing heritability" that may in part be due to rare variants in the classical pharmacogenes, but current evidence suggests that largely unexplored resources with potential for pharmacogenetics exist, both within already known pharmacogenes and in entirely new areas. In particular, recent studies suggest that epigenetic processes and noncoding RNAs, including mostly microRNAs (miRNAs), represent important and largely unexplored layers of DMET gene regulation that may fill some of the gaps in understanding interindividual variability and lead to new biomarkers. In this chapter we summarize recent advances in the understanding of genetic variability in epigenetic and miRNA-mediated processes with focus on their significance for DMET regulation and pharmacokinetic or pharmacological endpoints.

Deciphering DMET genetic data: comprehensive assessment of Northwestern Han, Tibetan, Uyghur populations and their comparison to eleven 1000 genome populations.

We investigated the allele frequencies of drug absorption, distribution, metabolism and elimination (ADME)-related drug-metabolizing enzymes and transporters (DMET) genes in the Northwestern Han, Tibetan and Uyghur populations and compared the related genes in these three populations with those in eleven 1000 Genome populations. We examined 1936 single nucleotide polymorphisms of 225 DMET genes involved in ADME processes and found 732, 679 and 804 sites were polymorphic in Han, Tibetan and Uyghur. Tibetan differed from Han in only four sites (p < .05), whereas Uyghur differed from Han and Tibetan in 24 and 21 sites, respectively (p < .05). The distributions of 1058 genotyping data of 245 individuals from Han, Tibetan and Uyghur were compared with 1207 other individuals from the eleven 1000 Genomes populations. The top four populations in Han that exhibited the smallest pairwise Fst values were CHB, Tibetan, CHD and JPT; those in Tibetan were Han, CHB, Uyghur and CHD; and those in Uyghur were Han, Tibetan, GIH and CEU. MEGA results revealed that CHB, CHD, JPT, Han, Tibetan and Uyghur were grouped in cluster 1. GIH, MEX, CEU and TSI were grouped in cluster 2. MKK, ASW, LWK and YRI were grouped in cluster 3.

Genetic variants associated with Fabry disease progression despite enzyme replacement therapy.

Enzyme replacement therapy (ERT) has been widely used for the treatment of Fabry disease, a rare X-linked recessive disorder due to absent or reduced activity of lysosomal enzyme α-galactosidase A. It is still unclear why some patients under ERT show disease progression typically with renal, cardiovascular and cerebrovascular dysfunctions. Here, we investigated the involvement of drug absorption, distribution, metabolism, and excretion gene variants in response variability to ERT, genotyping 37 patients with the Affymetrix Drug Metabolizing Enzyme and Transporters (DMET) Plus microarray. We found three single nucleotide polymorphisms in human alcohol dehydrogenase (ADH)4 gene (rs1126670, rs1126671, rs2032349) and one in ADH5 gene (rs2602836) associated with disease progression (p < 0.05). Our data provide a basic tool for identification of patient with ERT non-response risk that may represent a framework for personalized treatment of this rare disease.

Genetic variants associated with gastrointestinal symptoms in Fabry disease.

Gastrointestinal symptoms (GIS) are often among the earliest presenting events in Fabry disease (FD), an X-linked lysosomal disorder caused by the deficiency of α-galactosidase A. Despite recent advances in clinical and molecular characterization of FD, the pathophysiology of the GIS is still poorly understood. To shed light either on differential clinical presentation or on intervariability of GIS in FD, we genotyped 1936 genetic markers across 231 genes that encode for drug-metabolizing enzymes and drug transport proteins in 49 FD patients, using the DMET Plus platform. All nine single nucleotide polymorphisms (SNPs) mapped within four genes showed statistically significant differences in genotype frequencies between FD patients who experienced GIS and patients without GIS: ABCB11 (odd ratio (OR) = 18.07, P = 0,0019; OR = 8.21, P = 0,0083; OR=8.21, P = 0,0083; OR = 8.21, P = 0,0083),SLCO1B1 (OR = 9.23, P = 0,0065; OR = 5.08, P = 0,0289; OR = 8.21, P = 0,0083), NR1I3 (OR = 5.40, P = 0,0191) and ABCC5 (OR = 14.44, P = 0,0060). This is the first study that investigates the relationships between genetic heterogeneity in drug absorption, distribution, metabolism and excretion (ADME) related genes and GIS in FD. Our findings provide a novel genetic variant framework which warrants further investigation for precision medicine in FD.

Minimum information required for a DMET experiment reporting.

AIM: To provide pharmacogenomics reporting guidelines, the information and tools required for reporting to public omic databases. MATERIAL & METHODS: For effective DMET data interpretation, sharing, interoperability, reproducibility and reporting, we propose the Minimum Information required for a DMET Experiment (MIDE) reporting. RESULTS: MIDE provides reporting guidelines and describes the information required for reporting, data storage and data sharing in the form of XML. CONCLUSION: The MIDE guidelines will benefit the scientific community with pharmacogenomics experiments, including reporting pharmacogenomics data from other technology platforms, with the tools that will ease and automate the generation of such reports using the standardized MIDE XML schema, facilitating the sharing, dissemination, reanalysis of datasets through accessible and transparent pharmacogenomics data reporting.

DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine.

In the era of personalized medicine, high-throughput technologies have allowed the investigation of genetic variations underlying the inter-individual variability in drug pharmacokinetics/pharmacodynamics. Several studies have recently moved from a candidate gene-based pharmacogenetic approach to genome-wide pharmacogenomic analyses to identify biomarkers for selection of patient-tailored therapies. In this aim, the identification of genetic variants affecting the individual drug metabolism is relevant for the definition of more active and less toxic treatments. This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.

Identification of polymorphic variants associated with erlotinib-related skin toxicity in advanced non-small cell lung cancer patients by DMET microarray analysis.

PURPOSE: Erlotinib is a targeted agent commonly used in advanced non-small cell lung cancer (aNSCLC). However, drug-related skin toxicity often may affect the quality of life of cancer patients and lead to treatment discontinuation. Genetic polymorphisms in drug transporters and metabolizing enzymes play a major role in the interindividual variability in terms of efficacy and toxicity of erlotinib treatment. The aim of our study was to identify genetic determinants in adsorption, distribution, metabolism, and excretion genes influencing skin rash (SR) by the novel drug-metabolizing enzyme and transporter (DMET) microarray Affymetrix platform in aNSCLC patients. METHODS: In a retrospective study, 34 erlotinib-treated aNSCLC patients were genotyped by DMET Plus chip: 23 patients experienced SR (cases), while 11 patients did not (controls). Peripheral blood DNA was genotyped. Genotype association was analyzed by Fisher's exact test, and the toxicity-associated gene sets underwent Ingenuity Pathway Analysis (IPA). RESULTS: Seven SNPs in six genes (CYP27B1, MAT1A1, CHST1, CYP4B1, ADH6, and SLC22A1) were associated with the occurrence of SR or with a protective effect. Specifically, the rs8176345 in CYP27B1 gene was significantly correlated with SR (p = 0.0003, OR 55.55, 95% CI 2.7036-1141.1707). The IPA on SR-related genes highlighted the role of a variety of canonical pathways including 1,25-dihydroxyvitamin D3 biosynthesis, S-adenosyl-L-methionine biosynthesis, and methionine degradation I (to homocysteine) in SR development. CONCLUSION: Although exploratory, this study indicates rs8176345 in CYP27B1 gene as significantly correlated with erlotinib-induced SR in aNSCLC patients probably through a mechanism mediated by vitamin D3 and inflammation at skin level.

Predicting paclitaxel-induced neutropenia using the DMET platform.

AIM: The use of paclitaxel in cancer treatment is limited by paclitaxel-induced neutropenia. We investigated the ability of genetic variation in drug-metabolizing enzymes and transporters to predict hematological toxicity. PATIENTS & METHODS: Using a discovery and validation approach, we identified a pharmacogenetic predictive model for neutropenia. For this, a drug-metabolizing enzymes and transporters plus DNA chip was used, which contains 1936 SNPs in 225 metabolic enzyme and drug-transporter genes. RESULTS: Our 10-SNP model in 279 paclitaxel-dosed patients reached 43% sensitivity in the validation cohort. Analysis in 3-weekly treated patients only resulted in improved sensitivity of 79%, with a specificity of 33%. None of our models reached statistical significance. CONCLUSION: Our drug-metabolizing enzymes and transporters-based SNP-models are currently of limited value for predicting paclitaxel-induced neutropenia in clinical practice. Original submitted 9 March 2015; Revision submitted 20 May 2015.

Current Challenges in Development of a Database of Three-Dimensional Chemical Structures.

We are developing a database named 3DMET, a three-dimensional structure database of natural metabolites. There are two major impediments to the creation of 3D chemical structures from a set of planar structure drawings: the limited accuracy of computer programs and insufficient human resources for manual curation. We have tested some 2D-3D converters to convert 2D structure files from external databases. These automatic conversion processes yielded an excessive number of improper conversions. To ascertain the quality of the conversions, we compared IUPAC Chemical Identifier and canonical SMILES notations before and after conversion. Structures whose notations correspond to each other were regarded as a correct conversion in our present work. We found that chiral inversion is the most serious factor during the improper conversion. In the current stage of our database construction, published books or articles have been resources for additions to our database. Chemicals are usually drawn as pictures on the paper. To save human resources, an optical structure reader was introduced. The program was quite useful but some particular errors were observed during our operation. We hope our trials for producing correct 3D structures will help other developers of chemical programs and curators of chemical databases.