[Associations between ALDH2 and ADH1B Genotypes and Ethanol-Induced Cutaneous Erythema in Young Japanese Women].

OBJECTIVES: The purpose of this study was to identify associations between ALDH2 and ADH1B genotypes and ethanol-induced cutaneous erythema and assess the accuracy of an ethanol patch test in young Japanese women. METHODS: The subjects were 942 female Japanese university students. They were given an ethanol patch test and examined for ethanol-induced cutaneous erythema both immediately after removing the patch and 10 minutes after removing the patch. A saliva sample was used to determine the ALDH2 and ADH1B genotype of each subject by realtime PCR. RESULTS: The sensitivity and specificity of erythema immediately after removing the patch as the marker for the presence of inactive ALDH2 were 69.6% and 87.7%, respectively, and the sensitivity and specificity of erythema 10 minutes after removing the patch were 85.2% and 85.1%, respectively. The sensitivity of erythema after 10 minutes was markedly lower in the ADH1B*1/*1 carriers than in the ADH1B*2 carriers (8.3% vs. 89.7%, p<0.0001), and the specificity was significantly higher in the ADH1B*1/*1 carriers than in the ADH1B*2 carriers (96.9% vs. 84.3%, p<0.05). CONCLUSIONS: Overall, both sensitivity and specificity were satisfactorily high, but having the ADH1B*1/*1 genotype prevented a positive reaction for inactive ALDH2 and caused false-negative results. The data also suggested that having the ADH1B*2/*2 genotype caused a positive reaction in subjects with the ALDH2*1/*1 genotype. Despite these exceptions, the ethanol patch test has enough accuracy and can be used easily to subjects who don't drink alcohol. This is a valuable tool for improving the health literacy of younger generation subjects.

Combination analysis in genetic polymorphisms of drug-metabolizing enzymes CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A5 in the Japanese population.

The Cytochrome P450 is the major enzyme involved in drug metabolism. CYP enzymes are responsible for the metabolism of most clinically used drugs. Individual variability in CYP activity is one important factor that contributes to drug therapy failure. We have developed a new straightforward TaqMan PCR genotyping assay to investigate the prevalence of the most common allelic variants of polymorphic CYP enzymes CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A5 in the Japanese population. Moreover, we focused on the combination of each genotype for clinical treatment. The genotype analysis identified a total of 139 out of 483 genotype combinations of five genes in the 1,003 Japanese subjects. According to our results, most of subjects seemed to require dose modification during clinical treatment. In the near future, modifications should be considered based on the individual patient genotype of each treatment.

Direct detection of single nucleotide polymorphism (SNP) by the TaqMan PCR assay using dried saliva on water-soluble paper and hair-roots, without DNA extraction.

We have developed a new method for directly using unprocessed biological specimens as templates for the TaqMan assay. DNA extraction and purification had been believed to be required for the assay, but our new method could avoid hindering fluorescence detection, even if the templates were used directly. Saliva was needed to be put on water-soluble paper and dried, and hairs were cut to be about 10 mm long. This method could reduce both the time and effort involved, and also the risk of contamination. It should prove to be very valuable for genetic diagnoses in various fields.

Long PCR-based genotyping for a deleted CYP2D6 gene without DNA extraction.

In the post-genome era, a simple and inexpensive method for diagnostic analysis is in high demand. Cytochrome P450 (CYP) 2D6 is one of the most widely investigated CYPs in relation to genetic polymorphism. Detection of CYP2D6*5 is difficult since long PCR is used. Especially for samples without DNA extraction, the detection is not sensitive enough for population analysis. Therefore, we developed a CYP2D6*5 genotyping method that involves nested long PCR, directly using human whole saliva as a template without DNA extraction. This method will be very useful for genetic diagnoses and can be an efficient tool for individualization of drug therapy in clinical studies.

Genotyping of polymorphisms in alcohol and aldehyde dehydrogenase genes by direct application of PCR-RFLP on dried blood without DNA extraction.

We have developed a simple, labor-saving, inexpensive, and rapid single nucleotide polymorphism (SNP) genotyping method that works directly on whole human blood. This single-tube genotyping method was used to successfully and reliably genotype ADH1B and ALDH2 polymorphisms without DNA isolation using a 1.2-mm disc of dried blood and the KOD FX PCR enzyme kit. SNP genotyping was performed by a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. In addition to the labor and expense advantages, the possibility of sample contamination was considerably decreased, since the DNA extraction step was eliminated. In the post-genome era, a simple and inexpensive method for diagnostic analysis is in high demand, and this method will be very useful for genetic diagnoses in biological and medical laboratories.

Single-tube genotyping from a human hair root by direct PCR.

We have developed a simple, labor-saving, inexpensive and rapid SNP genotyping method that directly uses a human hair root as the template. This single-tube genotyping method was used to successfully and reliably genotype the ADH1B and ALDH2 polymorphisms using a hair root (without DNA isolation) and the polymerase chain reaction (PCR) enzyme kit KOD FX. Since the DNA extraction step was eliminated, the possibility of sample contamination was considerably decreased. The single-tube SNP genotyping was performed by coupling the PCR enzyme kit with allele-specific primer (ASP)-PCR. In the post-genome era, a simple and inexpensive method for diagnostic analysis is in high demand, and this PCR method with a hair root as a template will be very useful for genetic diagnoses in biological and medical laboratories.

All-in-one tube method for quantitative gene expression analysis in oligo-dT(30) immobilized PCR tube coated with MPC polymer.

In this report, we have developed a novel quantitative RT-PCR protocol in which the procedure including mRNA purification can be performed in an all-in-one tube. To simplify gene expression analysis, oligo-dT(30) immobilized PCR tubes were used serially to capture mRNA, synthesize solid-phase cDNA, and amplify specific genes. The immobilized oligo-dT(30) can efficiently capture mRNA directly from crude human cell lysates. The captured mRNA is then amplified by one-step reverse transcription PCR (RT-PCR) with initial cDNA synthesis followed by PCR. In RT-PCR, this new reusable PCR tube device can be employed for multiple PCR amplifications with different primer sets from a solid-phase oligo-dT(30) primed cDNA library. This paper introduces a novel and highly reliable all-in-one tube method for rapid cell lysis, followed by quantitative preparation and expression analysis of target mRNA molecules with small amounts of sample. This procedure allows all steps to be carried out by sequential dilution in a single tube, without chemical extraction. We demonstrate the utility of this novel method by quantification of two housekeeping genes, beta-actin and GAPDH, in HeLa cells. We believe this new PCR device can be useful as a platform for various mRNA expression analyses, including basic research, drug screening, and molecular toxicology, as well as for molecular pathological diagnostics.

Using gene expression profiling to identify a prognostic molecular spectrum in gliomas.

Histopathological classification of gliomas is often clinically inadequate due to the diversity of tumors that fall within the same class. The goal of the present study was to identify prognostic molecular features in diffusely infiltrating gliomas using gene expression profiling. We selected 3456 genes expressed in gliomas, including 3012 genes found in a gliomal expressed sequence tag collection. The expression levels of these genes in 152 gliomas (100 glioblastomas, 21 anaplastic astrocytomas, 19 diffuse astrocytomas, and 12 anaplastic oligodendrogliomas) were measured using adapter-tagged competitive polymerase chain reaction, a high-throughput reverse transcription-polymerase chain reaction technique. We applied unsupervised and supervised principal component analyses to elucidate the prognostic molecular features of the gliomas. The gene expression data matrix was significantly correlated with the histological grades, oligo-astro histology, and prognosis. Using 110 gliomas, we constructed a prediction model based on the expression profile of 58 genes, resulting in a scheme that reliably classified the glioblastomas into two distinct prognostic subgroups. The model was then tested with another 42 tissues. Multivariate Cox analysis of the glioblastoma patients using other clinical prognostic factors, including age and the extent of surgical resection, indicated that the gene expression profile was a strong and independent prognostic parameter. The gene expression profiling identified clinically informative prognostic molecular features in astrocytic and oligodendroglial tumors that were more reliable than the traditional histological classification scheme.

RPN2 gene confers docetaxel resistance in breast cancer.

Drug resistance acquired by cancer cells has led to treatment failure. To understand the regulatory network underlying docetaxel resistance in breast cancer cells and to identify molecular targets for therapy, we tested small interfering RNAs (siRNAs) against 36 genes whose expression was elevated in human nonresponders to docetaxel for the ability to promote apoptosis of docetaxel-resistant human breast cancer cells (MCF7-ADR cells). The results indicate that the downregulation of the gene encoding ribophorin [corrected] II (RPN2), which is part of an N-oligosaccharyl transferase complex, most efficiently induces apoptosis of MCF7-ADR cells in the presence of docetaxel. RPN2 silencing induced reduced glycosylation of the P-glycoprotein, as well as decreased membrane localization, thereby sensitizing MCF7-ADR cells to docetaxel. Moreover, in vivo delivery of siRNA specific for RPN2 markedly reduced tumor growth in two types of models for drug resistance. Thus, RPN2 silencing makes cancer cells hypersensitive response to docetaxel, and RPN2 might be a new target for RNA interference-based therapeutics against drug resistance.

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

PURPOSE: Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. EXPERIMENTAL DESIGN: The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. RESULTS: Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. CONCLUSIONS: Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

A novel technique for measuring variations in DNA copy-number: competitive genomic polymerase chain reaction.

BACKGROUND: Changes in genomic copy number occur in many human diseases including cancer. Characterization of these changes is important for both basic understanding and diagnosis of these diseases. Microarrays have recently become the standard technique and are commercially available. However, it is useful to have an affordable technique to complement them. RESULTS: We describe a novel polymerase chain reaction (PCR)-based technique, termed competitive genomic PCR (CGP). The main characteristic of CGP is that different adaptors are added to the sample and control genomic DNAs after appropriate restriction enzyme digestion. These adaptor-supplemented DNAs are subjected to competitive PCR using an adaptor-primer and a locus-specific primer. The amplified products are then separated according to size differences between the adaptors. CGP eliminates the tedious steps inherent in quantitative PCR and achieves moderate throughput. Assays with different X chromosome numbers showed that it can provide accurate quantification. High-resolution analysis of neuroblastoma cell lines around the MYCN locus revealed novel junctions for amplification, which were not detected by a commercial array. CONCLUSION: CGP is a moderate throughput technique for analyzing changes in genomic copy numbers. Because CGP can measure any genomic locus using PCR primers, it is especially useful for detailed analysis of a genomic region of interest.

A multi-class predictor based on a probabilistic model: application to gene expression profiling-based diagnosis of thyroid tumors.

BACKGROUND: Although microscopic diagnosis has been playing the decisive role in cancer diagnostics, there have been cases in which it does not satisfy the clinical need. Differential diagnosis of malignant and benign thyroid tissues is one such case, and supplementary diagnosis such as that by gene expression profile is expected. RESULTS: With four thyroid tissue types, i.e., papillary carcinoma, follicular carcinoma, follicular adenoma, and normal thyroid, we performed gene expression profiling with adaptor-tagged competitive PCR, a high-throughput RT-PCR technique. For differential diagnosis, we applied a novel multi-class predictor, introducing probabilistic outputs. Multi-class predictors were constructed using various combinations of binary classifiers. The learning set included 119 samples, and the predictors were evaluated by strict leave-one-out cross validation. Trials included classical combinations, i.e., one-to-one, one-to-the-rest, but the predictor using more combination exhibited the better prediction accuracy. This characteristic was consistent with other gene expression data sets. The performance of the selected predictor was then tested with an independent set consisting of 49 samples. The resulting test prediction accuracy was 85.7%. CONCLUSION: Molecular diagnosis of thyroid tissues is feasible by gene expression profiling, and the current level is promising towards the automatic diagnostic tool to complement the present medical procedures. A multi-class predictor with an exhaustive combination of binary classifiers could achieve a higher prediction accuracy than those with classical combinations and other predictors such as multi-class SVM. The probabilistic outputs of the predictor offer more detailed information for each sample, which enables visualization of each sample in low-dimensional classification spaces. These new concepts should help to improve the multi-class classification including that of cancer tissues.

Prediction of docetaxel response in human breast cancer by gene expression profiling.

PURPOSE: Docetaxel is one of the most effective anticancer drugs available in the treatment of breast cancer. Nearly half of the treated patients, however, do not respond to chemotherapy and suffer from side effects. The ability to reliably predict a patient's response based on tumor gene expression will improve therapeutic decision making and save patients from unnecessary side effects. PATIENTS AND METHODS: A total of 44 breast tumor tissues were sampled by biopsy before treatment with docetaxel, and the response to therapy was clinically evaluated by the degree of reduction in tumor size. Gene expression profiling of the biopsy samples was performed with 2,453 genes using a high-throughput reverse transcriptase polymerase chain reaction technique. Using genes differentially expressed between responders and nonresponders, a diagnostic system based on the weighted-voting algorithm was constructed. RESULTS: This system predicted the clinical response of 26 previously unanalyzed samples with over 80% accuracy, a level promising for clinical applications. Diagnostic profiles in nonresponders were characterized by elevated expression of genes controlling the cellular redox environment (ie, redox genes, such as thioredoxin, glutathione-S-transferase, and peroxiredoxin). Overexpression of these genes protected cultured mammary tumor cells from docetaxel-induced cell death, suggesting that enhancement of the redox system plays a major role in docetaxel resistance. CONCLUSION: These results suggest that the clinical response to docetaxel can be predicted by gene expression patterns in biopsy samples. The results also suggest that one of the molecular mechanisms of the resistance is activation of a group of redox genes.