Molecular genetics and epigenetics of the cytochrome P450 gene family and its relevance for cancer risk and treatment

The cytochromes P450 (CYPs) are very efficient catalysts of foreign compound metabolism and are responsible for the major part of metabolism of clinically important drugs. The enzymes are important in cancer since they (a) activate dietary and environmental components to ultimate carcinogens, (b) activate or inactivate drugs used for cancer treatment, and (c) are potential targets for anticancer therapy. The genes encoding the CYP enzymes active in drug metabolism are highly polymorphic, whereas those encoding metabolism of precarcinogens are relatively conserved. A vast amount of literature is present where investigators have tried to link genetic polymorphism in CYPs to cancer susceptibility, although not much conclusive data have hitherto been obtained, with exception of CYP2A6 polymorphism and tobacco induced cancer, to a great extent because of lack of important functional polymorphisms in the genes studied. With respect to anticancer treatment, the genetic CYP polymorphism is of greater importance, where treatment with tamoxifen, but also with cyclophosphamide and maybe thalidomide is influenced by CYP genetic variants. In the present review we present updates on CYP genetics, cancer risk and treatment and also epigenetic aspects of interindividual variability in CYP expression and the use of these enzymes as targets for cancer therapy. We conclude that the CYP polymorphism does not predict cancer susceptibility to any large extent but that this polymorphism might be an important factor for optimal cancer therapy using selected anticancer agents.     

Risk assessment and mitigation strategies for reactive metabolites in drug discovery and development

Drug toxicity is a leading cause of attrition of candidate drugs during drug development as well as of withdrawal of drugs post-licensing due to adverse drug reactions in man. These adverse drug reactions cause a broad range of clinically severe conditions including both highly reproducible and dose dependent toxicities as well as relatively infrequent and idiosyncratic adverse events. The underlying risk factors can be split into two groups: (1) drug-related and (2) patient-related. The drug-related risk factors include metabolic factors that determine the propensity of a molecule to form toxic reactive metabolites (RMs), and the RM and non-RM mediated mechanisms which cause cell and tissue injury. Patient related risk factors may vary markedly between individuals, and encompass genetic and non-genetic processes, e.g. environmental, that influence the disposition of drugs and their metabolites, the nature of the adverse responses elicited and the resulting biological consequences. We describe a new strategy, which builds upon the strategies used currently within numerous pharmaceutical companies to avoid and minimize RM formation during drug discovery, and that is intended to reduce the likelihood that candidate drugs will cause toxicity in the human population. The new strategy addresses drug-related safety hazards, but not patient-related risk factors. A common target organ of toxicity is the liver and to decrease the likelihood that candidate drugs will cause liver toxicity (both non-idiosyncratic and idiosyncratic), we propose use of an in vitro Hepatic Liability Panel alongside in vitro methods for the detection of RMs. This will enable design and selection of compounds in discovery that have reduced propensity to cause liver toxicity. In vitro Hepatic Liability is assessed using toxicity assays that quantify: CYP 450 dependent and CYP 450 independent cell toxicity; mitochondrial impairment; and inhibition of the Bile Salt Export Pump. Prior to progression into development, a Hepatotoxicity Hazard Matrix combines data from the Hepatic Liability Panel with the Estimated RM Body Burden. The latter is defined as the level of covalent binding of radiolabelled drug to human hepatocyte proteins in vitro adjusted for the predicted human dose. We exemplify the potential value of this approach by consideration of the thiazolidinedione class of drugs.     

Pharmacogenetic basis for therapeutic optimization in Alzheimer's disease

Alzheimer's disease is a major health problem in developed countries. Approximately 10-15% of direct costs in dementia are attributed to pharmacological treatment, and only 10-20% of the patients are moderate responders to conventional antidementia drugs, with questionable cost effectiveness. The phenotypic expression of Alzheimer's disease is characterized by amyloid deposition in brain tissue and vessels (amyloid angiopathy), intracellular neurofibrillary tangle formation, synaptic and dendritic loss, and premature neuronal death. Primary pathogenic events underlying this neurodegenerative process include genetic factors involving more than 200 different genes distributed across the human genome, accompanied by progressive cerebrovascular dysfunction, and diverse environmental factors. Mutations in genes directly associated with the amyloid cascade (APP, PSEN1, PSEN2) are present in less than 5% of the Alzheimer's disease population; however, the presence of the epsilon4 allele of the apolipoprotein E gene (APOE) represents a major risk factor for more than 40% of patients with dementia. Genotype-phenotype correlation studies and functional genomics studies have revealed the association of specific mutations in primary loci and/or APOE-related polymorphic variants with the phenotypic expression of biological traits. It is estimated that genetics accounts for between 20% and 95% of the variability in drug disposition and pharmacodynamics. Recent studies indicate that the therapeutic response in Alzheimer's disease is genotype specific, depending on genes associated with Alzheimer's disease pathogenesis and/or genes responsible for drug metabolism (e.g. cytochrome P450 [CYP] genes). In monogenic studies, APOEepsilon4/epsilon4 genotype carriers are the worst responders to conventional treatments. Some cholinesterase inhibitors currently being use in the treatment of Alzheimer's disease are metabolized via CYP-related enzymes. These drugs can interact with many other drugs that are substrates, inhibitors or inducers of the CYP system, this interaction eliciting liver toxicity and other adverse drug reactions. CYP2D6 enzyme isoforms are involved in the metabolism of more than 20% of drugs used in CNS disorders. The distribution of the CYP2D6 genotypes in the European population of the Iberian peninsula differentiates four major categories of CYP2D6-related metabolizer types: (i) extensive metabolizers (EM) [51.61%]; (ii) intermediate metabolizers (IM) [32.26%]; (iii) poor metabolizers (PM) [9.03%]; and (iv) ultra-rapid metabolizers (UM) [7.10%]. PMs and UMs tend to show higher transaminase activity than EMs and IMs. EMs and IMs are the best responders, and PMs and UMs are the worst responders to pharmacologic treatments in Alzheimer's disease. At this early stage of the development of pharmacogenomic/pharmacogenetic procedures in Alzheimer's disease therapeutics, it seems very plausible that the pharmacogenetic response in Alzheimer's disease depends on the interaction of genes involved in drug metabolism and genes associated with Alzheimer's disease pathogenesis.     

细胞色素P450基因多态性与药物代谢研究进展

细胞色素P450（cytochrome P450,CYP450）在人体药物代谢过程中起着非常重要的作用并参与代谢80%以上的临床药物。由于CYP450在不同种族和不同人群中存在基因多态性,从而造成药物反应的个体差异,一度成为药物基因组学研究的热点。通过查阅国外相关文献,综述了近年来关于CYP1A2、CYP2C9、CYP2C19、CYP2D6和CYP3A4五种主要的药物代谢酶的基因多态性和药物代谢的研究进展,为临床指导个体化用药、避免药物不良反应和新药研发提供科学参考依据。     

CYP3A4基础与临床研究进展

细胞色素P4503A4(CYP3A4)是存在人类肝脏及肠道中的一种主要的细胞色素CYP450酶,约占成人肝脏CYP450酶总量的25%左右。临床中约有50%的药物是通过其代谢,并且其基因位点突变也与其多种疾病相关,知晓CYP3A4的表达水平和不同功能的遗传学基础,无论是对疾病的发病基础、临床药物的应用,会带来前所未有的启发,在药物应用过程中,通过对基因组学的认识,从而可以在基因层面了解个体代谢差异产生的原因,调整药物用量,提高疗效,最终使药物副作用降到最低限。目前对CYP3A4的研究渐趋于成熟,已逐渐阐明了其药物间相互作用的机制,它能够被多种药物竞争性抑制或者诱导,并受到某些蛋白受体的调控影响,可改变药物的药代动力学,增强或降低药效,造成个体用药差异,这也是造成药物间相互作用的重要原因。然而CYP3A4基因多态性与基因导向治疗关系,还有待进一步深入研究。该文对CYP3A4基因多态性、分布以及与临床疾病及用药的研究现状作一综述。     

The QT Interval and Selection of Alpha-Blockers for Benign Prostatic Hyperplasia

The QT interval is the electrocardiographic manifestation of ventricular depolarization and repolarization. Drug-induced long QT syndrome is characterized by acquired, corrected QT (QTc) interval prolongation that is associated with increased risk of torsade de pointes. Every physician must recognize if the drugs he or she prescribes prolongs the QTc interval, especially if the drug is prescribed for a chronic condition in older patients who are on polypharmacy. The evolution of alpha-blockers for the treatment of benign prostatic hyperplasia has allowed the development of drugs that are easier to administer and better tolerated. Because alpha-blockers generally have equivalent efficacy, this class of drugs is typically differentiated by safety and side effects. Studies suggest that alpha-blockers may vary in regard to their effect on the QT interval, and, therefore, on their predisposition to cause potentially life-threatening ventricular arrhythmias.     

Role of genetics and drug metabolism in human cancer risk

The research field concerning responses to drugs having a hereditary basis is called 'pharmacogenetics'. At least 5 dozen pharmacogenetic polymorphisms have been described in clinical medicine; many are responsible for marked differences in genetic predisposition toward toxicity or cancer. Three are detailed here: the acetylation, the debrisoquine, and the AH locus polymorphism. All 3 are very common among the United States' population: 1 in 2 is a 'slow acetylator', 1 in 12 is a 'poor metabolizer' for more than 2 dozen commonly prescribed drugs in the debrisoquine panel, and the CYP1A1 and CYP1A2 (cytochromes P(1)450 and P(3)450) genes are highly inducible by cigarette smoke in 1 of 10 patients. Differences in xenobiotic metabolism between individuals in the same family can be greater than 200-fold, suggesting that occupationally hazardous chemicals, as well as prescribed drugs having a narrow therapeutic window, might cause strikingly dissimilar effects between patients of differing genotypes. Our ultimate goal is 'preventive toxicology', i.e. the development of simple, inexpensive, unequivocal and sensitive assays to predict individual risk of toxicity or cancer. These tests could help the individual in choosing a safer life style or place of work and might aid the physician in deciding which drug to prescribe.     

Risk factors for drug-induced long-QT syndrome

Congenital long-QT syndrome (cLQTS) is a ventricular arrhythmia that is characterised by a prolonged QT interval on the surface electro-cardiogram (ECG). Clinical symptoms include sudden loss of consciousness (syncopes), seizures, cardiac arrest and sudden death. The prevalence of this inherited disease is approximately one in 10,000 in Caucasians. Over the last decade, more than 200 different diseases causing mutations have been identified in five genes that encode ion channels involved in the delicate balance of inward and outward K/Ca currents during the cardiac action potential. A prolonged QT interval accompanied by very similar clinical symptoms as in cLQTS can also occur in otherwise healthy individuals after the intake of specific drug(s). This phenomenon is known as ''acquired'' or ''drug-induced'' long-QT syndrome. Because the clinical symptoms of the two forms are very similar, the question arises whether a common underlying genetic basis also exists. Several studies indicate that only a minority (approximately 10%) of the drug-induced LQTS cases can be explained by a mutation or polymorphism in one of the known LQTS genes. Even though the disease can often at least partially be explained by environmental factors, mutations or polymorphisms in other genes are also expected to be involved, including genes encoding drug-metabolising enzymes, adrenergic receptors, hormone-related genes and mitochondrial genes. This article reviews the current knowledge on risk factors for drug-induced LQTS, with a special emphasis on the role of genetic determinants.     

Functional evaluation of genetic and environmental regulators of p450 mRNA levels

Variations in the activities of Cytochrome P450s are one of the major factors responsible for inter-individual differences in drug clearance rates, which may cause serious toxicity or inefficacy of therapeutic drugs. Various mRNA level is one of the key factors for different activity of the major P450 genes. Although both genetic and environmental regulators of P450 gene expression have been widely investigated, few studies have evaluated the functional importance of cis- and trans-regulatory factors and environmental factors in the modulation of inter-individual expression variations of the P450 genes. In this study, we measured the mRNA levels of seven major P450 genes (CYP1A1, CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4 and CYP3A5) in 96 liver biopsy samples from Chinese population. Both trans-acting (mRNA levels and non-synonymous SNPs of putative regulator genes) and cis-acting (gene copy number and functional SNPs) factors were investigated to identify the determinants of the expression variations of these seven P450 genes. We found that expression variations of most P450 genes, regulator genes and housekeeping genes were positively correlated at the mRNA level. After partial correlation analysis using ACTB and GAPDH expression to eliminate the effect of global regulators, a UPGMA (Unweighted Pair Group Method with Arithmetic Mean) tree was constructed to reveal the effects of specific regulation networks potentially masked by global regulators. Combined with the functional analysis of regulators, our results suggested that expression variation at the mRNA level was mediated by several factors in a gene-specific manner. Cis-acting genetic variants might play key roles in the expression variation of CYP2D6 and CYP3A5, environmental inducers might play key roles in CYP1A1 and CYP1A2 variation and global regulators might play key roles in CYP2C9 variation. In addition, the functions of regulators that play less important roles in controlling expression variation for each P450 gene were determined.     

Reduction in hepatic drug metabolizing CYP3A4 activities caused by P450 oxidoreductase mutations identified in patients with disordered steroid metabolism

Cytochrome P450 3A4 (CYP3A4), the major P450 present in human liver metabolizes approximately half the drugs in clinical use and requires electrons supplied from NADPH through NADPH-P450 reductase (POR, CPR). Mutations in human POR cause a rare form of congenital adrenal hyperplasia from diminished activities of steroid metabolizing P450s. In this study we examined the effect of mutations in POR on CYP3A4 activity. We used purified preparations of wild type and mutant human POR and in vitro reconstitution with purified CYP3A4 to perform kinetic studies. We are reporting that mutations in POR identified in patients with disordered steroidogenesis/Antley-Bixler syndrome (ABS) may reduce CYP3A4 activity, potentially affecting drug metabolism in individuals carrying mutant POR alleles. POR mutants Y181D, A457H, Y459H, V492E and R616X had more than 99% loss of CYP3A4 activity, while POR mutations A287P, C569Y and V608F lost 60-85% activity. Loss of CYP3A4 activity may result in increased risk of drug toxicities and adverse drug reactions in patients with POR mutations.     

Antituberculosis drug-induced hepatitis: risk factors, prevention and management

Apart from infectious or viral hepatitis, other most common non-infectious causes of hepatitis are alcohol, cholestatic, drugs and toxic materials. The most common mode that leads to liver injuries is antituberculosis drug-induced hepatitis. The severity of drug-induced liver injury varies from minor nonspecific changes in hepatic structure to fulminant hepatic failure, cirrhosis and liver cancer. Patients receiving antitubercular drug frequently develop acute or chronic hepatitis. The time required for the metabolites to reach hepatotoxic levels is much earlier with isoniazid plus rifampicin treatment than isoniazid alone and this has been shown to be synergistic rather than additive. Antituberculosis drug (ATT)-inducible cytochrome P-4502E1 (CYP2E1) is constitutively expressed in the liver. Recent studies show that polymorphism of the N-acetyltransferase 2 (NAT2) genes and glutathione-S-transferase (GST) are the major susceptibility risk factors for ATT-induced hepatitis. The hepatic NAT and GST are involved in the metabolism of several carcinogenic arylamines and drugs. The NAT2 enzyme has a genetic polymorphism in human. N-acetyltransferase 2 genes (NAT2) have been identified to be responsible for genetic polymorphism of slow and rapid acetylation in humans. Slow acetylators of NAT2 prove to develop more severe hepatotoxicity than rapid acetylators making it a significant risk factor. Deficiency of GST activity, because of homozygous null mutations at GSTM1 and GSTT1 loci, may modulate susceptibility to drug and xenobiotic-induced hepatotoxicity. Polymorphisms at GSTM1, GSTT1 and NAT2 loci had been linked to various forms of liver injury, including hepatocellular carcinoma.     

Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions

Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69); loratadine and alprazolam (RR = 1.86); loratadine and duloxetine (RR = 1.94); loratadine and ropinirole (RR = 3.21); and promethazine and tegaserod (RR = 3.00). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms.     

Drugs impact on CYP-450 enzyme family: A pharmacogenetical study of response variation

Pharmacogenetics is the study of genetic basis in the individual response to drugs. A thorough knowledge of this will lead to a future where tailor-made drugs, suiting an individual, can be used. Scandinavian countries have been known for wide usage of pharmacogenetics and the most widely used application is for genotyping CYP2D6 in treating psychiatric illness. The CYP-450 enzyme, a super family of microsomal drug-metabolizing enzymes, is the most important of enzymes that catalyzes phase-I drug metabolism reaction. CYP2D6 is a member of this family and it has been most intensively studied and the best example of pharmacogenetics variation in drug metabolism. Neuro-transmitter and drug acting CNS viz. codeine, dextromethorphan, metoprolol and tryptyline etc. are well metabolized by this enzyme. Thus, CYP2D6 is one of the most important and responsible enzymes which regulates bioavailability and metabolism of drug. Presently 75 alleles of CYP2D6 have been described which are responsible for variance of metabolism and toxicity of drugs. Thus, by determining variance of CYP2D6 using molecular approaches viz., PCR, real-time PCR, DNA micro-array and molecular docking can determine the adverse effects, drug toxicity, bioavailability and therapeutic potential of new drug.     

CYP3A4 and pregnane X receptor humanized mice

Marked species differences exist in P450 expression and activities. In order to produce mouse models that can be used to more accurately predict human drug and carcinogen metabolism, P450- and xenobiotic receptor humanized mice are being prepared using bacterial artificial chromosomes (BAC) and P1 phage artificial chromosomes (PAC) genomic clones. In some cases, transgenic mice carrying the human genes are bred with null-mice to produce fully humanized mice. Mice expressing human CYP1A1, CYP1A2, CYP2E1, CYP2D6, CYP3A4, and CYP3A7 were generated and characterized. Studies with the CYP3A4-humanized (hCYP3A4) mouse line revealed new information on the physiological function of this P450 and its role in drug metabolism in vivo. With this mouse line, CYP3A4, under certain circumstances, was found to alter the serum levels of estrogen resulting in deficient lactation and low pup survival as a result of underdeveloped mammary glands. This hCYP3A4 mouse established the importance of intestinal CYP3A4 in the pharmacokinetics of orally administered drugs. The hCYP3A4 mice were also used to establish the mechanisms of potential gender differences in CYP3A4 expression (adult female > adult male) that could account for human gender differences in drug metabolism and response. The pregnane X receptor (PXR) is also involved in induction of drug metabolism through its target genes including CYP3A4. Since species differences exist in ligand specificity between human and mice, a PXR-humanized mouse (hPXR) was produced that responds to human PXR activators such as rifampicin but does not respond to the rodent activator pregnenalone 16alpha-carbonitrile.     

Harvesting Candidate Genes Responsible for Serious Adverse Drug Reactions from a Chemical-Protein Interactome

Identifying genetic factors responsible for serious adverse drug reaction (SADR) is of critical importance to personalized medicine. However, genome-wide association studies are hampered due to the lack of case-control samples, and the selection of candidate genes is limited by the lack of understanding of the underlying mechanisms of SADRs. We hypothesize that drugs causing the same type of SADR might share a common mechanism by targeting unexpectedly the same SADR-mediating protein. Hence we propose an approach of identifying the common SADR-targets through constructing and mining an in silico chemical-protein interactome (CPI), a matrix of binding strengths among 162 drug molecules known to cause at least one type of SADR and 845 proteins. Drugs sharing the same SADR outcome were also found to possess similarities in their CPI profiles towards this 845 protein set. This methodology identified the candidate gene of sulfonamide-induced toxic epidermal necrolysis (TEN): all nine sulfonamides that cause TEN were found to bind strongly to MHC I (Cw*4), whereas none of the 17 control drugs that do not cause TEN were found to bind to it. Through an insight into the CPI, we found the Y116S substitution of MHC I (B*5703) enhances the unexpected binding of abacavir to its antigen presentation groove, which explains why B*5701, not B*5703, is the risk allele of abacavir-induced hypersensitivity. In conclusion, SADR targets and the patient-specific off-targets could be identified through a systematic investigation of the CPI, generating important hypotheses for prospective experimental validation of the candidate genes.     

Network controllability-based algorithm to target personalized driver genes for discovering combinatorial drugs of individual patients

Multiple driver genes in individual patient samples may cause resistance to individual drugs in precision medicine. However, current computational methods have not studied how to fill the gap between personalized driver gene identification and combinatorial drug discovery for individual patients. Here, we developed a novel structural network controllability-based personalized driver genes and combinatorial drug identification algorithm (CPGD), aiming to identify combinatorial drugs for an individual patient by targeting personalized driver genes from network controllability perspective. On two benchmark disease datasets (i.e. breast cancer and lung cancer datasets), performance of CPGD is superior to that of other state-of-the-art driver gene-focus methods in terms of discovery rate among prior-known clinical efficacious combinatorial drugs. Especially on breast cancer dataset, CPGD evaluated synergistic effect of pairwise drug combinations by measuring synergistic effect of their corresponding personalized driver gene modules, which are affected by a given targeting personalized driver gene set of drugs. The results showed that CPGD performs better than existing synergistic combinatorial strategies in identifying clinical efficacious paired combinatorial drugs. Furthermore, CPGD enhanced cancer subtyping by computationally providing personalized side effect signatures for individual patients. In addition, CPGD identified 90 drug combinations candidates from SARS-COV2 dataset as potential drug repurposing candidates for recently spreading COVID-19.     

Genetics-directed drug discovery for combating Mycobacterium tuberculosis infection

Mycobacterium tuberculosis (Mtb), the pathogen of tuberculosis (TB), is one of the most infectious bacteria in the world. The traditional strategy to combat TB involves targeting the pathogen directly; however, the rapid evolution of drug resistance lessens the efficiency of this anti-TB method. Therefore, in recent years, some researchers have turned to an alternative anti-TB strategy, which hinders Mtb infection through targeting host genes. In this work, using a theoretical genetic analysis, we identified 170 Mtb infection-associated genes from human genetic variations related to Mtb infection. Then, the agents targeting these genes were identified to have high potential as anti-TB drugs. In particular, the agents that can target multiple Mtb infection-associated genes are more druggable than the single-target counterparts. These potential anti-TB agents were further screened by gene expression data derived from connectivity map. As a result, some agents were revealed to have high interest for experimental evaluation. This study not only has important implications for anti-TB drug discovery, but also provides inspirations for streamlining the pipeline of modern drug discovery.