Cancer Pharmacogenomics: SNPs, Chips, and the Individual Patient

Impact of germline and somatic missense variations on drug binding sites

Advancements in next-generation sequencing (NGS) technologies are generating a vast amount of data. This exacerbates the current challenge of translating NGS data into actionable clinical interpretations. We have comprehensively combined germline and somatic nonsynonymous single-nucleotide variations (nsSNVs) that affect drug binding sites in order to investigate their prevalence. The integrated data thus generated in conjunction with exome or whole-genome sequencing can be used to identify patients who may not respond to a specific drug because of alterations in drug binding efficacy due to nsSNVs in the target protein's gene. To identify the nsSNVs that may affect drug binding, protein–drug complex structures were retrieved from Protein Data Bank (PDB) followed by identification of amino acids in the protein–drug binding sites using an occluded surface method. Then, the germline and somatic mutations were mapped to these amino acids to identify which of these alter protein–drug binding sites. Using this method we identified 12 993 amino acid–drug binding sites across 253 unique proteins bound to 235 unique drugs. The integration of amino acid–drug binding sites data with both germline and somatic nsSNVs data sets revealed 3133 nsSNVs affecting amino acid–drug binding sites. In addition, a comprehensive drug target discovery was conducted based on protein structure similarity and conservation of amino acid–drug binding sites. Using this method, 81 paralogs were identified that could serve as alternative drug targets. In addition, non-human mammalian proteins bound to drugs were used to identify 142 homologs in humans that can potentially bind to drugs. In the current protein–drug pairs that contain somatic mutations within their binding site, we identified 85 proteins with significant differential gene expression changes associated with specific cancer types. Information on protein–drug binding predicted drug target proteins and prevalence of both somatic and germline nsSNVs that disrupt these binding sites can provide valuable knowledge for personalized medicine treatment. A web portal is available where nsSNVs from individual patient can be checked by scanning against DrugVar to determine whether any of the SNVs affect the binding of any drug in the database.

Pharmacogenomics of fluorouracil -based chemotherapy toxicity

INTRODUCTION

5- fluorouracil (5-FU), alone or in combination, is the most prevalent and effective chemotherapeutic agent for the treatment of cancers of the head and neck, breast, pancreas and gastrointestinal tract.

AREAS COVERED

Three rare DPYD mutations, a splice mutation in intron 14 (c.1905+1G>A) and two nonsynonymous coding variants (c.1679T>G, c.2846A>T), have consistently been associated with severe 5-FU toxicity. A relatively common haplotype, hapB3, containing three intronic polymorphisms (c.483+18G>A; c.680+139G>A; c.959-51T>C) and a synonymous mutation c.1236G>A linked to c.1129-5923C>G, is a major contributor to early onset severe toxicity. TYMS VNTR 2R and TYMS-3'-UTR 6-bp ins-del variants were associated with global toxicity in capecitabine-treated patients. A candidate gene study of capecitabine-related toxicity reported that the s12132152 were strongly associated with hand-foot syndrome (HFS), whereas rs7548189 was associated with diarrhea. The rs2612091 and rs2741171, which are downstream of TYMS and intronic for ENOSF1, were associated with increased global toxicity and HFS.

EXPERT OPINION

Sex-dependent differences, ethnicity, cancer types and 5-FU-based chemotherapy regimens might affect the heterogeneity of genetic variants for predictive 5-FU-related toxicity. Future approaches using genome-wide association analyses may help in identifying additional candidate genes causally involved in the path mechanisms of 5-FU-related toxicity.

Genetic polymorphisms and microRNAs: new direction in molecular epidemiology of solid cancer

MicroRNAs (miRNAs) are small non-coding RNAs, which regulate gene expression. Single nucleotide polymorphisms (SNPs) may occur in miRNA biogenesis pathway genes, primary miRNA, pre-miRNA or a mature miRNA sequence. Such polymorphisms may be functional with respect to biogenesis and actions of mature miRNA. Specific SNPs were identified in predicted miRNA target sites within 3′ untranslated regions of mRNAs. These SNPs have a potential to affect the efficiency of miRNA binding to the target sites or can create or disrupt binding sites. Resulting gene dysregulation may involve changes in phenotype and may eventually prove critical for the susceptibility to cancer and its onset as well as for estimates of prognosis and therapy response. In this review, we provide a comprehensive list of potentially functional miRNA-related SNPs and summarize their importance as candidate cancer biomarkers.

Proteomics for identifying mechanisms and biomarkers of drug resistance in cancer

A major problem in chemotherapy of cancer patients is drug resistance as well as unpredictable response to treatment. During chemotherapy, multiple alterations of genetics and epigenetics that contribute to chemoresistance take place, eventually impacting on disease outcome. A more complex picture of the mechanisms of drug resistance is now emerging through application of high-throughput proteomics technology. We have entered an exciting time where proteomics are being applied to characterize the mechanisms of drug resistance, and to identify biomarkers for predicting response to chemotherapy, thereby leading to personalized therapeutic strategies of cancer patients. Comparative proteomics have identified a large number of differentially expressed proteins associated with chemoresistance. Although roles and mechanisms of such proteins in chemoresistance need to be further proved, at least some of them may be potential biomarkers for predicting chemotherapeutic response. Herein, we review the recent advancements on proteomic investigation of chemoresistance in human cancer, and emphasize putative biomarkers for predicting chemotherapeutic response and possible mechanisms of chemoresistance identified through proteomic approaches. Suggested avenues for future work are discussed.

Molecular response prediction in multimodality treatment for adenocarcinoma of the esophagus and esophagogastric junction

Cancers arising from the esophagus are becoming more common in the United States and Europe. In 2009, an estimate of 14,530 new cases will be diagnosed and more than 90% will die of their disease. Esophageal cancer is currently the most rapidly increasing cancer in the western world and is coinciding with a shift in histological type and primary tumor location. Despite recent improvements in the detection, surgical resection, and (radio-) chemotherapy, the overall survival (OS) of esophageal cancer remains relatively poor. It is becoming increasingly apparent that neoadjuvant chemoradiation followed by surgery may be beneficial in terms of increasing resectability and OS compared to surgery alone. Results from clinical trials are encouraging; however, they also demonstrated that only patients with major histopathological response (pCR) will benefit from neoadjuvant therapy. In addition, these therapies are expensive and the prognoses of patients who do not respond to trimodality treatment strategies appear to be inferior to that of patients who had surgery alone. Accordingly, the development of validated predictive molecular markers may not only be helpful in identifying EA patients who are more likely to respond, but they will also be critical in selecting more efficient treatment strategies with the means of a tailored, targeted, and effective therapy to the molecular profile of both the patient and their disease while minimizing and avoiding life-threatening toxicities.

Molecular markers in the treatment of metastatic colorectal cancer

Although significant progress has been made in colorectal cancer (CRC) treatment within the last decade with the approval of multiple new agents, the prognosis for patients with metastatic CRC remains poor with 5-year survival rates of approximately 8%. Resistance to chemotherapy remains a major obstacle in effective CRC treatment and many patients do not receive any clinical benefit from chemotherapy. In addition, other patients will experience adverse reactions to treatment resulting in dose modifications or treatment withdrawal, which can severely reduce treatment efficacy. Currently, significant research efforts are attempting to identify reliable and validated biomarkers with which will guide clinicians to make more informed treatment decisions. Specifically, the use of molecular profiling has the potential to assist the clinician in administering the correct drug, dose, or intervention for the patient before the onset of therapy thereby selecting a treatment strategy likely to have the greatest clinical outcome while minimizing adverse events. However, until recently, personalized medicine is a paradigm that has existed more in conceptual terms than in reality with very few validated biomarkers used routinely in metastatic CRC treatment. Rapid advances in genomic, transcriptomic and proteomic technologies continues to improve our understanding of tumor biology, but the search for reliable biomarkers has turned out to be more challenging than previously anticipated with significant disparity in published literature and limited translation into routine clinical practice. Recent progress with the identification and validation of biomarkers to the anti-epidermal growth factor receptor monoclonal antibodies including KRAS and possibly BRAF provide optimism that the goal of individualized treatment is within reach. This review will highlight and discuss current progress in the search for biomarkers, the challenges this emerging field presents, and the future role of biomarkers in advancing CRC treatment.

Thymidylate synthase gene variations: predictive and prognostic markers

Since its introduction more than 50 years ago by Heidelberger et al., the fluoropyrimidine 5-fluorouracil (5-FU) has remained the mainstay of therapeutic regimens used in the treatment of colorectal cancer and other human malignancies, with single-agent response rates of 20% to 25% in advanced disease stage. Pharmacogenomics has emerged as a useful tool to address interindividual gene variations by analyzing the interplay of host and tumor genotype and drug efficacy and toxicity. Having a reliable panel of prognostic and predictive markers will be critical in selecting an individualized and tailored chemotherapy regimen based on the particular tumor and host genotype. Although conflicting results have been reported, higher thymidylate synthase (TS) protein and mRNA expression levels in tumors have generally been associated with poor clinical outcome in patients treated with 5-FU-based chemotherapy regimens. However, the cause of the variability in TS expression still remains not fully understood, although several germ-line polymorphisms seem to affect the expression of TS, some of which have been found to have an effect on prognosis and the probability of response to 5-FU-based chemotherapy. This review will provide an update on pharmacogenomic studies of TS that were aimed at elucidating their role as prognostic and predictive markers.

Exploring alternative individualized treatment strategies in colorectal cancer

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in men and women in the United States, with a predicted 154,000 new cases this year. For > 40 years, 5-fluorouracil (5-FU) has remained the central agent in therapeutic regimens used in the treatment of CRC, with single-agent response rates (RRs) of 20%-25% in advanced-stage disease. The past decade has witnessed the introduction of newer agents, such as the DNA-damaging agents oxaliplatin and irinotecan, which when used in combination with 5-FU, have dramatically increased RRs to 40%-50% in advanced disease and improved overall survival. The development of monoclonal antibodies targeting the epidermal growth factor receptor or vascular endothelial growth factor have now demonstrated additional clinical benefit for patients with metastatic disease, and the clinical development of these agents continues to progress. However, many patients will die, and a significant proportion will experience severe chemotherapy-induced toxicities, while deriving little or no benefit. Global efforts are currently under way to identify reliable and validated cassettes of markers with the ability to predict response and toxicity from a chemotherapeutic regimen. In addition, the ability to accurately predict patients with early-stage disease at high risk of recurrence will enable the appropriate administration of adjuvant therapy. The emerging cancer stem cell hypothesis continues to gain momentum with ongoing research, suggesting this might become one of the prime targets for future therapy. Together, these approaches are spearheading a paradigm shift toward individualized treatment strategies in CRC treatment.

Modelling the influence of MDR1 polymorphism on digoxin pharmacokinetic parameters

OBJECTIVES

Digoxin is a well-known probe for the activity of P-glycoprotein. The objective of this work was to apply different methods for covariate selection in non-linear mixed-effect models to study the relationship between the pharmacokinetic parameters of digoxin and the genotype for two major exons located on the multi-drug-resistance 1 (MDR1) gene coding for P-glycoprotein.

METHODS

Thirty-two healthy volunteers were recruited in three pharmacokinetic drug interaction studies. The data after a single oral administration of digoxin alone were pooled. All subjects were genotyped for the MDR1 C3435T and G2677T/A genotypes. The concentration-time profile of digoxin was established using 12-16 blood samples taken between 15 min and 72 h after administration. We modelled the pharmacokinetics of digoxin using non-linear mixed-effect models. Parameter estimation was performed using the stochastic approximation EM method (SAEM). We used three methods to select the covariate model: selection from a full model using Wald tests, forward inclusion using the log-likelihood ratio test and model selection using the Bayesian Information Criterion.

RESULTS

The three covariate inclusion methods led to the same final model. Carriers of two T alleles for the C3435T polymorphism in exon 26 of MDR1 had a lower apparent volume of distribution than carriers of a C allele. The only other covariate effect was a shorter absorption time-lag in women.

CONCLUSION

The apparent volume of distribution of digoxin is lower in TT subjects, probably reflecting differences in bioavailability. Non-linear mixed-effect models can be useful for detecting the influence of covariates on pharmacokinetic parameters.

Molecular-based choice of cancer therapy: realities and expectations

Current choice of cancer therapy is usually empirical and relies mainly on the statistical prediction of the treatment success. Molecular research provides some opportunities to personalize antitumor treatment. For example, life-threatening toxic reactions can be avoided by the identification of subjects, who carry susceptible genotypes of drug-metabolizing genes (e.g. TPMT, UGT1A1, MTHFR, DPYD). Tumor sensitivity can be predicted by molecular portraying of targets and other molecules associated with drug response. Tailoring of antiestrogen and trastuzumab therapy based on hormone and HER2 receptor status has already become a classical example of customized medicine. Other predictive markers have been identified both for cytotoxic and for targeted therapies, and include, for example, expression of TS, TP, DPD, OPRT, ERCC1, MGMT, TOP2A, class III beta-tubulin molecules as well as genomic alterations of EGFR, KIT, ABL oncogenes.

Human pharmacogenomic variations and their implications for antifungal efficacy

Pharmacogenomics is defined as the study of the impacts of heritable traits on pharmacology and toxicology. Candidate genes with potential pharmacogenomic importance include drug transporters involved in absorption and excretion, phase I enzymes (e.g., cytochrome P450-dependent mixed-function oxidases) and phase II enzymes (e.g., glucuronosyltransferases) contributing to metabolism, and those molecules (e.g., albumin, A1-acid glycoprotein, and lipoproteins) involved in the distribution of antifungal compounds. By using the tools of population genetics to define interindividual differences in drug absorption, distribution, metabolism, and excretion, pharmacogenomic models for genetic variations in antifungal pharmacokinetics can be derived. Pharmacogenomic factors may become especially important in the treatment of immunocompromised patients or those with persistent or refractory mycoses that cannot be explained by elevated MICs and where rational dosage optimization of the antifungal agent may be particularly critical. Pharmacogenomics has the potential to shift the paradigm of therapy and to improve the selection of antifungal compounds and adjustment of dosage based upon individual variations in drug absorption, metabolism, and excretion.

Azathioprine dosed by thiopurine methyltransferase activity for moderate-to-severe atopic eczema: a double-blind, randomised controlled trial

BACKGROUND

Atopic eczema affects 1-2% of adults, and can cause considerable morbidity. We aimed to assess the safety and efficacy of azathioprine as systemic monotherapy for moderate-to-severe atopic eczema, and the therapeutic importance of the thiopurine methyltransferase (TPMT) polymorphism (a key determinant of azathioprine-induced myelotoxicity) by using TPMT enzyme activity to establish azathioprine dose.

METHODS

We did a parallel-group, double-blind, placebo-controlled trial in an outpatient setting. Minimisation was used to assign 63 patients with active disease despite optimum topical therapy to treatment with azathioprine (n=42) or placebo (n=21) for 12 weeks. As maintenance treatment, patients with heterozygous range TPMT activity received azathioprine 1.0 mg/kg daily, compared with 2.5 mg/kg daily in patients with normal TPMT activity. For the first 4 weeks, all participants received lower azathioprine doses (0.5 and 1.0 mg/kg daily, respectively) to reduce gastrointestinal side-effects. The primary measure of clinical response was disease activity assessed by the SASSAD (six area six sign atopic dermatitis) score. Analysis was by intention-to-treat. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN58943280.

FINDINGS

54 (86%) participants completed the study; two (3%) withdrew from the placebo group and seven (11%) from the azathioprine group. At week 12, there was a 37% (12.0 unit) improvement in mean disease activity with azathioprine compared with a 20% (6.6 unit) improvement with placebo (17% [5.4 unit] difference, 95% CI 4.3-29%). This finding was accompanied by significant improvements in patient-reported itch, area of involvement, global assessment, and quality of life. Between participants there was a wide variation in response to the drug. Generally, azathioprine was well tolerated, although two individuals developed drug hypersensitivity. Participants with heterozygous range TPMT activity responded to azathioprine in similar proportions to other participants, but none developed bone-marrow toxicity. TPMT-based dosing seemed to reduce predicted toxicity, and drug efficacy was maintained.

INTERPRETATION

Treatment with azathioprine as systemic monotherapy produces clinically relevant improvement in moderate-to-severe atopic eczema that remains active despite optimum therapy with topical corticosteriods. We believe the study of azathioprine as systemic monotherapy for atopic eczema has major advantages, which should allow clarification of the relation between azathioprine effectiveness and metabolite profiles in other inflammatory diseases.

High-throughput techniques in breast cancer: A clinical perspective

High-throughput technologies such as DNA-microarrays, RT-PCR and proteomics can improve the prognostic and predictive information acquired from classical parameters. Unlike information gathered by classical methods, high-throughput technologies can accurately inform clinicians on patient response to adjuvant therapy or those who will resist the effect of that therapy. Studies performed in breast cancer with high-throughput techniques have focused on tumour biology, prognosis, prediction of response to a few agents and, more recently, early diagnosis. However, further refinement is needed before these techniques become part of clinical routine. In the meantime, they will be used in clinical investigation, particularly in the areas of hormonal therapy and adjuvant chemotherapy, where modest improvements in the capacity of prediction can benefit many women. Close cooperation among clinicians, pathologists and basic investigators is essential to take high-throughput techniques to daily practice. New diagnostic tools will be complex but they will provide valuable patient information.

Genetic determinants of cancer drug efficacy and toxicity: practical considerations and perspectives

Drug-metabolizing enzymes are responsible for the activation or detoxification of cytotoxic drugs. Allelic variants are present with a variable frequency in different populations around the world and have an important role in the therapeutic index of such drugs. It is known that polymorphisms in thiopurine methyltransferase and dihydropyrimidine dehydrogenase have been associated with altered drug metabolism and increased risk of severe toxicity from 6-mercaptopurine and 5-fluorouracil, respectively. Additionally, a variant number of dinucleotide-repeat sequences in the promotor for uridine 5'-diphosphate glucuronosyltransferase 1A1 influences the glucuronidation of SN-38, the active metabolite of irinotecan, which is associated with severe toxicity, including diarrhea and neutropenia. In the same way, polymorphisms in thymidylate synthase have been associated with pyrimidine-associated toxicity and also with response to chemotherapy. The examples shown in this review demonstrate the usefulness of pre-screening patients for well-characterized polymorphism to identify the best-tolerated and most-effective treatment.

Genetics and the Dutch Hypothesis

BACKGROUND

Increasingly, molecular genetic techniques are being used to improve our understanding of a number of common late onset complex disorders, such as hypertension, Alzheimer's disease and noninsulin dependent diabetes mellitus. Molecular genetic approaches have the potential to yield new information about disease pathogenesis that may be of great importance for the development of future treatments.

AIMS

This review discusses the evidence for a genetic contribution to the development of chronic obstructive pulmonary disease (COPD) and specifically focuses on the hypothesis that asthma and COPD share some pathogenic mechanisms as originally proposed in 1960 in a theory that has since become known as the Dutch Hypothesis. In particular we will review the evidence from molecular genetics, both in support of and against the theory.

Cancer pharmacogenomics: powerful tools in cancer chemotherapy and drug development

Interindividual differences in tumor response and normal tissue toxicities are consistently observed with most chemotherapeutic agents or regimens. While many clinical variables have been associated with drug responses (e.g., age, gender, diet, drug-drug interactions), inherited variations in drug disposition (metabolism and transport) genes and drug target genes also likely contribute to the observed variability in cancer treatment outcome. Pharmacogenomic studies aim to elucidate the genetic bases for interindividual differences and to use such genetic information to predict the safety, toxicity, and/or efficacy of drugs. There exist several clinically relevant examples of the utility of pharmacogenomics that associate specific genetic polymorphisms in drug metabolizing enzymes (e.g., TPMT, UGT1A1, DPD), drug transporters (MDR1), and drug target enzymes (TS) with clinical outcomes in patients treated with commonly prescribed chemotherapy drugs, such as 5-fluorouracil and irinotecan (Camptosar; Pfizer Pharmaceuticals; New York, NY http://www.pfizer.com). Techniques to discover and evaluate the functional significance of these polymorphisms have evolved in recent years and may soon be applied to clinical practice and clinical trials of currently prescribed anticancer drugs as well as new therapeutic agents. This review discusses the current and future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.

Genomic and proteomic technologies for individualisation and improvement of cancer treatment

The development of microarray-based technologies for characterising tumours, both at the genomic and proteomic levels, has had a significant impact on the field of oncology. Gene expression profiling of various human tumour tissues has led to the identification of expression patterns related to disease outcome and drug resistance, as well as to the discovery of new therapeutic targets and insights into disease pathogenesis. Protein microarray technologies, such as reverse-phase protein arrays, provide the unique opportunity to profile tissues and assess the activity of signalling pathways within isolated cell populations. This technology can be used to identify patients likely to benefit from specific treatment modalities and also to monitor therapeutic response in samples obtained during and after treatment. Routine application of genomic and proteomic microarray technologies in clinical practice will require significant efforts to standardise the techniques, controls and reference standards, and analytical tools used. Extensive, independent validation using large, statistically-powered datasets will also be necessary. Inclusion of concomitant genomic and proteomic-based molecular profiling techniques into clinical trial protocols will bring us closer to the reality of patient-tailored therapy.

A model of survivorship in cancer genetic care

OBJECTIVES

To propose a shift in the paradigm of survivorship in genetic cancer care.

DATA SOURCES

Published articles and, studies.

CONCLUSION

Previous models of survivorship are insufficient to address the evolving needs of patients and families with heritable cancers. The construction of a new model of survivorship is needed to address the unique concerns of individuals who have undergone hereditary cancer risk assessment and counseling.

IMPLICATIONS FOR NURSING PRACTICE

Health care providers must be familiar with the recommendations for treatment, surveillance, and follow-up care for individuals and families with heritable cancers to maximize their quantity and quality of life.

From pharmacogenetics to personalized medicine: a vital need for educating health professionals and the community

The field of pharmacogenetics will soon celebrate its 50th anniversary. Although science has delivered an impressive amount of information in these 50 years, pharmacogenetics has suffered from lack of integration into clinical practice. There are several reasons for this, including the unmet need for education at medical schools and the lack of awareness about the impact of genetic medicine on healthcare in the community. Recently, the FDA announced that it considers pharmacogenomics one of three major opportunities on the critical path to new medical products. This notion by the FDA is filling the regulatory void that existed between drug developers and drug users. However, in order to bring pharmacogenetic testing to the prescription pad successfully, healthcare professionals and policy makers, as well as patients, need to have the necessary background knowledge for making educated treatment decisions. To effectively move pharmacogenetics into everyday medicine, it is therefore imperative for scientists and teachers in the field to take on the challenge of disseminating pharmacogenetic insights to a broader audience.

Primer on medical genomics. Part XII: Pharmacogenomics--general principles with cancer as a model

The Human Genome Project has resulted in a new era in the field of pharmacogenetics in which researchers are rapidly discovering new genetic variation, which may help to explain interindividual variability in drug efficacy and toxicity. Pharmacogenetics is the study of the role of genetic inheritance in individual variation in drug response and toxicity. With the convergence of advances in pharmacogenetics and human genomics, the field of pharmacogenomics has emerged during the past decade. Pharmacogenomics is used to refer to the study of the relationship between specific DNA-sequence variation and drug effect. In few other disciplines of medicine are the clinical examples of pharmacogenetics more striking than in oncology. In this field, treatment of patients with cancer is accomplished primarily through the use of chemotherapeutic drugs that have narrow therapeutic indexes, ie, the difference between the toxic and therapeutic dose is relatively small. In this review, we discuss several selected, clinically relevant examples of ways in which sequence variation in genes that encode drug enzymes, transporters, and drug targets can alter the efficacy and/or adverse-effect profile of "standard" doses of chemotherapeutic drugs. Additionally, we discuss some of the ways in which physicians are currently applying this knowledge in the treatment of patients with cancer.