Recent development in pharmacogenomics: from candidate genes to genome-wide association studies

Considering hormone-sensitive cancers as a single disease in the UK biobank reveals shared aetiology

Hormone-related cancers, including cancers of the breast, prostate, ovaries, uterine, and thyroid, globally contribute to the majority of cancer incidence. We hypothesize that hormone-sensitive cancers share common genetic risk factors that have rarely been investigated by previous genomic studies of site-specific cancers. Here, we show that considering hormone-sensitive cancers as a single disease in the UK Biobank reveals shared genetic aetiology. We observe that a significant proportion of variance in disease liability is explained by the genome-wide single nucleotide polymorphisms (SNPs), i.e., SNP-based heritability on the liability scale is estimated as 10.06% (SE 0.70%). Moreover, we find 55 genome-wide significant SNPs for the disease, using a genome-wide association study. Pair-wise analysis also estimates positive genetic correlations between some pairs of hormone-sensitive cancers although they are not statistically significant. Our finding suggests that heritable genetic factors may be a key driver in the mechanism of carcinogenesis shared by hormone-sensitive cancers.

Integration of pharmacogenomics and theranostics with nanotechnology as quality by design (QbD) approach for formulation development of novel dosage forms for effective drug therapy

To cater to medication needs in the future healthcare system, we need to shift from the conventional system of drug delivery to modern molecular signature-based drug delivery systems. The current drug therapies are either less effective, ineffective, or produce numerous adverse reactions. One scientific principle or discipline cannot adequately address all the problems, so we need an innovative application of the current scientific principles. Here we are proposing a novel concept of nanoformulation based on pharmacogenomics and theranostics for personalized error-free and targeted therapeutic agent delivery. The addition of more knowledge about the human genome opens the new way to study disease-gene, gene-drug, and drug-effect interactions, which is the basis of future medicines. Pharmacogenomics provides information about the disease etiology, role in genes in disease pathophysiology, disease biomarkers, drug targets, drug effects, and the fate of drugs inside the body. Theranostics approach utilizes the above information in diagnosis, treatment, and monitoring of the disease on a real-time basis. Personalized dosage forms can be formulated into a nanoformulation that provides a better therapeutic effect and minimizes adverse drug reactions. The therapeutic system needs to be shifted from the principle of one drug fits all to one drug unique population. In the present manuscript, we tried to conceptualize a modern therapeutic system by combining the three approaches viz. pharmacogenomics, theranostics, and nanotechnology applied in the area of formulation development to produce a multifunctional single tiny entity.

Impact of New Genomic Technologies on Understanding Adverse Drug Reactions

It is well established that variations in genes can alter the pharmacokinetic and pharmacodynamic profile of a drug and immunological responses to it. Early advances in pharmacogenetics were made with traditional genetic techniques such as functional cloning of genes using knowledge gained from purified proteins, and candidate gene analysis. Over the past decade, techniques for analysing the human genome have accelerated greatly as knowledge and technological capabilities have grown. These techniques were initially focussed on understanding genetic factors of disease, but increasingly they are helping to clarify the genetic basis of variable drug responses and adverse drug reactions (ADRs). We examine genetic methods that have been applied to the understanding of ADRs, review the current state of knowledge of genetic factors that influence ADR development, and discuss how the application of genome-wide association studies and next-generation sequencing approaches is supporting and extending existing knowledge of pharmacogenetic processes leading to ADRs. Such approaches have identified single genes that are major contributing genetic risk factors for an ADR, (such as flucloxacillin and drug-induced liver disease), making pre-treatment testing a possibility. They have contributed to the identification of multiple genetic determinants of a single ADR, some involving both pharmacologic and immunological processes (such as phenytoin and severe cutaneous adverse reactions). They have indicated that rare genetic variants, often not previously reported, are likely to have more influence on the phenotype than common variants that have been traditionally tested for. The problem of genotype/phenotype discordance affecting the interpretation of pharmacogenetic screening and the future of genome-based testing applied to ADRs are also discussed.

Enhancing Literacy in Cardiovascular Genetics: A Scientific Statement From the American Heart Association

Advances in genomics are enhancing our understanding of the genetic basis of cardiovascular diseases, both congenital and acquired, and stroke. These advances include finding genes that cause or increase the risk for childhood and adult-onset diseases, finding genes that influence how patients respond to medications, and the development of genetics-guided therapies for diseases. However, the ability of cardiovascular and stroke clinicians to fully understand and apply this knowledge to the care of their patients has lagged. This statement addresses what the specialist caring for patients with cardiovascular diseases and stroke should know about genetics; how they can gain this knowledge; how they can keep up-to-date with advances in genetics, genomics, and pharmacogenetics; and how they can apply this knowledge to improve the care of patients and families with cardiovascular diseases and stroke.

Genetic Variations in Vesicoureteral Reflux Sequelae

Urinary tract infections (UTI) are a common condition in children. Vesicoureteral reflux (VUR) represents a common associated condition with childhood UTI. UTI susceptibility appears to have a genetic component based on family and UTI cohort studies. Targeted analysis of innate immune system genetic variations indicate that these variations are important in UTI susceptibility. In this overview, we discuss how current cohorts and genetic strategies can be implemented to discover new susceptibility loci in patients with UTI.

Cytogenetically visible copy number variations (CG-CNVs) in banding and molecular cytogenetics of human; about heteromorphisms and euchromatic variants

Background

Copy number variations (CNVs) having no (obvious) clinical effects were rediscovered as major part of human genome in 2004. However, for every cytogeneticist microscopically visible harmless CNVs (CG-CNVs) are well known since decades. Harmless CG-CNVs can be present as heterochromatic or even as euchromatic variants in clinically healthy persons.

Results

Here I provide a review on what is known today on the still too little studied harmless human CG-CNVs, point out which can be mixed up with clinically relevant pathological CG-CNVs and shortly discuss that the artificial separation of euchromatic submicroscopic CNVs (MG-CNVs) and euchromatic CG-CNVs is no longer timely.

Conclusion

Overall, neither so-called harmless heterochromatic nor so-called harmless euchromatic CG-CNVs are considered enough in evaluation of routine cytogenetic analysis and reporting. This holds especially true when bearing in mind the so-called two-hit model suggesting that combination of per se harmless CNVs may lead to clinical aberrations if they are present together in one patient.

Pharmacogenetic associations with vascular endothelial growth factor inhibition in participants with neovascular age-related macular degeneration in the IVAN Study

PURPOSE

To determine if prespecified genetic polymorphisms influence responsiveness to vascular endothelial growth factor (VEGF) inhibition in neovascular age-related macular degeneration (nAMD). The objectives were to replicate 3 reported pharmacogenetic associations of response in nAMD and to test for novel associations.

DESIGN

Cohort study, combining information about patients' genotypes with information from a randomized controlled trial about responsiveness to anti-VEGF therapy for nAMD.

PARTICIPANTS

Five hundred nine participants with nAMD, enrolled in the Alternative Treatments to Inhibit VEGF in Patients with Age-Related Choroidal Neovascularisation (IVAN) trial.

METHODS

Participants were classified as responders or nonresponders to VEGF inhibition based on the optical coherence tomography (OCT) metric of total retinal thickness (TRT). We computed the change in TRT from baseline to the latest time point for which OCT data were available (3, 6, 9, or 12 months). Eyes with changes in TRT greater than or equal to the 75th percentile or more were classified as responders, and those with changes less than or equal to the 25th percentile or lower were classified as non-responders. Three previously reported associations of response to VEGF inhibition in nAMD involving single nucleotide polymorphisms (SNPs) at the CFH, FZD4, and HTRA1/ARMS2 loci were tested for replication. An additional 482 SNPs also were tested using a candidate gene approach. Associations were estimated as odds ratios (ORs) with confidence intervals (CIs).

MAIN OUTCOME MEASURES

The primary outcome was evidence of a genetic association with response to VEGF inhibition as measured by change in TRT.

RESULTS

One hundred twenty-six participants were classified as responders and 128 were classified as nonresponders. The SNP rs10490924 in HTRA1/ARMS2 showed a borderline association with responsiveness after Bonferroni correction (OR, 1.53; CI, 0.99-2.36; P = 0.055, Bonferroni correction). None of the other 484 additional SNPs tested for association was significant after Bonferroni correction for multiple testing. The smallest corrected P value was 0.84 (P = 0.002, uncorrected) for rs9679290 in the EPAS1 (HIF2A) gene on chromosome 2. Four of the 10 most significant results were in this gene.

CONCLUSIONS

We estimated pharmacogenetic associations using high-quality phenotype data from a randomized controlled clinical trial of nAMD. No significant association or replication of previous associations were observed. Further investigation of the EPAS1 (HIF2A) gene, however, may, be merited.

A new way to protect privacy in large-scale genome-wide association studies

Motivation: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues.

Results: We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees.

Contact:jaak.vilo@ut.ee

Supplementary information:Supplementary data are available at Bioinformatics online.

CD6 and syntaxin binding protein 6 variants and response to tumor necrosis factor alpha inhibitors in Danish patients with rheumatoid arthritis

BACKGROUND

TNFα inhibitor therapy has greatly improved the treatment of patients with rheumatoid arthritis, however at least 30% do not respond. We aimed to investigate insertions and deletions (INDELS) associated with response to TNFα inhibitors in patients with rheumatoid arthritis (RA).

METHODOLOGY AND PRINCIPAL FINDINGS

In the DANBIO Registry we identified 237 TNFα inhibitor naïve patients with RA (81% women; median age 56 years; disease duration 6 years) who initiated treatment with infliximab (n=160), adalimumab (n=56) or etanercept (n=21) between 1999 and 2008 according to national treatment guidelines. Clinical response was assessed at week 26 using EULAR response criteria. Based on literature, we selected 213 INDELS potentially related to RA and treatment response using the GeneVa® (Compugen) in silico database of 350,000 genetic variations in the human genome. Genomic segments were amplified by polymerase chain reaction (PCR), and genotyped by Sanger sequencing or fragment analysis. We tested the association between genotypes and EULAR good response versus no response, and EULAR good response versus moderate/no response using Fisher's exact test. At baseline the median DAS28 was 5.1. At week 26, 68 (29%) patients were EULAR good responders, while 81 (34%) and 88 (37%) patients were moderate and non-responders, respectively. A 19 base pair insertion within the CD6 gene was associated with EULAR good response vs. no response (OR=4.43, 95% CI: 1.99-10.09, p=7.211×10(-5)) and with EULAR good response vs. moderate/no response (OR=4.54, 95% CI: 2.29-8.99, p=3.336×10(-6)). A microsatellite within the syntaxin binding protein 6 (STXBP6) was associated with EULAR good response vs. no response (OR=4.01, 95% CI: 1.92-8.49, p=5.067×10(-5)).

CONCLUSION

Genetic variations within CD6 and STXBP6 may influence response to TNFα inhibitors in patients with RA.

Characteristics of successful recruitment in prospective pediatric pharmacogenetic studies

BACKGROUND

There is a need to explore feasible means of accruing an appropriate study cohort to help fill the knowledge gap between pharmacogenetic contributions to drug response and clinical application in the pediatric population.

OBJECTIVES

The aim of this study was to identify factors affecting recruitment of eligible subjects in pharmacogenetic studies at a large Midwestern pediatric academic medical center. The objectives were to evaluate recruitment success of ongoing trials and ascertain contributors to differential recruitment rates. We hypothesized that studies with good recruitment of eligible subjects would share characteristics not present in studies with lower than anticipated recruitment. The goal was to better understand barriers to good recruitment in pharmacogenetic studies to help inform future trial and infrastructure design.

METHODS

Investigators designed a survey with proposed elements of success, which was then completed by lead and/or site investigators of all pharmacogenetics studies at the institution. Results were evaluated using an investigator-developed likelihood of success scoring system.

RESULTS

Two studies recruited >95% of the approached eligible patients; 4 studies were consistent with investigator-anticipated recruitment (>50%), and 1 study did not meet expected recruitment. A study's total score on the investigator-devised scoring tool correlated well with the proportion of approached patients recruited (Pearson's correlation, r = 0.82; P < 0.001). Multiple factors impacted successful recruitment into these pharmacogenetic studies. Features of studies with successful recruitment included standardized clinical care, an ongoing team-patient relationship, severe and/or life-threatening outcome measures, study coordinator with experience in clinical research, a study medication with few or no alternative treatment options, and active involvement of the research team in clinical care.

CONCLUSIONS

A scoring system for study characteristics may be useful to calculate the risk of failure for successful recruitment, allow discrimination among characteristics contributing to the risk, and permit study design alterations to improve likelihood of successful recruitment in pediatric pharmacogenetic studies.

Pharmacogenetics and pharmacogenomics of sexual dysfunction: current status, gaps and potential applications

Although treatment of different types of sexual dysfunction has improved in the past decade with the introduction of phosphodiesterase type 5 inhibitors and selective serotonin reuptake inhibitors, response rates to these targeted therapies are variable. There are a number of studies in the published literature that provide proof-of-concept that genetic variation contributes to the variable response. Pharmacogenomics will most likely be one part of our therapeutic armamentarium in the future and will provide a stronger scientific basis for optimizing drug therapy on the basis of each patient’s genetic constitution. This article will review English language medical literature on the state-of-the-art genetic polymorphisms of drug targets, transporters and signaling molecules as well as pharmacogenetic studies of sexual dysfunction and suggested possible applications. Collectively, the data demonstrate that pharmacogenomics in the field of sexual medicine is still in its infancy. More research will provide further intriguing new discoveries in years to come.

Using expression and genotype to predict drug response in yeast

Personalized, or genomic, medicine entails tailoring pharmacological therapies according to individual genetic variation at genomic loci encoding proteins in drug-response pathways. It has been previously shown that steady-state mRNA expression can be used to predict the drug response (i.e., sensitivity or resistance) of non-genotyped mammalian cancer cell lines to chemotherapeutic agents. In a real-world setting, clinicians would have access to both steady-state expression levels of patient tissue(s) and a patient's genotypic profile, and yet the predictive power of transcripts versus markers is not well understood. We have previously shown that a collection of genotyped and expression-profiled yeast strains can provide a model for personalized medicine. Here we compare the predictive power of 6,229 steady-state mRNA transcript levels and 2,894 genotyped markers using a pattern recognition algorithm. We were able to predict with over 70% accuracy the drug sensitivity of 104 individual genotyped yeast strains derived from a cross between a laboratory strain and a wild isolate. We observe that, independently of drug mechanism of action, both transcripts and markers can accurately predict drug response. Marker-based prediction is usually more accurate than transcript-based prediction, likely reflecting the genetic determination of gene expression in this cross.

Clinical application of cytokine-related gene polymorphism analysis using a newly developed DNA chip in critically ill patients

OBJECTIVES

To investigate the usefulness of analysis of single nucleotide polymorphism (SNP) using a newly developed DNA chip assay involving single base extension(SBE) and subsequent hybridization in cytokine-related genes in critical care patients.

DESIGN AND METHODS

Genotyping was performed in 76 ICU patients admitted to the ICU. First, the DNA samples from 58 patients were subjected to PCR and SBE conditioning for DNA. Second, another 18 patients were subjected to genotyping for SNPs in IL-6 -596G/A, -572C/G, -174G/C, TNF-alpha -308G/A, -238G/A, IL-1beta -511C/T and -31T/C by both TaqMan and DNA chip method, and by DNA direct sequencing prospectively.

RESULTS

First, PCR and SBE condition were established with initial sample sets, which were consistent with results by TaqMan method. Second, no difference was observed between two assay methods in prospective validation set.

CONCLUSIONS

The genotyping assay using the new chip was developed and its usefulness was confirmed.

Generating genome-scale candidate gene lists for pharmacogenomics

A critical task in pharmacogenomics is identifying genes that may be important modulators of drug response. High-throughput experimental methods are often plagued by false positives and do not take advantage of existing knowledge. Candidate gene lists can usefully summarize existing knowledge, but they are expensive to generate manually and may therefore have incomplete coverage. We have developed a method that ranks 12,460 genes in the human genome on the basis of their potential relevance to a specific query drug and its putative indications. Our method uses known gene-drug interactions, networks of gene-gene interactions, and available measures of drug-drug similarity. It ranks genes by building a local network of known interactions and assessing the similarity of the query drug (by both structure and indication) with drugs that interact with gene products in the local network. In a comprehensive benchmark, our method achieves an overall area under the curve of 0.82. To showcase our method, we found novel gene candidates for warfarin, gefitinib, carboplatin, and gemcitabine, and we provide the molecular hypotheses for these predictions.

Copy-number variations associated with autism spectrum disorder

Autism spectrum disorder (ASD) is a clinically heterogeneous developmental disorder with a strong genetic component. Rare genetic disorders and various chromosomal abnormalities are thought to account for approximately 10% of people with ASD. The etiology of the remaining cases remains unknown. Recent advances in array-based technology have increased the resolution in detecting submicroscopic deletions and duplications, referred to as copy-number variations. ASD-associated copy-number variations, which are considered to be present in individuals with ASD but not in unaffected individuals, have been extensively investigated. These data will provide us with an opportunity not only to search for genes causing or contributing to ASDs but also to understand the genetics of ASD.

Web-Based Software for Storage, Statistical Processing and Analysis of SNP Data in Studies on Complex Disorders

Single nucleotide polymorphisms (SNPs) have become a very powerful tool for molecular genetics studies. Public databases provide information on over 10 million polymorphisms in the human genome. The candidate gene approach and genomewide association studies through SNP analysis have opened a new avenue for defining the genetics of complex disorders. However, analysis of large numbers of SNPs is time-consuming, cost-intensive, and requires huge experimental and statistical resources in association studies. We have developed a web-based product that facilitates the processing and statistical analysis of SNP-genotyping data for casecontrol association studies and provides for custom design, a structured database and practical export layout. Here we describe the software product database and how it helps in high-speed comprehensive SNP analysis.

Thiopurine methyltransferase activity is related to the risk of relapse of childhood acute lymphoblastic leukemia: results from the NOPHO ALL-92 study

Myelotoxicity during thiopurine therapy is enhanced in patients, who because of single nucleotide polymorphisms have decreased activity of the enzyme thiopurine methyltransferase (TPMT) and thus more thiopurine converted into 6-thioguanine nucleotides. Of 601 children with acute lymphoblastic leukemia (ALL) who were treated by the NOPHO ALL-92 protocol, 117 had TPMT genotype determined, whereas for 484 patients only erythrocyte TPMT activity was available. The latter were classified as heterozygous, if TPMT activity was <14 IU/ml, or deficient (<1.0 IU/ml). 526 patients had TPMT wild type, 73 were presumed heterozygous, and two were TPMT deficient. Risk of relapse was higher for the 526 TPMT wild type patients than for the remaining 75 patients (18 vs 7%, P=0.03). In Cox multivariate regression analysis, sex (male worse; P=0.06), age (higher age worse, P=0.02), and TPMT activity (wild type worse; P=0.02) were related to risk of relapse. Despite a lower probability of relapse, patients in the low TPMT activity group did not have superior survival (P=0.82), possibly because of an excess of secondary cancers among these 75 patients (P=0.07). These data suggest that children with ALL and TPMT wild type might have their cure rate improved, if the pharmacokinetics/-dynamics of TPMT low-activity patients could be mimicked without a concurrent excessive risk of second cancers.

Pharmacogenetics in drug discovery and development: a translational perspective

The ability to predict a patient's drug response on the basis of their genetic information is expected to decrease attrition during the development of new, innovative drugs, and reduce adverse events by being able to predict individual patients at risk. Most pharmacogenetic investigations have focused on drug-metabolism genes or candidate genes that are thought to be involved in specific diseases. However, robust new genetic tools now enable researchers to carry out multi-candidate gene-association and genome-wide studies for target discovery and drug development. Despite the expanding role of pharmacogenetics in industry, however, there is a paucity of published data. New forms of effective and efficient collaboration between industry and academia that may enhance the systematic collection of pharmacogenetic data are necessary to establish genetic profiles related to drug response, confirm pharmacogenetic associations and expedite the development of new drugs and diagnostic tests.

A HapMap harvest of insights into the genetics of common disease

The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the initial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits. These associations provided new insights into pathophysiology, suggesting previously unsuspected etiologic pathways for common diseases that will be of use in identifying new therapeutic targets and developing targeted interventions based on genetically defined risk. In addition, HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments. In this review we examine the origin, development, and current status of the HapMap; its prospects for continued evolution; and its current and potential future impact on biomedical science.

CFH and LOC387715/ARMS2 genotypes and treatment with antioxidants and zinc for age-related macular degeneration

OBJECTIVE

To determine if CFH and LOC387715/ARMS2 genotypes influence treatment response to AREDS-type nutritional supplementation with antioxidants and zinc.

DESIGN

Retrospective analysis of participants in a randomized, controlled clinical trial, the Age-Related Eye Disease Study (AREDS).

PARTICIPANTS AND/OR CONTROLS

Eight hundred seventy-six AREDS study participants who were considered at high risk for developing advanced age-related macular degeneration (AMD).

METHODS

Using DNA extracted from venous blood of 876 white participants in AREDS categories 3 and 4, that is, those considered to be at high risk for progression to advanced AMD, the authors genotyped for the single nucleotide polymorphisms in the CFH (Y402H, rs1061170) and LOC387715/ARMS2 (A69S, rs10490924) genes. The authors performed adjusted unconditional logistic regression analysis and assessed interactions of these genotypes to determine the relationship between CFH and LOC387715/ARMS2 genotype and treatment with antioxidants plus zinc.

MAIN OUTCOME MEASURES

Interaction between genetic variants and treatment response as determined by progression from high-risk to advanced AMD.

RESULTS

Progression occurred in 264 of 876 patients from AREDS category 3 (intermediate AMD) to category 4 or 5 (unilateral or bilateral advanced AMD, respectively), or from category 4 to category 5. A treatment interaction was observed between the CFH Y402H genotype and supplementation with antioxidants plus zinc (CC; P = 0.03). An interaction (P = 0.004) was observed in the AREDS treatment groups taking zinc when compared with the groups taking no zinc, but not in groups taking antioxidants compared with those taking no antioxidants (P = 0.59). There were no significant treatment interactions observed with LOC387715/ARMS2.

CONCLUSIONS

The findings of this study indicate that an individual's response to AREDS supplements may be related to CFH genotype. This could have clinical relevance by predicting treatment outcome and potentially preventing unwanted side effects in those who may not benefit. Corroboration of these analyses is needed before considering modification of current management. This is among the first pharmacogenetic studies to suggest interaction between genotype and treatment.

Battling the hematological malignancies: the 200 years' war

The delineation of the hematological malignancies began near the end of the first third of the 19th century with the recognition of the similarity among cases with lymph node tumors and an enlarged spleen (Hodgkin's disease). Descriptions of chronic and acute leukemia and myeloma followed thereafter. In the first years of the 20th century the discovery of x-radiation permitted palliative orthovoltage radiation therapy of Hodgkin's disease. Following World War II, legitimate drug therapy for the hematological malignancies was introduced: nitrogen mustard, adrenocorticotropic hormone and cortisone acetate, and anti-folic acid derivatives, initially aminopterin. Today, about 14 classes of drugs (different mechanisms of action) and >50 individual agents are being used, with others under study. Several examples of agents targeting specific transcription factors or oncoproteins have been introduced. Despite remarkable progress, including the ability to cure acute leukemia in about 70% of children, cure several genetic variants of acute myelogenous leukemia in younger adults, cure some cases of lymphoma in children and younger adults, and induce prolonged remission in many affected persons, the majority of patients face an uncertain outcome and shortened life. Thus, we have much to do in the next several decades. The significant hurdles we must overcome include: the apparent infrequency of an exogenous cause that can be avoided, the exponential increase in incidence rates with age and the dramatic negative effect of aging on the results of treatment, the challenge of one trillion or more disseminated cancer cells among which are a smaller population of cancer stem cells, the profound genetic diversity of the hematological malignancies (apparently hundreds of unique genetic primary lesions), the redundant growth and survival pathways defining the cancer phenotype, the decreasing market for pharmaceutical companies as therapy becomes more specific (fewer target patients) and drug development costs become more expensive, and the significant negative long-term effects of current therapy on both children and adults. These challenges will be gradually overcome, if we (a) develop new models of cooperation among academia, industry, and government, (b) continue the growth of international participation in cancer research (more keen minds to the task), and (c) convince the governments of the world, including that of the U.S., that an investment in minimizing the effects of cancer is as important as defending against other threats to the welfare and longevity of their citizens.

Development of genomic markers that predict response to molecularly targeted antileukemic therapy

BACKGROUND

The cancer genome is characterized by the accumulation of multiple mutations and alterations that ultimately result in the deregulation of various cell-signaling pathways. Knowledge of these genetic alterations has provided a unique opportunity to develop therapies targeted against these pathways and to identify which patients are likely to benefit from them.

OBJECTIVE

The progress that has been made in identifying genomic biomarkers that can predict response to antileukemic therapies is highlighted.

METHODS

Global gene expression profiling approaches utilizing tipifarnib in acute myeloid leukemia as an in-depth example are focused on. The challenges in developing associated theranostic molecular assays are discussed.

CONCLUSION

The integration of validated genomic-based assays with common morphological tests may allow for improved prediction of antileukemic drug response.

The plasma proteome, adductome and idiosyncratic toxicity in toxicoproteomics research

Toxicoproteomics uses the discovery potential of proteomics in toxicology research by applying global protein measurement technologies to biofluids and tissues after host exposure to injurious agents. Toxicoproteomic studies thus far have focused on protein profiling of major organs and biofluids such as liver and blood in preclinical species exposed to model toxicants. The slow pace of discovery for new biomarkers, toxicity signatures and mechanistic insights is partially due to the limited proteome coverage derived from analysis of native organs, tissues and body fluids by traditional proteomic platforms. Improved toxicoproteomic analysis would result by combining higher data density LC-MS/MS platforms with stable isotope labelled peptides and parallel use of complementary platforms. Study designs that remove abundant proteins from biofluids, enrich subcellular structures and include cell specific isolation from heterogeneous tissues would greatly increase differential expression capabilities. By leveraging resources from immunology, cell biology and nutrition research communities, toxicoproteomics could make particular contributions in three inter-related areas to advance mechanistic insights and biomarker development: the plasma proteome and circulating microparticles, the adductome and idiosyncratic toxicity.