Howard L. McLeod

Characterizing genetic variants for clinical action

Genome‐wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome‐scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop.

Exploring the Distribution of Genetic Markers of Pharmacogenomics Relevance in Brazilian and Mexican Populations

Studies of pharmacogenomics-related traits are increasingly being performed to identify loci that affect either drug response or susceptibility to adverse drug reactions. However, the effect of the polymorphisms can differ in magnitude or be absent depending on the population being assessed. We used the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array to characterize the distribution of polymorphisms of pharmacogenetics and pharmacogenomics (PGx) relevance in two samples from the most populous Latin American countries, Brazil and Mexico. The sample from Brazil included 268 individuals from the southeastern state of Rio de Janeiro, and was stratified into census categories. The sample from Mexico comprised 45 Native American Zapotecas and 224 self-identified Mestizo individuals from 5 states located in geographically distant regions in Mexico. We evaluated the admixture proportions in the Brazilian and Mexican samples using a panel of Ancestry Informative Markers extracted from the DMET array, which was validated with genome-wide data. A substantial variation in ancestral proportions across census categories in Brazil, and geographic regions in Mexico was identified. We evaluated the extent of genetic differentiation (measured as FST values) of the genetic markers of the DMET Plus array between the relevant parental populations. Although the average levels of genetic differentiation are low, there is a long tail of markers showing large frequency differences, including markers located in genes belonging to the Cytochrome P450, Solute Carrier (SLC) and UDP-glucuronyltransferase (UGT) families as well as other genes of PGx relevance such as ABCC8, ADH1A, CHST3, PON1, PPARD, PPARG, and VKORC1. We show how differences in admixture history may have an important impact in the distribution of allele and genotype frequencies at the population level.

The relationship of polymorphisms in ABCC2 and SLCO1B3 with docetaxel pharmacokinetics and neutropenia: CALGB 60805 (Alliance)

Docetaxel-related neutropenia was associated with polymorphisms in the drug transporters ABCC2 and SLCO1B3 in Japanese cancer patients. We hypothesized that this association is because of reduced docetaxel clearance, associated with polymorphisms in those genes. We studied 64 US cancer patients who received a single cycle of 75 mg/m of docetaxel monotherapy. We found that the ABCC2 polymorphism at rs-12762549 trended to show a relationship with reduced docetaxel clearance (P=0.048), but not with neutropenia. There was no significant association of the SLCO1B3 polymorphisms with docetaxel clearance or neutropenia. We conclude that the relationship between docetaxel-associated neutropenia and polymorphisms in drug transporters identified in Japanese patients was not confirmed in this cohort of US cancer patients.

A Community-Based Multicenter Trial of Pharmacokinetically Guided 5-Fluorouracil Dosing for Personalized Colorectal Cancer Therapy

BACKGROUNDnPharmacokinetically guided (PK-guided) versus body surface area-based 5-fluorouracil (5-FU) dosing results in higher response rates and better tolerability. A paucity of data exists on PK-guided 5-FU dosing in the community setting.nnnPATIENTS AND METHODSnSeventy colorectal cancer patients, from one academic and five community cancer centers, received the mFOLFOX6 regimen (5-FU 2,400 mg/m(2) over 46 hours every 2 weeks) with or without bevacizumab at cycle 1. The 5-FU continuous-infusion dose was adjusted for cycles 2-4 using a PK-guided algorithm to achieve a literature-based target area under the concentration-time curve (AUC). The primary objective was to demonstrate that PK-guided 5-FU dosing improves the ability to achieve a target AUC within four cycles of therapy. The secondary objective was to demonstrate reduced incidence of 5-FU-related toxicities.nnnRESULTSnAt cycles 1 and 4, 27.7% and 46.8% of patients achieved the target AUC (20-25 mg × hour/L), respectively (odds ratio [OR]: 2.20; p = .046). Significantly more patients were within range at cycle 4 compared with a literature rate of 20% (p < .0001). Patients had significantly higher odds of not being underdosed at cycle 4 versus cycle 1 (OR: 2.29; p = .037). The odds of a patient being within range increased by 30% at each subsequent cycle (OR: 1.30; p = .03). Less grade 3/4 mucositis and diarrhea were observed compared with historical data (1.9% vs 16% and 5.6% vs 12%, respectively); however, rates of grade 3/4 neutropenia were similar (33% vs 25%-50%).nnnCONCLUSIONnPK-guided 5-FU dosing resulted in significantly fewer underdosed patients and less gastrointestinal toxicity and allows for the application of personalized colorectal cancer therapy in the community setting.

Using pharmacogene polymorphism panels to detect germline pharmacodynamic markers in oncology.

The patient (germline) genome can influence the pharmacokinetics and pharmacodynamics of cancer therapy. The field of pharmacogenetics (PGx) has primarily focused on genetic predictors of pharmacokinetics, largely ignoring pharmacodynamics, using a candidate approach to assess single-nucleotide polymorphisms (SNP) with known relevance to drug pharmacokinetics such as enzymes and transporters. A more comprehensive approach, the genome-wide association study, circumvents candidate selection but suffers because of the necessity for substantial statistical correction. Pharmacogene panels, which interrogate hundreds to thousands of SNPs in genes with known relevance to drug pharmacokinetics or pharmacodynamics, represent an attractive compromise between these approaches. Panels with defined or customizable SNP lists have been used to discover SNPs that predict pharmacokinetics or pharmacodynamics of cancer drugs, most of which await successful replication. PGx discovery, particularly for SNPs that influence drug pharmacodynamics, is limited by weaknesses in both genetic and phenotypic data. Selection of candidate SNPs for inclusion on pharmacogene panels is difficult because of limited understanding of biology and pharmacology. Phenotypes used in analyses have primarily been complex toxicities that are known to be multifactorial. A more measured approach, in which sensitive phenotypes are used in place of complex clinical outcomes, will improve the success rate of pharmacodynamics SNP discovery and ultimately enable identification of pharmacodynamics SNPs with meaningful effects on treatment outcomes. See all articles in this CCR Focus section, “Progress in Pharmacodynamic Endpoints.” Clin Cancer Res; 20(10); 2530–40. ©2014 AACR.

Tamoxifen Dose Escalation in Patients With Diminished CYP2D6 Activity Normalizes Endoxifen Concentrations Without Increasing Toxicity

BACKGROUNDnPolymorphic CYP2D6 is primarily responsible for metabolic activation of tamoxifen to endoxifen. We previously reported that by increasing the daily tamoxifen dose to 40 mg/day in CYP2D6 intermediate metabolizer (IM), but not poor metabolizer (PM), patients achieve endoxifen concentrations similar to those of extensive metabolizer patients on 20 mg/day. We expanded enrollment to assess the safety of CYP2D6 genotype-guided dose escalation and investigate concentration differences between races.nnnMETHODSnPM and IM breast cancer patients currently receiving tamoxifen at 20 mg/day were enrolled for genotype-guided escalation to 40 mg/day. Endoxifen was measured at baseline and after 4 months. Quality-of-life data were collected using the Functional Assessment of Cancer Therapy-Breast (FACT-B) and Breast Cancer Prevention Trial Menopausal Symptom Scale at baseline and after 4 months.nnnRESULTSnIn 353 newly enrolled patients, genotype-guided dose escalation eliminated baseline concentration differences in IM (p = .08), but not PM (p = .009), patients. Endoxifen concentrations were similar in black and white patients overall (p = .63) and within CYP2D6 phenotype groups (p > .05). In the quality-of-life analysis of 480 patients, dose escalation did not meaningfully diminish quality of life; in fact, improvements were seen in several measures including the FACT Breast Cancer subscale (p = .004) and limitations in range of motion (p < .0001) in IM patients.nnnCONCLUSIONnDifferences in endoxifen concentration during treatment can be eliminated by doubling the tamoxifen dose in IM patients, without an appreciable effect on quality of life. Validation of the association between endoxifen concentration and efficacy or prospective demonstration of improved efficacy is necessary to warrant clinical uptake of this personalized treatment strategy.nnnIMPLICATIONS FOR PRACTICEnThis secondary analysis of a prospective CYP2D6 genotype-guided tamoxifen dose escalation study confirms that escalation to 40 mg/day in patients with low-activity CYP2D6 phenotypes (poor or intermediate metabolizers) increases endoxifen concentrations without any obvious increases in treatment-related toxicity. It remains unknown whether endoxifen concentration is a useful predictor of tamoxifen efficacy, and thus, there is no current role in clinical practice for CYP2D6 genotype-guided tamoxifen dose adjustment. If future studies confirm the importance of endoxifen concentrations for tamoxifen efficacy and report a target concentration, this study provides guidance for a dose-adjustment approach that could maximize efficacy while maintaining patient quality of life.

Pharmacogenomic assessment of Mexican and Peruvian populations

BACKGROUNDnClinically relevant polymorphisms often demonstrate population-specific allele frequencies. Central and South America remain largely uncategorized in the context of pharmacogenomics.nnnMATERIALS & METHODSnWe assessed 15 polymorphisms from 12 genes (ABCB1 3435C>T, ABCG2 Q141K, CYP1B1*3, CYP2C19*2, CYP3A4*1B, CYP3A5*3C, ERCC1 N118N, ERCC2 K751Q, GSTP1 I105V, TPMT 238G>C, TPMT 460G>A, TPMT 719A>G, TYMS TSER, UGT1A1*28 and UGT1A1xa0-3156G>A) in 81 Peruvian and 95 Mexican individuals.nnnRESULTSnSix polymorphism frequencies differed significantly between the two populations: ABCB1 3435C>T, CYP1B1*3, GSTP1 I105V, TPMT 460G>A, UGT1A1*28 and UGT1A1 -3156G>A. The pattern of observed allele frequencies for all polymorphisms could not be accurately estimated from any single previously studied population.nnnCONCLUSIONnThis highlights the need to expand the scope of geographic data for use in pharmacogenomics studies.

Genetic nondiscrimination legislation: a critical prerequisite for pharmacogenomics data sharing

Russ B Altman1†, Neal Benowitz2, David Gurwitz3, Jeantine Lunshof4, Mary Relling5, Jatinder Lamba5, Eric Wieben6, Sean Mooney7, Kathleen Giacomini2, Scott Weiss8, Julie A Johnson9, Howard McLeod10, David Flockhart7, Richard Weinshilboum6, Alan R Shuldiner11, Dan Roden12, Ronald M Krauss13 & Mark Ratain14 †Author for correspondence 1Stanford University, Department of Genetics and Bioengineering, Clark S172, Stanford, CA 94305-5444, USA E-mail: Russ.Altman@ stanford.edu 2University of California, San Francisco 3Tel-Aviv University 4VU University Medical Center 5St Jude Children’s Research Hospital 6Mayo Clinic 7Indiana University School of Medicine 8Harvard Medical School 9University of Florida 10University of North Carolina 11University of Maryland 12Vanderbilt School of Medicine 13Children’s Hospital Oakland Research Institute 14University of Chicago On 31st January 2007, the US Senate Health, Education, Labor and Pensions Committee approved the Genetic Information Nondiscrimination Act (GINA) by a vote of 19:2. It was unanimously approved by the US Congress Committee on Education and Labor 2 weeks later. This legislation, aimed at preventing genetic discrimination in employment and insurance [1], will be imperative for protecting altruistic individuals who volunteer for genetic research [2]. There is an emerging consensus among researchers that genetic data must be accessible to individual research participants upon their request [3], while not putting them at risk with respect to their employment, insurance and additional personal aspects [4]. The GINA balances individual freedoms and privacy rights with societal needs for affordable and more effective healthcare and helps to pave the way for more personalized medicine [5]. Indeed, genetic information can be used to improve healthcare, in particular with regard to reducing the alarming rates of adverse drug reactions, which led to 6.7% of all US hospital admissions during 2004–2005 [6], consistent with earlier studies in the UK [7]. Increased use of individual genetic information about drug-metabolizing and drug-target gene alleles as part of healthcare treatment decisions may substantially reduce such morbidity [8]. However, building up the required knowledge depends on the analysis of large individual genotype/phenotype data sets from patient cohorts and requires open data sharing so that large, meaningful and less biased data sets are available to researchers [9]. Lack of open data sharing, in particular between the private and public sectors, hinders our ability to assemble large aggregated data sets [9]. A key obstacle for data sharing is concern about depositing data sets from individual study participants into public databases; some researchers fear they will be held responsible in cases where the data are re-identified (using computational data-mining techniques) and subsequently used (by employers or insurers) to discriminate against study participants. We therefore believe that legislation that offers protection to individuals or groups who share genetic information – against both re-identification and discrimination – is essential for efforts to move genomic medicine into practice. Legislation barring discrimination or stigmatization based on genetic information has been proposed for years, but enactment has become particularly urgent in view of rapidly falling genotyping costs [10], the scope of ongoing genome-wide association studies [11] and the increasing availability of comprehensive personal data in the public domain [4]. We therefore strongly support the current efforts to establish a solid legal framework as a primary means to protect individuals against misuse of their genetic information and as an essential tool for allowing open data sharing in pharmacogenomics.

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.

Comprehensive assessment of cytochromes P450 and transporter genetics with endoxifen concentration during tamoxifen treatment

Objectives Tamoxifen bioactivation to endoxifen is mediated primarily by CYP2D6; however, considerable variability remains unexplained. Our aim was to perform a comprehensive assessment of the effect of genetic variation in tamoxifen-relevant enzymes and transporters on steady-state endoxifen concentrations. Patients and methods Comprehensive genotyping of CYP enzymes and transporters was performed using the iPLEX ADME PGx Pro Panel in 302 tamoxifen-treated breast cancer patients. Predicted activity phenotype for 19 enzymes and transporters were analyzed for univariate association with endoxifen concentration, and then adjusted for CYP2D6 and clinical covariates. Results In univariate analysis, higher activity of CYP2C8 (regression &bgr;=0.22, P=0.020) and CYP2C9 (&bgr;=0.20, P=0.04), lower body weight (&bgr;=−0.014, P<0.0001), and endoxifen measurement during winter (each &bgr;<−0.39, P=0.002) were associated with higher endoxifen concentrations. After adjustment for the CYP2D6 diplotype, weight, and season, CYP2C9 remained significantly associated with higher concentrations (P=0.02), but only increased the overall model R2 by 1.3%. Conclusion Our results further support a minor contribution of CYP2C9 genetic variability toward steady-state endoxifen concentrations. Integration of clinician and genetic variables into individualized tamoxifen dosing algorithms would marginally improve their accuracy and potentially enhance tamoxifen treatment outcomes.