Cancer pharmacogenomics and pharmacoepidemiology: setting a research agenda to accelerate translation.
ABSTRACT Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled "Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation" on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.
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ABSTRACT: Interindividual variability in drug response is a major clinical problem. Polymedication and genetic polymorphisms modulating drug-metabolising enzyme activities (cytochromes P450, CYP) are identified sources of variability in drug responses. We present here the relevant data on the clinical impact of the major CYP polymorphisms (CYP2D6, CYP2C19 and CYP2C9) on drug therapy where genotyping and phenotyping may be considered, and the guidelines developed when available. CYP2D6 is responsible for the oxidative metabolism of up to 25 % of commonly prescribed drugs such as antidepressants, antipsychotics, opioids, antiarrythmics and tamoxifen. The ultrarapid metaboliser (UM) phenotype is recognised as a cause of therapeutic inefficacy of antidepressant, whereas an increased risk of toxicity has been reported in poor metabolisers (PMs) with several psychotropics (desipramine, venlafaxine, amitriptyline, haloperidol). CYP2D6 polymorphism influences the analgesic response to prodrug opioids (codeine, tramadol and oxycodone). In PMs for CYP2D6, reduced analgesic effects have been observed, whereas in UMs cases of life-threatening toxicity have been reported with tramadol and codeine. CYP2D6 PM phenotype has been associated with an increased risk of toxicity of metoprolol, timolol, carvedilol and propafenone. Although conflicting results have been reported regarding the association between CYP2D6 genotype and tamoxifen effects, CYP2D6 genotyping may be useful in selecting adjuvant hormonal therapy in postmenopausal women. CYP2C19 is responsible for metabolising clopidogrel, proton pump inhibitors (PPIs) and some antidepressants. Carriers of CYP2C19 variant alleles exhibit a reduced capacity to produce the active metabolite of clopidogrel, and are at increased risk of adverse cardiovascular events. For PPIs, it has been shown that the mean intragastric pH values and the Helicobacter pylori eradication rates were higher in carriers of CYP2C19 variant alleles. CYP2C19 is involved in the metabolism of several antidepressants. As a result of an increased risk of adverse effects in CYP2C19 PMs, dose reductions are recommended for some agents (imipramine, sertraline). CYP2C9 is responsible for metabolising vitamin K antagonists (VKAs), non-steroidal anti-inflammatory drugs (NSAIDs), sulfonylureas, angiotensin II receptor antagonists and phenytoin. For VKAs, CYP2C9 polymorphism has been associated with lower doses, longer time to reach treatment stability and higher frequencies of supratherapeutic international normalised ratios (INRs). Prescribing algorithms are available in order to adapt dosing to genotype. Although the existing data are controversial, some studies have suggested an increased risk of NSAID-associated gastrointestinal bleeding in carriers of CYP2C9 variant alleles. A relationship between CYP2C9 polymorphisms and the pharmacokinetics of sulfonylureas and angiotensin II receptor antagonists has also been observed. The clinical impact in terms of hypoglycaemia and blood pressure was, however, modest. Finally, homozygous and heterozygous carriers of CYP2C9 variant alleles require lower doses of phenytoin to reach therapeutic plasma concentrations, and are at increased risk of toxicity. New diagnostic techniques made safer and easier should allow quicker diagnosis of metabolic variations. Genotyping and phenotyping may therefore be considered where dosing guidelines according to CYP genotype have been published, and help identify the right molecule for the right patient.Molecular Diagnosis & Therapy 04/2013; 17(3). · 2.59 Impact Factor
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ABSTRACT: Molecular biomarkers, a cornerstone of precision oncology, are critical in breast, gastroesophageal, and non-small cell lung cancer management (BC, GEC, NSCLC). Testing practices are intensely debated, impacting diagnostic quality and affecting pathologists, oncologists and patients. However, little is known about testing approaches used in practice. Our study described biomarker practices in BC, GEC, and NSCLC at the leading US cancer centers.JNCI Journal of the National Cancer Institute 10/2014; 106(10). · 15.16 Impact Factor
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ABSTRACT: Pharmacogenomics aims to identify the genome-based variability in drug disposition (metabolism and transport), which inﬂ uences its efﬁ cacy and toxicity, and also to develop diagnostics and therapeutics on the basis of genetic variants so as individualize pharmacotherapy. Progress made in the last two decades in pharmacogenomics study of gynecological diseases has enabled us to predict the therapy outcome on the basis of inherited or acquired genetic mutations. The present chapter focuses on the clinical relevance of genetic variation in terms of diagnosis, prognosis, and therapeutics in context to this group of diseases with special reference to gynecological cancers. Various disease susceptibility genes and their polymorphisms of gynecological disorders have been identiﬁ ed, and their molecular diagnostics and targeted therapies developed. To name a few well studied are BRCA1/2, HER2, GSTT1, GSTM1, CYP1B1, PPAR- γ , VEGF, etc. Detailed account of the genetic components and their variants associated with each disease and how it inﬂ uences the discourse of the disease and individualization of the therapy is given here.Omics for Personalized Medicine, Edited by Barh D, Dhawan D, Ganguly NK eds, 01/2013: pages 707-741; Springer New Delhi Heidelberg New York Dordrecht London., ISBN: 978-81-322-1183-9
1698 Commentary | JNCI Vol. 102, Issue 22 | November 17, 2010
Advance Access publication on October 13, 2010.
Published by Oxford University Press 2010.
This is an Open Access article distributed under the terms of the Creative Com mons Attribution
Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted
non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The fields of pharmacogenomics and pharmacoepidemiology are
interrelated in that the goal of both is to understand why individuals
respond differently to drug therapy, in terms of both adverse effects
and treatment efficacy. Pharmacogenomics focuses on under-
standing how genetic variants that encode for drug-metabolizing
enzymes, drug transporters, drug targets, and proteins involved in
disease biology influence individual differences in terms of treatment
efficacy, effectiveness, and adverse effects. Pharmacoepidemiology
uses a variety of study designs to identify patterns and determinants
of the use of drug therapy and its effects in clinical and population
settings. The study of genomic factors can be readily integrated into
pharmacoepidemiologic studies along with nongenetic factors,
leading to a natural convergence of the two fields.
Five key trends are creating new opportunities, challenges, and
questions in cancer research. These include 1) expanded develop-
ment and approval of new cancer therapies allowing more
therapeutic choices, 2) rapid expansion of knowledge and high-
throughput tools to evaluate genomic variation, 3) increasing
numbers of cancer survivors who may experience late effects of
treatment, 4) widespread use of prescription pharmaceutical agents
in the United States population, and 5) increasing numbers of
public–private partnerships and research consortia. The tools and
methods of pharmacogenomics and pharmacoepidemiology are
well suited to study and take advantage of these trends and to
conduct studies that can inform personalized cancer prevention
Recent advances in genetic technology, combined with new
discoveries in pharmacogenomics, have shed light on the substan-
tial role of genomic factors to predict drug response and the clin-
ical potential of genomic testing. Several pharmacogenomic
markers have been or are currently being evaluated to determine
their clinical value (Table 1). Examples of these markers include
cytochrome P450 2D6 (CYP2D6) genotypes in tamoxifen treatment
for breast cancer (1), UDP-glucuronosyltransferase 1A1 (UGT1A1)
genotypes in irinotecan treatment for colorectal cancer (2), and
epidermal growth factor receptor (EGFR) mutations in non–small
cell lung cancer treatment (3,4). These markers may be able to
identify subgroups of patients who will optimally benefit from a
particular cancer therapy, other patients who might derive little or
no benefit, and/or individuals who are at elevated risk for serious
Cancer Pharmacogenomics and Pharmacoepidemiology: Setting
a Research Agenda to Accelerate Translation
Andrew N. Freedman, Leah B. Sansbury, William D. Figg, Arnold L. Potosky, Sheila R. Weiss Smith, Muin J. Khoury,
Stefanie A. Nelson, Richard M. Weinshilboum, Mark J. Ratain, Howard L. McLeod, Robert S. Epstein, Geoffrey S. Ginsburg,
Richard L. Schilsky, Geoffrey Liu, David A. Flockhart, Cornelia M. Ulrich, Robert L. Davis, Lawrence J. Lesko,
Issam Zineh, Gurvaneet Randhawa, Christine B. Ambrosone, Mary V. Relling, Nat Rothman, Heng Xie, Margaret R. Spitz,
Rachel Ballard-Barbash, James H. Doroshow, Lori M. Minasian
Manuscript received April 5, 2010; revised September 8, 2010; accepted September 10, 2010.
Correspondence to: Andrew N. Freedman, PhD, National Cancer Institute, National Institutes of Health, 6130 Executive Blvd, Rm 5128, Bethesda, MD
20892-7393 (e-mail: firstname.lastname@example.org).
Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer
therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individ-
uals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities
as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a
workshop titled “Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation” on July 21, 2009, in
Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-
based recommendations that were identified as a result of discussions held during this workshop. Key recommendations
include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some
observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the
ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic re-
search; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommen-
dations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer
treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic
and pharmacoepidemiologic information is translated into clinical practice.
J Natl Cancer Inst 2010;102:1698–1705
JNCI | Commentary 1699
adverse events. However, the clinical utility for the most promising
pharmacogenomic markers is still being investigated.
A few genetic and genomic tests have recently been integrated
into standard clinical practice and/or incorporated into the Food
and Drug Administration (FDA) label. However, there appears to
be substantial variation in the rate of clinical adoption and accep-
tance of such testing. At one extreme, testing for KRAS mutations
to determine whether to use cetuximab and panitumumab in treat-
ing metastatic colorectal cancer was adopted quickly (5). By con-
trast, testing of thiopurine methyltransferase (TPMT) genotypes to
determine optimal treatment for acute lymphocytic leukemia (6)
and of EGFR mutations and/or expression to determine non–small
cell lung cancer treatment (4) has been variable in clinical practice.
So, the discovery of substantial genomic influence over the effec-
tiveness or safety of a cancer drug does not always translate imme-
diately into clinical practice. There may be numerous reasons
for this variability: Oncologists may not be convinced that the
genomic test is of clinical value, physicians may not know about
the tests, drug labels may not describe the usefulness of genetic
information, or insurance coverage may not be available for the
genetic test (Table 1). For example, in the case of TPMT testing,
some physicians may not be convinced of its clinical utility and/or
cost-effectiveness and they may believe that how they currently
manage chemotherapy-induced myelosuppression is an adequate
way to screen for potential toxicities. Also, many physicians may
have never treated the rare (one in 400) homozygous patient who
would experience life-threatening toxicity without TPMT testing.
Discoveries from cancer pharmacogenomics and pharmaco-
epidemiology research can help to optimize the benefit to risk
ratio of treatment strategies in general clinical practice.
Translation of these discoveries may more efficiently target ther-
apies to patients who will benefit and avoid or anticipate poten-
tially serious adverse events among high-risk patients and thus
may reduce cancer morbidity and mortality and reduce the cost of
cancer care. Equally important, these discoveries provide novel
insights into the underlying biology of drug response phenotypes.
Full realization of the potential of pharmacogenomics research
will require the integration of basic discoveries in drug develop-
ment and pharmacogenomic variability, of genomic and outcome
data from phase I–III randomized clinical trials, and of data on the
effects of drugs and their interactions with genomic variants in
large populations. Here, we report on results from the National
Cancer Institute (NCI)–sponsored workshop titled “Cancer
Pharmacogenomics: Setting a Research Agenda to Accelerate
Translation” which took place on July 21, 2009 and the group’s
recommendations to address priorities, resources, and infrastruc-
ture needs to advance the fields of cancer pharmacoepidemiology
and pharmacogenomic research (7).
To address the interdisciplinary and translational nature of this
field, and the need for input across various disciplines, the Trans-
NCI Pharmacogenomics and Pharmacoepidemiology Working
Group (PPWG) was chartered by NCI in January 2008 (8). The
PPWG is responsible for planning, developing, directing, coordi-
nating, and evaluating a program of research in pharmacogenom-
ics and pharmacoepidemiology research across NCI. To begin this
task, three subcommittees of the PPWG were created to address
issues specific to basic biomedical research, clinical research, and
population science research. Each subcommittee identified pri-
ority areas and research goals important to their specific area of
research, analyzed the portfolio of NCI-sponsored pharmacoge-
nomics and pharmacoepidemiology studies of common pharma-
ceuticals and cancer therapies, and developed recommendations
to advance a pharmacogenomics and pharmacoepidemiology
Table 1. Pharmacogenomic markers in cancer treatment*
Biomarkers DrugCancer site Effect
in the FDA drug label
Routinely used in
United States practices
ALL and AML
* 5-FU = 5-fluorouracil; 6-MP = 6-mercaptopurine; 6-TG = 6-thioguanine; ALL = acute lymphoblastic leukemia; AML = acute myeloid leukemia; CML = chronic
myelogenous leukemia; EGFR = epidermal growth factor receptor; FDA = Food and Drug Administration; Tx = treatment.
† Device approval.
1700 Commentary | JNCI Vol. 102, Issue 22 | November 17, 2010
research agenda at NCI. The subcommittee recommendations
were then brought to the full PPWG to be combined in a final
draft of summary recommendations.
To further refine the recommendations, input was sought from
members of the broader cancer research community. In July 2009,
NCI brought together these external scientists with representa-
tives of the PPWG, the National Institutes of Health, and other
key federal agencies (eg, the United States FDA, the Agency for
Healthcare Research and Quality, the Centers for Disease Control
and Prevention [CDC], and the Department of Defense) to partic-
ipate in an NCI-sponsored workshop at which invitees discussed
the draft recommendations, priorities for cancer pharmacogenom-
ics and pharmacoepidemiology research initiatives, and the needs
of the fields in general. The resulting nine recommendations are
presented in this commentary.
Overview of Recommendations: Future
The recommendations reflect the input of NCI and extramural
clinical and research investigators from a wide variety of disci-
plines, including medical oncology, genomics, clinical and basic
pharmacology, epidemiology, statistics, health services, pathology,
molecular biology, and bioinformatics, among others. The goal
of these recommendations is to improve both the speed and
efficiency of discovery and the translation of this rapidly evolving
new knowledge into clinical practice. These recommendations
will serve as the roadmap for the programs, resources, and
infrastructure needed to maintain a pipeline of such discoveries.
Here we summarize the priorities relevant to each of the nine rec-
ommendations, which have been divided into five scientific-based
recommendations and four infrastructure-based recommendations
Knowledge Gaps in Pharmacogenomics and
Recognizing the need to identify gaps in knowledge and to priori-
tize research, recommendation 1 calls for the development and
ongoing support of an expert panel tasked on an ongoing basis to
synthesize evidence, identify knowledge gaps, and develop prior-
ities and specific research questions with the goal of speeding
translation of pharmacogenomics and pharmacoepidemiology re-
search findings into clinical practice. This group would synthesize
and process pharmacogenomic and pharmacoepidemiologic evi-
dence relevant to cancer from trials and observational studies and
would provide guidance as to the additional study data that would
be needed to translate new evidence into clinical practice. Several
ongoing initiatives could be leveraged for this group, of which
three are CDC initiatives––the Evaluation of Genomic Applications
in Practice and Prevention initiative (9), the Human Genome
Epidemiology Network (10), and the new Genomic Applications
in Practice and Prevention Network (11)––and one from the
National Institutes of Health’s Pharmacogenetics Research
Network, the Pharmacogenetics and Pharmacogenomics
Knowledge Base (PharmGKB) (12). Ideally comprised of members
from the public as well as private entities, the group would consist
Table 2. Key recommendations
1. Develop and support a knowledge synthesis study group/board to identify gaps and prioritize cancer pharmacoepidemiology and
2. Develop and support opportunities to identify clinical, sociodemographic, lifestyle, and genomic markers related to treatment response and/or
adverse events in NCI-sponsored clinical trials.
Support pharmacoepidemiology and pharmacogenomic studies using previously collected clinical data and biospecimens from existing and
ongoing clinical trials.
Develop and support opportunities to routinely collect and store DNA specimens in new and existing NCI-sponsored clinical trials for future
Develop and support the incorporation of pharmacogenomic markers and/or epidemiological information into the design of clinical trials.
3. Support observational studies that identify clinical, sociodemographic, lifestyle, and genomic factors of treatment response and adverse events.
Use predictive clinical, sociodemographic, lifestyle, and genomic factors associated with treatment response and adverse events discovered
in clinical trial analyses to develop and support opportunities to validate findings in large, heterogeneous, observational studies.
Develop and support opportunities to identify predictive factors of treatment response and adverse events that cannot be obtained using
existing clinical trial and correlative study data.
Support observational studies of cancer patients (eg, patient cohorts) with standardized protocols and comprehensive biospecimen collections
at multiple time points to identify clinical, sociodemographic, lifestyle, and genomic factors that affect cancer treatment and prevention outcomes.
Support observational studies of pharmacoepidemiology of cancer prevention and risk.
4. Support basic pharmacology research on the pharmacodynamics, pharmacokinetics, and targets of cancer drugs, and their relationships with
genetic variations that affect drug response because of differential gene expression, protein production, receptor-binding affinity, and enzyme
level and activity.
5. Provide support for research on the utility of promising pharmacogenetic applications in general clinical practice.
6. Support health information technology enhancements in existing research networks and data systems to facilitate pharmacoepidemiology
and pharmacogenomic studies of observational and clinical trial data.
7. Support research on the ethical, legal, social, and data-sharing implications of collecting biospecimens for pharmacogenomics research in
population-based and clinical trial research settings.
8. Support the development of transdisciplinary training programs in cancer pharmacogenomics and pharmacoepidemiology.
9. Support, facilitate, and coordinate a trans-NCI effort to partner with other relevant groups, including other federal agencies and
industry to develop initiatives and activities in pharmacogenomic and pharmacoepidemiology cancer research that ensure the
integration of basic, clinical, and population sciences.
JNCI | Commentary 1701
of scientists, policy makers, and patient advocates. Membership
should reflect a broad spectrum of expertise, including oncology,
genomics, clinical and basic pharmacology, epidemiology, and
Pharmacogenomics and Pharmacoepidemiology Within
Recommendation 2 calls for support of the collection, storage, and
analysis of biospecimens from clinical trials. The workshop partic-
ipants noted that in clinical trials, biospecimens are not routinely
collected; therefore, the availability of tumor and DNA samples
varies considerably across studies. Even when such samples have
been collected and stored, there has been limited use of the exist-
ing clinical and biospecimens data for pharmacogenomic and
pharmacoepidemiologic research. Workshop participants agreed
that studies, including genome-wide association studies (GWAS),
that use previously collected clinical data and biospecimens from
existing and ongoing clinical trials could provide important data
that could be rapidly translated into clinical practice and improve
treatment management. To promote the pursuit of such studies, it
will be necessary to coordinate access, collection, inventory, and
pooling of clinical trial data and specimens across trials and across
sponsors. Mechanisms for long-term follow-up of clinical trial
patients also need to be developed to examine long-term benefits
and adverse late effects of various treatments. Last, it is important
to develop rapid, open, transparent, and equitable processes for the
review of applications for access to these biospecimens.
As of June 2008, more than 300 000 blood samples that had
been collected from patients from NCI-sponsored Clinical Trials
Cooperative Group Program trials (13,14) were stored in tissue
banks. Even more samples are potentially available through the
NCI-sponsored Specialized Programs of Research Excellence (15),
Cancer Centers (16), and individual investigator research projects.
Pharmaceutical company–sponsored studies are another major
source of biospecimens if data sharing, material transfer agreements,
and access for outside investigators can be negotiated. Important
research findings using retrospective analyses of tumor markers
from completed clinical trials already have been successfully trans-
lated into clinical practice. For example, numerous clinical trials
have shown that colorectal cancer therapy with cetuximab or pani-
tumumab is ineffective in tumors with somatic mutations in
codons 12 and 13 of exon 2 of the KRAS gene. These findings
prompted the American Society of Clinical Oncology to develop
guidelines to target the clinical use of these drugs based on these
genetic markers (17) and the European Medicines Agency and the
FDA to include these data in the prescribing information for
cetuximab and panitumumab.
Collaborations have been established between Pharmacogenetic
Research Network investigators (18), the NCI, the Cooperative
Groups, and the Rikagaku Kenkyusho Center for Genomic
Medicine in Japan (19) to use GWAS to find genetic variations of
germline DNA associated with cancer treatment and prevention
responses and adverse events. A recent GWAS from the
Postmenopausal Breast Cancer Adjuvant Trial MA.27 found sev-
eral single-nucleotide polymorphisms associated with musculo-
skeletal adverse events in women who received adjuvant therapy
with aromatase inhibitors for early breast cancer (20). These novel
findings may lead to the prevention of musculoskeletal adverse
events in women who receive these therapies, and they specifically
illustrate the incredible opportunity to advance discoveries in per-
sonalized cancer medicine by conducting pharmacogenomic
research using pooled trial data and specimens.
Federal agencies can ensure that collected specimens are avail-
able and are used to answer critical clinical questions most effi-
ciently by 1) establishing mechanisms and common protocols that
allow specimens to be pooled across studies and shared with out-
side investigators; 2) creating a searchable inventory of specimen
collections, accompanied by annotated data for each patient,
to facilitate their use; and 3) developing mechanisms to fund main-
tenance of biospecimen repositories and sustained long-term
follow-up of trial participants, including cohorts created de novo
Answering future research questions requires a substantial
amount of planning and coordination today. As much as possible,
the most versatile DNA specimens should be collected for future
research use (eg, blood samples may provide more analytic flexi-
bility than saliva samples). Methods for specimen collection,
storage, and handling should be standardized to provide consis-
tently high-quality samples that can be pooled across studies.
However, the samples alone are of little value without careful
annotation of drug exposures, clinical outcomes, and demo-
graphics. Additionally, information concerning dietary, environ-
mental, and other lifestyle factors should be collected to greatly
add to the validity of studies. Currently, information concerning
these variables is not consistently collected within clinical trials nor
coordinated across studies. The development of new statistical
methodologies is needed to harmonize, manage, and analyze these
large and complex pooled datasets. The Breast Cancer Intergroup
of North America has established systems and procedures for
sharing specimens and has already conducted several collaborative
pharmacogenomic research investigations. Lessons learned from
their successes and challenges can help direct efforts for other
cancer and clinical trial networks (21).
Pharmacogenomics and Pharmacoepidemiology in
Observational and Population-Based Studies
Recommendation 3 calls for the support of observational studies
that identify clinical, sociodemographic, lifestyle, clinical, and ge-
nomic factors that influence treatment response and/or adverse
events. Observational studies can be useful to validate clinical trial
findings of predictive factors associated with treatment response
and adverse events and to evaluate treatments in patients who were
not represented in the clinical trials. Observational studies can be
particularly important to assess rare adverse events and the impact
of age, organ-system impairment, lifestyle factors, and other dis-
eases on the effectiveness and safety of newly approved therapies.
In many situations, specimens and/or clinical and epidemiolog-
ical data, such as comorbid conditions and lifestyle factors, may not
have been collected in adequate numbers within existing clinical
trials and correlative studies to answer important clinical ques-
tions. In these situations, observational studies can be helpful to
discover and validate new associations. These studies may include
analyses of 1) rare or long-term events, including toxicities and
future outcomes of cancer; 2) effects or outcomes of off-label use;
1702 Commentary | JNCI Vol. 102, Issue 22 | November 17, 2010
3) drug–drug interactions; and 4) contributions of lifestyle, demo-
graphic factors, and other comorbid conditions. Observational
studies would help to confirm the importance of genomic varia-
tions identified in cancer therapy trials, particularly when trials are
underpowered, and also to study the impact of genetic variations
in response to therapy and/or to study toxicities among diverse
patient populations and ethnic groups that were not adequately
represented in clinical trials.
There are several examples of how observational studies have
been used to identify clinically important associations. One recent
example involves the association of cytochrome P450 2D6 gene
(CPY2D6) polymorphisms with outcome among women with
breast cancer who were treated with tamoxifen. Retrospective
analyses of clinical trials (22–27) showed that breast cancer patients
who were classified as poor or intermediate metabolizers based on
their CYP2D6 genotype had unfavorable outcomes on tamoxifen.
However, the clinical relevance was uncertain because of small
sample sizes within studies and inconsistent quality and results
across several clinical studies. Recently, Schroth et al. (28) pub-
lished the first adequately powered study, an observational study of
a cohort of 1325 breast cancer patients that showed a statistically
significant association between CYP2D6 genotypes and clinical
outcomes. This study validated the previous retrospective clinical
trials analyses and provides additional evidence for the clinical
relevance of using CYP2D6 genotypes to inform breast cancer
treatment. A study by Ross et al. (29) that demonstrated that vari-
ants in the genes for thiopurine methyltransferase (TPMT) and
catechol-O-methyltransferase (COMT) were strongly associated
with hearing loss among children receiving cisplatin chemotherapy
is an excellent example of the use of an observational cohort study
design to identify the cause of an otherwise idiosyncratic adverse
event. They analyzed candidate genes in an initial cohort of 54
children treated in pediatric oncology units, followed by a replica-
tion in a second cohort of 112 children recruited through a na-
tional surveillance network for adverse drug reactions in Canada.
In an example of a pharmacogenomic observational study that
examined factors related to survival, Chan et al. (30) analyzed a
prospective cohort of 1279 men and women with colorectal cancer
and found that regular aspirin use after the diagnosis of colorectal
cancer is associated with a lower risk of colorectal cancer-specific
and overall mortality, especially among individuals with tumors
that overexpressed cyclooxygenase-2.
A comprehensive and coordinated research approach is
necessary to translate promising findings such as these into clinical
practice. The workshop participants recommended developing
and supporting opportunities for the creation of new observational
patient cohort studies that include standardized and uniform col-
lection of comprehensive specimen and treatment data. These
patient cohorts would be essential not only for measuring genomic
factors and biomarkers within high-standard biospecimens but also
for assessing health behavior and lifestyle factors during critical
time periods, such as during and shortly after therapy. In addition,
it would be beneficial to leverage existing population-based
research studies and networks to answer questions that cannot be
addressed through existing resources. Such efforts should include
establishing sustainable cohorts of cancer patients; obtaining epi-
demiological, clinical, and biological data on study participants
over a number of years; and/or leveraging existing networks, such
as the NCI-sponsored Health Maintenance Organization–Cancer
Research Network (31), health maintenance organizations (32),
and other private entities with electronic medical records through
which to obtain information on prescription drug use.
Pharmacogenomics in Basic Science
Recommendation 4 calls for support of basic pharmacological re-
search on the pharmacodynamics and pharmacokinetics of drugs
used in the prevention and treatment of cancer. There is a need to
better understand complex pharmacokinetic and pharmacody-
namic pathway mechanisms at early stages of drug development as
well as after drug approval. This includes the study of the targets
of cancer drugs, and their relationships with genetic variations that
affect drug response because of differential gene expression,
protein production, receptor-binding affinity, and/or enzyme level
and activity. Functional analyses of the proteins encoded by genes
identified in GWAS also will be valuable in clinically homoge-
neous case subsets. Such research will help to identify the genomic
contributions to drug response and adverse events and will provide
novel insight into mechanisms of drug action and disease
There are a number of recent examples of the impact of phar-
macokinetic and pharmacodynamic analysis on our understanding
of variation of response to cancer treatment. Pharmacokinetic and
pharmacodynamic evaluation of the CYP2D6-mediated metabo-
lism of tamoxifen implicated endoxifen as the key active metabo-
lite, leading NCI to begin development of endoxifen as an agent to
be used alone in treating breast cancer (33). Pharmacokinetic and
pharmacodynamic studies can also inform our mechanistic under-
standing of adverse events. As mentioned above, a recently pub-
lished GWAS (20) identified three single-nucleotide polymorphisms
on chromosome 14 associated with musculoskeletal adverse events
in women receiving aromatase inhibitors. Functional analysis of
these single-nucleotide polymorphisms indicates that they are
associated with decreased T-cell leukemia/lymphoma protein 1A
(TCL1A) expression related to estrogen exposure (20).
Clinical Effectiveness, Utility, and Dissemination of
Pharmacogenomics and Pharmacoepidemiology
Recommendation 5 provides support for studies of clinical utility
that focus on the effectiveness of pharmacogenomic applications in
general clinical practice and the implications of incorporating these
tests in representative patient populations and/or general popula-
tions. Translational research that moves pharmacoepidemiology
and pharmacogenomic discoveries from basic science and clinical
trials to the bedside has been limited at best. Research is needed to
help clarify the levels of evidence that are needed for acceptable
adoption of new pharmacogenomics technology into clinical prac-
tice. Although randomized clinical trials are gold standard for
determining the efficacy of treatments, prospective and retrospec-
tive observational studies with high-quality phenotyping data
might be adequate for the adoption of some diagnostic tests and
certain treatment decisions. In addition to assessing immediate
clinical endpoints, studies should incorporate longer-term out-
comes, such as survival, patient-reported outcomes, and cost–benefit
JNCI | Commentary 1703
analyses, as well as key factors influencing patients’ decisions and
preferences for cancer treatment. To address this need, under pro-
visions for the National Institutes of Health in the American
Recovery and Reinvestment Act, NCI recently funded seven large
projects (34) for 2-year efforts that will advance methods for the
evaluation of the clinical validity and utility of existing and
emerging genomic personalized medicine applications in cancer
control and prevention. These initiatives should enhance the clin-
ical and population data infrastructure to support comparative ef-
fectiveness research initiatives in genomic personalized medicine.
Dissemination studies that focus on barriers and facilitators to
wide-scale adoption of proven pharmacogenomic technologies or
on the overuse or misuse of technologies that have questionable
risk to benefit profiles should be supported. In addition, research
on effective processes, such as clinical decision support tools,
should be supported to integrate pharmacogenomic technologies
into clinical practice. Furthermore, the existence of different prac-
tice settings, such as rural clinics, academic institutions, medical
centers, should be taken into account as part of the strategy for
enhancing the incorporation of pharmacogenomics information
into regular clinical practice.
Recommendation 6 supports the development of new bioinfor-
matics methodologies and statistical expertise to process large vo-
lumes of data and to harmonize and combine existing samples,
population information, and data. Linking pharmacogenomic and
pharmacoepidemiology data, particularly the results of GWAS
regarding the association of gene variants with adverse events,
drug response, patient characteristics, and other data, will also be
important. These activities will need to be coordinated with the
new Biomedical Informatics Grid Health Consortium (35), NCI’s
cancer Biomedical Informatics Grid (36), Human Genome
Epidemiology Network (10), and the PharmGKB (11).
Ethical, Legal, Social, and Data-Sharing Implications
Recommendation 7 recognizes a need to implement specific and
consistent procedures for data sharing and protection of confiden-
tiality. The long-term follow-up of patients, the analysis of stored
specimens for new purposes, and the sharing of information across
investigations that includes sharing across government and private
sector boundaries, bring new legal, ethical, and social challenges
that must be addressed. Support is needed at all levels, including
the development of educational resources to help institutional
review boards better understand that the risks of collecting phar-
macogenomics marker data on patients differ substantially from
the risks of collecting data for other types of disease markers. Data-
sharing policies will also be needed (especially for multinational
collaborations), and appropriately flexible informed consent forms
will be needed to ensure that patients have the opportunity to give
or deny consent to use their biospecimens and other data in studies
that may be conceived years––or potentially, even decades––after
their original consent.
Combining two rather young fields, pharmacogenomics and
pharmacoepidemiology, depends on the integration of genetics,
epidemiology, and pharmaceutical sciences, which may require
additional training and the development of new skill sets. A suc-
cessful investigator in these fields must be conversant in such
disparate disciplines as pathology, statistical genetics, and infor-
mation technology. Such expertise takes considerable time to
develop. Recommendation 8 states that efforts are needed
to expand transdisciplinary training programs in pharmacoge-
nomics, pharmacoepidemiology, and clinical pharmacology.
Fellowships and career development training grants at NCI,
FDA, other federal agencies, and universities are needed to pro-
mote doctoral- and postdoctoral-level training to enable physi-
cians and other researchers to obtain these skills.
Coordination and Partnerships of Public and Private
Last, workshop participants recommended that the PPWG con-
tinue its work to support, facilitate, and coordinate trans-NCI ef-
forts to develop initiatives and activities in pharmacoepidemiology
and pharmacogenomic cancer research that ensure the integration
of the basic, clinical, and population sciences. To facilitate collab-
oration and avoid overlapping efforts beyond the NCI, it will be
critical to identify ongoing efforts by other federal agencies, in the
private sector, throughout the European Union, and globally to
foster partnerships that may include the FDA, HMOs, pharmacy
benefit providers, the CDC, the Centers for Medicaid and
Medicare Services, the Agency for Healthcare Research and
Quality, the Department of Defense, the Department of Veterans
Affairs, and professional medical societies.
Summary of Workshop: Research Priorities
The advancement of cancer pharmacogenomics and pharmacoepi-
demiology research has promise to facilitate the discovery and
translation of research findings that will improve clinical decision
making and increase cancer survival while reducing the harms as-
sociated with cancer treatment. The trans-NCI PPWG and partic-
ipants of an NCI-sponsored Pharmacogenomics Workshop
considered how best to foster cancer pharmacogenomic and phar-
macoepidemiology research. Their ideas included ways to rapidly
translate the results of bench research into medical practice and
ways to test hypotheses generated from epidemiological and clin-
ical investigations in the laboratory. Together, these complemen-
tary and interacting approaches will help us realize the benefits of
a personalized approach to cancer treatment and prevention. As
currently envisioned, a cancer pharmacogenomics and pharmaco-
epidemiology initiative will also encourage collaboration across
disciplines and partner with other federal agencies with shared
interests to leverage resources and knowledge. The research spon-
sored by such an initiative will improve our understanding of
adverse drug events through systematic, rather than anecdotal, risk
to benefit analyses; increase our ability to understand and monitor
the effects of commonly used drugs on cancer risk; enable us to
more efficiently track off-label drug use and its effects; improve
cancer treatment and cancer prevention trial designs; improve
postmarketing surveillance (particularly of new antineoplastic
agents); and potentially reduce the cost of cancer care by matching
treatments to patients most likely to benefit.
1704 Commentary | JNCI Vol. 102, Issue 22 | November 17, 2010
1. Hoskins JM, Carey LA, McLeod HL. CYP2D6 and tamoxifen: DNA
matters in breast cancer. Nat Rev Cancer. 2009;9(8):576–586.
2. Palomaki GE, Bradley LA, Douglas MP, et al. Recommendations from
the EGAPP Working Group: can UGT1A1 genotyping reduce morbidity
and mortality in patients with metastatic colorectal cancer treated with
irinotecan? Evaluation of Genomic Applications in Practice and Prevention
Working Group. Genet Med. 2009;11(1):15–20.
3. Dahabreh IJ, Linardou H, Siannis F, et al. Somatic EGFR mutation and
gene copy gain as predictive biomarkers for response to tyrosine kinase
inhibitors in non-small cell lung cancer. Clin Cancer Res. 2010;16(1):
4. Paez JG, Jänne PA, Lee JC, et al. EGFR mutations in lung cancer: corre-
lation with clinical response to gefitinib therapy. Science. 2004;304(5676):
5. Plesac TP, Hunt JL. KRAS mutation testing in colorectal cancer. Adv
Anat Pathol. 2009;16(4):196–203.
6. Relling MV, Hancock ML, Rivera GK, et al. Mercaptopurine therapy
intolerance and heterozygosity at the thiopurine S-methyltransferase gene
locus. J Natl Cancer Inst. 1999;91(23):2001–2008.
7. Cancer pharmacogenomics. setting a research agenda to accelerate
translation workshop. National Cancer Institute.Web site. http://www
.team-psa.com/CPSRAAT2009/home.asp. Accessed June 9, 2010.
8. Trans-NCI Pharmacogenomics and Pharmacoepidemiology Working
Group (PPWG). National Cancer Institute. Web site. http://epi.grants
.cancer.gov/pharm/ppwg.html. Updated May 11, 2010. Accessed June 9,
9. Evaluation of Genomic Applications in Practice and Prevention
(EGAPP). Centers for Disease Control and Prevention. Web site.
http://www.egappreviews.org. Updated May 3, 2010. Accessed June 9,
10. Human Genome Epidemiology Network (HuGENet). Centers for
Disease Control and Prevention. Web site. http://www.cdc.gov/
genomics/hugenet/default.htm. Updated April 14, 2010. Accessed June
11. Khoury MJ, Feero WG, Reyes M, et al. The Genomic Applications in
Practice and Prevention Network. GAPPNet Planning Group. Genet Med.
12. Pharmacogenetics and Pharmacogenomics Knowledge Base (PharmGKB).
Stanford University. Web site. http://www.pharmgkb.org. Accessed June
13. Community Clinical Oncology Program (CCOP). National Cancer
Institute. Web site. http://dcp.cancer.gov/programs-resources/programs
/ccop. Accessed September 27, 2010.
14. Clinical Trials Cooperative Group Program. National Cancer Institute.
Web site. http://dctd.cancer.gov/MajorInitiatives/06CTEPCoopGrps.
htm. Accessed June 9, 2010.
15. Specialized Programs of Research Excellence (SPOREs). National Cancer
Institute. Web site. http://spores.nci.nih.gov. Accessed June 9, 2010.
16. Cancer Centers Program. National Cancer Institute. Web site. http:
//cancercenters.cancer.gov/. Accessed September 27, 2010.
17. Allegra CJ, Jessup JM, Somerfield MR, et al. American Society of Clinical
Oncology provisional clinical opinion: testing for KRAS gene mutations
in patients with metastatic colorectal carcinoma to predict response to
anti-epidermal growth factor receptor monoclonal antibody therapy.
J Clin Oncol. 2009;27(12):2091–2096.
18. Pharmacogenetics Research Network (PGRN). http://www.nigms.nih
.gov/Initiatives/PGRN. National Institute of General Medical Sciences
Web site. Updated May 18, 2010. Accessed June 9, 2010.
19. Center for Genomic Medicine (CGM). RIKEN Yokohama Institute. Web
site. http://www.src.riken.jp/english/. Accessed September 27, 2010.
20. Ingle JN, Schaid DJ, Goss PE, et al. Genome-wide associations and func-
tional genomic studies of musculoskeletal adverse events in women re-
ceiving aromatase inhibitors. J Clin Oncol. Published online on September
27, 2010; DOI:10.1200/JCO.2010.28.5064.
21. The Breast Cancer Intergroup of North America (TBCI). National
Cancer Institute. Web site. http://ctep.cancer.gov/investigatorResources/
tbci. Updated June 22, 2009. Accessed June 9, 2010.
22. Goetz MP, Rae JM, Suman VJ, et al. Pharmacogenetics of tamoxifen
biotransformation is associated with clinical outcomes of efficacy and hot
flashes. J Clin Oncol. 2005;23(36):9312–9318.
23. Goetz MP, Knox SK, Suman VJ, et al. The impact of cytochrome P450
2D6 metabolism in women receiving adjuvant tamoxifen. Breast Cancer Res
24. Schroth W, Antoniadou L, Fritz P, et al. Breast cancer treatment outcome
with adjuvant tamoxifen relative to patient CYP2D6 and CYP2C19 geno-
types. J Clin Oncol. 2007;25(33):5187–5193.
25. Lim HS, Ju Lee H, Seok Lee K, et al. Clinical implications of CYP2D6
genotypes predictive of tamoxifen pharmacokinetics in metastatic breast
cancer. J Clin Oncol. 2008;25(25):3837–3845.
26. Xu Y, Sun Y, Yao L, et al. Association between CYP2D6*10 genotype and
survival of breast cancer patients receiving tamoxifen treatment. Ann
27. Kiyotani K, Mushiroda T, Sasa M, et al. Impact of CYP2D6*10 on
recurrence-free survival in breast cancer patients receiving adjuvant ta-
moxifen therapy. Cancer Sci. 2008;99(5):995–999.
28. Schroth W, Goetz MP, Hamann U, et al. Association between CYP2D6
polypmorphisms and outcomes among women with early stage breast
cancer treated with tamoxifen. JAMA. 2009;302(13):1429–1436.
29. Ross CJ, Katzov-Eckert H, Dubé MP, et al. Genetic variants in TPMT
and COMT are associated with hearing loss in children receiving cisplatin
chemotherapy. CPNDS Consortium. Nat Genet. 2009;41(12):1345–1349.
30. Chan AT, Ogino S, Fuchs CS. Aspirin use and survival after diagnosis of
colorectal cancer. JAMA. 2009;302(6):649–659.
31. HMO Research Network. Web site. http://www.hmoresearchnetwork.
org. Accessed June 9, 2010.
32. Cancer Registries and Other Population-Based Resources. National
Cancer Institute. Web site. http://riskfactor.cancer.gov/tools/pharmaco
/registries.html. Updated May 26, 2009. Accessed June 9, 2010.
33. Doroshow JH. NCI’s roadmap to personalized cancer treatment. Talk
presented at: National Cancer Institute Board of Scientific Advisors
Meeting; June 22, 2009, Bethesda, MD. Web site. http://deainfo.nci.nih.
Accessed September 27, 2010.
34. Comparative Effectiveness Research in Genomics and Personalized
Medicine. National Cancer Institute. Web site. http://cancercontrol.
cancer.gov/od/phg/research.asp?type=CER. Updated February 24, 2010.
Accessed September 27, 2010.
35. Biomedical Informatics Grid (BIG) Health Consortium. http://big
healthconsortium.org/about/cabig.asp. Accessed June 9, 2010.
36. Cancer Informatics Biomedical Grid (caBIG) Community. National
Cancer Institute. Web site. https://cabig.nci.nih.gov. Accessed June 9, 2010.
NCI sponsored the 2009 workshop and the Pharmacogenomics and
Pharmacoepidemiology working group. The funding source has not dictated
any of the content of this commentary.
We gratefully acknowledge the contributions of many individuals with whom
we have had discussions and who have been supportive of this effort. These
include current members of the PPWG (Supplementary Material A, available
online) and participants in the workshop (Supplementary Material B, available
online). We particularly thank Dr Rochelle Long for her invaluable insight and
contributions to this article and participation in the workshop. We also thank
Ms Linda Anderson for her editorial assistance.
Dr Mark Ratain reports receiving royalties from the University of Chicago
in regard to UGT1A1 genotyping and relationships with Bristol-Myers Squibb,
Genentech, and Novartis. Dr Geoffrey Ginsburg reports business relationships
with Cancer Guide Diagnostics, Inc, and Pappas Ventures. Dr Mary Relling
reports receiving research funding from Sigma-Tau Pharmaceuticals and royalties
from St Jude for licensing of patents related to TPMT and GGH polymorphisms.
Affiliations of authors: Division of Cancer Control and Population Sciences
(ANF, LBS, SAN, RB-B), Medical Oncology Branch, Center for Cancer
JNCI | Commentary 1705
Research (WDF), Division of Cancer Epidemiology and Genetics (NR), Division
of Cancer Treatment and Diagnosis (JHD), and Division of Cancer Prevention,
National Cancer Institute, Bethesda, MD (LMM); Health Services Research,
Lombardi Comprehensive Cancer Center, Georgetown University,
Washington, DC (ALP); Center for Drug Safety, University of Maryland School
of Pharmacy, Baltimore, MD (SRWS); Office of Public Health Genomics,
Centers for Disease Control and Prevention, Atlanta, GA (MJK); Division of
Clinical Pharmacology, Mayo Clinic College of Medicine, Rochester, MN
(RMW); Clinical Sciences, Cancer Research Center, University of Chicago
Medical Center, Chicago, IL (MJR); UNC Institute for Pharmacogenomics and
Individualized Therapy, University of North Carolina, Chapel Hill, NC (HLM);
Medco Health Solutions, Inc, Franklin Lakes, NJ (RSE); Center for Genomic
Medicine, Duke Institute for Genome Sciences & Policy, Duke University,
Durham, NC (GSG); Section of Hematology-Oncology, University of Chicago
Medical Center, Chicago, IL (RLS); Ontario Cancer Institute, Princess
Margaret Hospital, University of Toronto, Toronto, Ontario (GL); Division of
Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN
(DAF); Division of Preventive Oncology, German Cancer Research Center and
National Center for Tumor Diseases, Heidelberg, Germany (CMU); Public
Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle,
WA (CMU); The Center for Health Research, Kaiser Permanente, Atlanta, GA
(RLD); Office of Clinical Pharmacology and Biopharmaceutics, Center for Drug
Evaluation and Research, Food and Drug Administration, Silver Spring, MD
(LJL, IZ); Center for Outcomes and Evidence, Agency for Healthcare Research
and Quality, Rockville, MD (GR); Department of Cancer Prevention and
Control, Roswell Park Cancer Institute, Buffalo, NY (CBA); Department of
Pharmaceutical Sciences, St Jude Children’s Research Hospital, Memphis,
TN (MVR); Division for Clinical Research Resources, National Center for
Research Resources, National Institutes of Health, Bethesda, MD (HX);
University of Texas M.D. Anderson Cancer Center, Houston, TX (MRS).