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Chapter23
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Pharmacogenomics
Leo Kager1 and William E. Evans
1
St Anna Children’s Hospital, St. Anna Children’s Cancer Research Institute, Medical University Vienna, Vienna, Austria
2
Pharmacy and Pharmaceutical Sciences Department, St Jude Children’s Research Hospital, Memphis, TN, USA
Introduction, 343
Principles of pharmacogenomics, 344
Pharmacogenomics to improve childhood ALL therapy, 347
Introduction
2
Pharmacogenomics to optimize oral antithrombotic therapy, 353
Summary and challenges for the future, 356
Further reading, 357
P4502C9 (CYP2C9) and vitamin K epoxide reductase complex 1
(VKORC1) that affect the efficacy and toxicity of warfarin–
It has long been recognized that there is great heterogeneity
in the way people respond to medications. For example,
when a standard dose of a certain drug is given to a cohort of
patients, some will respond and some will not respond, some
will respond only partially, and some will experience adverse
drug reactions (ADRs) that can be life threatening. This
variation in both host toxicity and treatment efficacy can
have many different causes, including environmental (e.g.
nutrition, drug interactions), physiological (e.g. age, gender,
nutritional status, organ functions), pathophysiological (e.g.
pathogenesis and severity of the disease being treated), and
genetic as well as epigenetic factors. Overall, genetic factors
are estimated to account for 15–30% of interindividual differences in drug metabolism and response. For certain drugs,
however, genetic factors are of the utmost importance and
can account for up to 95% of interindividual variability in
drug disposition and effects.
The science of pharmacogenetics, which was defined by
Friedrich Vogel as the “the study of the role of genetics in
drug response,” has a long tradition in the field of hematology. In the 1950s, the relationship between hemolysis after
antimalarial therapy and the inherited glucose- 6- phosphate
dehydrogenase (G6PD) activity in erythrocytes was identified. This discovery explained why the ADR of hemolysis is
observed mainly in Africans, where up to 10% of individuals
are deficient in G6PD, but is rarely seen in other ethnic
groups like Europeans, in whom G6PD deficiency is uncommon. Until 2000, efforts were mainly concentrated on mapping highly penetrant monogenic loci for drug- metabolizing
enzymes that strongly influence the effects of medications.
Interestingly, two of the most important clinical examples of
Mendelian pharmacogenetics– variants in the thiopurine Smethyltransferase (TPMT) gene that affect the efficacy and
toxicity of thiopurines, and variants in the cytochrome
were again discovered in the field of hematology, namely in
the treatment of acute lymphoblastic leukemia (ALL) and
oral anticoagulant therapy, respectively.
However, it is well recognized that most pharmacological
effects result from the interplay of numerous gene products,
and since the human genome has been sequenced and the
human haplotypes of the most common form of genetic variation, namely singlemapped, genome- wide approaches (i.e. pharmacogenomics)
are often used to elucidate the genomic contributors of
variability in drug effects. The terms “pharmacogenetics”
and “pharmacogenomics” are synonymous for all practical
purposes, and we herein use the term pharmacogenomics.
Besides pharmacogenomics, also the field of pharmacoepigenomics, which focuses on the identification of pharmacologically relevant epigenetic variants, has evolved.
Advances in genome, transcriptome, and epigenome
interrogation technologies (e.g. arrays for genome- wide SNV,
mRNA, and DNA- methylation analyses, “next- generation”
DNA sequencing technologies like whole- exome sequencing–
WES, coding regions and “untranslated regions” only– and
whole- genome sequencing– WGS, coding and non- coding
regions) and in silico analytical approaches have become
sufficiently robust and costagnostic genome wide investigations to identify pharmacologically relevant relationships between genomic variants and
well- defined pharmacological endpoints, for example in
genome- wide association studies (GWAS). Moreover, progress was also achieved to analyze somatic variants in single
cells, e.g. in hematological malignancies. Single- cell multiomics technologies and methods can help to characterize for
example leukemia cell states and activities by integrating
different single omics methods that profile e.g. the transcriptome, genome, epigenome, proteome or metabolome.
nucleotide variants (SNVs), have been
effective and allow essentially
Molecular Hematology, Fifth Edition. Edited by Drew Provan and Hillard M. Lazarus.
© 2024 John Wiley & Sons Ltd. Published 2024 by John Wiley & Sons Ltd.
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343
344 Molecular Hematology
Genomic variants
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These methods have helped to characterize the clonal nature
of somatic variants, to identify genetic- drivers and sub- clones
that are either primary resistant to conventional cancer chemotherapy or develop drug resistance under the selective pressure on leukemia cells e.g. via commonly used medications
like thiopurines or glucocorticoids.
A broader contemporary definition of pharmacogenomics is: “the study of genomic technologies to enable the optimization of drug dose and choice in individual patients to
maximize efficacy and to minimize toxicity, and to enable
the discovery and development of novel drugs.” Of note,
pharmacogenomics plays an emerging role in drug development, and 2/3 of US Food and Drug Administration (FDA)
approved drugs in 2021 had supportive human genomic
evidence.
In 2015, the US president Barak Obama announced the
precision medicine initiative, and pharmacogenomics is
animportant element of precision medicine. More recently,
comprehensive functional genomic landscapes, which
include also “pharmacotyping” (i.e. invitro drug screens
like the MTT drug- resistance assay or image- based singlecell functional precision medicine approach), were provided
for hematological malignancies, and individualized therapies based on the insights gained from such studies achieved
clinical benefits for some patients, including exceptional
responders.
In this short chapter, validated, clinically relevant examples
are presented to illustrate how pharmacogenomics can be used
to rationally improve current drug therapy in hematological
diseases and to identify novel targets for developing new
therapeutic approaches in hematological diseases.
Principles ofpharmacogenomics
The effects of drugs are determined by the interplay of many
gene products that influence the pharmacokinetics and pharmacodynamics of medications. Whereas pharmacokinetics
describes the absorption, distribution, metabolism, and excretion of drugs (so- called ADME), pharmacodynamics studies
the relationship between the pharmacokinetic properties of
drugs and their pharmacological effects, which can be desired
or adverse. The ultimate goal of pharmacogenomics is to
elucidate functionally relevant genomic determinants for
drug disposition (germline variants) and response (variants
in drug targets) to select medications and dosage of medications on the basis of each patient’s inherited ability to metabolize, eliminate, and respond to specific drugs (Figure23.1). In
hematological malignancies, for example, the genomic architecture differs between the normal host cells (i.e. germline)
and the malignant cells (i.e. the therapeutic target or targets),
which harbor germline and acquired somatic variants. Many
variants in the human genome and epigenome and in cancer
cells have been identified that influence the expression and
activity of pharmacologically relevant proteins.
Variation inthe human genome
The human genome consists of about 3 × 109 bp (3 Gb).
Although any two humans are thought to be up to 99.6%
identical in their DNA sequence, the remaining small fraction of the genome, which constitutes the genetic diversity
among individuals, contains many forms of variation, ranging
from large, microscopically visible chromosome anomalies
Genotype
Host cells
(germline)
Single-nucleotide polymorphisms (SNPs)
insertions/deletions (Indels <50 bp)
Varying number of tandem repeats (VNTR)
Copy number variants (CNV, <50 bp)
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Target
Epigenetic variants
Somatic variants
cells
Genotype
Drugs
Delivery
Absorption
Distribution
PK
PD
Pharmacological effects
Metabolism
Excretion
Target
Mechanism of action
Drug responses
ToxicityEfcacy
Figure23.1 General principles of pharmacogenomics. One goal of pharmacogenomics is to
identify variants in regulatory and coding regions
of genes (i.e. pharmacogenes) that influence
pharmacokinetics (PK) and pharmacodynamics
(PD) of delivered drugs by increasing or decreasing
protein (i.e. pharmacoproteins) expression or
function, thereby influencing both efficacious and
toxic effects. Investigating these functionally
important pharmacovariants in the human
population can help to explain some differences in
drug effects.
Pharmacogenomics 345
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to single- nucleotide changes. Variants that are about 3 Mb or
more in size are referred to as microscopic variants. The
smaller, and much more abundant, variants include SNVs,
small (<50 bp) insertions and deletions (indels) of nucleotides,
variation in the number of repeats of a specific motif
(i.e. variable- number tandem repeats, minisatellites, and
microsatellites), duplications, and variants of DNA segments
50 bp or larger that are collectively defined as copy number
variations (CNVs). Like SNVs, a single nucleotide polymorphism (SNP) is also a single base substitution, but it
must be present in at least 1% of the population. Projects on
population- scale NGS analyses have provided millions of
genomic variants, many of which are publicly available in
variant repositories, like the Genome Aggregation Database
(gnomAD, https://gnomad.broadinstitute.org/).
Single- nucleotide variants
The most common and most extensively studied inherited
genomic variations are SNVs, positions in the genome where
individuals have inherited a different nucleotide. SNVs in exons
that cause amino acid substitutions, which have the potential
to change the function of a protein (e.g. by alteration of the
catalytic cleft of an enzyme), are named missense variants.
Currently, >4million missense variants have been identified
in the human genome, and in WES and WGS analyses on 208
pharmacogenes in 130 000 individuals, each individual was
found to carry ~144 missense variants, ~155 synonymous,
and ~12nonsense variants in these pharmacogenes.
In contrast to missense variants, synonymous variants
(sSNVs) do not affect the amino acid sequence, but can for
example affect the rate of translation (e.g. disrupt the activity
of cis- regulatory elements which regulate gene activity),
modulate the splicing of genes, and alter protein folding.
Whereas they are as frequent as missense variants, yet, only a
few sSNVs were identified to functionally affect pharmacogenes; e.g. the sSNVs rs1128503 and rs1045642in the gene
ABCB1, which encodes the pharmacologically important
adenosine triphosphate (ATP)-
binding cassette transporter
ABCB1, affect protein folding and function.
Nonsense variants (i.e. stop- gain, frameshift and splice
variants) can have different effects including protein truncation or degradation of the transcript by nonsense- mediated
decay. They often, but not always, are functionally deleterious and were 10 times rarer observed in pharmacogenes
compared to missense variants.
SNVs in genomic regions that influence the expression of
functionally relevant genes like transcription factors or
microRNA binding sites can also have pharmacological
consequences. For example, a miR- 24microRNA bindingsite variant was found to be associated with antifolate resistance by influencing the expression of the antifolate target
dihydrofolate reductase (DHFR) gene. In addition, a promoter
polymorphism in the gene encoding centrosomal protein
72kD (CEP72), which creates a binding site for a transcriptional repressor, leading to lower expression of CEP72
mRNA, was found to be significantly associated with
vincristine-
induced peripheral neuropathy in children with
ALL; and these results were confirmed in adults with ALL.
Haplotypes, linkage disequilibrium, andhaplotype map
SNVs and other genomic variants are not inherited independently, but rather belong to segments of DNA that are
inherited as units, with each unit referred to as a haplotype.
Genome- wide haplotypes can be constructed by linkage
disequilibrium (LD) analysis, a statistical measure of the
extent to which particular alleles or SNVs at two loci are
associated with each other in the population. LD occurs
when haplotype combinations of alleles or SNVs at different
loci occur more frequently than would be expected from
random association. SNVs and alleles of interest are presumably inherited together if they are physically close to each
other (typically 50 kb apart or closer), producing strong LD.
The international HapMap consortium created a genomewide
map of haplotypes, which revealed a block- like structure of
LD, as well as the existence of areas of low or high recombination rate, leading to the identification of so- called tagging
(tag) SNVs. Tag SNVs can be used to predict with high
probability the alleles at other cosegregating “tagged” SNVs.
It was also found that common SNVs are in LD with other
common variants in the human genome (e.g. structural
variants), and HapMap data are available through the public
database dbSNP (https://www.ncbi.nlm.nih.gov/snp/).
Copy number variants
DNA segments 50 bp or larger and which are present at
variable copy number in comparison with a reference
genome are defined as CNVs. In a recent investigation 97%
of 208 studied pharmacogenes harbored CNVs, and they
accounted for >5% of loss-
of- function (LOF) alleles. CNVs
have been identified to increase or decrease the activity of
major drug metabolizers like CYP isoenzymes, and fully
functional gene multiplication or deletion of CYP2D6,
which encodes the enzyme responsible for the metabolism
of more than 30% of all orally administered drugs (e.g.
opioids, antidepressants, etc.), can result in ultra- rapid drug
metabolism and therapeutic failure, or excessive response
in patients.
One example, which illustrates the potential importance
of CYP2D6 copy numbers on drug effects, is severe intoxica-
tion with codeine (which is often used to treat children
suffering from pain crisis in sickle cell disease, SCD), an
analgesic prodrug that is metabolized by CYP2D6 to the
active metabolite morphine. High levels of morphine can
be caused by ultra- rapid activation due to three copies of
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CYP2D6, exemplified by a woman who had taken codeine
for pain shortly after she had given birth. Whereas the
woman survived the intoxication, her child died from a
lethal dose of morphine via her breast milk. Though very
important, analytical testing for CNVs is non- trivial and
more laborious than for SNVs, and current efforts focus on
the development of clinically useful assays for pharmacogenomic CNV analyses. Catalogues for CNVs are the Database
of Genomic Variants (http://dgv.tcag.ca/dgv/app/home), the
database of genomic structural variation (dbVar, https://
www.ncbi.nlm.nih.gov/dbvar) and the gnomAD browser.
Somatic variations
Non- random genetic abnormalities, including gains and
losses of chromosomes, can be found in the majority of
hematological malignancies. This can create differences
between normal host cells (i.e. germline genotype) and cancer cells (acquired somatic variants), and such differences
can have pharmacologically relevant consequences. For
example, resistance mechanisms against thiopurines, which
are key components in the successful therapy of childhood
ALL, have been identified in pre- existing drug- resistant
clones and in blasts that acquire drug resistance during treatment. This include somatic deletions of genes encoding proteins that regulate the stability of the DNA mismatch repair
(MMR) enzyme MSH2, acquired activating mutations in the
genes encoding the cytosolic nucleotidase NT5C2, and the
purine biosynthesis enzyme phosphoribosyl pyrophosphate
synthetase 1 (PRPS1). Thiopurines have also been identified
to be one driving force for mutational processes and clonal
relapse evolution in ALL blasts, especially when blasts harbor defects in DNA MMR (so called “thio- dMMR genetic
signature”). Collectively, such findings can help to establish
mechanistic models for drug resistance in cancer cells, can
help to predict relapse (and to refine stratification of patients
into different treatment arms), and can be used to develop
strategies to circumvent drug resistance mechanisms in
hematological malignancies.
Epigenetic variations andepidrugs
Besides genome sequence variation, epigenetic regulation of
gene expression is increasingly recognized to contribute to
differences in the pharmacological effects of many medications, referred to as pharmacoepigenomics. Epigenetic
signaling is mediated through DNA methylation, DNA
hydroxymethylation, and post- translational histone modifications. Epigenetic biomarkers for drug responses have been
identified in the therapy of hematological malignancies. One
example is somatic hypomethylation of the promoters of caspase 1 (CASP1) and its activator NLR family, pyrin domain
containing 3 (NLRP3) in ALL cells, leading to overexpression of both genes, and higher caspase1 activity in leukemia
cells. This has been shown to lead to glucocorticoid resistance in ALL cells, due to caspase 1 cleavage of the glucocorticoid receptor.
Small molecules that interfere with the epigenetic control
of gene expression, for example inhibitors of DNA methyltransferases (DNMTi), histone deacetylases (HDACi), histone methyltransferases (HMTi), histone demethylases
(HDMi) or histone acetyltransferases (HATi) are often
referred to as “epidrugs.” Of note is that epidrugs were initially developed to treat hematological malignancies, and the
first FDA approved epidrugs were the DNMTi azacitidin for
the treatment of myelodysplastic syndromes (MDS, later on
also approved for acute and chronic myeloid leukemias,
AML and CML), and the HDACi vorinostat for the treatment of advanced cutaneous T-
cell lymphoma (CTLC).
Other yet FDA approved epidrugs for hematological malignancies include the DNMTi decitabine (MDS, CML and
AML), the HDACis romidepsin (CTCL and peripheral T- cell
lymphoma, PTCL), panobinostat (multiple myeloma), and
belinostat (PTCL), the HDMi enasidenib (AML) and the
HMTi tazemetostat (follicular lymphoma).
Adverse drug reactions andimmunopharmacogenomics
In adults, adverse drug reactions (ADRs) account for about
6.5% of hospitalizations, and about 15% of inpatients experience ADRs. ADRs can be classified into pharmacologically
predictable (type A, “on- target”), and unpredictable (type
B, “off- target”) reactions, and both types can be affected
by genetic factors. Dose dependent hematotoxicity after
treatment with thiopurines in TPMT or nudix hydrolase 5
(NUDT15) deficient patients is a typical type A ADR, and dose
reduction ameliorates the ADR. However, there is usually no
dose dependency in type B reactions, and this often requires
discontinuation of the drug. Many type B ADRs are immune
mediated, and the classical example are hypersensitivity
reactions to the anti- HIV drug abacavir, which are linked to
the human leukocyte allele HLA-
B*57:01. In addition, HLA-
DRB1*07:01, DQA1*02:01, and DQB1*02:02 alleles were
found to be associated with a higher risk for hypersensitivity
reactions to pegasparaginase in children treated for ALL from
European ancestries. For abacavir, the association with HLA-
B*57:01 has been prospectively validated, and upfront HLA
testing is now worldwide recommended before start of therapy. This shows how immunopharmacogenomics (IPGx)
can help to predict “unpredictable” type B ADRs, and to
avoid sometimes life- threatening hypersensitivity reactions.
Moreover, insights from IPGx investigations have shed light
on the pathophysiology of some type B ADRs, in that certain
drugs and/or their metabolites interact with specific HLA
molecules and T- cell receptors; and this causes clonal T- cell
proliferation and cytokine release, which mediates clinical
hypersensitivity.
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Pharmacogenomics 347
+ May identify new associations
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Single-gene approach
Drug-related
• Analyzes the possible
candidate gene
• Requires a large
cohort to test the
association
− Carries the risk of not
nding an association
+ Provides proof of
principle if an
association is found
Figure23.2 Comparison of single- gene, candidate pathway- gene and genome- wide pharmacogenomic approaches to the analysis
of drug- related phenotypes. The main characteristics (•), disadvantage (−) and advantage (+) of each approach is indicated. The arrows
between the three approaches indicate that any approach can lead to another and that a combination of approaches might be considered. SNVs,
single- nucleotide variants; CNVs, copy number variants. Adapted from Cheok MH, Evans WE. (2006) Acute lymphoblastic leukaemia: a model for
the pharmacogenomics of cancer therapy. Nature Reviews. Cancer, 6, 117–129, with permission.
• Analyzes the whole genome
(expression and SNP)
• Requires smaller cohorts to test
associations
− Difcult assessment of biological
meaning (i.e. risk of false positives)
phenotype
Genome-wide approach
Pathway-gene approach
• Analyzes several
functionally related
candidate genes
• Requires a smaller
cohort to test the
association
− Carries the risk of
missing important
genes
+ Provides a more
biologically meaningful
association
Genetic variation among ethnic groups
It is well known that differences in the frequency and nature
of genetic variants among ethnic groups must also be recognized when attempting to extrapolate research from one
population to another. For example, allele frequencies and
types of variants in the TPMT and NUDT5 genes, which
influence the efficacy and toxicity of thiopurine therapy, vary
greatly among different ethnic groups. Whereas pharmacologically relevant variants in TPMT are frequent in Europeans
and Africans, these variants are rare in Asians. Conversely,
actionable NUDT15 variants are frequently found in East
Asians and Hispanics, but they are rare in Europeans and not
observed in Africans. Moreover, genetic predisposition in
hypersensitivity to pegasparaginase, and important medication to treat ALL, was shown to differ among ancestries.
Therefore, pharmacogenomic relations must be validated for
each therapeutic indication within different ethnic groups.
Approaches forestablishing pharmacogenomic
models
Pharmacogenomics is a broad strategy for establishing
models by integrating information from functional genomics, high- throughput molecular analyses, pharmacokinetics,
and pharmacodynamics. These models can be used to
further optimize existing drug therapy or identify novel
therapeutic targets. As described above, there is a bewildering array of human genomic variation, and a central issue in
pharmacogenomics is to elucidate those genomic determinants that are pharmacologically relevant, namely which
genomic variants are associated with certain drug- related
phenotypes. Pharmacogenomic models can be established
using two broad strategies: candidate gene or agnostic
genome- wide strategies. More details including the advantages and disadvantages of these approaches are provided in
Figure23.2.
We herein provide selected examples of how candidate
gene and genome-
wide approaches have been used to optimize therapies in hematological diseases and focus on
improvement of childhood ALL therapy and oral antithrombotic therapies.
Pharmacogenomics to improve
childhood ALL therapy
Childhood ALL is the most common cancer in children.
Insights from genome profiling and sequencing have
improved our understanding of ALL pathogenesis and
have further proven that ALL is a heterogeneous and often
polyclonal disease. There are more and more ALL subtypes
identified, each of which has distinctive somatic genomic
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alterations, which propel tumorigenesis and influence response
to antileukemic medications. For example, in a recent WGS,
WES, whole transcriptome RNA- seq and gene expression
profiling investigation on 2754 children and adolescents
with ALL, significant alterations in 376 putative driver genes
were identified; and 34 molecular ALL subtypes defined.
Although about 90% of children with ALL can be cured
with risk- adapted therapies in industrialized countries, ALL
remains a leading cause of death from disease in children.
Stratification in treatment protocols can be based for
example on the patient’s age (infants versus older), leukemia cell immunophenotype (B- lineage versus T- lineage),
genetics, as well as invitro (i.e. pharmacotyping) and invivo
response (i.e. minimal residual disease, MRD) assessment to
therapies. Currently >30 molecular ALL subtypes have
been identified; which include for example “good- prognosis”
ETV6- RUNX1, hyperdiploid and NUTM1- R (- R; rearranged)
ALL, “intermediate- prognosis” TCF3- PBX1, DUX4- R, PAX5alt
(alt; alterations like fusions, mutation or amplifications), and
ZNF384- R ALL, as well as “poor- prognosis” BCR- ABL1- like,
BCR- ABL1, KMT2A- R, TCF3- HLF, MEF2D- R ALL.
Major causes of death in childhood ALL are treatment
failure (i.e. relapse or less frequent, progressive disease during
therapy) and ADRs, like bone marrow toxicity- associated
lethal infections. The significant reduction in treatment failures during the last decades, which resulted in significant
improvements in outcomes, was mainly achieved by shifting
a higher proportion of patients into more intensive treatment
arms (i.e. “high- risk” ALL therapies) based on “high- risk” profiles, such as a high minimal residual disease (MRD) load, age
(i.e. infant ALL) or genetics (e.g. BCR- ABL ALL). However,
a higher treatment burden is associated with a higher risk
for significant short- and long- term side effects, like severe
infections or osteonecrosis. Therefore, there is an urgent
need to identify those patients who are at high risk for lethal
ADRs or for death due to treatment failure, in order to tailor
their supportive and/or antileukemia therapy accordingly,
or to develop novel therapeutic strategies and design novel
innovative treatment protocols.
We herein provide selected clinically relevant examples to
demonstrate the potential of pharmacogenomics in this
context. We describe how testing for G6PD deficiency can
help to prevent the occurrence of potentially lethal hemolysis
after administration of rasburicase (which is the standard
medication to treat hyperuricemia), and how results from
candidate gene (variants in TPMT) and genome-
wide investigations (which identified functionally relevant variants in
NUDT15) have provided important insights that can be
used to develop strategies to avoid the potentially lethal
ADR leukopenia in “at- risk” patients treated with thiopurines.
Pertinent information on other germline genetic variants,
which have been reported to be associated with ADRs of ALL
medicines, including the non- lethal ADRs glucocorticoid
induced osteonecrosis and vincristine-
induced neuropathy,
are summarized in Table 23.1. We furthermore provide
examples on how genome- wide interrogation investigations
have helped to identify thiopurine resistance mechanisms
(somatic variants in NT5C2 and PRPS1) in ALL cells from
relapse, and how this information can be used to develop
strategies to overcome these drug resistance mechanisms.
In addition, we describe how an integrated drug response
profiling approach has been successfully used to identify
novel therapies for patients with TCF3- HLF ALL, a rare
lethal subtype when treated with current treatment protocols; and we have summarized in Table23.2 the results
of pharmacogenomic investigations, which have identified
potential actionable somatic genomic variants in patients
with other “high- risk” ALL subtypes; that is, histone- lysine
N- methyltransferase 2A leukemia (KMT2A)- rearranged
infant ALL, BCR- ABL ALL, and “BCR- ABL1- like” ALL
(which is a subgroup of ALL that has a similar gene expression signature and outcome as BCR- ABL1 ALL, but lacks the
BCR- ABL1 aberration).
Rasburicase and G6PD deficiency
Tumor lysis syndrome (TLS) is the most common disease
related emergency in hematological cancers. TLS occurs
when tumor cells release their contents into the bloodstream
(either spontaneously or due to therapy), and this causes
electrolyte and metabolic disturbances (i.e. hyperuricemia,
hyperkalemia, etc.), which, untreated, will result in renal
insufficiency, cardiac arrhythmias, and ultimately death due
to multiorgan failure. Hyperuricemia, which contributes to
TLS, can be prevented/treated via rasburicase, an enzyme
which catalyzes the cleavage of uric acid to hydrogen peroxide, and which is then further metabolized via glutathione
peroxidase (GSHPX). In patients with G6PD deficiency,
however, the activity of GSHPX is markedly reduced in red
blood cells (RBCs), and treatment with rasburicase results in
oxidative damage to RBCs (i.e. acute hemolytic anemia,
AHA). Rasburicase administration is an essential element of
supportive therapy in children with ALL at diagnosis and
during initial induction therapy.
However, fatalities have been reported after rasburicase
administration in ALL patients with G6PD deficiency. G6PD
deficiency is a very common disorder, and about 5% of the
world population (highest incidence in the subtropical girdle
with high malaria prevalence) is affected. As of 2020, >200
functionally relevant variants had been identified in the
G6PD pharmacogene, most of which are missense mutations
that alter G6PD stability. Complete loss of G6PD is lethal;
and only a few rare, complex variants that cause significant
reduction in enzyme activity result in severe transfusion
dependent chronic non-
spherocytic hemolytic anemia. As
rasburicase administration can cause lethal ADRs, the FDA
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Table23.1 Selected examples of germline genetic variants (for TPMT and NUDT15 see text) associated with ADRs of ALL medications,
identified via GWAS
Gene (variant SNP ID) and function(s)
of the encoded protein Drug(s) Possible mechanism(s) of action ADR
SLCO1B1 (rs11045879), solute carrier
organic anion transporter family
member 1B1, drug transporter
near the GRIN3A locus (rs10989692),
glutamate ionotropic receptor NMDA
type subunit 3A, glutamate regulated
ion channels
BMP7 (rs75161997), bone morphogenic
protein 7, member of the transforming
growth factorplays a role in bone, kidney and brown
adipose tissue development and bone
homeostasis
CEP72 (rs924607), centrosomal protein
72kD, involved in the recruitment of
key centrosomal proteins to the
centrosome and microtubule formation
HAS3, (rs2232228), hyaluron synthase 3,
enzyme that produces lowweight hyaluron
CPA2 (rs199695765), carboxypeptidase
A2, secreted pancreatic enzyme
beta family of proteins,
molecular-
Methotrexate (MTX) MTX transporter, altered MTX clearance Gastrointestinal
toxicity
Drugs that contribute to
osteonecrosis
(dexamethasone,
asparaginase, MTX)
Drugs that contribute to
osteonecrosis
(dexamethasone,
asparaginase, MTX)
Vincristine (VCR) rs924607 T promotor variant creates a
Anthracyclines Hyaluron is enriched in tissues
Asparaginase rs199695765, non- sense variant;
Glutamate is involved in osteoblast
activation and impairs endothelial
barrier function
Variants in BMP7may alter bone
metabolism and formation, BMP7 is
also toxic to smooth muscles; may
induce vascular injury in bone
vasculature
binding site for a transcription
repressor, leading to lower CEP72
mRNA expression
undergoing remodeling after injury–
impaired remodeling after cardiac
injury
loss- of- function variants in CPA1 were
found to be associated with a risk for
chronic pancreatitis
Osteonecrosis in
children and
adults
Osteonecrosis in
children <10
years
VCR neuropathy
Cardiotoxicity
pancreatitis
Table23.2 ALL subtypes andselected examples ofdruggable targets that have been identified via pharmacogenomics investigations
ALL Subtype Identified drug targets Drugs
BCR- ABL1 or Philadelphia (Ph)- ALL
(more frequent in adolescents
and adults)
ABL1- like” ALL, exhibit a
“BCR-
gene expression profile similar
to that of Ph- ALL but lacks the
BCR- ABL1 fusion protein
Abbreviations: ABL1, ABL proto- oncogene 1, non- receptor tyrosine kinase, CSF1R, colony stimulating factor 1 receptor; EPOR, erythropoietin
receptor; IL7R, interleukin 7 receptor; JAK2, janus kinase 2; NTRK3; neurotrophic receptor tyrosine kinase 3; PDGFRB, platelet derived growth
factor receptor beta; Ph, Philadelphia; SH2B3, SH2B adaptor protein 3; TKI, tyrosine kinase inhibitor.
and the European Medicines Agency (EMA) have contraindicated the use of this drug in patients with G6PD deficiency.
Exhaustive information on pharmacogenes are provided
at the “Pharmacogenomics Knowledge Base” (PharmGKB),
the chimeric fusion protein BCR- ABL1has tyrosine kinase
activity, and can be selectively blocked via tyrosine kinase
inhibitors (TKIs)
Genetic subgroups with therapeutic implications have been
identified:
a. ABL- class rearrangements targeting ABL1, ABL2, CSF1R,
and PDGFRB, which are sensitive to imatinib and dasatinib
b. JAK2 fusions, EPOR rearrangements, and IL7R/SH2B3
alterations are sensitive to JAK inhibitors
c. NTRK3- fusion
which is an interactive tool for researchers investigating
how genetic variation affects drug response (http://www.
pharmgkb.org). PharmGKB displays for example genotype,
molecular, and clinical knowledge integrated into pathway
TKIs (ABL1inhibitors): imatinib, dasatinib
a. TKIs: imatinib, dasatinib
b. JAK inhibitor: ruxolitinib
c. NTRK inhibitor: larotrectinib
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350 Molecular Hematology
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representations and “Very Important Pharmacogene (VIP)”
summaries. G6PD was designated as a “Tier 1 (= genes with
substantial evidence to support their importance in pharmacogenomics)– VIP,” and more details, including information
on G6PD genetic and activity tests, as well as WHO classification (classes I–V) of variants, are available at the PharmGKB
website (https://www.pharmgkb.org/vip/PA166169539). In
addition, more information on the clinical application of
pharmacogenetic testing for G6PD variants is provided at
the “Clinical Pharmacogenetics Implementation Consortium
(CPIC)” website (https://cpicpgx.org/guidelines/cpic- guideline-
for- g6pd/).
Optimization ofthiopurine therapy
The thiopurine antimetabolites mercaptopurine (MP) and
thioguanine (TG) are essential components in childhood
ALL treatment protocols. Thiopurines have narrow therapeutic indices, which explain the frequently observed toxicities, including severe myelosuppression (mainly leukopenia)
with the risk of life- threatening infections. To exert cytotoxicity, the prodrugs MP and TG have to undergo anabolism
to form active cytotoxic thioguanine nucleotides (TGNs).
These multistep anabolic reactions, which include conversion into thioguanosine triphosphate (TGTP) and reduction
to deoxythioguanosine triphosphate (TdGTP), are in competition with direct drug inactivation (S- methylation) via
TPMT and (hydrolysis of the triphosphates TGTP and TdGTP
to monophosphates TGMP and TdGMP) via NUDT15.
TPMT and NUDT15 activities determine how much thiopurine is inactivated and how much remains for incorporation
into DNA.
Variants in TPMT
Variations in TPMT activity are regulated primarily by
variants in the TPMT gene. Three non- synonymous SNPs
account for more than 95% of the relevant TPMT variants,
namely TPMT*2 (dbSNP identification number rs1800462,
nucleotide change c.238G>C, hereafter referred to as amino
acid change p.Ala80Pro), TPMT*3C (p.Tyr240Cys), and
TPMT*3A (p.Ala154Thr
+ p.Tyr240Cys). One in 300 persons
carries two variant TPMT alleles and does not express functional TPMT activity (due to lesser stability of the variant
protein); about 5–10% are heterozygous and have intermediate levels of enzyme activity, whereas 95% of individuals are
homozygous for the wild- type allele (TPMT*1/TPMT*1) and
have normal TPMT activity (Figure23.3). Population studies
have shown significant differences in TPMT pharmacogenetics among ethnic groups. For example, TPMT*3A is the
most common variant allele in Europeans, whereas TMPT*3C
accounts for more than 50% of variants in Africans. TMPT*3C
is also the major variant allele in East Asian populations,
which generally lack the TPMT*3A allele.
Patients who carry two non-
functional TPMT alleles
experience severe hematotoxicity if treated with conventional doses of thiopurines. Depending on the dose (e.g.
60 mg/m2 daily) and the comedications, many patients with
one nonfunctional TPMT allele can tolerate MP therapy at
full doses. However, these patients might be at higher risk
of dose limiting hematotoxicity with slightly higher mercaptopurine doses (e.g. 75 mg/m2 daily), but may experience
better leukemia control than do those who have two wild- type
TPMT alleles. Moreover, patients with one non- functional
TPMT allele may be at increased risk of irradiation- induced
brain tumors as a result of thiopurine therapy, and of venoocclusive disease of the liver following thioguanine therapy.
Most importantly, results from the St Jude Children’s
Research Hospital (SJCRH) Total XIIIB childhood ALL
treatment trial provide proof of principle that prospective
MP dose adjustment based on TPMT genotypes can decrease
toxicity without a compromise in treatment efficacy. Based
on an FDA advisory committee recommendation, a change
in labeling for MP, with TPMT testing and dosage recommendations provided for TPMT- deficient patients, was
implemented in 2004. More details on TPMT- guided preemptive thiopurine dose adjustment, which is considered a prototype of pharmacogenomic precision medicine approaches,
are available at the CPIC website (https://cpicpgx.org/guidelines/guideline- for- thiopurines- and- tpmt/). Information on
the TPMT nomenclature can be found at (https://liu.se/en/
research/tpmt- nomenclature- committee), which currently
catalogs 45 variant TPMT star (*) alleles, TPMT*2 to *46
(TPMT*1 designates the wt). Additional information is
provided at PharmGKB (https://www.pharmgkb.org/vip/
PA166169909). Patients who share the same TPMT genotypes still exhibit considerable variations in their response to
thiopurines, and other genetic variations that contribute to
the toxicity and response to thiopurines have been identified
via GWAS studies. The major finding was the identification
of four loss- of- function germline NUDT15 coding variants,
which play an important role in thiopurine intolerance,
especially in East Asian populations.
Variants in NUDT15
It is well known that the frequency of TPMT deficiency
causing variants is lower in Asians compared to individuals
of European descent (~3% versus ~10%). The frequency of
thiopurine- induced myelotoxicity, however, is considerably
higher in Asians. In order to identify other genetic variants
that contribute to thiopurine- induced myelotoxicity in
Asians, a case–control GWAS study was performed in
Korean patients who were treated with thiopurines, used as
an immunosuppressant, for chronic inflammatory bowel
disease. This research identified a SNV missense variant in
exon 3 of the NUDT15 gene (NM_018283.4:c.415C>T,
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Pharmacogenomics 351
100
(A)
(D)
(C)
Time (h)
https://t.me/med1917
Figure23.3 Thiopurine methyltransferase
(TPMT). (A) Mercaptopurine (MP) can be activated
to thioguanine nucleotides (TGN) by hypoxanthine
phosphoribosyltransferase (HPRT) or inactivated to
methylmercaptopurine (MeMP) via TPMT. The
genetic polymorphism in TPMT results in a
trimodal population frequency distribution in
TPMT activity, with deficient activity caused by
inheritance of two variant (var) alleles, intermediate
activity caused by heterozygosity, and high activity
associated with homozygote wildgenotypes. (B) TPMT activity is directly proportional
to the amount of TPMT protein and (C) is inversely
related to intracellular concentrations of active
TGN metabolites in hematopoietic cells following
MP therapy. (D) The biochemical basis for low
protein conferred by the most common var.
polymorphism (719A>G) is illustrated by the longer
half- life for invitro expressed wt TPMT when
compared with the rapidly degraded var. protein.
From Jones TS, Yang W, Evans WE, Relling MV.
(2007) Using HapMap tools in pharmacogenomic
discovery: the thiopurine methyltransferase
polymorphism. Clinical Pharmacology and
Therapeutics, 81, 729–734, with permission.
type (wt)
80
60
40
Percent of population
20
(B)
2000
1000
TGN concentration
100
10
Percent remaining
0
1
MP
var/var
var/var
0
(HPRT)
(TPMT)
Toxicity Risk of relapse
= 0.25 h
t
1/2
719 var
TGN
(active)
MeMP
(inactive)
wt/var
51015
TPMT activity
wt/var wt/wt
51015
wt/wt
20 25 30
Protein
level
Inherited differences
in drug levels
t
1/2
719 wt
= 18 h
Inherited
differences in
metabolism
20 25
rs116855232, hereafter referred to as p.Arg139Cys) that
encodes nudix hydrolase 15, which was strongly associated
with thiopurine- induced leukopenia.
Researchers from the SJCRH and from the Children’s
Oncology Group (COG) confirmed the importance of this
variant to causing MP intolerance in a GWAS study on more
than 1000 children treated for ALL. In addition, it was confirmed that NUDT15 deficiency (low- or intermediate- activity
diplotypes) was most common in East Asians (22.6%) and
Hispanics (for example, 21.2% in Peruvians), rare in
Europeans, and not observed in Africans. Subsequent targeted
sequencing of NUDT15 identified additional functionally
relevant loss- of- function variants that were associated with
thiopurine intolerance. The Pharmacogene Variation (Phar mVar,
https://www.pharmvar.org/) Consortium, which is a repository for pharmacogene variation that focuses on haplotype
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structure and allelic variation by designating star (*) alleles,
currently lists 19 variant NUDT15 star (*) alleles, NUDT15*2
to *20. The most important NUDT15 variant is the non-
function NUDT15*3 allele (p.Arg139Cys); others are the
non- function NUDT15*2 (p.Gly17_Val18dup, p.Arg139Cys)
and NUDT15*9, (p.Gly17_Val18del) as well as the likely non-
function NUDT15*14 (p.Cys28Glyfs*28) alleles. Of note is
that ALL cells carrying intermediate- activity NUDT15 diplotypes were shown to be significantly more sensitive to thiopurines compared to NUDT15 wild- type diplotypes. Therefore,
thiopurine dose reduction in NUDT15- deficient patients, in
order to avoid the ADR leukopenia, will most likely not result
in a compromise of therapeutic effect, because NUDT15deficient ALL cells are more sensitive to thiopurines.
To further personalize thiopurine therapy in different ethnic
populations, dosing recommendations that incorporate
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both TPMT and NUDT15 variants were established and are
available at the CPIC guideline website (https://cpicpgx.org/
guidelines/guideline- for- thiopurines- and- tpmt/).
Pertinent information on the Tier 1 VIP NUDT15 is provided at the PharmGKB website (https://www.pharmgkb.
org/vip/PA166178335). Whereas preemptive testing for
TPMT and NUDT15 before initiation of thiopurine therapy
can help to avoid some of the drug’s toxicities, wt/wt results
in these tests are no guarantee that no toxicity can occur, and
other factors still have to be identified and monitoring, e.g. of
CBCs remains necessary.
Relapsed ALL and drug resistance, thiopurine
resistance and variants in NT5C2 and PRPS1
About 10–15% of children with ALL experience disease
recurrence, and unfortunately, many of them will die. The
identification of mechanisms of drug failure in resistant ALL
clones is underway, and insights from such studies can help to
develop pre- emptive strategies to prevent disease recurrence
and develop more- effective therapies. For example, genomic
profiling and sequencing investigations of ALL samples
obtained from diagnosis, remission, and relapse have helped
to identify different pathways (e.g. transcription- , cell cycle-
and epigenetic regulation, tumor suppression, mismatch
repair, as well as nucleoside and folate metabolism), in which
somatic genetic defects (e.g. in TP53, NR3C1/2, CREBBP,
WHSC1, NT5C2, PRPS1/2, PMS2, MSH2/6, and FPGS) are
enriched or exclusively present at relapses which occurred
>9 months after diagnosis. Interestingly, these relapse specific
variants occur in genes, which encode proteins that play a role
in the development of resistance to glucocorticoids (NR3C1/2,
CREBBP and WHSC1), thiopurines (NT5C2, MSH2/6, PMS2
and PRPS1/2) and MTX (FPGS). On the other hand, blast
cells from very early relapses (<9 months from diagnosis)
harbored only a few of these variants, suggesting that these
relapses rather arise from the outgrowth of a priori multidrug resistant sub- clones, which cannot be eliminated via
conventional therapy, and this relapse pattern was mainly
observed in poor- prognosis subtypes like KMT2A- R and
BCR- ABL1 ALLs. This argues for the implementation of
novel treatment strategies (e.g. immunotherapies) in these
intrinsically resistant leukemias, and recently the use of the
bispecific T- cell engager molecule blinatumomab, which
targets CD19, resulted in exceptional improved two- year
disease- free survival (81.6% with blinatumomab + standard
therapy vs. 49.4% with standard therapy only) in infants with
the poor prognostic KMT2A- R ALL.
Of note, a comprehensive recent study which included
1951 samples from pediatric and adult ALL patients, provided evidence that first- line thiopurine therapy can induce
a TP53 hotspot mutation (i.e. TP53 R248Q) through a specific mutational signature (i.e. thio- dMMR) in mismatch
repair (MMR)-
deficient ALL (i.e. ALL with variants in
MMR genes like MSH2, MSH6, PMS2 or MLH1). ALLs with
acquired TP53 R248Q variants are associated with ontreatment relapse, poor treatment response and emergence
of multi- drug resistant clones. If further validated, caution
must be noted on the further use of thiopurines in patients
whose leukemia blasts have acquired variants that cause
MMR- deficiency.
We herein discuss in more detail mutations in the nucleotide metabolism pathway and provide two examples of
functionally relevant variants in key genes of nucleotide
metabolism (i.e. NT5C2 and PSPR1) that have been identified to play an important role in resistance to thiopurines
and development of relapse in a subset of children with ALL.
Variants in NT5C2
Two groups of researchers found, that up to 10% of B- cell
precursor (BCP)- ALL, and up to 20% of T- ALL relapse
samples harbor somatic gain- of- function variants in the
gene NT5C2. NT5C2 encodes a 5′ nucleotidase, which can
selectively inactivate thiopurines, thereby protecting ALL
cells against thiopurine induced apoptosis. NT5C2 enzyme
activity was measured to be increased up to 48- fold in the
variant proteins. In vitro experiments confirmed that variants with high NT5C2 activity conferred resistance against
thiopurines, but not against other antileukemic agents.
Ultra- deep sequencing revealed that in 2 out of 7 patients,
the minor mutant clone already existed at ALL diagnosis. It
is assumed that NT5C2gain- of- function harboring clones
exist at diagnosis or evolve early during therapy, and can
selectively outgrowth in treatment phases, when thiopurines
play a major role, like in oral maintenance therapy, which is
given for >1 year as final element of ALL therapy. Indeed,
there was a significant association between activating NT5C2
variants and ALL relapse occurring within 36 months from
diagnosis; and this early outgrowth of resistant clones during
or shortly after completion of maintenance therapy supports
this assumption. Strategies to overcome the drug resistance
somatic phenotype gain-
of- function in NT5C2 can focus
either on the inhibition of NT5C2 via small molecules, or
on the use of drugs that are not inactivated via NT5C2.
Recently, CRCD2, a small- molecule first- in- class nucleotidase (NT5C2) inhibitor was developed and was effective in
reversing MP resistance in ALLs, which harbored relapseassociated NT5C2 variants. Of note, CRCD2 also increased
the sensitivity of NT5C2 wild- type ALL to MP, and subsequently NT5C2 Ser502 phosphorylation was identified as a
non- genetic mechanism interfering with efficacy of MP in
ALL. The study provides a basis for the development of clinically active NT5C2inhibitors like CRCD2; and if clinically
applicable, this could be the first resistance- directed targeted
therapy in ALL precision medicine.
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