Use of Pharmacogenetics in Clinical Medicine – Tristan Sissung

Tristan Sissung:
Okay, well, thanks for having me today. I think I saw in the — I was billed as an
M.D. Ph.D., so while I appreciate the honorary degree, I’m only a Ph.D. and an M.S, and I’m
basically a bench scientist who does a lot of translational research, so that’s my perspective. I’m going to talk a lot about molecular pathways
and that sort of thing today. So, anyway, let me launch in. I’m going to talk about pharmacogenetics today,
and I think probably one of the best compelling stories for pharmacogenetics is this paper
right here. It’s a case report about a 2-year-old boy
who went — underwent a tonsillectomy. After his surgery, everything went fine. He was in outpatient, he went home, took codeine
to manage the pain, and died a couple of days later of respiratory depression. So didn’t really understand why this had happened. According to the paper, because he had taken
the correct amount of pills, there was nothing — no overdose due to the pills. But somebody got smart and genotyped him,
and found out that he has, instead of two copies of a gene that activates codeine into
morphine, called CYP2D6, right here, he has three copies of this gene. So everybody inherits one chromosome from
Mom and Dad. In general, you have two genes. This kid had a duplication on one of his chromosomes
that gave him three copies, so he was considered an ultra-rapid metabolizer of codeine into
morphine, and while there is probably about 5 percent of the U.S. population has this
ultra-rapid metabolizer genotype, this probably indicates that this kid had some other confounding
issues. It wasn’t just that. Nonetheless, had he been genotyped, codeine
would have been avoided, and he probably would still be alive today. On the other side of the coin, people go to
the dentist, they get dental work done, they are given codeine to manage the pain when
they get home. When they get home, sometimes they take the
codeine, and it doesn’t really have much of an effect. This is because there’s a lot of people in
the population who are deficient in CYP2D6 and cannot turn codeine into morphine. Codeine has very little analgesic effect. It’s really the morphine conversion that is
needed for that. So the same gene can cause inefficacy, and
it can cause severe toxicities. So I work at the NCI, so a lot of my slides
have cancer drugs on them, so this is no different. There is a lot of variation in most drug therapies,
especially in cancer, but, you know, you can see 3- to 50-fold variation in certain drug
therapies, and this variability is partially, oftentimes, attributed to genetics, but not
always, which leads to the next slide. I’m sure people in this room can probably
think of more sources of variability, but I’m just going to go through them each here. So drug specific, dose schedule, the dosage
form, how the drug is formulated, et cetera, can affect the variability. Body size, body composition, demographic variables
such as age, race, sex, can affect drug therapies. Physiologic, especially disease states, hepatic
and renal function, can affect how drugs are handled in the body. Environmental interactions, like drug-drug
interactions, drug-food interactions, these sorts of things, can affect. And genetics is just one sort of these many
variables that will affect drug therapy. So we see this more as a useful tool and not
the “end all, be all” of determining variability in drug therapies. Now sometimes the genetics is extremely important,
and sometimes it’s not important, barely at all. So today I’m going to be primarily talking
about cases where the genetics really contributes a lot to the variability, and it’s actually
useful for making clinical decisions. There are several types of pharmacogenetic
endpoints that we use at the NCI. We’re — like I said, I’m more of a wet bench
kind of guy so I’ve been, you know, handling a lot of the mining, a lot of the samples
in our clinical pharmacology program, primarily from cancer patients, and we will notice from
time to time that there is an association between a gene SNP and some sort of clinical
outcome that we can then go and figure out why this is happening. So here we had a group of patients with prostate
cancer treated with docetaxel. We found that a polymorphism in a gene, CYP1B1,
was related to the outcome. So men carrying the wild-type *1 SNP had a
double overall survival compared to people carrying the *3 SNP. This gene does not metabolize docetaxel, so
we had to do a little investigative work to figure out what was going on. We found out that estradiol is actually metabolized
by CYP1B1. CYP1B1 is also upregulated in almost every
single prostate tumor. Those carrying the *3 allele turn estradiol
into a very reactive metabolite that binds to docetaxel and adducts it. And this form of docetaxel is not very potent
at all. It also interferes with microtubule polymerization,
because this reactive form of estradiol will bind to practically everything in the cell,
and it really likes the sulfinyl groups on tubulin. So we would have never found this interaction
without the use of pharmacogenetics, so we use it in the discovery capacity. We’re also doing a lot of clinical trials
at the NIH, as I’m sure you all know, and so we’re often looking at variation in phenotypes. So there’s a molecular pathway that feeds
into a variation of phenotypes. So here we were studying an investigative
drug that was shown to cause QT prolongation. We knew the drug was handled by a transporter
that existed in the heart, and basically, the transporter functioned so that when the
drug got into the heart, it was pumped back out. Patients who were not able to pump the drug
out as effectively, because of a genetic polymorphism, are shown here, they had QT prolongation,
whereas patients who were more effectively able to pump the drug out had barely any,
if at all, QT prolongation. So here we’re looking at a variation of phenotype. We had the molecular pathway sort of characterized. Now both of these feed into clinical trial
inclusion and exclusion criteria. You can take people who are responders, non-responders,
or you’re going to get significant toxicities. You can take them out of your population and
treat them with other sorts of drugs, and subset your population for people where you
think the drug is going to be more effective. And all of this, of course, leads into actual
translation of these findings into clinical practice. So today, the objectives are: to review the
molecular and physiological basis for drug-drug — or gene-drug interactions; to appreciate
the impact on drug therapy; to discuss the future of pharmacogenetics and drug development
and treatment. So basically, I’m going to sort of give you
a bird’s eye view of pharmacogenes and what they do. I’m going to talk about how the molecular
pathway will alter phenotype, which will then alter drug therapy. And then, at the very end of the talk, the
NIH has instituted a pharmacogenetics program where a patient comes into the hospital, they
are genotyped, and that genotype follows them around the hospital in our computer system. So if they’re given — if the doc wants to
give them a drug, they will have to put it into the system. The system will flag if there is a genetic
issue with administering that particular drug. So I’m going to talk about the drugs that
we’ve flagged as important at the NIH at the end. So just launching with the types of pharmacogenes. So probably the — when people think of pharmacogenetics,
they tend to think of these sorts of interactions where you have Phase I metabolism, which tends
to be just redox reactions that oxidize drugs. Sorry, the arrow got scooted over there. So here you just have the drug that’s oxygenated
and becomes more polar. Now this can have two effects. One, it can activate drugs, like with codeine,
but, in general, it deactivates drugs and makes them more soluble, readily excretable. Phase II metabolism is also the chemical modification
of a drug. Here, you take a polar R group and add it
onto the drug. So you have drug, drug R; the R is polar,
it’s more soluble, and easier to detoxify the drug. Before I go into the CYPs that I’m going to
talk about, it’s helpful to think about what are the major CYPs that metabolize most of
the pharmaceutical armamentarium. In general, it’s CYP3A4. 3A family probably metabolizes 40 to 60 percent
of the drugs that are available right now. This is an old slide, but little has changed
in the last 13, 14 years. This gene really does not have very many genetic
polymorphisms that are very predictive, so I’m not going to really talk about CYP3As
today; however, the next two most frequent metabolizers of drugs, CYP2C9 and CYP2D6,
do have some very important genetic variants that will alter their activity. So I’m going to talk about those today. Phase II metabolizing enzymes tend to be the
UGTs. You have — you have these UGTs in the liver,
the glucuronidate drugs, and make them more readily excretable in the bile and urine. Then your sulfotransferases, and then a host
of others that are more or less important in the major metabolism of multiple drugs. I’m going to talk about TPMT today. Even though this is a very small sliver, this
particular gene is quite important in pharmacology. So I’m going to give you the first example
here, CYP2D6 and tamoxifen. It’s already mentioned codeine will activate
— or, I’m sorry, CYP2D6 will activate codeine. CYP2D6 actually also activates tamoxifen. When tamoxifen was developed, people were
thinking, “I believe that the NDM, or the 4-hydroxy, were the major metabolites that
were actually active.” Relatively recently, some studies at Georgetown
proved that it was endoxifen that’s really the active compound of tamoxifen. Endoxifen is formed through N-desmethyl tamoxifen,
which I’m going to call NDM, and it forms this compound which is 3- to 100-fold more
active than tamoxifen or NDM alone. Also, when tamoxifen was being used, people
noticed that SSRIs actually inhibited the hot flashes that people would experience when
they were, you know, undergoing tamoxifen therapy, and I don’t think people really understood
why until recently, when they found that really, what they were doing, was inhibiting the enzyme
that formed the active metabolite. So you had less active metabolite and less
hot flashes due to that. So it’s kind of useful to think about, “How
does the population break down in terms of CYP2D6 genetics?” We would expect, just to back up, that people
who were deficient in this would have more N-desmethyl tamoxifen to endoxifen ratio. People who were very were rapid would have
more endoxifen to NDM. The poor metabolizers who do not form as much
of the active metabolize comprise probably about 10 percent of the population, roughly,
and they’re at the top right here. On the bottom right, you’ll see about maybe
another 5 to 10 percent who are ultra-rapid metabolizers; they form a lot of endoxifen
and the drug is actually, probably, more effective in these people, especially. When the drug was developed, though, these
two extreme ends of the genetic spectrum here were not the general population. The drug was really developed for people sort
of in the middle. And the people at the ends, unfortunately,
don’t benefit as well from the drug, or they have more hot flashes, more toxicity to deal
with. So, you know, this is how the population breaks
down. Go ahead and talk about the plasma concentrations
of the drugs now. So if you look at the endoxifen to NDM ratio,
and you take the population, look at their plasma concentrations, you get — they put
it on a Normit plot, which just is sort of a statistical method to figure out what groups
of people comprise this population. You’ll find four bell-shaped curves that are
very distinct of endoxifen-to-NDM ratio. These people on the left end here have little
endoxifen to NDM, these have high endoxifen to NDM, so we would expect then, that if CYP2D6
was really an important genetic predictor of endoxifen concentration, that you would
see this curve enriched for poor metabolizers and this one enriched for rapid metabolizers. And that’s exactly what you see. Draw your attention to the right-hand side
of the table here. The poor metabolizers over here are the major
constituents of Group 1, which has low endoxifen. The ultra-rapid, or extensive metabolizers,
are those that comprise Group 4, which have high endoxifen. Here’s another way to look at the data, and
I want to point something out here. The poor metabolizers tend to cluster low
on the endoxifen-to-NDM ratio, whereas the extensive metabolizers are high on it. However, you’ll notice how much the data really
spread here. There’s several extensive metabolizers that
look like poor metabolizers. This is because this gene is not a perfect
predictor of anything. However, it is still a very useful predictor. So if you look at patients with extensive
metabolizing versus poor metabolizing, how long it takes them to have recurrent breast
cancer, you’ll see this, where patients with extensive metabolism are benefitting much
more from tamoxifen than patients who are poor metabolizers. So, basically, we think that the poor metabolism
group here really is not benefitting as much from tamoxifen. They should probably be given another drug,
such as an aromatase inhibitor or something else, whereas people who are extensive metabolizers
probably benefit more from tamoxifen than they do from other drugs. So when you think about, you know, this issue
in terms of, “How does tamoxifen stack up with one of these aromatase inhibitors,” for
example. Tamoxifen is causing a little bit more recurrence,
however, this part of the Kaplan-Meier analysis here is composed of a lot of poor metabolizers
who are sort of dragging down the efficacy of tamoxifen. And right now, studies are really trying to
compare these two curves to see if taking poor metabolizers out of here and moving them
to here will actually improve this curve. And some early data from one of these trials
is indicating that poor metabolizers that are switched to anastrozole after two years
of tamoxifen experience no increase in breast cancer recurrence. So the poor metabolizers who are switched
are actually doing better than they would have done on tamoxifen, is really the idea. So I talked about a Phase I metabolizing enzyme,
CYP2D6; now I’m going to switch gears and talk about Phase II metabolizing enzymes. We’ll talk about thiopurine methyltransferase
and 6-mercaptopurine and its analogs. So the thiopurine methyltransferase just simply
methylates drugs and deactivates them through methylation. 6-mercaptopurine and its analogs are used
to treat ALL, inflammatory bowel disease, and autoimmune disorders. They’re fairly heavily used in the transplant
community as well, especially azathioprine and the transplant community, I’ll mention
that in a minute. These drugs basically just incorporate cytotoxic
thioguanine nucleotides into the DNA, which causes the cell to die. However, they also do a second thing. They inhibit de novo purine synthesis, so
the cell is not as able to synthesize DNA and divide it as it otherwise would be. So they’re very good drugs. 6-mercaptopurine was heavily used in childhood
ALL, and some of the initial pharmacogenetics studies actually were very concerned with
this drug because this drug can cause severe hemotoxicity, in childhood patients can cause
death, so St. Jude was very interested in it, and it was heavily developed at St. Jude. So the TPMT, which basically functions to
take azathioprine, which is converted into 6-MP, right, and then it goes into one of
two fates, inhibiting de novo purine synthesis or incorporating it into DNA and leading to
cytotoxicity. But before it can do that, it will see a lot
of TPMT in the blood and other tissues, where it just gets methylated and inactivated. So when the drug was developed, the dosing
was based off of people who were very able to metabolize mercaptopurine through TPMT
and inactivate it. So the metabolism of these mercaptopurine
drugs is decreased with polymorphic TPMT variation by up to 200-fold. So 200-fold is a very large number in any
therapy, and it has a lot of cytotoxicity in patients who are not able to methylate
it and get rid of it, and these are the kids that are really experiencing very severe toxicity
from 6-MP, so I’ll talk about the SNPs in a second. The rapid metabolizers are resistant to the
drug, the slow metabolizers are at risk. So the rapid metabolizers are these wild-type
individuals who have functional TPMT. They’re about 80 to 98 percent of the population,
depending on which population you’re looking at. The intermediate metabolizers are — they
carry one wild-type allele, and one allele that’s not functional. And they’re about 65 — they need about 65
percent of the dose, but they’re — they have some toxicity but it’s not nearly as severe
as this group down here of slow metabolizers, who carry two copies of these two TPMT-deficiency
alleles. And they carry about 10 to 15 percent of the
original dose. And if you’re talking about kids, these people
are also at risk for secondary malignancy; so you give them these drugs in childhood,
they can develop cancers later on because they were just administered too much for what
they needed. I’m — just got some results back from the
largest pediatric cohort treated with azathioprine, and the results are very positive. The exact same thing is going on with azathioprine
as it is with 6-MP, and the results should be published within the next year. So it’s not only 6-MP that’s affected, it’s
these other drugs as well, and it’s not just pediatric patients, it’s also adult patients. Oh, by the way, I wanted to mention one other
thing: The genetic variation in TPMT explains 95 percent of these hemotoxicity issues with
6-MP. So all of this information is high level of
evidence. We’ll talk about high levels of evidence in
a minute, but it’s made it into the package insert of 6-MP, at least, and the package
insert says that “substantial dosage reductions may be required to avoid the development of
life-threatening bone marrow suppression in these patients.” Now I’m not a clinician, but I’ve heard that
there is not a lot of genotyping in these patients going on, and this is something that
probably needs to be translated clinically to avoid some of these severe toxicities,
especially in children. So I’m going to switch gears again, to talk
about UGT1A1. This is also a Phase II metabolizing enzyme,
very important. It is involved — first, let me talk about
the SNPs. So you have these TA repeats in the promoter
of UGT1A1. Normal, functioning UGT1A1 has six TA repeats. A gene that carries seven TA repeats is expressed
much less effectively in the liver. And if people carry two copies of this allele,
called UGT1A1*28, they have a decreased expression and function of UGT1A1. UGT1A1 is the primary glucuronidator of bilirubin,
so these patients have a slight jaundice phenotype, known as Gilbert’s syndrome, and this is about
10 percent of the U.S. population has this deficiency. There are some other SNPs that also that are
predictive, I’m not going to go through them, though. These SNPs explain about 40 percent of the
variability in glucuronidation reactions as a whole. Glucuronidation is absolutely key in irinotecan
toxicity. So irinotecan is administered IV, goes into
the blood. These carboxylesterases cleave certain groups
off of irinotecan that turn it into its active metabolite, called SN38. SN38 is rapidly glucuronidated by UGT1A1,
and is completely detoxified when that happens. If a patient is unable to glucuronidate their
SN38, the drug becomes very toxic, and you can see some severe ADRs again. However, this is very dependent on the irinotecan
dose. This is really what I wanted to bring up. At high dose, almost 100 percent of the patients
who carry this SNP get a severe hemotoxicity, whereas, you know, a moderate amount of patients
with wild-type alleles get the hemotoxicity. However, if you go down to 125 mgs/meter squared,
the — this SNP no longer really matters at all. So this is a very dose-dependent situation,
and so sometimes when we think of pharmacogenetics association, we have to consider other issues
other than just the gene. Yeah, let me go on. So irinotecan toxicity through glucuronidation
reactions has made its way to the package insert of the drug. The package insert — this one says that the
glucuronidation of bilirubin, such as those with Gilbert’s syndrome, people with that
will be at a greater risk of myelosuppression. I think the updated one actually does list
UGT1A1*28 now. Switch gears from Phase II metabolizing enzymes
to transporters. Going to talk about one transporter in particular
that’s been very highly studied in the past five years, and I think is on its way to making
it into pharmacogenetics-directed therapy. It’s this OATP1B1 here. So a patient receives a statin, it goes into
the gut, goes through the gut wall into the portal blood. It can be metabolized in the gut wall by CYP3A4,
or pumped back into the gut wall by MDR1 and MRP2. Once in the portal blood, it basically needs
to see an OATP. OATP1B1 is the primary transporter of simvastatin. There are some other OATPs that are very important,
but unless this statin sees an OATP, it does not very effectively get into the liver cell. Once in the liver cell, it’s metabolized and
eliminated. Some of it makes it into the bloodstream,
and, you know, you have varying levels of AUC exposure in these patients. What happened there? Here’s a slightly more complex version of
what’s going on in the liver cell. There is a SNP in this gene, a single nucleotide
polymorphism, SNP, in this gene that affects how much statin actually gets into the liver
cell. The SNP is what’s called a non-synonymous
transition. You have N in most people, those are the wild-type
allele, at position 130 gets changed to a D, and this actually has a great effect on
AUC exposure of statins. We knew this back in 2006; a very good paper
was published showing that thing is heavily linked to the AUC of statins. Now, greater exposure to statins can lead
to statin-induced myopathies. So in patients carrying the SNP that can’t
get their statins into the liver cell as well, you worry that they’re overexposed and they’re
going to get a myopathy. Another study was published more recently,
looking at 500,000 alleles in the genome. I love this study. It shows that only one polymorphism was associated
with statin-induced myopathy, and not only was it associated, it was several orders of
magnitude over the association threshold, which was just denoted by that brownish line
there. This SNP is almost in 100 percent complete
linkage, meaning it’s co-inherited with that NI30D SNP. So this SNP is probably just a passenger that’s
riding along with the N130D SNP, causing overexposure to statins and statin-induced myopathies. This group also took these data into a validation
cohort, where they had cumulative percentages of myopathy, and they found that, again, they
see the same SNP is — about 20 percent of the patients are getting statin-induced myopathy,
and about 60 percent of statin-induced myopathy cases could be attributed to this SNP. So this is a very predictive allele, and the
present SNP has a 15 percent representation in the U.S. population. So this is a very frequent SNP. There’s a lot of people getting statins that
are probably at risk for myopathy, just due to this issue alone. At this point, the FDA has not really weighed
in on whether or not we should genotype for this one yet, but I think it’s coming soon,
and at the NIH, we are genotyping for this. I’m going to talk about targets today as well. So, you know, drugs are designed to bind to
something in the body, and, you know, so these are drug targets. Most people, when they think of drug targets,
think of, you know, your Imatinibs of the world where they — it’s targeted to a somatic
mutation in something like BCR-ABL. I’m not really going to talk about that today
because I’m really concerned more with the germ-line variation, the DNA that Mom and
Dad gave us, not mutations in tumors. There are other types of targets that are
subject to germ-line variation, and I’m going to talk about that instead. So before I get to the targets, here are two
cytochromes, P450, that take warfarin and convert it into an inactive form of warfarin. So these — more hydroxylation through 2C9
and CYP4F2 leads to less active warfarin in the bloodstream. But I’m not really going to focus on the CYP
story, I’m going to focus over here. Warfarin is designed to bind to the vitamin
K oxidoreductase C1. By doing so, it reduces the amount of reduced
vitamin K, which reduced vitamin K is pro-clotting — has a pro-clotting function. So warfarin binds to this target. There is a SNP in this target gene, VKORC1,
that has the — causes the expression of the gene to go down by many-fold. So if a patient lacks sufficient expression
of VKORC1, warfarin will bind it all up and cause bleeding events. Brief aside on CYP4F2, it was fairly recently
discovered, using a platform I’m going to talk about in a minute, called the DMET platform. Here’s the association, it’s very strong. The FDA has, again, not weighed in on this
one, but I think it’s going to be up and coming. So here is the incidence of warfarin sensitivity
— I like this paper a lot — showing basically what causes warfarin sensitivity in the general
population. And you can see this sort of red/pink piece
of the pie chart and this yellow piece of the pie chart, correspond to CYP2C9 and VKORC. So about 40 percent of warfarin sensitivity
in the general population can be attributed to these polymorphisms alone. Incidentally, this CYP2C9 polymorphism, which
metabolizes warfarin, is about 1 to 15 percent of the U.S. population. VKORC variants are more frequent, especially
in Caucasians; about 40 percent of us carry these SNPs that lower VKORC1, and it’s about
12 percent in African Americans. If you look at the package insert, you’ll
find this little table which gives you a warfarin starting dose based on these two SNPs, or,
actually, it’s three SNPs, in VKORC1 and CYP2C9. There’s even a neat little iPhone app that
allows you to put this information in and get a warfarin starting dose. It’s pretty neat. In this case, if the warfarin was already
— dose was already decided upon based on INRs, then, obviously, you don’t need this
information, but it still is useful as a starting dose — to decide on a starting dose. Okay, I’m going to switch gears again. So I’ve talked about targets, now I’m going
to talk about genes that have effects that are not necessarily related to the target
but are sort of ancillary, you know, targets themselves. Okay, so, you know, I’ll show you what I’m
talking about in a second if that doesn’t make sense. So you have a tumor lysis syndrome. You have cellular breakdown, which spills
out a lot of DNA. This DNA is catabolized into a lot of purines. These purines can cause hypouricemia. This uric acid can precipitate in renal tubules
and cause renal failure, so this is known as tumor lysis syndrome. A drug is given to avoid this — actually
two drugs, Allopurinol and Rasburicase can be used. Rasburicase, here, takes uric acid and converts
it into a readily excretable form of uric acid called allantoin. Here is the actual reaction up here. When urate is converted into allantoin it
produces a lot of hydrogen peroxide. This hydrogen peroxide is clear by glucose-6-phosphate
dehydrogenate. There is a group of people that do not have
functional G6PD. They tend to be Mediterranean in origin, and
it’s the same group that cannot eat fava beans, which is why I have the broad bean up here,
because the toxin in fava beans will actually cause the exact same thing to happen. They’ll get severe hemolysis due to too much
hydrogen peroxide. Just an interesting aside, it’s thought that
this population has this deficiency because they want to produce a lot of peroxide in
the bloodstream because they want to combat malaria. It’s a kind of interesting idea. So, anyway, genotyping for G6PD is a very,
very good predictor of G6PD function and so this is a genetic test as well. And the last type of gene-drug interaction
I’m going to talk about are these hypersensitivity reactions which are becoming increasingly
important, I think, in pharmacotherapy. So a drug like abacavir goes into an antigen-presenting
cell where it sees one of these major histocompatability complexes. These image C proteins are encoded by human
leukocyte antigen, which is called HLA. These are the genes in the genome, so I’m
going to say HLA referring to these proteins here, the genes for these proteins, anyway. These proteins will bind to your drug, go
out and start to amount an immune response to the drug itself which causes hypersensitivity. And it’s really — it’s a Stevens-Johnson
syndrome in general. And here’s a kid with Stevens-Johnson. This is really considered — it’s starting
to be considered malpractice to not genotype for this before you give some certain drugs,
especially abacavir. There are similar results with carbamazepine
and Allopurinol, still only recommended by the FDA, but it’s still extremely predictive
of hypersensitivity reactions. Just a simple genotype test can really tell
you who’s going to get it and who will not. About 5 percent of patients get abacavir hypersensitivity. If they have one of these HLA loci, you can
have up to 103-fold odds ratio of risk of getting hypersensitivity reactions. It’s 100 percent positive predictive value;
if the patient has this genetic background, they are almost certain to get a hypersensitivity. It also has a 97 percent negative predictive
value; if they don’t have the SNP, you can be 97 percent sure that they’re not going
to get hypersensitivity. And here is one of the — the conclusion of
one of the Sentinel papers investigating this, I’m just going to read it. “In our population” — Australians — “withholding
abacavir and those with HLA-B*5701 or these other HLAs should reduce the prevalence of
hypersensitivity from 9 to 2.5 percent without inappropriately denying abacavir to any patient.” And I think that’s really a very good summation
of the power of these HLA genotypes. So I have sort of given you the bird’s eye
view of all of the pharmacogenes that are currently out there and are probably moving
towards the translation side. Now, I’m going to just briefly mention one
of the platforms that we use to actually get the genotypes in these patients, just talk
to you a little bit about it. This ChIP, it’s an array-based technology
called DMET, which stands for drug metabolizing enzymes and transporters. It has 2,000 variants and 235 PK/PD genes,
so you can see all of these Phase I enzymes, you’ll see the ones I mentioned in there;
the Phase II enzymes, you’ll see the ones I mentioned in there; transporters you’ll
see the ones, again, the SLCO1B1 is in here. And then these other genes that can have effects
on PK/PD, so here’s G6PD, for example, cytidine deaminase, which is important for certain
other drugs, et cetera. This ChIP is actually — it only costs about
$500 to do the ChIP, and if you batch a lot of samples, as we’ve learned, it actually
costs only about $50 a patient. So it’s not some outrageously costly thing
to do. However, it does have one major deficiency
that we’ve identified, and that is that it takes three days to actually get data out
of this, and that’s a fast turnaround time. So for a lot of these drugs, if you need the
information right away, you cannot get it, it’s just not possible. This isn’t CSI Miami; we can’t just genotype
something in 15 minutes. So, basically, what we’ve done at the NIH
to combat this issue is we have made a policy where a patient gets admitted, and then they
get this genotyping test done; the information follows them around so that if a clinical
decision has to be made rapidly, then this information is there and available, and will
be flagged to the clinician who is going to give them the drug. We’ve based the — talking about our experience
with PG testing at NIH, we’ve sort of used this website called PharmGKB, which is run
by a lot of the pharmacogenetic experts in this country. They are all a part of a network called PGRN,
and they have really curated the pharmacogenetics literature very well. So if you’re interested in this, PharmGKB
is an excellent resource for learning more. They’ve published levels of evidence, so we
have only selected those that have the highest levels of evidence that are available; published
control studies of good quality relating to phenotype and/or genotype patients; healthy
volunteers having relevant pharmacokinetic and clinical influence. Pretty much everything I’m going to discuss
today has that high of a level of evidence. It also has a very high level of clinical
relevance, so even though maybe you have a high level of evidence that a SNP is associated
with some outcome, that outcome may not be that clinically important. So they’ve also curated the clinical importance
of this, and all of these genes I’m about to talk about have a high level of clinical
importance as well. So I’m just going to go through the list,
because I think, you know, you may see some of your favorite drugs on this list, and I’m
going to keep it short so that I don’t keep you here for too long, but here we go. Abacavir, I already mentioned this one, HLA,
B57O1; this one is recommended, so if an investigator will get flagged, this says you really should
— you really need to get this genotype before you can administer abacavir. And even though it says — the test says TBD,
our laboratory medicine branch actually runs this test all of the time so we’re currently
processing this SNP through that branch, anybody treated with abacavir. Allopurinol, another drug with hypersensitivity
reactions. Same story, it’s recommended and can be run
through the lab right now. Azathioprine or any of these mercaptopurine
drugs, I already mentioned these so I won’t go through the mechanism; this is also a very,
very highly, strongly-recommended SNP to test before administering any of these drugs, and
we can actually use the DMET platform to do so. Carbamazepine is another HLA. The FDA recommends testing this in Asian populations. Now, this is an issue here. So I have a friend in — I’m from California
— I have a friend who’s grandfather is — was one of the original Japanese immigrants to
the United States, and he doesn’t look at all Asian, but he has a significant part of
his genome that is Asian. He wouldn’t identify himself as Asian, he
would identify himself as a Caucasian. If he was treated with this drug, because
he wasn’t Asian and we decided not to genotype him, then he could potentially experience
some severe reaction here. So we’ve decided that really looking at a
person’s self-identified race is not the way to go about this. We really need to actually genotype every
patient to find out if they have this SNP or not. So this one is actually very recommended;
test is, again, through the laboratory branch. Clopidogrel, Plavix, the poor metabolizers
have non-responsiveness to clopidogrel. Higher doses may be needed in these patients,
or there’s new anti-platelet agents out that can be used instead of clopidogrel. This one we consider optional or available,
but we assume that since the information’s already available to the clinician, that they
will just opt for one of those other anti-platelet agents. Codeine, I already mentioned it; we don’t
use a lot of codeine at the NIH. This one’s still is optional or available;
the DMET will give you the information. Fluoropyrimidine’s metabolized by DPYD. Patients with deficiencies of DPYD will have
some potentially fatal toxicities, so this test is recommended, and it’s already available
to the clinician by the DMET ChIP. Interferon alpha has an association with IL28-β
SNP. This is — one SNP is very predictive to who
is going to respond well to this drug, and then another is predictive of who will not
respond well to the drug. We consider this optional or available. We have to go outside of NIH to LabCorp to
really do this one. Irinotecan, I already mentioned it. We — DMET ChIP already tests UGT1A1 so this
one’s already being used. Isoniazid with NAT2; NAT2 is a phase two conjugating
enzyme that acetylates isoniazid and gets rids of a very reactive intermediate metabolite. If people are slow acetylators, they’re have
a threefold increase in drug-induced liver injuries. This one is considered optional or available;
the DMET tests it. CYP2D1, similar story, go through it optional
or available. Phenytoin: difficult drug to dose. There is some variance in CYP2C9, which affect
the toxicity and efficacy. This information will be available for dosing
phenytoin. Phenytoin also causes some hypersensitivity
reactions, and there’s an HLA that’s predictive, so this one’s strongly recommended, and the
test is done through the laboratory branch. Rasburicase, which I already mentioned; G6PD
genotyping is already available through DMET. Statins and OATP1B1, mentioned it; test is
available through DMET. Tamoxifen 2D6; test is available through DMET. Warfarin: same SNPs, DMET test. And then we have the molecular pathology laboratory
who is already doing all of the somatic mutations for these targeted agents, so I’ll just run
through the targeted agents and not mention much about them. Trastuzumab, lapatinib, imatinib, dasatinib,
and nilotinib. And imatinib also affects KIT, so we have
the molecular pathologies test KIT for us. Gefitinib, renotalib [spelled phonetically],
and these others. BRAF inhibitors, EGFR inhibitors, RET inhibitors;
alkylating agents, and that’s it. So those are all the drugs that we have implemented
at this point at the NIH in the PG testing arena. So just a couple of final thoughts. How many drugs have pharmacogenetic markers
in the label? Well, at this point, there are 114 of these
drugs, and if you go on to this website at the FDA, you can look at all of these drugs. How many drugs had FDA recommendations that
are actually actionable? Seven have boxed warnings that — where the
testing is very important; 29 have indications and usage information; and 24 will give you
information about the dosage. So a subset of those are actionable. And the last slide here, just considering
the prevalence of use of pharmacogenetically-affected drugs. There’s about 24 million people — this was
in 2008 — using drugs that are — that have pharmacogenetic information that’s available
that you can just genotype them and know what — know more information, anyway, about what
to do to make clinical decisions. There’s a lot of people using these drugs. This number is just ever increasing, and eventually,
they think this stuff is really going to be important in clinical medicine. And Doug Figg, my boss, always ends his talk
by saying, one day, he envisions a child is born, the child gets a DMET ChIP-like genetic
test, and that test can be carried with them through life on a thumb drive, and they can
go hand it to their doctor one day, doc put it into a database, it’ll tell them, “Don’t
give this drug, do give this drug.” So, that seems to be the way that things are
going. And so that’s all I have to say, and thank
you very much. [applause] Male Speaker:
Comments or questions? Yes. Male Speaker:
If I want to start a patient on Clopidogrel — Tristan Sissung:
[affirmative] Male Speaker:
— how do I find out if it’s going to be effective, what do I actually do? Male Speaker:
Could you — could you paraphrase the question [inaudible]? Tristan Sissung:
Yeah. So the question was how do you find out if
a patient is at risk for Clopidogrel inefficacy? And you can use a few options. First option is you can send it off to have
it genotyped by a private company. There are several private companies out there
right now doing this. The test really needs to have, I think, three
different alleles, and each one of those alleles can cost a certain amount of money. We’ve found that it’s actually cheapest to
just have the DMET ChIP run on people. You can take the blood sample, you can send
it to the Coriell Institute, they will give you the information back. A guy named Norman Gerry there is the guy
we run through; he’s doing all of the NIH studies. You can get this information back, and then
make the decision based on that. Male Speaker:
Yes? Male Speaker:
Thank you for a great talk. You’ve raised a lot of important issues. I’m sure I see at least one patient a week
that’s either slow or rapid metabolizer that’s not doing well clinically. Tristan Sissung:
[affirmative] Male Speaker:
There was a Dr. Flockhart [spelled phonetically] in prior practice that used to do consults,
so how can we get consult in terms of private practice to help us, because these two issues,
one is a specific drug, one is — metabolizers slower that might affect many, many drugs,
and that might be beyond the expertise of the private practice doctor. Tristan Sissung:
That’s absolutely right. I know there is some agencies that are — that
are springing up that offer pharmacogenetic consulting to clinicians. It’s a very new thing, you can Google search
it, I know that Doug Figg was approached by one of these agencies, I forget the name of
it, but we’re also at the NIH, and I’m sure we can — we can direct you in the right direction. I think my email is up here. And if we can’t help you, I’m sure we can
put you in touch with somebody who can at this point. Male Speaker:
Those of you who are entrepreneurs, it sounds like that’s an opportunity. Tristan Sissung:
It is definitely. [laughter] Male Speaker:
I want to reiterate the excellent nature of this program, and quite timely and relevant
to private practice. Interestingly enough, just from an historical
point of view, the 6-MP discoverers won the Nobel Prize, you may be aware of that, [inaudible]
in the 1980’s, but to take that a step further, there have been some recent guidelines that
have been published by a national — our national organization suggesting that HLA-B5801 profiles
be obtained, and that certain groups of patients who are going to be admitted Allopurinol,
and happen to be the Kahn [spelled phonetically] Chinese and certain Thai subgroups. But getting back to your California story,
you wonder how many of these particular groups may be here and vulnerable because this is
so important for the Allopurinol hypersensitivity syndrome. So from bench to bedside, this is recommended,
we’re looking at the economics of this as we speak, and to the practicality and bench
to bedside we are told that this HLA-B5801 is now available commercially. Is this in the area that you are — have studied
more than your slides? Tristan Sissung:
I’m not an expert on HLAs by any stretch of the imagination, but I do know the Allopurinol
story, and I agree with the sentiment that we really need to genotype everyone. So I’m not sure exactly — can — is there
— did that answer your question, or? Male Speaker:
Well, a statement and a question, just to point out the relevancy of this discussion
relevant to clinical practice. Tristan Sissung:
Yeah. So, yeah, I think that this needs to be genotyped
in clinical practice; it absolutely needs to be done because it’s so predictive of who’s
going to get these toxicities, it’s very important. Male Speaker:
[inaudible] the national organizations who are suggesting it. This may entertain another low culpability
by not doing it. Tristan Sissung:
That’s true. I actually — I looked up before I came here
— I always look to see if there has been yet a lawsuit for malpractice about one of
these things popping up. Nobody has yet sued anybody and won, as far
as I can tell from Google, for not doing one of these HLA tests. However, I have found — you mentioned Allopurinol
— a woman was misdiagnosed with gout, was given Allopurinol, got Stevens-Johnson, sued,
and won $6 million. So, clearly, it is, it is something that needs
to be addressed clinically. Male Speaker:
Well, you’ll see [unintelligible] on television very quickly on this matter, I think. [laughter] Tristan Sissung:
Lawyers are entrepreneurs, too. [laughs] Male Speaker:
I’m reminded of Norman Shumway in response to a congressional question at a hearing made
the observation that none of us are purebreds. Tristan Sissung:
That’s definitely true, especially in America. We are very admixed. Female Speaker:
Hi. Thank you — Tristan Sissung:
Hi. Female Speaker:
— for a wonderful talk. Tristan Sissung:
Thank you. Female Speaker:
I’m curious — I remember what you mentioned about package inserts having warnings about
genomics, and you also talked about [unintelligible] and how that’s not really helpful, how you
haven’t actually genotype everyone. So I wanted to know if you have an opinion
or if you’d offer your perspective, considering translation, what role or lack of role do
you think these package inserts are playing right now in the translation of this pharmacogenomic
information as to actual use in practice. Tristan Sissung:
Yeah, thank you. So there was a paper published by the people
at St. Jude who came up with the TPMT observation, and they talked about genetic excellence,
that the genetic tests are held to a higher standard than your standard clinical assays
just because they’re — people want them to be so predictive of everything, although they
never really will meet that benchmark. So I think that there is a lot of resistance
out there right now to implementing a lot of this stuff because of that issue. Secondarily, the CYP2D6 tamoxifen story has
been recently stalled by two published studies that came out at the San Antonio Breast Cancer
Symposium showing no relationship between CYP2D6 and tamoxifen outcome. Now, these two studies were fundamentally
flawed. There’s a editorial by Mark Ratain in Cancer
Letters talking about how these two studies both violate a fundamental law of nature:
the random sorting of alleles amongst populations. And the reason for this is that these folks
genotyped tumors and did not genotype the germ-line DNA. The tumors get mutated, and it’s not an accurate
reflection of what’s going on in the liver, how much endoxifen is actually being formed. So these studies have a lot of impediments
to them that are outside the control of a lot of us who are doing the science, so… Male Speaker:
Thank you. Male Speaker:
Yes, again, I’d like to thank you for an outstanding talk. [inaudible] Ph.D. initiative of the hospital,
so when I hear something like this, you know, my mouth waters a bit. And I wondered is the Institute interested
or thinking about perhaps doing some test drives in community hospitals in terms of
typing individuals coming in and seeing its impact since you all put [spelled phonetically],
certainly at NCI. Where are you with that? Tristan Sissung:
I think that, you know, our group would be partially interested in — Doug Price here
has come for some moral support, he’s a fellow staff scientist in our lab, so, I mean, I
think we could probably talk to Doug Figg about that, maybe doing some of those studies. Juan Lertora is the guy that runs the PG program
right now at NIH, and I think you could definitely approach him and ask. He would be — he’s always interested to talk
about this sort of information. Male Speaker:
Would you comment on the role of — the traditional role of pharmacists in protecting patients
and how you see that evolve? Tristan Sissung:
Well, I mean, for this, I think — pharmacists are not geneticists, and I know that very
well because I am a geneticist and I have to deal with pharmacists all of the time. I think that what needs to really happen here
on the pharmacy side is that we need to have some very good curated databases where you
can just put in genotype information, and the people who are experts in genetics and
all of the other fields that are needed to really understand this information, that this
database just spits out a clinical decision that should be made, rather than having the
pharmacist do it all. Male Speaker:
So, in fact, at the end of the day, one could conceive of a system that doesn’t lead to
alarm fatigue, which happens now a lot in pharmacies, I think. Get a bunch of interaction messages, and eventually
a pharmacist ignore them. It’s going to take a lot of work it seems. Tristan Sissung:
Yeah. Male Speaker:
There is a small, but significant incidence of — sorry — small but significant incidence
of fatal malignancies, lymphomas, I believe, in inflammatory bowel patients, and maybe
rheumatoid arthritis patients [inaudible]. Any data on genotyping those? Tristan Sissung:
I don’t know of any, but I’m more of a cancer researcher so I can’t say that there is not. I was actually recently diagnosed with psoriatic
arthritis, and my doc actually mentioned that to me when I went to him. So — Male Speaker:
Could you repeat the question? Could you repeat — Tristan Sissung:
Oh, I’m sorry, the question was basically there’s secondary malignancies in certain
diseases like arthritis, inflammatory bowel disease, and the question was, do you see
secondary malignancies that are related to those diseases, I think is basically what
you’re saying, right? Male Speaker:
Or is there a genotype that would be predisposed? Tristan Sissung:
Or a genotype that’s predisposed. So that’s more of a risk allele, less of a
pharmacogenetic allele. I could see maybe that if you were treated
with azathioprine for inflammatory bowel disease, that you might see secondary malignancies
in patients with certain variants, but the disease alleles, I just don’t know much about. Male Speaker:
You raised an important issue in terms of clinical trials, and that is, you know, maybe
we should lower the patient population to people most likely to benefit. One example that I see every day is glucosamine
chondroitin works in a subset of the population, but it’s said ineffective when you look at
the whole population. Tristan Sissung:
Interesting. Male Speaker:
Are we any closer to using genetics in clinical trials to make drugs more effective? Tristan Sissung:
There are several out there in the literature right now. They’re finally doing this, which is exciting. I mean we really needed the prospective side
of this. Now, I know that there is some resistance
to drug companies to do — from drug companies to do these sorts of studies because they
want their drug to work in the whole population and in any one subset. So oftentimes you’ll see these prospective
studies already being done on approved drugs. I’m not aware of any drugs that are being
developed at this point with pharmacogenetics in mind, but I also don’t work for drug companies,
so I don’t really know for sure. [laughs] Male Speaker:
Other comments or questions? Yes, sir? Male Speaker:
In the world of saving a few bucks, have you ever noticed any difference between a generic
drug and a — from a genetic point of view — the same drug produced generically versus
the standard drug? Tristan Sissung:
I don’t think anybody has ever done a study like that. I think we primarily assume that a generic
and an on-label, or, I’m sorry, I forget the name, you know, a drug that’s produced by
a drug company are the same compound. So I don’t think we ever look at generics
versus the drug companies’ drugs. Male Speaker:
So the American College of Physicians did a survey on something like 500 of their fellows
and members, and asked a bunch of questions about this sort of thing, and found that,
a) each of us believe that this is a really important field for future practice of medicine;
and b) felt very incompetent in being able to use it. And it seems to me that revolves around competency
rather than knowledge. And one of the reasons we were very interested
in having pharmacogenetics talk here is that this one is very, very close to the clinic
on the bedside. And it seems like maybe we ought to do some
more of this. What do you think? I see heads nodding, maybe we should do a
bit more of it. I want to thank you very much, Dr. Sissung. Tristan Sissung:
Yes, thank you very much.

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