Breast Cancer Liver Mets

lee j. helman:well, thank you, and good morning. it's a pleasure to be here. i spent a lot of timewith dr. passamani as suburban was transitioning, and actually it's also a pleasure to be partof the human genome institute series on genetics and genomics. so i thought i would try, asthe kickoff lecture, to just sort of paint an overview of why there's so much excitement,why there's so much interest, and just where we think new technologies in genomics -- lookingfor my -- there we go, sorry -- will lead us. so, during this talk, i'll first spend a littlebit of time defining some terms. because all of us come from different backgrounds, andi just want to make sure the jargon is at

least somewhat understood. then talk aboutour vision for how genetic characterization of tumors will change treatment paradigmsfor cancer in the future, and end with a description of some ongoing clinical trials. but beforethat, actually, talk a little bit about what are the pitfalls and the difficulties? wecan paint a very rosy picture, but we're learning there's a lot of more hurdles to be overcome.a lot more hurdles to be overcome. so, let me first define a few terms, and theni'll show you some examples of what surveys of these look like. single-nucleotide polymorphismsare snps. i'm sure you've come across this in your reading, or even in the newspapers,now. and what we mean by that is a variation in a single base in the dna, acgt. most commonvariants in the genome. they're really over

probably many more, but last i looked therewere over 50 million snps identified. and snp arrays are used to interrogate the entiregenome. and usually we're looking at dna from the germline. so remember there's germlineand somatic mutations. the germline is something -- is how the dna looks in every cell in aperson's body. a somatic mutation is when we're talking about a mutation that specificallyhappens in a tumor, and you don't see in all the normal cells. and i'll show you. and thesesnp arrays are often used in another term i want to define, which is genome-wide associationstudies, or gwas. so they use snp arrays, usually to compare populations, and it's usuallya disease state or not a disease state. sometimes we use a gwas to look at how certain drugsare handled. so there can be polymorphisms

that affect metabolism of drugs. and thatgoes across all of medicine. and they're often used to determine risk or susceptibility tosome state. mishandling of a drug, risk for cancer, et cetera. rna expression profiles were one of the first,sort of, globally used genetic approaches because they could be done quite rapidly.and they're used to determine global messenger rna expressions, so that's the part that turnsinto protein, that's the code for protein, in a sample. and, typically, they've usedhybridization of messenger rna to a chip. and i'll show you an example of that. andthat's led to the sort of oncotype and these kinds of analyses of tumors that are alreadyin use today.

perhaps a slightly newer application of chiparrays are methylation arrays. so, so far we've talked about looking at the dna or lookingat the rna, at the changes in the base pair in the coding sequences. methylation arraysdetermine global methylation of the genome. so that's an epigenetic change, in that itdoesn't change the base pairs. what it does, typically, is it -- we have methyl groupsinserted at what are referred to as cpgs, so cytocine guanine. there are these cpg islands.and that methylation alters dna. typically it silences, but not always. but they are-- so there are changes that we refer to as epigenetic changes. and it alters the transcription,typically. and, again, it's hybridization of the dna to a chip.

and last, but not least, which is really,eventually, going to replace all of these chip technologies, is the development of massivelyparallel sequencing, which allows for rapid sequencing of either the entire genome, whichyou sometimes see referred to as wes, or whole exome sequencing, or whole genome, which is,of course -- remember, most of the dna doesn't encode protein. so, when we do whole exomesequencing, we're looking for, typically, genes that encode proteins. but we can alsodo whole genome sequencing, or wgs. and of course, we used to think of this as garbage.but we now understand this dna has an awful lot to do with how genes function. we're stilltrying and figuring out how. and then there's also -- you can take cdna, which is a copyof rna, and do what we call rna-seq. but they

all use the same approach, and i'll go throughthat technology briefly. so this is the way a gwas would be reported,and this was actually a data reported out a few years ago. when a gwas study was used,looking at snp arrays, and this area is all around -- this is around 8, chromosome 8,arm q. so the long arm of chromosome 8 in a region called q24. so this is a distanceacross this particular region in centimorgans. and what you see are these outlying areasin red, which, through these large population studies, identified a region, several regions,in 8q24. so i put here -- this is myc. so myc is an oncogene. so these regions weredistal to myc. but these regions were found to be distinct snps. so certain snps wouldexist in patients that had increased risks

for either prostate and colon, breast, orprostate only. two regions of prostate only, a region of breast, and a region prostateand colon. and these areas were not encoding dna sequences. so, by interrogating the wholegenome, we find these alleles, these polymorphisms that seem to be more frequent, statistically,tracking with people that have an increased risk of developing a particular cancer. questionis, how do we deal with that information? and the next slide shows the difficulty. so,we've all heard of brca1 and brca2. so this shows the risk, so the population -- the relativerisk. so if you have brca, there's a huge effect, right? so you have a really high riskof developing breast cancer. but the frequency of that, this is the frequency in the population,is extremely low. so the very potent polymorphisms

or mutations in the germline that increasethe risk of cancer are very strong, but they're extremely rare in the population. what wemore likely and typically see with these types of studies are alleles that are much morefrequent in the population, so, for example, the 8q24 allele: 30 percent of the population,but the risk is just over one. so the frequent alleles that we think predispose to cancerhave an intensity that's quite low. and what we're beginning to think, it's probably anaccumulation of multiple of these alleles that ultimately we need to understand, thatwill lead to better predictions of what risk factors are. but you can see, mathematically,this is pretty complicated. so, just showing you: these are very uncommon and rare, butthey're clearly actionable today. these are

much more common, but we don't know what theaction should be. so this is an example of rna expression profiling.and this is data from lou staudt's laboratory over in our -- at the center for cancer research.and he was interested in diffuse large b-cell lymphoma. and you can see all of these tumorsbasically, histologically, look the same. and when he looked at rna expression usingthese expression arrays, he was able to divide these into three distinct categories. andeach of these red dots represents a particular gene that's highly expressed. and you cansee this group of genes is highly expressed in a subgroup, about a third of these tumors.this group of genes is highly expressed in another third, and this group of genes isuniquely highly expressed in a much smaller

subgroup. and dr. staudt was then able todivide these into what he calls activated b-cell and germinal center b-cell, partlybecause of the genes that are turned on. these genes more look like an activated b-cell expression,what the rnas look like, and this looks more like a germinal center b-cell. why is that important? what we're beginningto understand -- and this is now just at the expression, this has nothing to do with thesequence at this point -- is that the germinal center b-cells using current therapy havea survival of about 75 percent, whereas the activated b-cells have a survival of 40 percent.histologically identical. so now we can begin to take action, because this is unacceptable.and what lou has gone on to do with a series

of beautiful papers, now using some sequencing,which i'll get to, is he's found specific mutations in pathways that have to do withnf-kappa beta signaling. and there are some treatments -- btk, bruton's tyrosine kinaseinhibitors. and those are actually in clinical trial now. specifically to get on that trial,you have to have an expression profile that looks like this. and this now can -- onceyou have those genes, you can target -- instead of looking at all the array, you can lookat 20 genes and say, "if these are on, i know you're an activated b-cell type, and you cango on this clinical trial." so, in summary then, with expression profiling,sort of two images of breast cancer. so this is what breast cancer looks like under a microscope,and this is what it might look like trying

to look at all the expressed genes. and thatled to what many of you are well aware of. we now know that breast cancer can be subdividedinto luminal a, luminal b, her2 positive, er negative, and basal-like, or triple negative.and these are just four genes that you can see can really separate, just looking forthe expression. an oncotype, i believe, i should know this, uses 14 or so genes thatcan now allow us, using otherwise similar tumors, to now separate these. and we knowthese have vastly different outcomes. so i apologize, this is a little bit blurry.so this is data from our group looking at hypermethylation. so we were looking at gisttumors, and there were gist tumors that had mutations in c-kit, and there were what wecalled wild-type gist tumors. and what we

found is that the wild-type gist tumors turnedout to have a mutation in another gene. in the krebs cycle, for those of you who rememberyour freshman biochemistry in medical school, the succinate dehydrogenase gene. so thesewere the normal gists that respond to imatinib, and you can see, hopefully a little bit -- thisis looking at cgh, comparative genomic hybridization. this just shows that the genome has a lotof losses and gains. unstable genome that we typically see in cancer. and the expressis sdh. this is a tumor that's sdh -- no sdh. and the genome looks like a normal cell. there'sreally no gains or losses. it really looks, at the genome level, to be normal. but when we looked at the epigenome, whenwe looked at methylation patterns, all of

these tumors that looked so quiet geneticallyhad completely hypermethylated across their entire genome. we don't understand what thismeans, but these are the mutated tumors, and their genome looks pretty normal, methylation-wise.these are the tumors that we can't find many mutations, but the methylation pattern iscompletely abnormal compared to normal tissue. so this is another layer of information. what about massively parallel sequencing,or sometimes referred to as next-generation sequencing, or ngs. so, basically, you cantake dna or rna or cdna, you fragment it, you collect those fragments, you put littlepieces of adaptors on them, and you do -- it's called massively parallel because you're sequencinglittle bits of dna that have been broken up

and fragmented in these machines, and thenyou have to align each of these small reads on the genome using a reference genome. butit allows you to sequence the entire exome, if you want to just capture exomes, or thewhole genome. these are the kinds of information you canget, and i just took this from a review a few years ago now by matt meyerson at thebroad institute. and you can find point mutations -- again, you're always aligning to a referencesequence, so you can see point mutations. you can find insertions and deletions, whichyou'll see referred to as indels. so little pieces of dna get put in, little pieces ofdna get lost. you can see whole deletions, so here, you know, you might miss a wholepiece of the normal reference sequence. you

can have that be homozygous or heterozygous,so you might find it in both alleles, or just one allele. you get copy number alterations,where you might have an extra copy of a piece of the dna. and you can also, using the rna-seq,you can find translocation. so you find a piece of expression from chromosome 1, andsuddenly it's hooked to a piece of dna that lines up to a totally different chromosome.so all of that can be garnered from this massively parallel sequencing. so here's the technology. so there's an astonishingarray of machines now, from various companies and various sizes. this ion torrent, you cansee, is -- a lot of people are using this, you can put this on your desktop and actuallysequence targeted areas. so to confirm, we

use this often to confirm. illumina is oneof the big players in the market, and they keep coming up with new generations. the currentgeneration is called a hiseq, but they also have something called a miseq that's morelike a personalized one to use in your laboratory. but this technology is changing at an astonishingrate. the point about this is only that they are extremely rapid. the standard operatingprocedures are getting very clearly defined, and we can generate enormous amounts of sequencedata very, very quickly. but just to give you an idea, for clinicalpractice currently, if we want to do a whole exome sequence -- because you have to analyzethe data. so, generating the sequence, you can do in a couple days or a day now. butyou still have to analyze it, and that -- the

computing power is still trying to catch up.but it will take us two months or so from the time a patient walks in the door. so we'renot yet able to take whole genome sequence and apply it within a couple days of a patientwalking in the door. we can take targeted sequencing, 15 genes, 20 genes, but not thewhole exome or whole genome yet. so i want to go through, now, a couple ofvignettes that i think will give you an idea of how this is impacting clinical oncology.so this is some data i took from javed khan, also in the pediatric oncology branch, a closecolleague. and he was looking at sequencing the tumor that's near and dear to my heart,rhabdomyosarcoma, which is a pediatric sarcoma of the skeletal muscle origin. and he didwhole genome sequencing. so this is clearly

an experimental approach, this is not involvedin the clinic yet. from 46 rhabdomyosarcomas divided into -- about half were one subtypecalled alveolar, and half were another subtype called embryonal. he also did snp arrays,which i just described to you. and then using this high throughput, he then validated allof the alterations found using a different technology, in this case, either solid orthe illumina technology, in a much larger number. so you can see, he took 133 rhabdomyosarcomasto see how this discovery set held up when he used the larger. so the first thing to point out is, in thefirst 46 samples, two of those patients didn't have rhabdomyosarcoma. and we figure thatout by the genetic analysis. so one of these

actually had a fusion of alk and npm1, whichwe know is probably anaplastic large cell lymphoma. alk stands for anaplastic lymphomakinase. so that was just somebody -- it's hard to tell sometimes. and there was anothersample that we found another translocation, ret to nco4. probably a parathyroid person.so some of the times, we actually get a little bit more specific diagnosis. it was amazingto us, though, that that was only two out of 46 samples. so the pathologists do prettywell. so this is what we see. this is a circos plot.i don't expect you to understand, or, you know -- this is not the way data would bereported out in practice. but it gives you a sense of what you can actually get off ofthis analysis. so these are all the chromosomes,

1 through 22, and then the x and the y. youcan see this patient doesn't have a y, so this is a female patient. and you can get-- so, this is the chromosome position around the outside circle. and then you can get copynumber alterations, you can look at losses and gains, you can find translocation. so,this is when you see a line drawn from here to here. that means this chromosome got hookedin this chromosome in this case, two and 13. and you can find copy number alterations andsingle nucleotide variants. so, here is the translocation. we know this is common in alveolarrhabdomyosarcoma. so, we could find that easily. and the other thing was that there was, youknow, there was this loss of heterozygosity. so, here's looking at copy number, and yousee suddenly this has only lost -- it's a

copy. so, it's a loss of 11p15 so only oneallele here. but the genome in general looks pretty quiet. you don't see a lot of wildchanges here. so, that's one type of rhabdomyosarcoma. here's an embryonal, and in this case whatwe see is many more changes. so, here are all these mutations on the outside. i justlabeled them here. so, there are about seven or eight mutations, no translocation, anda few more copy number alterations. you see much more -- you see areas here in additionto 11p15 which is pretty typical across all rhabdomyosarcomas. so, what are we finding? we found the typicaltranslocations that -- we also found a novel translocation as well as this pax to a differentfusion partner. so, most of these pax -- these

two has been identified. we found a novelthree -- we found three alveolar rhabdos that should have a fusion that we couldn't find. we found something quite interesting; here'sa tumor where this chromosome 2 -- rather than you seeing a nice line, there's thiscomplete alteration of chromosome 2. and what that looks like is a -- so this was one ofthe ones we couldn't find the 213. and what we found is massive rearrangement of chromosome2. it just kept breaking and reconnecting and breaking and reconnecting. and so andthat's depicted here. so, you see multiple changes. so, we don'tunderstand how that does the same thing as a fusion to a forkhead gene or foxo1 gene.but these are some of the things we're learning.

we did rna seq as i mentioned. and then thisnovel fusion. in fact, it was expressed. so, we could find the pax, and then if you goalong it now starts reading sequence to this other gene on exon 11. so, question is how does all this change whatwe do in the clinic? and so i'm going to now try to go to some commenters [spelled phonetically].i do pediatric cancer. but most of you won't see pediatric cancers. but here's a slideactually i think i borrowed from charles sawyers. and this is something as common as lung cancer. so, here's how we used to think of lung cancer.there was adenocarcinoma squamous and large cell. and in 1987, we knew a small portion,maybe a third, maybe between a quarter and

a third, had kras mutations. in 2004, we foundegfr amplifications. and five years later, we now found these translocations, these alttranslocations, her2 over expressions, some braf mutations, some metal alterations, someakt, some pic3ca, or pi3 kinase mutations. so, now we filled up as many kras mutationswith these other -- but look what's happening. each of these samples now we're taking a commontumor. and we're making them rarer and rarer and rarer. so, in a global sense, i sort of view thisas really the whole -- all of medicine, but in particular in oncology, the paradigm isshifting. we're going from descriptive medicine by understanding what something looks likeunder a microscope to understanding the mechanisms.

no, it's not good enough to say this is anon-small cell lung cancer. is it alk fusion? is it pi3 kinase mutated? and that helps gofrom empiric diagnosis to mechanism-based diagnosis. i'll come back to this in a littlebit. it's not even clear ultimately that everythingwill get grouped by organ site. it may be that we'll group things by disease driversalthough that's still unclear. and i'll illustrate that. but we will certainly go from uniformtreatment. this has already happened in breast cancer. it's already happened in lung cancer.the problem is, what do we do with rare tumors like pediatric tumors, where we're now sub-typingthem? it gets pretty difficult to do a clinical trial.

we hope that by understanding the earliestchanges in a tumor, we will have earlier biomarkers. and we can go from retrospectively diagnosinga disease to once we treat and we think we cure someone to be able to intervene beforewe ever see a change on an x-ray. but maybe when we start to see that -- and this is seethat alteration. and this is in fact what's happened in cml. and hopefully we can go fromacute care to early detention and early intervention. so, this is just a graphic depiction. andwe like to call it -- you know, a lot of people call it individualized therapy. we like tocall it precision therapy because most of us as physicians, i think, have been givingindividualized treatment to our patients our entire careers. at least i'd like to thinki have. but we've not had precision tools.

and so the idea is if you treat everyone thesame, and you see a responder, the question is can we figure out what the lesion is andwhat we need to target and not treat the three out of four patients that aren't going torespond. and in addition as i briefly mentioned, these pharmaco dynamic measurements that maybe identified through snp arrays may tell us certain patients that would handle a drugdifferently. so, we can select drugs not just based on the tumor but also on how a patientwill handle it, the molecular diagnostic approach. and again, so you can just see that breastcancer now will have two red types of tumor, one yellow type, and three gray types. so,that's really the theme. so, now let me say why this is had such an early impact in cancer.well, for many years, i think, it's been fairly

well established that cancer is in fact adisease of the genome. so, we all thought, okay, if we precisely define the cancer genome,we'll understand and cure cancer. we got to be cautious about this, and clearly this isa direction we need to go. it's clearly going to change the paradigm, but as usual in medicinein physiology in biology, it's not so simple. so, now i want to do a few more definitionsbecause you'll hear about founder mutations. and what we mean by founder mutations is usuallyit's the first genetic alteration we can detect. and it usually then is established, and you'llsee that in all tumors that are biopsied. and then often lesions that lead to geneticor genomic instability like p53 or rb these are, you know, p53 is called the guardianof the genome.

so, one of the problem is many of these foundermutations makes the genome unstable. and they're often not fully transforming. now we talkabout driver mutations. and what we mean by that is that those are required for the expressionof a fully transformed phenotype. and the driver mutations are those that we think weshould be able to target and then successfully alter the disease biology. then there are what we call passenger mutations.and i refer to them as collateral damage. they're mutations that you find that justget accumulated because the genome is unstable. but they're not necessarily -- if you findthat mutation and you block it, it may not have any function at all on the growth orsurvival of those tumors, and so it may be

noise. and so since most cancers are rapidly evolvingbecause they have an unstable genome, it's really a major task to sort out drivers frompassengers. and i'll give you a few little graphic illustrations of that. so this isa slide that borrowed from gad getz at the broad institute. and so he just sort of plottedhere the frequency of mutation per base, you know, per mega base here across a number oftumors. so, on the right is melanoma, and on the leftare pediatric tumors. and what you see is different tumors have higher or lower frequencyof mutation rates. and it's interesting the highest mutation rates are in diseases thatwe know the environment damages dna, uv radiation

we know causes dna. and you can see -- i don'tneed to go into this, but in the bottom it the colors represent the kind of dna changesyou get. so, the yellow means you have a c to t transversion. and so there are different types of changesthat occur but much higher in lung cancer. again we think smoking has a major impact.we know smoke causes dna damage. and as you get across, here's multiple myeloma ovariancancer. so, here's rhabdomyosarcoma. so, the genome there's pretty quiet. but differenttypes of tumors have different amounts; some of these are enormously high. and this leadto the problem of sorting out, what are the important mutations and what are just mutationsthat are not selected for that the genome

is just unstable? so, here's another way of looking at that.this, i think -- i don't remember what the tumor type was here. this was an interestingpaper published from the sanger institute where they actually were able to look at variouspoints along the tumor. and what's shown here is that there was rb and p53 mutation thatoccurred early in time. and by looking at tumors across time, they can sort of set up.here's what happened first, here's what happened second. and what you see are these branchingchains. each of these represent what we might call a private mutation that may just be occurringin this particular area of the tumor but not in this area at the same point in time. you'llfind two private mutations what we call private

mutations because they're only in one areaof the tumor. so, this is another problem. even in one tumor we find heterogeneity. andi'll show you some illustrations of that. another point another problem is and we'velearned this in spades is that these even when we find the driver mutations, they'reusually kinases at least so far because we can target those. they're components of ahighly integrated wiring that's not one way. and they're normally important for normalcell function. and so they're highly regulated. so, not surprisingly when we perturb it oftenthe cancer cell figures out a way to get around it. and so this was an illustration of that.this is from a nice review that i would recommend talking about resistance in jco, i guess,two years ago now by levi garraway's group.

so, there are -- here's an oncogene. you inhibitthat oncogene. and often so in cml or in gist, what we find is you select for mutations inthe same gene. so in the bcr-abl gene in the case of cml that not doesn't respond to thatkinase. but there's still mutations in the same gene. and what we think is happeningis what we call clonal evolution. i'll come back to that in a few minutes. but we're really those clones exist. they'remuch they're low frequency and by now killing the cells that are susceptible, we allow theseclones that have already mutated developed a point mutation that are now resistant tothat particular kinase. but another defined mechanism is what we call a bypass, in whichyou block that particular pathway and now

the tumor just activates another pathway downstreamof that. so it's not even a mutation in the same gene, it just alters some other pathway. and that's been demonstrated now in vemurafenib.and i think that paper was actually defining that -- because for the first time. so, theseare melanomas about half have mutations in braf. and now we're finding these mutationsmuch rarer in other tumors. but it's a mutation from v to e. it's called a v600e mutation.and what we learned is that doses of this braf inhibitor that inhibit 90 percent ofthis kinase activity most patients the overwhelming majority of patients respond quite rapidlywith tumor shrinkage. unfortunately, the overwhelming majority of patients recur less than 12 monthslater. and so what we've learned is that they're

not mutating their braf like we saw with cml.they're activating other downstream pathways. and another interesting thing remember thatpart i talked about we might treat instead of by organ site we might treat by braf mutanttumors or her2 amplified tumors. well, here's a word of caution. this was a phenomenal paperpublished a year ago by bernards' group. and bernards' group in the netherlands where we'rebeginning to find braf mutations scattered throughout. so they found, you know, a fairnumber of braf mutations in colon cancer. and the idea was they should respond to vemurafenib.but they didn't respond. and it turns out when you treated these patientswith the same drug, vemurafenib, they activated egfr, so epidermal growth factor receptor.and the mechanism appeared to be that braf

leaves the inhibition of this other pathwaycalled mek and erk, and that changed the phosphatase activity which then shot off egfr. so, nowwhen you perturb this, now you up-regulated egfr. and that then was driving the tumor. so, the reason i spent a little time to talkabout that is that it's not going to be so simple as treating every -- define the mutationand if it occurs in colon cancer it'll be the same as if it occurs in a melanoma. so,context is going to matter because the wiring is going to be different depending on whatpart of the, you know, what's the histology and what organ you're looking at. so, lifeis getting more and more complicated. now i want to come back to this idea of clonalevolution. this is a whole other -- so we

talked about resistance. so let's talk aboutclonal evolution and how that's also a difficulty. and this is again data i took from javed khan.so, he's also been sequencing neuroblastomas; very rare tumor and children over one it occursin young children, and it's got a horrible survival rate less than 30 percent. so, wewere very motivated. we thought, "let's understand the genome. and let's find new ways to treatthis tumor." so, this is actually an older patient, a patientthat had high risk neuroblastoma. he had metastasis in the bone marrow. and at diagnosis, hisbone marrow was chock full of neuroblastoma. so, that was easy access to tumor unfortunatefor him. he had this big tumor in his liver and his primary tumor in his adrenal. he wastreated with four cycles of induction chemotherapy.

he got surgeries. so, we were able to lookat the primary tumor. and the tumor unfortunately was viable at the margin. he got additionalcycles of chemotherapy did well for a few years and he ultimately died. and we wereable to go look at a second metastasis a second site at the time of death when he died. and so we did a whole genome sequencing ofthe liver metastasis. we did an rna sequencing also of the first metastasis and also of theprimary tumor and the metastasis. so, the first thing is that in the liver metastasis44 mutations were found. so, how are we going to deal with 44? and look at all these translocationshere. so, here's all of the mutations. there's lots of translocations lots of copy numberalterations. so, this genome was quite abnormal.

actually something called chromothripsis hadoccurred. and that's it's almost like the chromosome blows up. and we see this now.this has been well described. and in this particular liver met it had happened in chromosomefour and chromosome 13. the chromosome was just massively rearranged as if it just blewup and got hooked back together obviously not in the right order. so, then we re-sequenced using the e torrentof the primary bone so all the abnormalities and the bone marrow, the four areas of theprimary tumor, and then the metastasis. and the first thing was we found differences.there were small variants in four areas of the same tumor. we could find some differences.and that's been described now in kidney cancer.

so, that's another thing. you got a big tumoryou look at, you know, the north south east and west poles, you'll find specific mutationsthat are what we call private to those parts of the tumor. we -- the good news is there are common mutations.but if one of those new mutations can be a driver, then we have to treat all of those.and so here's 14 of those 44 mutations were found across -- this is looking at the metone the primary the bone marrow or met two and the primary tumor. so, the good news is,you know, a third of those were really common. so, those are probably the ones we would goafter. but the bad news is a lot of them were privatemutations in each of those individual tumors.

we found three genes that were high in allthese tumors that might indicate these could be targets. but the bad news is 30 of the44 mutations in the second metastasis that was so genetically unstable were only seenin that liver metastasis. so, and some of these could be drivers. we don't know. butthis is the kind of heterogeneity that, you know, is a nightmare for an oncologist. so, neuroblastoma and we have remember i showedyou neuroblastoma at the left end the low mutation rate of cancer. so, there's everyreason to believe in other tumors it's going to be more complicated. it's marked by aneuploidy,and what we mean by that a messed up genome in recurring regions. but frequently the mutationsare not recurring. they're private. it's possible

that some of these mutations may drive tumorgenesis. but it's also possible that each individualtumor has its own set of drivers. and that's a nightmare. and ongoing efforts are now -- we'retrying to see what are the commonalities and if could we find two or three if we targetall three would take care of all of this. so, we just don't know the answers to thatyet. another problem is that sometimes we finddrivers. and remember i mentioned these epigenetic. so, these are things that alter epigeneticit -- they alter methylation of either the genome itself, the cbg islands. sometimeswe find things that alter the methylation marks of a histone which then determines whethera gene is going to be activated. and all of

these in red are mutations that are clearlyfound as drivers. and here's the histology they occur in. andwe're find these more and more frequently. and we don't have targets for those. we don'treally know how to target many of these mutations. so, resistance is a problem, clonal evolutionis a problem, and finding mutations that are drivers that we don't have drugs for is anotherproblem. so, i want to end with a study that's justabout to open across the street. partly it's an advertisement. we'd love to have patientsreferred for this study. so, it's really now up to all of us to ask. we can find thesealterations. we can find alterations that we have drugs for. what's the evidence thattreating those is actually better than doing

what we've done for many years which is takethe, you know, the combinations that we know have some activity and treating them. of course, we have to ask those questionsethically. so, we have to start with advanced tumor patients. but the question is can weobjectively show in cancer, i mean, we clearly know that when we find a driver mutation likea braf mutation patients respond. but they all recur. so, can we really show that theuse of this expensive analysis at some point during the lifetime of a patient's tumor thatit's worth having that information and that we can act? and so the objective of this study is to accesswhether response rate and four months regression-free

survival is improved following treatment withagents chosen based on the presence of specific mutations. and only patients with predefinedmutations will be eligible. and i'll show you that in minute. and the study's treatmentswill be standardized and chosen from a list of regiments in the protocol. and i'll describethat in a minute as well. and arm a will then receive the treatmentbased on identifying a mutation and saying yes these are the agents that we should targetthat. and arm b is just we're going to pick one of the other arms. so, here's the patientpopulation. pretty standard, so they have to have refractory solid tumors, normal organfunction, and the standard early phase study. and we're looking at the mutations and dnarepair pathways. and if we find those depending

on what the repair pathway is there's a parpinhibitor plus an alkylating agent or a wee-1 inhibitor plus a carboplatin. for those thathave mutations in the pi3 kinase or loss it this pathway pi3 kinase akt, they will treatedwith an mtor inhibitor. and for those that have mutations in ras we'll treat with a mekinhibitor that's just downstream of ras. so, here's the study design. everyone hasto get a biopsy. the patients are sequenced. if no mutation is detected -- and obviouslywe're targeting, so we're not doing whole genome. we're targeting those pathways dnarepair, akt, and so we can do this quickly. if we don't find a mutation in one of thosepathways, they're off study. if we find a mutation, they're then randomly assigned toarm a or b. and the clinical team is blinded

to where they're assigned, and then they'lleither get targeted therapy or they'll get the alternative for one of the other targets.and there's allowed crossover because obviously, you know, if somebody gets randomized to acombination that doesn't target their pathway and they progress we'd still like to givethem the opportunity. so, they'll be randomized two to one with more favoring the targetedtherapy; up to 30 patients will be treated. the two arms will be compared with respectto objective response and regression-free survival. and it's a randomized. so, hereare the pathways that we're looking at. so, this is the ras pathway. so, we're lookingfor mutations here. and there either gains or losses, but these patients will be treatedwith mek inhibitors. here's akt, pi3 kinase

p10. so, there's either gain or loss, andhere they'll be treated with an mtor inhibitor, and here we're looking for dna repair. anddepending on which gene is mutated, we'll either treat them with a wee1 inhibitor pluscarboplatin or a parp inhibitor plus temozolomide. and i should've -- i thought i had this buti didn't show this. so, the patient so let's say we find a patient with a ras mutation.two of those patients will get randomized to be treated on the mek inhibitor. and theother patients will either get one of the other the regime determined to be targetingthis or this. so, that you know, so that everyone's getting one of three treatments. but eitherit's specific or it's chosen because it's not specific.

so, i'm just going to conclude with a coupleof sweeping generalities. certainly we believe that the ability to obtain full genomic dataon a given tumor will allow us to make much more rational choices for therapy. we hopethat functional genomics may provide help in choosing combination therapy. and i didn'thave time to go through functional genomics. but it's a way of just when anticipating resistance,i believe, by when we have a targeted therapy you can look in vitro and see that other pathwaysget activated. and by using specific inhibitor of pathways,either genetically or with drugs, we can predict what gets activated and then maybe be preparedas a patient develops resistance to add-on additional therapy or even start with combinationtherapy. i believe that we've done most of

our studies to date using single-agent targetedtherapy. and as many of you know, as i've been practicing oncology for 30 years nowsingle agents don't cut it. we never try to cure anybody with single cytotoxic therapy.we know that we have to combine targeted therapies. and in my mind, we need to get much fasterat getting to those combinations. but combinations are not panacea either because we alreadyhave learned that some combinations just like with chemotherapy have two much, you know,toxicity. so, it may be a perfect combination except the patient doesn't tolerate. so, we'regoing to have to learn, but we have to quicker in getting to combinations. and i would just end with saying, i think,in the end our hope is if we can't cure patients,

we can turn these into chronic diseases. andthat's not such a bad thing. as long as we recognize the rapid development of resistancein clonal evolution, it may be that we just continue, the patient responds, and then developsa resistant clone. maybe we don't stop the therapy they're on. maybe we just keep addingthings assuming that they tolerate it. and so that's sort of the hope for the future.i hope i've given you some sense of where genomics is today, where we hope to take itin the future, and also given you a realistic picture of, "we've got a lot of work to do."thank you very much for your attention. [applause] male speaker:any comments or questions for dr. helman?

i have one. [unintelligible] that you mentioned,is it possible [unintelligible] therapy? lee j. helman:that's a good question. i believe occasionally these have been found in de novo tumors. so,i don't think it's a function of -- but it -- we might -- it's possible that it's morecommon in the setting of chemotherapy. i don't think we have enough data yet. male speaker:other comments or questions? and could you paraphrase these for us? male speaker:are you accepting brain tumor patients in the study?

lee j. helman:so, the question was: for the last study i described, are brain tumor patients accepted?i believe so. so, the p.i. of that study is shivaani kummar. it's k-u-m-m-a-r. first nameis shivaani. you should be able to find her. i should've put up a contact phone number.in fact, i can find you afterward; i have it on my iphone, so i can give you her contact.she'd be delighted to take any calls for referrals. study isn't open, but hopefully it's goingto be open very shortly. male speaker:other comments or questions? i have another, which has to do with the pharmacogenomics.it seems like that plus the clonal stuff and the resistance really gives you a very complexproblem to solve. could you comment?

lee j. helman:i -- that was the point i was trying to make. [laughter] i think we're going to have -- and of course,all i talked about was the tumor. there's been a lot of interest in interactions between-- i don't like to use the word host because i think it's a little bit of a messy term,but the normal stroma surrounding the tumor and how that may be influencing. certainlywe know there are signals going from the normal surrounding stromal tissue to the transformedtumor tissue, and there may be changes there as well. certainly the pharmacogenomics, i think, we'rejust scratching the surface, and that may

alter our selection of certain drugs as welearned which drugs may be more toxic in a certain snp background or genetic backgroundthan another. so, this is complicated. that's why i think, you know, our sort of initialblush of 'we're going to sequence the genome and find the cure for cancer' is a littlebit more optimistic than realistic. but there's no question it's going to change our treatment. male speaker:i was under the impression that the reason we had so many noise mutations in adults wasbecause of the accumulated mutations we get as we become adults. so, given that why wasso many mutations in the pediatric tumors, because they're not around as much to getthose mutations?

lee j. helman:so, the question was, it's understandable why adult tumors -- adults with cancer havea lot of mutations, because we all accumulate some mutations as we age; why do pediatrictumors have so many mutations? well, first i'll tell you a story. one of the reason,having been trained in medicine, i decided to focus on pediatric tumors was i thoughtthey would be very simple. we'd find the one or two genes, i'd find the target, and i'dgo home a hero and retire at age 50. it turns out because founder mutations and tumors,even pediatric tumors, often lead to genomic instability that, even though they are quieterthan adult tumors, you know, you only see 20 mutations instead of 600. that's a lot-- there's still a lot of noise. and i believe

most of that is due to the fact that onceyou're fully transformed, you're inherently either genetically unstable, or as i triedto point out in some cases, epigenetically unstable. and we're just scratching the surface. we now have an example, an excellent exampleof pediatric diffuse intrinsic pontine gliomas, or glioblastoma, which are completely distinguishablefrom adult glioblastoma, because they have specific mutations in a histone that leadsto just global changes in the ability of certain genes to be turned on and turned off. so,there are going to be epigenetic changes, and we're seeing more and more of that inpediatric tumors. so, i'm a little worried that many of the pediatric tumors, even thoughwe don't see so many mutations, are going

to have more epigenetic alterations that themore common epithelial cancers. that -- we'll have to see if that pans out. male speaker:at the risk of confessing something i should i know, but are pediatric tumors germline[unintelligible], or are they -- lee j. helman:well, of course, there are -- the li-fraumeni syndrome was first described -- the indexcases was a rhabdomyosarcoma. so, those are germline p53 mutations. there are germlineneurofibromatosis 1 genes, and those patients have a fairly high incidence -- 10 percent,or so -- of malignant peripheral nerve sheath tumors. but those are the vast minority. thoseare quite rare across all pediatric tumors.

male speaker:[unintelligible], did you put your [unintelligible] back up and give us a little bit of -- i noticethere [unintelligible], and i wondered if you could just run us through a little bitof that. lee j. helman:i don't know how to get to the slide sort of quickly. the clonal evolution, you know,that -- male speaker:you had one there. just the circular plot. lee j. helman:oh, okay. sorry. circus plot. male speaker:yeah, there. lee j. helman:yes, so there are two alleles. so exactly.

male speaker:[inaudible] lee j. helman:yeah, yeah. so you lose -- exactly. male speaker:have you ever [unintelligible] studied families who don't have cancer at all? is there a reasonfor them to be resistant to mutations, or resistant to develop a cancer? perhaps there'ssome information on that note. lee j. helman:well, you know, it's a good question. the parallel, i would say, is there was a -- therewere -- the niaid spent some time with patients that were hiv-infected and never developedfull blown aids. and they were trying to understand how they became resistant. it's a little harderto do that in cancer. so, i don't know if

anyone's taken, you know, an 85-year-old withoutcancer or a series of patients, older patients, where the risk is, you know, accumulates overtime and seeing whether there's some common -- it's a good question. i can't really answerit. male speaker:it's a preventive doctor's dilemma -- lee j. helman:yes. male speaker:-- a patient says, well, and martha smoked all her life, and died of [unintelligible]. lee j. helman:let me just add one thing, though, because i didn't -- again, i didn't want to run outof time, and i didn't mention it. but sort

of the reverse -- not the reverse, but a similartheme is you may come across in reading, there's been a lot of discussion in oncology literature,certainly the genomics oncology literature, of what we've referred to as n-of-1 studies. so, there's been a lot of interest in youmight treat 20 patients with a new drug; let's say it's an inhibitor of mek. and one patientresponds. and that patient has a response that lasts a year. one out of 20, that drug'snot going to go forward, but somebody had an amazing response. so the question is, canyou go back to that patient by sequencing that genome and understand what's different?can you say -- with a series of these say, this predicts that if you have this particularmutation? and so people are doing that now,

and they're finding very interesting mutationsthat may suggest that. the problem then is, if it occurs in one in 20 patients, you know,it could take 15 years to prove that, in fact, that's the -- but that's an area that genomicsis letting us get to. some unusual responsive patients and trying to dissect what makesthem respond better. male speaker:has anyone looked into the 140 [unintelligible] genes and tumor suppression genes in thatsense? that there are people that have a surfeit of suppressor, or -- lee j. helman:i don't know the answer to that. male speaker:[unintelligible] it's not unusual for pathologists

to record indeterminate; they are not sure.i know there is a company -- [unintelligible], it is called, -- that does the gene expression.do you have any experience [unintelligible]? lee j. helman:well, you know, it depends on the company and it depends on the test. but if there are-- and i'm not -- male speaker:could you paraphrase, please? lee j. helman:i'm sorry, the question was, in -- when you do thyroid nodule aspirations and you getan indeterminate -- we're not sure if it's, you know, a situation we're commonly confrontedwith -- there are now companies that will do gene expression analysis. and you try touse that to sort of say whether it's likely

to be malignant or not. so, i'm not specifically aware of the thyroidcancer field, but i do know there's been a lot of genetics done there. and i suspect-- and that's one of the things we've been able to do with expression profiling. expressionprofiling is sort of one-off. you feel better if there's a ret mutation than, you know,you shouldn't see a ret mutation in a benign thyroid cancer. although there are some mutant-- some mutations that you can find in normal tissue. but i think genetics can help in thoseparticular dilemmas, as long as you know that company is reputable, that they are, you knowthey're quality-controlled, they're clea-certified. and the literature supports strongly thatthese particular constellation of genes really

are seeing -- are good biomarkers of malignantversus benign. so, i think we're getting to that. i can't answer specifically in the caseof thyroid cancer. male speaker:[unintelligible] in california, and the test is called afirma test. and it's being donenow, so i was wondering -- lee j. helman:well, you know, i can -- i'd be happy to talk to our thyroid cancer expert and ask him.i'm just -- i can't -- i'm just not in that field, so i can't specifically give him aheads up or not. thank you. [inaudible commentary] [end of transcript]