I admit that I'm a little bit nervous here because I'm going to say some radical things, about how we should think about cancer differently, to an audience that contains a lot of people who know a lot more about cancer than I do. But I will also contest that I'm not as nervous as I should be because I'm pretty sure I'm right about this. (Laughter) And that this, in fact, will be the way that we treat cancer in the future. In order to talk about cancer, I'm going to actually have to -- let me get the big slide here. First, I'm going to try to give you a different perspective of genomics. I want to put it in perspective of the bigger picture of all the other things that are going on -- and then talk about something you haven't heard so much about, which is proteomics. Having explained those, that will set up for what I think will be a different idea about how to go about treating cancer.
Moram priznati da sam malo nervozan s obzirom da planiram da predstavim večeras veoma radikalne ideje koje imaju za cilj da promene naš generalni pogled na rak ispred veoma mnogo ljudi koji znaju znatno više o raku u poređenju sa mnom. Ali moram priznati da nisam onoliko nervozan koliko bi se to očekivalo jer sam poprilično siguran da sam u pravu. (Smeh) Tvrdim da će ovo zaista biti način lečenja raka u budućnosti. Kako bih mogao da pričam sa vama o raku, moraću da vam pokažem ovaj ogroman slajd. Pre svega, želim da vam predstavim drugačiji pogled na genomiku. Želim da posmatramo genomiku iz šire perspektive, koja uključuje različita znanja do kojih dolazimo a potom želim da govorim o metodologiji o kojoj niste mnogo čuli, a to je proteomika. Mislim da ćemo, nakon objašnjenja koja će uslediti, biti spremni da govorimo o novoj i drugačijoj ideji o lečenju raka.
So let me start with genomics. It is the hot topic. It is the place where we're learning the most. This is the great frontier. But it has its limitations. And in particular, you've probably all heard the analogy that the genome is like the blueprint of your body, and if that were only true, it would be great, but it's not. It's like the parts list of your body. It doesn't say how things are connected, what causes what and so on. So if I can make an analogy, let's say that you were trying to tell the difference between a good restaurant, a healthy restaurant and a sick restaurant, and all you had was the list of ingredients that they had in their larder. So it might be that, if you went to a French restaurant and you looked through it and you found they only had margarine and they didn't have butter, you could say, "Ah, I see what's wrong with them. I can make them healthy." And there probably are special cases of that. You could certainly tell the difference between a Chinese restaurant and a French restaurant by what they had in a larder. So the list of ingredients does tell you something, and sometimes it tells you something that's wrong. If they have tons of salt, you might guess they're using too much salt, or something like that. But it's limited, because really to know if it's a healthy restaurant, you need to taste the food, you need to know what goes on in the kitchen, you need the product of all of those ingredients.
Pa, hajde da počnemo sa objašnjenjem genomike. Danas je to poprilično popularna tema. To je oblast u kojoj najviše učimo. To je tehnologija koja ima velike potencijale, ali isto tako ima i svoja ograničenja. Naročito bih naglasio da ste svi vi čuli analogiju koja govori da je vaš genom zapravo slika vašeg tela. I kada bi to bilo tačno, to bi bilo odlično, ali nije. To je nešto kao lista sastavnih delova vašeg tela. Ne govori ništa o tome kako su komponente vašeg organizma povezane, šta uzrokuje koji proces i tako dalje. Tako da bih ja želeo da napravim ovde jednu analogiju, recimo da vi želite da objasnite razliku između dobrog restorana, restorana zdrave hrane, i restorana brze hrane, i sve što imate na raspolaganju jeste lista sastojaka koji pomenuti restorani imaju u svojoj ostavi. Tako možemo zamisliti, da ukoliko ste analizirali listu sastojaka koju koristi francuski restoran i pri tome pronašli da oni koriste samo margarin i da nemaju puter u ostavi, mogli biste da kažete : "Ah, pa vidim zašto je ovde hrana loša. Mogu da im pomognem da pređu na zdrav način." I verovatno postoje izdvojeni slučajevi kao ovaj. Mogli biste da uočite razliku između kineskog i francuskog restorana na osnovu liste sastojaka koje možete naći u njihovoj ostavi. Tako da vam definitivno lista sastojaka nešto govori, i ponekada možete na osnovu iste zaključiti šta je loše. Ukoliko ste pronašli velike količine soli, možete pretpostaviti da oni koriste previše soli ili nešto slično. Ali te informacije imaju limitirani kapacitet, jer da biste znali da li je to restoran zdrave hrane, morate probati hranu, morate znati šta se dešava u kuhinji, neophodan vam je kranji produkt koji nastaje sjedinjavanjem tih sastojaka.
So if I look at a person and I look at a person's genome, it's the same thing. The part of the genome that we can read is the list of ingredients. And so indeed, there are times when we can find ingredients that [are] bad. Cystic fibrosis is an example of a disease where you just have a bad ingredient and you have a disease, and we can actually make a direct correspondence between the ingredient and the disease. But most things, you really have to know what's going on in the kitchen, because, mostly, sick people used to be healthy people -- they have the same genome. So the genome really tells you much more about predisposition. So what you can tell is you can tell the difference between an Asian person and a European person by looking at their ingredients list. But you really for the most part can't tell the difference between a healthy person and a sick person -- except in some of these special cases.
Tako da ukoliko ja pogledam jednu osobu i analiziram genom te osobe, to je apsolutno ista stvar. Deo genoma koji mi možemo dešifrovati je ništa drugo do lista sastojaka. I naravno, ponekada možemo naći sastojke koji su loši. Cistična fibroza jeste odličan primer bolesti tog tipa gde imate loš sastojak i imate bolest i mi u ovom slučaju možemo napraviti direktnu vezu između "sastojka" i bolesti. Ali u većini slučajeva, vi morate znati šta se dešava u kuhinji, s obzirom da su bolesni ljudi najčešće bili pre toga zdravi - što znači da imaju isti genom. Tako da vam genom moze reći mnogo više o određenim predispozicijama. Ono sto vi možete prepoznati jeste razlika između Azijata i Evropljana na osnovu analize njihove liste sastojaka. Ali u realnosti vi najčešće ne možete uočiti razliku između zdrave i bolesne osobe sem u specifičnim slučajevima.
So why all the big deal about genetics? Well first of all, it's because we can read it, which is fantastic. It is very useful in certain circumstances. It's also the great theoretical triumph of biology. It's the one theory that the biologists ever really got right. It's fundamental to Darwin and Mendel and so on. And so it's the one thing where they predicted a theoretical construct. So Mendel had this idea of a gene as an abstract thing, and Darwin built a whole theory that depended on them existing, and then Watson and Crick actually looked and found one. So this happens in physics all the time. You predict a black hole, and you look out the telescope and there it is, just like you said. But it rarely happens in biology. So this great triumph -- it's so good, there's almost a religious experience in biology. And Darwinian evolution is really the core theory.
Usled čega se pravi onda velika pompa oko genetike? Pa, pre svega, mi genom možemo da "pročitamo", što je fantastično. U određenim situacijama to je veoma korisno. Takođe, predstavlja neverovatan teoretski uspeh biologije. To je jedina teorija oko koje su biolozi ikada bili u pravi. To je fundamentalna osnova Darvinove teorije kao i Mendelove teorije nasleđivanja. To je otkriće kojim su biolozi u mogućnosti da predivide teorijski konstrukt. Mendel je imao ideju o genima u apstraktnom smislu. I Darvin je uspostavio čitavu teoriju koja u potpunosti zavisi od postojanja gena. I kada su Vatson i Krik proučavali nasledne jedinice, napokon su ih i pronašli. Ovo se dešava u fizici sve vreme. Vi predvidite postojanje crne rupe, pogledate kroz teleskop i pronađete je, baš kao što ste i rekli. Ali to se retko dešava u biologiji. Tako da je ovaj fantastičan trijumf - toliko fascinirajući - da je to skoro religiozno iskustvo u biologiji. I Darvinova teorije evolucije jeste zaista centralna teorija.
So the other reason it's been very popular is because we can measure it, it's digital. And in fact, thanks to Kary Mullis, you can basically measure your genome in your kitchen with a few extra ingredients. So for instance, by measuring the genome, we've learned a lot about how we're related to other kinds of animals by the closeness of our genome, or how we're related to each other -- the family tree, or the tree of life. There's a huge amount of information about the genetics just by comparing the genetic similarity. Now of course, in medical application, that is very useful because it's the same kind of information that the doctor gets from your family medical history -- except probably, your genome knows much more about your medical history than you do. And so by reading the genome, we can find out much more about your family than you probably know. And so we can discover things that probably you could have found by looking at enough of your relatives, but they may be surprising. I did the 23andMe thing and was very surprised to discover that I am fat and bald. (Laughter) But sometimes you can learn much more useful things about that.
I drugi razlog popularnosti genetike jeste činjenica da je digitalna, genom možete da izmerite. I u stvari, zahvaljujući Kariju Malisu, vi možete izmeriti svoj genom u kuhinji uz pomoć nekoliko ekstra sastojaka. Na primer, odgonetajući genom, naučili smo koliko smo srodni sa ostalim životinjskim vrstama na osnovu sličnosti naših genoma, ili kako smo međusobno povezani - porodično stablo, ili stablo života. Možemo doći do mnogo informacija o genetici na osnovu jednostavnog poređenja genetičkih sličnosti. Naravno i primena ovih znanja u medicini, je jako korisna s obzirom da je to isti tip informacije koji doktor dobija analizirajući istoriju bolesti vaše famlije, sa tom razlikom da najverovatnije vaš genom zna mnogo više o vašoj istoriji bolesti od vas samih. Tako da dešifrujući genom, možemo da saznamo mnogo više o vašoj porodici nego što vi sami znate. Tako da možemo da otkrijemo činjenice do kojih biste i vi sami mogli doći ukoliko biste ispitali dovoljno vaših rođaka, ali te činjenice mogu da budu iznenađujuće. Ja sam uradio "23 i ja" test i bio sam veoma iznenađen kad sam otkrio da sam debeo i ćelav. (Smeh) Ali ponekada možete saznati mnogo korisnije informacije o tome.
But mostly what you need to know, to find out if you're sick, is not your predispositions, but it's actually what's going on in your body right now. So to do that, what you really need to do, you need to look at the things that the genes are producing and what's happening after the genetics, and that's what proteomics is about. Just like genome mixes the study of all the genes, proteomics is the study of all the proteins. And the proteins are all of the little things in your body that are signaling between the cells -- actually, the machines that are operating -- that's where the action is. Basically, a human body is a conversation going on, both within the cells and between the cells, and they're telling each other to grow and to die, and when you're sick, something's gone wrong with that conversation. And so the trick is -- unfortunately, we don't have an easy way to measure these like we can measure the genome.
Ali najčešće ono što je vama potrebno da znate da li ste bolesni nisu vaše predispozicije, nego ono što se zaista događa u datom trenutku u vašem telu. A da biste to uradili, ono što je zaista neophodno da uradite jeste da sagledate produkte kodirane vašim genima i šta se dešava nizvodno od nivoa genetike. To je ono što definiše proteomiku. Baš kao što genomika ispituje sve gene, proteomika se bavi izučavanjem svih proteina jednog organizma. A proteini su "radilice" vašeg organizma koje prenose informacije između ćelija u principu mašine koje odrađuju sve funkcije organizma. Proteini su nosioci radnih delatnosti. U principu, ljudsko telo jeste komunikacija, razgovor na globalnom nivou, i to na oba nivoa, i u ćeliji i između ćelija, i oni saopštavaju jedni drugima da rastu i da umiru. A kada ste bolesni, to znači da je došlo do greške u tom razgovoru. Tako da je trik u tome da - na nesreću, nemamo odgovarajući način da izučavamo proteine kao što možemo da izučavamo genom.
So the problem is that measuring -- if you try to measure all the proteins, it's a very elaborate process. It requires hundreds of steps, and it takes a long, long time. And it matters how much of the protein it is. It could be very significant that a protein changed by 10 percent, so it's not a nice digital thing like DNA. And basically our problem is somebody's in the middle of this very long stage, they pause for just a moment, and they leave something in an enzyme for a second, and all of a sudden all the measurements from then on don't work. And so then people get very inconsistent results when they do it this way. People have tried very hard to do this. I tried this a couple of times and looked at this problem and gave up on it.
Dakle, problem je u tom merenju - ukoliko probate da izmerite sve proteine, to je veoma zahtevna procedura. To zahteva stotine pojedinačnih koraka, i zahteva mnogo, mnogo vremena. I važno je koliko je proteina prisutno. Može biti veoma značajno da je 10% proteina promenjeno, tako da ovde ne pričamo o finom, digitalnom fenomenu kao što je DNK. Naš je problem da neko u samoj sredini ovog veoma dugog procesa, pauzira za samo jedan trenutak, i ostavi nešto u enzimu na samo sekund, i odjednom, od tog momenta sva merenja koja slede ne funkcionišu. I usled toga ljudi dobijaju veoma nekonzistentne rezultate kada pokušaju da rade na opisani način. Ljudi su uložili puno truda kako bi uspeli da urade ovo. Ja sam probao nekoliko puta skoncentrisao se na problem i odustao od istog.
I kept getting this call from this oncologist named David Agus. And Applied Minds gets a lot of calls from people who want help with their problems, and I didn't think this was a very likely one to call back, so I kept on giving him to the delay list. And then one day, I get a call from John Doerr, Bill Berkman and Al Gore on the same day saying return David Agus's phone call. (Laughter) So I was like, "Okay. This guy's at least resourceful." (Laughter) So we started talking, and he said, "I really need a better way to measure proteins." I'm like, "Looked at that. Been there. Not going to be easy." He's like, "No, no. I really need it. I mean, I see patients dying every day because we don't know what's going on inside of them. We have to have a window into this." And he took me through specific examples of when he really needed it. And I realized, wow, this would really make a big difference, if we could do it, and so I said, "Well, let's look at it."
Ali me je jedan onkolog zvao telefonom non-stop po imenu Dejvid Agus. I mnogi ljudi zovu "Primenjene Umove", ljudi koji žele pomoć u rešavanju svojih problema, i nisam mislio da ima mogućnosti de će ovaj zvati ponovo, i tako je razgovor sa njim bio non-stop na listi čekanja. I potom jednog dana, pozvaše mene Džon Doer, Bil Berkman i Al Gor istoga dana da mi kažu da pozovem Dejvid Agusa. (Smeh) I ja pomislih: "Okej, ovaj tip barem ima puno kontakata." (smeh) Tako mi počesmo da razgovaramo, i on mi reče: "Zaista mi je neophodan bolji način da analiziram proteine." Ja rekoh, "Već sam razmišljao o tome. Išao sam tim stopama. Ovo neće biti lako." On reče: "Ali ne, ne. Meni je to zaista neophodno. Ja gledam pacijente kako umiru svakoga dana samo zato što mi ne razumemo šta se dešava u njihovim telima. Moramo napraviti prozor koji će omogućiti da to sagledamo." Onda mi je izneo specifične primere situacija u kojima su mu te nove metode apsolutno neophodne. I ja shvatih da ovo zaista može da napravi ogromnu razliku, ukoliko bismo mogli to da odradimo. rekao sam, "Pa, hajde da pokušamo."
Applied Minds has enough play money that we can go and just work on something without getting anybody's funding or permission or anything. So we started playing around with this. And as we did it, we realized this was the basic problem -- that taking the sip of coffee -- that there were humans doing this complicated process and that what really needed to be done was to automate this process like an assembly line and build robots that would measure proteomics. And so we did that, and working with David, we made a little company called Applied Proteomics eventually, which makes this robotic assembly line, which, in a very consistent way, measures the protein. And I'll show you what that protein measurement looks like.
"Primenjeni Umovi" imaju zaista dovoljno para u igri da možemo jednostavno da radimo na problemu bez traženja novih sredstava i specijalnih dozvola ili bilo čega. Tako da smo počeli da se zanimamo ovim. I dok smo se bavili time, shvatili smo da je to osnovni problem - upravo taj srk kafe činjenica da su ljudi izvršavali ovu komplikovanu proceduru i da je zaista bilo neophodno automatizovati proces kao pokretnu traku i napraviti robote koji bi analizirali proteomiku. I tako smo to i uradili. Dok sam radio sa Dejvidom, osnovali smo malu kompaniju koju smo nazvali "Primenjena Proteomika", koja prozivodi robotizovanu pokretnu traku, koja, na veoma konzsistentan način, analizira proteine. I sada ću vam pokazati kako to merenje proteina izgleda.
Basically, what we do is we take a drop of blood out of a patient, and we sort out the proteins in the drop of blood according to how much they weigh, how slippery they are, and we arrange them in an image. And so we can look at literally hundreds of thousands of features at once out of that drop of blood. And we can take a different one tomorrow, and you will see your proteins tomorrow will be different -- they'll be different after you eat or after you sleep. They really tell us what's going on there. And so this picture, which looks like a big smudge to you, is actually the thing that got me really thrilled about this and made me feel like we were on the right track. So if I zoom into that picture, I can just show you what it means. We sort out the proteins -- from left to right is the weight of the fragments that we're getting, and from top to bottom is how slippery they are. So we're zooming in here just to show you a little bit of it. And so each of these lines represents some signal that we're getting out of a piece of a protein. And you can see how the lines occur in these little groups of bump, bump, bump, bump, bump. And that's because we're measuring the weight so precisely that -- carbon comes in different isotopes, so if it has an extra neutron on it, we actually measure it as a different chemical. So we're actually measuring each isotope as a different one.
U principu, ono što mi radimo je da uzmemo kap krvi iz pacijenta i izolujemo proteine u toj kapi krvi na osnovu onoga koliko su ti proteini teški i koliko su pokretljivi, i poređamo ih u sveobuhvatnu sliku. Tako da nam to omogućava da bukvalno analiziramo stotine hiljada karaktersitika u jednom datom momentu iz samo jedne kapi krvi. Sledećeg dana možemo uzeti novu kap i videćete da će vaši proteini sledećeg dana biti drugačiji - drugačiji u zavisnosti od toga da li ste upravo jeli ili se probudili. Govore nam o procesima koji se dešavaju u telu čoveka. Tako da ovde prikazana slika, koja vama izgleda kao ogromna mrlja, je u principu otkriće koje je mene jako uzbudilo i zbog kojeg sam pomislio da smo na pravom putu. Ukoliko ja uveličam ovu sliku, mogu vam pokazati šta to zaista znači. Mi grupišemo proteine: s leva na desno na osnovu težine fragmenata koje analiziramo. A od vrha na dole, na osnovu njihove pokretljivosti. Sad ćemo uveličati kako bih vam pokazao mali deo. Svaka od ovih linija predstavlja u principu neku vrstu signala koju mi dobijamo od dela proteina. I isto tako možete primetiti patern linija - to su male grupe sastavljene od blagih krivina, krivina, krivina, krivina. To se dešava zato što merimo težinu toliko precizno da - s obzriom da ugljenik ima različite izotope, ukoliko ima jedan dodatni neutron, mi u principu učitavamo to kao drugačiju supstancu. Tako da mi beležimo svaki izotop kao drugačiji.
And so that gives you an idea of how exquisitely sensitive this is. So seeing this picture is sort of like getting to be Galileo and looking at the stars and looking through the telescope for the first time, and suddenly you say, "Wow, it's way more complicated than we thought it was." But we can see that stuff out there and actually see features of it. So this is the signature out of which we're trying to get patterns. So what we do with this is, for example, we can look at two patients, one that responded to a drug and one that didn't respond to a drug, and ask, "What's going on differently inside of them?" And so we can make these measurements precisely enough that we can overlay two patients and look at the differences.
Na osnovu ovoga možete razumeti koliko je fantastično osetljiv opisani sistem. Gledanje ove slike je slično kao kada bismo bili Galilej i gledali u zvezde kroz teleskop po prvi put i iznenada rekli, "Opa, mnogo je komplikovanije nego što smo mislili." Ali mi sada možemo da sagledamo taj mali univerzum i uočimo njegove karakteristike. Ovo je skup podataka iz kojih pokušavamo da izvučemo obrasce. Ono što mi radimo sa informacijama ovog tipa je da, na primer možemo analizirati dva pacijenta, jednog koji je reagovao na lek i drugog koji nije, i postaviti pitanje, "Koji je proces koji je drugačiji u organizmima ovih ljudi?" Takođe možemo da odradimo ta merenja dovoljno precizno da možemo da uporedimo dva pacijenta i uočimo razlike.
So here we have Alice in green and Bob in red. We overlay them. This is actual data. And you can see, mostly it overlaps and it's yellow, but there's some things that just Alice has and some things that just Bob has. And if we find a pattern of things of the responders to the drug, we see that in the blood, they have the condition that allows them to respond to this drug. We might not even know what this protein is, but we can see it's a marker for the response to the disease. So this already, I think, is tremendously useful in all kinds of medicine. But I think this is actually just the beginning of how we're going to treat cancer. So let me move to cancer.
Ovde možete videti Alis u zelenom kodu i Boba predstavljenog crvenim kodom. Poredimo njihove podatke. Ovo su pravi rezulati. Postoji puno sličnosti i obeležene su žutom bojom ali postoje određeni proteini koje ima samo Alis i određeni proteini koje ima samo Bob. I ukoliko pronađemo šablon koji opisuje grupu ljudi na koje postojeći lek ispoljava željeni efekat, mi vidimo to u krvi, oni imaju uslove koji im omogućuju da uspešno odreaguju na tretman. Mi možda čak ni ne znamo koji je to protein, ali znamo da taj protein jeste marker, koji govori da će određeni tretman biti uspešan. Već ovo saznanje, po mom mišljenju, jeste od neopisive koristi za različite grane medicine. Ali ja isto tako mislim da je ovo tek početak razvijanja procedura kojima ćemo se boriti protiv raka. A sada bih da pričam malo više o raku.
The thing about cancer -- when I got into this, I really knew nothing about it, but working with David Agus, I started watching how cancer was actually being treated and went to operations where it was being cut out. And as I looked at it, to me it didn't make sense how we were approaching cancer, and in order to make sense of it, I had to learn where did this come from. We're treating cancer almost like it's an infectious disease. We're treating it as something that got inside of you that we have to kill. So this is the great paradigm. This is another case where a theoretical paradigm in biology really worked -- was the germ theory of disease. So what doctors are mostly trained to do is diagnose -- that is, put you into a category and apply a scientifically proven treatment for that diagnosis -- and that works great for infectious diseases. So if we put you in the category of you've got syphilis, we can give you penicillin. We know that that works. If you've got malaria, we give you quinine or some derivative of it. And so that's the basic thing doctors are trained to do, and it's miraculous in the case of infectious disease -- how well it works. And many people in this audience probably wouldn't be alive if doctors didn't do this.
Zanimljiva činjenica o kanceru je ta da kada sam ja počeo da se bavim ovim zaista nisam znao ništa o raku, ali radeći rame uz rame sa Dejvidom Agusom počeo sam da razumevam kako mi danas lečimo rak i odlazio sam na operacije koje su imale za cilj otklanjanje raka. I kada sam sagledao tu proceduru, to meni i nije baš imalo puno smisla, takav pristup lečenju raka. I kako bih razumeo proces lečenja, morao sam naučiti kako smo došli do današnjih tretmana. Borimo se protiv raka na način na koji se borimo protiv infektivnih bolesti. Tretiramo ih kao nešto što vas je inficiralo i što moramo da ubijemo. To je velika paradigma. Ovo je drugi primer u biologiji gde se teorijskom paradigmom zaista došlo do rezultata, a to je "patogen - teorija bolesti". Doktori su u najvećem broju slučajeva obučeni da uspostave dijagnozu - - što znači da vas oni svrstavaju u određenu kategoriju i onda primene naučno odobreni tretman protiv bolesti za koju su postavili dijagnozu. To je odličan pristup u lečenju infektivnih bolesti. Tako da ukoliko je ustanovljeno da bolujete od sifilisa, možemo vas lečiti penicilinom. Mi znamo da je to uspešan način. Ukoliko bolujete od malarije, prepisaćemo vam kinin ili neki od derivata kinina. To je u principu osnovna stvar za koju su doktori obučeni. Tako da je zapravo čudesno kako u slučajevima infektivnih bolesti - ovi tretmani ekeftivno rešavaju probleme. Mnogi ljudi u ovoj publici najverovatnije ne bi bili živi da lekari ne rade ovo.
But now let's apply that to systems diseases like cancer. The problem is that, in cancer, there isn't something else that's inside of you. It's you; you're broken. That conversation inside of you got mixed up in some way. So how do we diagnose that conversation? Well, right now what we do is we divide it by part of the body -- you know, where did it appear? -- and we put you in different categories according to the part of the body. And then we do a clinical trial for a drug for lung cancer and one for prostate cancer and one for breast cancer, and we treat these as if they're separate diseases and that this way of dividing them had something to do with what actually went wrong. And of course, it really doesn't have that much to do with what went wrong because cancer is a failure of the system. And in fact, I think we're even wrong when we talk about cancer as a thing. I think this is the big mistake. I think cancer should not be a noun. We should talk about cancering as something we do, not something we have. And so those tumors, those are symptoms of cancer. And so your body is probably cancering all the time, but there are lots of systems in your body that keep it under control.
Hajde da pokušamo da primenimo ovaj princip na sistemski tip bolesti kao što je rak. Problem je što u slučaju raka ne postoji strano telo koje treba ubiti, koje je ušlo u vaš organizam. To ste vi, vaše ćelije su nefunkcionalne. Komunikacija koja postoji na sistemskom nivou u vašem telu je postala pometena na neki način. Kako možemo da dijagnostikujemo problem u komunikaciji? U ovom trenutku grupišemo rak prema različitm delovima tela - znate, gde se pojavio - i stavimo vas u različite kategorije na osnovu dela vašeg tela. I onda sprovedemo klinička istraživanja za lek koji pokazuje efekat na rak pluća i za lek koji deluje na rak prostate, rak dojke, i lečimo ove slučajeve kao da su različite bolesti kao da ovaj način na koji grupišemo pod-tipove raka ima ikakve veze sa onim što nije u redu. I naravno, to nema baš puno veze sa tim šta je pošlo naopako. Jer rak je malfunkcionisanje sistema. U principu, ja mislim da je potpuno pogrešno pričati o raku kao o predmetu, stvari. Ja mislim da je to velika greška. Ja mislim da rak ne bi trebalo da bude imenica. Mi treba da pričamo o ovoj bolesti kao o "rakovanju" nečemu što mi sami radimo, a ne nečemu što imamo. Različiti tumori su simptomi raka. Tako da vaše telo verovatno "rakuje" sve vreme. Ali postoji puno sistema u vašem telu koji taj proces drže pod kontrolom.
And so to give you an idea of an analogy of what I mean by thinking of cancering as a verb, imagine we didn't know anything about plumbing, and the way that we talked about it, we'd come home and we'd find a leak in our kitchen and we'd say, "Oh, my house has water." We might divide it -- the plumber would say, "Well, where's the water?" "Well, it's in the kitchen." "Oh, you must have kitchen water." That's kind of the level at which it is. "Kitchen water, well, first of all, we'll go in there and we'll mop out a lot of it. And then we know that if we sprinkle Drano around the kitchen, that helps. Whereas living room water, it's better to do tar on the roof." And it sounds silly, but that's basically what we do. And I'm not saying you shouldn't mop up your water if you have cancer, but I'm saying that's not really the problem; that's the symptom of the problem.
Da bih vam dao ideju analogije na koju konkretno mislim kada govorim "rakovati" u vidu glagola, zamislite da ne znamo ništa o vodoinstalaterstvu, tako da bismo pričali o tome na sledeći način, došli bismo kući i uočili da je u kuhinji procurela voda i rekli bismo, "Oh, u mojoj kući ima vode." Vodoinstalater bi rekao, "Pa, gde je ta voda u kući?" "Pa, u kuhinji." "Oh, pa vi onda imate kuhinjsku vodu." To je plastični primer nivoa našeg sagledavanja stvari. "Kuhinjska voda? Pa, pre svega, mi ćemo obrisati dosta vode. Isto tako znamo da ukoliko koristimo "Mr. Musculo" u kuhinji, to će sigurno pomoći. Dok u slučaju vode u dnevnoj sobi bolje rešenje je da popravimo krov." Znam da zvuči ludo, ali u principu to je ono što danas radimo. Ne kažem da ne treba da izbacite vodu ukoliko imate rak. Ali želim da poručim da to nije uzrok problema; to je samo simptom problema.
What we really need to get at is the process that's going on, and that's happening at the level of the proteonomic actions, happening at the level of why is your body not healing itself in the way that it normally does? Because normally, your body is dealing with this problem all the time. So your house is dealing with leaks all the time, but it's fixing them. It's draining them out and so on. So what we need is to have a causative model of what's actually going on, and proteomics actually gives us the ability to build a model like that.
Mi zaista treba da tretiramo proces koji se dešava, a taj proces se dešava na nivou proteina i njihove komunikacije, pitanje je zašto vaše telo ne štiti sebe na način na koji se to normalno dešava? Vaše telo se suočava sa problemima ovog tipa svakog dana. Vaša kuća se bori protiv prokišnjavanja sve vreme. Ali se i odupire prokišnjavanju. Isušuje vodu. Tako da je nama neophodan sada uzročni model onoga što se zaista dešava. Proteomika nam pruža mogućnost da napokon izgradimo takav model.
David got me invited to give a talk at National Cancer Institute and Anna Barker was there. And so I gave this talk and said, "Why don't you guys do this?" And Anna said, "Because nobody within cancer would look at it this way. But what we're going to do, is we're going to create a program for people outside the field of cancer to get together with doctors who really know about cancer and work out different programs of research." So David and I applied to this program and created a consortium at USC where we've got some of the best oncologists in the world and some of the best biologists in the world, from Cold Spring Harbor, Stanford, Austin -- I won't even go through and name all the places -- to have a research project that will last for five years where we're really going to try to build a model of cancer like this. We're doing it in mice first, and we will kill a lot of mice in the process of doing this, but they will die for a good cause. And we will actually try to get to the point where we have a predictive model where we can understand, when cancer happens, what's actually happening in there and which treatment will treat that cancer.
Dejvid me je pozvao da održim govor na Nacionalnom Institutu Izučavanja Raka i Ana Barker je bila tamo. Tako sam održao taj govor i rekao, "Zašto vi ne biste uradili ovo?" I Ana reče, "Zato što niko ko se bavi problemom raka ne bi gledao na problem raka na ovaj način. Ali mi ćemo svakako uspostaviti program koji će okupiti ljude koji se ne bave rakom i povezaćemo te stručanjake sa medicinarima koji znaju puno o raku i na taj način ćemo smisliti drugačiji program istraživanja." Tako smo Dejvid i ja konkurisali za pomenuti program i stvorili konzorcijum na Univerzitetu Južne Kalifornije gde smo okupili neke od najboljih onkologa sveta i neke od najboljih biologa sveta iz Kold Spring Harbora Stanforda, Ostina... Ne mogu sada navesti imena svih instituticija - kako bismo odradili naučno-istraživački projekat koji će trajati pet godina sa krajnjim ciljem postavljanja modela kancera po opisanim principima. Radićemo ova istraživanja prvo na miševima. Puno ce miševa stradati u toku razvijanja ovih eksperimenata ali će oni umreti za opšte dobro. Mi ćemo u principu pokušati da dođemo do momenta kada imamo uspostavljeni uzročni model na osnovu kog možemo da razumemo, kada se rak desi, šta se u osnovi dešava u organizmu i koji specifičan tretman će biti efektan u lečenju.
So let me just end with giving you a little picture of what I think cancer treatment will be like in the future. So I think eventually, once we have one of these models for people, which we'll get eventually -- I mean, our group won't get all the way there -- but eventually we'll have a very good computer model -- sort of like a global climate model for weather. It has lots of different information about what's the process going on in this proteomic conversation on many different scales. And so we will simulate in that model for your particular cancer -- and this also will be for ALS, or any kind of system neurodegenerative diseases, things like that -- we will simulate specifically you, not just a generic person, but what's actually going on inside you.
I za sam kraj bih vam pokazao mali shematski prikaz kako ja zamišljam da tretman protiv raka izgleda u budućnosti. Ja mislim da na kraju, kada budemo imali ovakav model za ljude, koji ćemo svakako na kraju imati - naša istraživačka grupa neće sama doći do cilja ali ćemo na kraju imati veoma dobar kompjuterski model - nešto kao globalni model vremenske prognoze. Model će imati puno različitih informacija o procesima koji se dešavaju u toku komunikacije u proteomu na različitim nivoima. Na taj način mi ćemo simulirati tim modelom specifičan rak od kojeg osoba boluje i taj model će imati primenu i za amiotrofičnu lateralnu sklerozu (ALS) ili bilo koju sistemsku neurodegenerativnu bolest, bolesti kao te mi ćemo simulirati Vas posebno, ne neku generičku osobu, nego baš same procese koji se odvijaju unutar vašeg tela.
And in that simulation, what we could do is design for you specifically a sequence of treatments, and it might be very gentle treatments, very small amounts of drugs. It might be things like, don't eat that day, or give them a little chemotherapy, maybe a little radiation. Of course, we'll do surgery sometimes and so on. But design a program of treatments specifically for you and help your body guide back to health -- guide your body back to health. Because your body will do most of the work of fixing it if we just sort of prop it up in the ways that are wrong. We put it in the equivalent of splints. And so your body basically has lots and lots of mechanisms for fixing cancer, and we just have to prop those up in the right way and get them to do the job.
I ono što možemo da uradimo u takvoj simulaciji jeste da specifično dizajniramo za Vas kombinaciju tretmana, koji mogu biti veoma blagi, veoma male doze lekova. To mogu biti saveti tipa: nemojte jesti ovog dana, ili primenićemo malu dozu hemoterapije, možda malo zračenja. Naravno, ponekad ćemo odraditi operativni zahvat. Ali ćemo dizajnirati poseban program tretmana samo za vas i pomoći vašem telu da se oporavi - tako ćemo usmeravati vaše telo ka zdravom stanju. Jer će vaše telo odraditi najveći deo posla da reši problem ukoliko mu mi samo pomognemo u tome. To bi bio ekvivalent metalnim udlagama. Vaš organizam ima veoma puno mehanizama koji se mogu uspešno boriti protiv raka i mi samo treba da stimulišemo te mehanizme na pravi način i pokrenemo ih da ponovo počnu da rade svoj posao.
And so I believe that this will be the way that cancer will be treated in the future. It's going to require a lot of work, a lot of research. There will be many teams like our team that work on this. But I think eventually, we will design for everybody a custom treatment for cancer.
Ja sam duboko ubeđen da će ovo biti način na koji ćemo lečiti rak u budućnosti. To će zahtevati mnogo, mnogo rada, mnogo istraživanja. Biće mnogo timova koji kao i naš tim pokušavaju da razumeju pomenuti fenomen. Ali ja mislim da ćemo u budućnosti biti u mogućnosti da dizajniramo specifičan tretman protiv raka za svaki pojedinačni slučaj.
So thank you very much.
Na kraju, mnogo vam hvala.
(Applause)
(Aplauz)