Danny Hillis: Understanding cancer through proteomics

57,327 views ・ 2011-03-16

TED


Please double-click on the English subtitles below to play the video.

Prevodilac: Jelena Nedjic Lektor: Ivana Korom
00:15
I admit that I'm a little bit nervous here
0
15330
3000
Moram priznati da sam malo nervozan s obzirom
00:18
because I'm going to say some radical things,
1
18330
3000
da planiram da predstavim večeras veoma radikalne ideje
00:21
about how we should think about cancer differently,
2
21330
3000
koje imaju za cilj da promene naš generalni pogled na rak
00:24
to an audience that contains a lot of people
3
24330
2000
ispred veoma mnogo ljudi
00:26
who know a lot more about cancer than I do.
4
26330
3000
koji znaju znatno više o raku u poređenju sa mnom.
00:30
But I will also contest that I'm not as nervous as I should be
5
30330
3000
Ali moram priznati da nisam onoliko nervozan koliko bi se to očekivalo
00:33
because I'm pretty sure I'm right about this.
6
33330
2000
jer sam poprilično siguran da sam u pravu.
00:35
(Laughter)
7
35330
2000
(Smeh)
00:37
And that this, in fact, will be
8
37330
2000
Tvrdim da će ovo zaista biti
00:39
the way that we treat cancer in the future.
9
39330
3000
način lečenja raka u budućnosti.
00:43
In order to talk about cancer,
10
43330
2000
Kako bih mogao da pričam sa vama o raku,
00:45
I'm going to actually have to --
11
45330
3000
moraću da vam pokažem
00:48
let me get the big slide here.
12
48330
3000
ovaj ogroman slajd.
00:53
First, I'm going to try to give you a different perspective of genomics.
13
53330
3000
Pre svega, želim da vam predstavim drugačiji pogled na genomiku.
00:56
I want to put it in perspective of the bigger picture
14
56330
2000
Želim da posmatramo genomiku iz šire perspektive,
00:58
of all the other things that are going on --
15
58330
3000
koja uključuje različita znanja do kojih dolazimo
01:01
and then talk about something you haven't heard so much about, which is proteomics.
16
61330
3000
a potom želim da govorim o metodologiji o kojoj niste mnogo čuli, a to je proteomika.
01:04
Having explained those,
17
64330
2000
Mislim da ćemo, nakon objašnjenja koja će uslediti,
01:06
that will set up for what I think will be a different idea
18
66330
3000
biti spremni da govorimo o novoj i drugačijoj ideji
01:09
about how to go about treating cancer.
19
69330
2000
o lečenju raka.
01:11
So let me start with genomics.
20
71330
2000
Pa, hajde da počnemo sa objašnjenjem genomike.
01:13
It is the hot topic.
21
73330
2000
Danas je to poprilično popularna tema.
01:15
It is the place where we're learning the most.
22
75330
2000
To je oblast u kojoj najviše učimo.
01:17
This is the great frontier.
23
77330
2000
To je tehnologija koja ima velike potencijale,
01:19
But it has its limitations.
24
79330
3000
ali isto tako ima i svoja ograničenja.
01:22
And in particular, you've probably all heard the analogy
25
82330
3000
Naročito bih naglasio da ste svi vi čuli analogiju
01:25
that the genome is like the blueprint of your body,
26
85330
3000
koja govori da je vaš genom zapravo slika vašeg tela.
01:28
and if that were only true, it would be great,
27
88330
2000
I kada bi to bilo tačno, to bi bilo odlično,
01:30
but it's not.
28
90330
2000
ali nije. To je nešto
01:32
It's like the parts list of your body.
29
92330
2000
kao lista sastavnih delova vašeg tela.
01:34
It doesn't say how things are connected,
30
94330
2000
Ne govori ništa o tome kako su komponente vašeg organizma
01:36
what causes what and so on.
31
96330
3000
povezane, šta uzrokuje koji proces i tako dalje.
01:39
So if I can make an analogy,
32
99330
2000
Tako da bih ja želeo da napravim ovde jednu analogiju,
01:41
let's say that you were trying to tell the difference
33
101330
2000
recimo da vi želite da objasnite razliku
01:43
between a good restaurant, a healthy restaurant
34
103330
3000
između dobrog restorana, restorana zdrave hrane,
01:46
and a sick restaurant,
35
106330
2000
i restorana brze hrane,
01:48
and all you had was the list of ingredients
36
108330
2000
i sve što imate na raspolaganju jeste lista sastojaka
01:50
that they had in their larder.
37
110330
3000
koji pomenuti restorani imaju u svojoj ostavi.
01:53
So it might be that, if you went to a French restaurant
38
113330
3000
Tako možemo zamisliti, da ukoliko ste analizirali listu
01:56
and you looked through it and you found
39
116330
2000
sastojaka koju koristi francuski restoran i pri tome pronašli
01:58
they only had margarine and they didn't have butter,
40
118330
2000
da oni koriste samo margarin i da nemaju puter u ostavi,
02:00
you could say, "Ah, I see what's wrong with them.
41
120330
2000
mogli biste da kažete : "Ah, pa vidim zašto je ovde hrana loša.
02:02
I can make them healthy."
42
122330
2000
Mogu da im pomognem da pređu na zdrav način."
02:04
And there probably are special cases of that.
43
124330
2000
I verovatno postoje izdvojeni slučajevi kao ovaj.
02:06
You could certainly tell the difference
44
126330
2000
Mogli biste da uočite razliku
02:08
between a Chinese restaurant and a French restaurant
45
128330
2000
između kineskog i francuskog restorana
02:10
by what they had in a larder.
46
130330
2000
na osnovu liste sastojaka koje možete naći u njihovoj ostavi.
02:12
So the list of ingredients does tell you something,
47
132330
3000
Tako da vam definitivno lista sastojaka nešto govori,
02:15
and sometimes it tells you something that's wrong.
48
135330
3000
i ponekada možete na osnovu iste zaključiti šta je loše.
02:19
If they have tons of salt,
49
139330
2000
Ukoliko ste pronašli velike količine soli,
02:21
you might guess they're using too much salt, or something like that.
50
141330
3000
možete pretpostaviti da oni koriste previše soli ili nešto slično.
02:24
But it's limited,
51
144330
2000
Ali te informacije imaju limitirani kapacitet,
02:26
because really to know if it's a healthy restaurant,
52
146330
2000
jer da biste znali da li je to restoran zdrave hrane,
02:28
you need to taste the food, you need to know what goes on in the kitchen,
53
148330
3000
morate probati hranu, morate znati šta se dešava u kuhinji,
02:31
you need the product of all of those ingredients.
54
151330
3000
neophodan vam je kranji produkt koji nastaje sjedinjavanjem tih sastojaka.
02:34
So if I look at a person
55
154330
2000
Tako da ukoliko ja pogledam jednu osobu
02:36
and I look at a person's genome, it's the same thing.
56
156330
3000
i analiziram genom te osobe, to je apsolutno ista stvar.
02:39
The part of the genome that we can read
57
159330
2000
Deo genoma koji mi možemo dešifrovati
02:41
is the list of ingredients.
58
161330
2000
je ništa drugo do lista sastojaka.
02:43
And so indeed,
59
163330
2000
I naravno,
02:45
there are times when we can find ingredients
60
165330
2000
ponekada možemo naći sastojke
02:47
that [are] bad.
61
167330
2000
koji su loši.
02:49
Cystic fibrosis is an example of a disease
62
169330
2000
Cistična fibroza jeste odličan primer bolesti tog tipa
02:51
where you just have a bad ingredient and you have a disease,
63
171330
3000
gde imate loš sastojak i imate bolest
02:54
and we can actually make a direct correspondence
64
174330
3000
i mi u ovom slučaju možemo napraviti direktnu vezu
02:57
between the ingredient and the disease.
65
177330
3000
između "sastojka" i bolesti.
03:00
But most things, you really have to know what's going on in the kitchen,
66
180330
3000
Ali u većini slučajeva, vi morate znati šta se dešava u kuhinji,
03:03
because, mostly, sick people used to be healthy people --
67
183330
2000
s obzirom da su bolesni ljudi najčešće bili pre toga zdravi -
03:05
they have the same genome.
68
185330
2000
što znači da imaju isti genom.
03:07
So the genome really tells you much more
69
187330
2000
Tako da vam genom moze reći mnogo više
03:09
about predisposition.
70
189330
2000
o određenim predispozicijama.
03:11
So what you can tell
71
191330
2000
Ono sto vi možete prepoznati
03:13
is you can tell the difference between an Asian person and a European person
72
193330
2000
jeste razlika između Azijata i Evropljana
03:15
by looking at their ingredients list.
73
195330
2000
na osnovu analize njihove liste sastojaka.
03:17
But you really for the most part can't tell the difference
74
197330
3000
Ali u realnosti vi najčešće ne možete uočiti razliku
03:20
between a healthy person and a sick person --
75
200330
3000
između zdrave i bolesne osobe
03:23
except in some of these special cases.
76
203330
2000
sem u specifičnim slučajevima.
03:25
So why all the big deal
77
205330
2000
Usled čega se pravi onda velika pompa
03:27
about genetics?
78
207330
2000
oko genetike?
03:29
Well first of all,
79
209330
2000
Pa, pre svega,
03:31
it's because we can read it, which is fantastic.
80
211330
3000
mi genom možemo da "pročitamo", što je fantastično.
03:34
It is very useful in certain circumstances.
81
214330
3000
U određenim situacijama to je veoma korisno.
03:37
It's also the great theoretical triumph
82
217330
3000
Takođe, predstavlja neverovatan teoretski uspeh
03:40
of biology.
83
220330
2000
biologije.
03:42
It's the one theory
84
222330
2000
To je jedina teorija
03:44
that the biologists ever really got right.
85
224330
2000
oko koje su biolozi ikada bili u pravi.
03:46
It's fundamental to Darwin
86
226330
2000
To je fundamentalna osnova Darvinove teorije
03:48
and Mendel and so on.
87
228330
2000
kao i Mendelove teorije nasleđivanja.
03:50
And so it's the one thing where they predicted a theoretical construct.
88
230330
3000
To je otkriće kojim su biolozi u mogućnosti da predivide teorijski konstrukt.
03:54
So Mendel had this idea of a gene
89
234330
2000
Mendel je imao ideju o genima
03:56
as an abstract thing,
90
236330
3000
u apstraktnom smislu.
03:59
and Darwin built a whole theory
91
239330
2000
I Darvin je uspostavio čitavu teoriju
04:01
that depended on them existing,
92
241330
2000
koja u potpunosti zavisi od postojanja gena.
04:03
and then Watson and Crick
93
243330
2000
I kada su Vatson i Krik proučavali
04:05
actually looked and found one.
94
245330
2000
nasledne jedinice, napokon su ih i pronašli.
04:07
So this happens in physics all the time.
95
247330
2000
Ovo se dešava u fizici sve vreme.
04:09
You predict a black hole,
96
249330
2000
Vi predvidite postojanje crne rupe,
04:11
and you look out the telescope and there it is, just like you said.
97
251330
3000
pogledate kroz teleskop i pronađete je, baš kao što ste i rekli.
04:14
But it rarely happens in biology.
98
254330
2000
Ali to se retko dešava u biologiji.
04:16
So this great triumph -- it's so good,
99
256330
3000
Tako da je ovaj fantastičan trijumf - toliko fascinirajući -
04:19
there's almost a religious experience
100
259330
2000
da je to skoro religiozno iskustvo
04:21
in biology.
101
261330
2000
u biologiji.
04:23
And Darwinian evolution
102
263330
2000
I Darvinova teorije evolucije
04:25
is really the core theory.
103
265330
3000
jeste zaista centralna teorija.
04:30
So the other reason it's been very popular
104
270330
2000
I drugi razlog popularnosti genetike
04:32
is because we can measure it, it's digital.
105
272330
3000
jeste činjenica da je digitalna, genom možete da izmerite.
04:35
And in fact,
106
275330
2000
I u stvari,
04:37
thanks to Kary Mullis,
107
277330
2000
zahvaljujući Kariju Malisu,
04:39
you can basically measure your genome in your kitchen
108
279330
4000
vi možete izmeriti svoj genom u kuhinji
04:43
with a few extra ingredients.
109
283330
3000
uz pomoć nekoliko ekstra sastojaka.
04:46
So for instance, by measuring the genome,
110
286330
3000
Na primer, odgonetajući genom,
04:49
we've learned a lot about how we're related to other kinds of animals
111
289330
4000
naučili smo koliko smo srodni sa ostalim životinjskim vrstama
04:53
by the closeness of our genome,
112
293330
3000
na osnovu sličnosti naših genoma,
04:56
or how we're related to each other -- the family tree,
113
296330
3000
ili kako smo međusobno povezani - porodično stablo,
04:59
or the tree of life.
114
299330
2000
ili stablo života.
05:01
There's a huge amount of information about the genetics
115
301330
3000
Možemo doći do mnogo informacija o genetici
05:04
just by comparing the genetic similarity.
116
304330
3000
na osnovu jednostavnog poređenja genetičkih sličnosti.
05:07
Now of course, in medical application,
117
307330
2000
Naravno i primena ovih znanja u medicini,
05:09
that is very useful
118
309330
2000
je jako korisna
05:11
because it's the same kind of information
119
311330
3000
s obzirom da je to isti tip informacije
05:14
that the doctor gets from your family medical history --
120
314330
3000
koji doktor dobija analizirajući istoriju bolesti vaše famlije,
05:17
except probably,
121
317330
2000
sa tom razlikom da najverovatnije
05:19
your genome knows much more about your medical history than you do.
122
319330
3000
vaš genom zna mnogo više o vašoj istoriji bolesti od vas samih.
05:22
And so by reading the genome,
123
322330
2000
Tako da dešifrujući genom, možemo
05:24
we can find out much more about your family than you probably know.
124
324330
3000
da saznamo mnogo više o vašoj porodici nego što vi sami znate.
05:27
And so we can discover things
125
327330
2000
Tako da možemo da otkrijemo činjenice
05:29
that probably you could have found
126
329330
2000
do kojih biste i vi sami mogli doći
05:31
by looking at enough of your relatives,
127
331330
2000
ukoliko biste ispitali dovoljno vaših rođaka,
05:33
but they may be surprising.
128
333330
3000
ali te činjenice mogu da budu iznenađujuće.
05:36
I did the 23andMe thing
129
336330
2000
Ja sam uradio "23 i ja" test i
05:38
and was very surprised to discover that I am fat and bald.
130
338330
3000
bio sam veoma iznenađen kad sam otkrio da sam debeo i ćelav.
05:41
(Laughter)
131
341330
7000
(Smeh)
05:48
But sometimes you can learn much more useful things about that.
132
348330
3000
Ali ponekada možete saznati mnogo korisnije informacije o tome.
05:51
But mostly
133
351330
3000
Ali najčešće ono što je
05:54
what you need to know, to find out if you're sick,
134
354330
2000
vama potrebno da znate da li ste bolesni
05:56
is not your predispositions,
135
356330
2000
nisu vaše predispozicije, nego
05:58
but it's actually what's going on in your body right now.
136
358330
3000
ono što se zaista događa u datom trenutku u vašem telu.
06:01
So to do that, what you really need to do,
137
361330
2000
A da biste to uradili, ono što je zaista neophodno
06:03
you need to look at the things
138
363330
2000
da uradite jeste da sagledate
06:05
that the genes are producing
139
365330
2000
produkte kodirane vašim genima
06:07
and what's happening after the genetics,
140
367330
2000
i šta se dešava nizvodno od nivoa genetike.
06:09
and that's what proteomics is about.
141
369330
2000
To je ono što definiše proteomiku.
06:11
Just like genome mixes the study of all the genes,
142
371330
3000
Baš kao što genomika ispituje sve gene,
06:14
proteomics is the study of all the proteins.
143
374330
3000
proteomika se bavi izučavanjem svih proteina jednog organizma.
06:17
And the proteins are all of the little things in your body
144
377330
2000
A proteini su "radilice" vašeg organizma
06:19
that are signaling between the cells --
145
379330
3000
koje prenose informacije između ćelija
06:22
actually, the machines that are operating --
146
382330
2000
u principu mašine koje odrađuju sve funkcije organizma.
06:24
that's where the action is.
147
384330
2000
Proteini su nosioci radnih delatnosti.
06:26
Basically, a human body
148
386330
3000
U principu, ljudsko telo
06:29
is a conversation going on,
149
389330
3000
jeste komunikacija, razgovor na globalnom nivou,
06:32
both within the cells and between the cells,
150
392330
3000
i to na oba nivoa, i u ćeliji i između ćelija,
06:35
and they're telling each other to grow and to die,
151
395330
3000
i oni saopštavaju jedni drugima da rastu i da umiru.
06:38
and when you're sick,
152
398330
2000
A kada ste bolesni, to znači
06:40
something's gone wrong with that conversation.
153
400330
2000
da je došlo do greške u tom razgovoru.
06:42
And so the trick is --
154
402330
2000
Tako da je trik u tome da -
06:44
unfortunately, we don't have an easy way to measure these
155
404330
3000
na nesreću, nemamo odgovarajući način da izučavamo proteine
06:47
like we can measure the genome.
156
407330
2000
kao što možemo da izučavamo genom.
06:49
So the problem is that measuring --
157
409330
3000
Dakle, problem je u tom merenju - ukoliko
06:52
if you try to measure all the proteins, it's a very elaborate process.
158
412330
3000
probate da izmerite sve proteine, to je veoma zahtevna procedura.
06:55
It requires hundreds of steps,
159
415330
2000
To zahteva stotine pojedinačnih koraka,
06:57
and it takes a long, long time.
160
417330
2000
i zahteva mnogo, mnogo vremena.
06:59
And it matters how much of the protein it is.
161
419330
2000
I važno je koliko je proteina prisutno.
07:01
It could be very significant that a protein changed by 10 percent,
162
421330
3000
Može biti veoma značajno da je 10% proteina promenjeno,
07:04
so it's not a nice digital thing like DNA.
163
424330
3000
tako da ovde ne pričamo o finom, digitalnom fenomenu kao što je DNK.
07:07
And basically our problem is somebody's in the middle
164
427330
2000
Naš je problem da neko u samoj sredini
07:09
of this very long stage,
165
429330
2000
ovog veoma dugog procesa,
07:11
they pause for just a moment,
166
431330
2000
pauzira za samo jedan trenutak,
07:13
and they leave something in an enzyme for a second,
167
433330
2000
i ostavi nešto u enzimu na samo sekund,
07:15
and all of a sudden all the measurements from then on
168
435330
2000
i odjednom, od tog momenta sva merenja koja
07:17
don't work.
169
437330
2000
slede ne funkcionišu.
07:19
And so then people get very inconsistent results
170
439330
2000
I usled toga ljudi dobijaju veoma nekonzistentne rezultate
07:21
when they do it this way.
171
441330
2000
kada pokušaju da rade na opisani način.
07:23
People have tried very hard to do this.
172
443330
2000
Ljudi su uložili puno truda kako bi uspeli da urade ovo.
07:25
I tried this a couple of times
173
445330
2000
Ja sam probao nekoliko puta
07:27
and looked at this problem and gave up on it.
174
447330
2000
skoncentrisao se na problem i odustao od istog.
07:29
I kept getting this call from this oncologist
175
449330
2000
Ali me je jedan onkolog zvao telefonom non-stop
07:31
named David Agus.
176
451330
2000
po imenu Dejvid Agus.
07:33
And Applied Minds gets a lot of calls
177
453330
3000
I mnogi ljudi zovu "Primenjene Umove",
07:36
from people who want help with their problems,
178
456330
2000
ljudi koji žele pomoć u rešavanju svojih problema,
07:38
and I didn't think this was a very likely one to call back,
179
458330
3000
i nisam mislio da ima mogućnosti de će ovaj zvati ponovo,
07:41
so I kept on giving him to the delay list.
180
461330
3000
i tako je razgovor sa njim bio non-stop na listi čekanja.
07:44
And then one day,
181
464330
2000
I potom jednog dana,
07:46
I get a call from John Doerr, Bill Berkman
182
466330
2000
pozvaše mene Džon Doer, Bil Berkman
07:48
and Al Gore on the same day
183
468330
2000
i Al Gor istoga dana
07:50
saying return David Agus's phone call.
184
470330
2000
da mi kažu da pozovem Dejvid Agusa.
07:52
(Laughter)
185
472330
2000
(Smeh)
07:54
So I was like, "Okay. This guy's at least resourceful."
186
474330
2000
I ja pomislih: "Okej, ovaj tip barem ima puno kontakata."
07:56
(Laughter)
187
476330
4000
(smeh)
08:00
So we started talking,
188
480330
2000
Tako mi počesmo da razgovaramo,
08:02
and he said, "I really need a better way to measure proteins."
189
482330
3000
i on mi reče: "Zaista mi je neophodan bolji način da analiziram proteine."
08:05
I'm like, "Looked at that. Been there.
190
485330
2000
Ja rekoh, "Već sam razmišljao o tome. Išao sam tim stopama.
08:07
Not going to be easy."
191
487330
2000
Ovo neće biti lako."
08:09
He's like, "No, no. I really need it.
192
489330
2000
On reče: "Ali ne, ne. Meni je to zaista neophodno.
08:11
I mean, I see patients dying every day
193
491330
4000
Ja gledam pacijente kako umiru svakoga dana
08:15
because we don't know what's going on inside of them.
194
495330
3000
samo zato što mi ne razumemo šta se dešava u njihovim telima.
08:18
We have to have a window into this."
195
498330
2000
Moramo napraviti prozor koji će omogućiti da to sagledamo."
08:20
And he took me through
196
500330
2000
Onda mi je izneo specifične primere
08:22
specific examples of when he really needed it.
197
502330
3000
situacija u kojima su mu te nove metode apsolutno neophodne.
08:25
And I realized, wow, this would really make a big difference,
198
505330
2000
I ja shvatih da ovo zaista može da napravi ogromnu razliku,
08:27
if we could do it,
199
507330
2000
ukoliko bismo mogli to da odradimo.
08:29
and so I said, "Well, let's look at it."
200
509330
2000
rekao sam, "Pa, hajde da pokušamo."
08:31
Applied Minds has enough play money
201
511330
2000
"Primenjeni Umovi" imaju zaista dovoljno para u igri
08:33
that we can go and just work on something
202
513330
2000
da možemo jednostavno da radimo na problemu
08:35
without getting anybody's funding or permission or anything.
203
515330
3000
bez traženja novih sredstava i specijalnih dozvola ili bilo čega.
08:38
So we started playing around with this.
204
518330
2000
Tako da smo počeli da se zanimamo ovim.
08:40
And as we did it, we realized this was the basic problem --
205
520330
3000
I dok smo se bavili time, shvatili smo da je to osnovni problem -
08:43
that taking the sip of coffee --
206
523330
2000
upravo taj srk kafe
08:45
that there were humans doing this complicated process
207
525330
2000
činjenica da su ljudi izvršavali ovu komplikovanu proceduru
08:47
and that what really needed to be done
208
527330
2000
i da je zaista bilo neophodno
08:49
was to automate this process like an assembly line
209
529330
3000
automatizovati proces kao pokretnu traku
08:52
and build robots
210
532330
2000
i napraviti robote
08:54
that would measure proteomics.
211
534330
2000
koji bi analizirali proteomiku.
08:56
And so we did that,
212
536330
2000
I tako smo to i uradili.
08:58
and working with David,
213
538330
2000
Dok sam radio sa Dejvidom, osnovali
09:00
we made a little company called Applied Proteomics eventually,
214
540330
3000
smo malu kompaniju koju smo nazvali "Primenjena Proteomika",
09:03
which makes this robotic assembly line,
215
543330
3000
koja prozivodi robotizovanu pokretnu traku,
09:06
which, in a very consistent way, measures the protein.
216
546330
3000
koja, na veoma konzsistentan način, analizira proteine.
09:09
And I'll show you what that protein measurement looks like.
217
549330
3000
I sada ću vam pokazati kako to merenje proteina izgleda.
09:13
Basically, what we do
218
553330
2000
U principu, ono što mi radimo je
09:15
is we take a drop of blood
219
555330
2000
da uzmemo kap krvi
09:17
out of a patient,
220
557330
2000
iz pacijenta
09:19
and we sort out the proteins
221
559330
2000
i izolujemo proteine
09:21
in the drop of blood
222
561330
2000
u toj kapi krvi
09:23
according to how much they weigh,
223
563330
2000
na osnovu onoga koliko su ti proteini teški
09:25
how slippery they are,
224
565330
2000
i koliko su pokretljivi,
09:27
and we arrange them in an image.
225
567330
3000
i poređamo ih u sveobuhvatnu sliku.
09:30
And so we can look at literally
226
570330
2000
Tako da nam to omogućava da bukvalno
09:32
hundreds of thousands of features at once
227
572330
2000
analiziramo stotine hiljada karaktersitika u jednom datom
09:34
out of that drop of blood.
228
574330
2000
momentu iz samo jedne kapi krvi.
09:36
And we can take a different one tomorrow,
229
576330
2000
Sledećeg dana možemo uzeti novu kap
09:38
and you will see your proteins tomorrow will be different --
230
578330
2000
i videćete da će vaši proteini sledećeg dana biti drugačiji -
09:40
they'll be different after you eat or after you sleep.
231
580330
3000
drugačiji u zavisnosti od toga da li ste upravo jeli ili se probudili.
09:43
They really tell us what's going on there.
232
583330
3000
Govore nam o procesima koji se dešavaju u telu čoveka.
09:46
And so this picture,
233
586330
2000
Tako da ovde prikazana slika,
09:48
which looks like a big smudge to you,
234
588330
2000
koja vama izgleda kao ogromna mrlja,
09:50
is actually the thing that got me really thrilled about this
235
590330
4000
je u principu otkriće koje je mene jako uzbudilo
09:54
and made me feel like we were on the right track.
236
594330
2000
i zbog kojeg sam pomislio da smo na pravom putu.
09:56
So if I zoom into that picture,
237
596330
2000
Ukoliko ja uveličam ovu sliku,
09:58
I can just show you what it means.
238
598330
2000
mogu vam pokazati šta to zaista znači.
10:00
We sort out the proteins -- from left to right
239
600330
3000
Mi grupišemo proteine: s leva na desno
10:03
is the weight of the fragments that we're getting,
240
603330
3000
na osnovu težine fragmenata koje analiziramo.
10:06
and from top to bottom is how slippery they are.
241
606330
3000
A od vrha na dole, na osnovu njihove pokretljivosti.
10:09
So we're zooming in here just to show you a little bit of it.
242
609330
3000
Sad ćemo uveličati kako bih vam pokazao mali deo.
10:12
And so each of these lines
243
612330
2000
Svaka od ovih linija predstavlja
10:14
represents some signal that we're getting out of a piece of a protein.
244
614330
3000
u principu neku vrstu signala koju mi dobijamo od dela proteina.
10:17
And you can see how the lines occur
245
617330
2000
I isto tako možete primetiti patern linija
10:19
in these little groups of bump, bump, bump, bump, bump.
246
619330
4000
- to su male grupe sastavljene od blagih krivina, krivina, krivina, krivina.
10:23
And that's because we're measuring the weight so precisely that --
247
623330
3000
To se dešava zato što merimo težinu toliko precizno da -
10:26
carbon comes in different isotopes,
248
626330
2000
s obzriom da ugljenik ima različite izotope,
10:28
so if it has an extra neutron on it,
249
628330
3000
ukoliko ima jedan dodatni neutron,
10:31
we actually measure it as a different chemical.
250
631330
4000
mi u principu učitavamo to kao drugačiju supstancu.
10:35
So we're actually measuring each isotope as a different one.
251
635330
3000
Tako da mi beležimo svaki izotop kao drugačiji.
10:38
And so that gives you an idea
252
638330
3000
Na osnovu ovoga možete razumeti
10:41
of how exquisitely sensitive this is.
253
641330
2000
koliko je fantastično osetljiv opisani sistem.
10:43
So seeing this picture
254
643330
2000
Gledanje ove slike
10:45
is sort of like getting to be Galileo
255
645330
2000
je slično kao kada bismo bili Galilej
10:47
and looking at the stars
256
647330
2000
i gledali u zvezde kroz
10:49
and looking through the telescope for the first time,
257
649330
2000
teleskop po prvi put i iznenada
10:51
and suddenly you say, "Wow, it's way more complicated than we thought it was."
258
651330
3000
rekli, "Opa, mnogo je komplikovanije nego što smo mislili."
10:54
But we can see that stuff out there
259
654330
2000
Ali mi sada možemo da sagledamo taj mali univerzum
10:56
and actually see features of it.
260
656330
2000
i uočimo njegove karakteristike.
10:58
So this is the signature out of which we're trying to get patterns.
261
658330
3000
Ovo je skup podataka iz kojih pokušavamo da izvučemo obrasce.
11:01
So what we do with this
262
661330
2000
Ono što mi radimo sa informacijama ovog tipa
11:03
is, for example, we can look at two patients,
263
663330
2000
je da, na primer možemo analizirati dva pacijenta,
11:05
one that responded to a drug and one that didn't respond to a drug,
264
665330
3000
jednog koji je reagovao na lek i drugog koji nije,
11:08
and ask, "What's going on differently
265
668330
2000
i postaviti pitanje, "Koji je proces koji je drugačiji
11:10
inside of them?"
266
670330
2000
u organizmima ovih ljudi?"
11:12
And so we can make these measurements precisely enough
267
672330
3000
Takođe možemo da odradimo ta merenja dovoljno precizno
11:15
that we can overlay two patients and look at the differences.
268
675330
3000
da možemo da uporedimo dva pacijenta i uočimo razlike.
11:18
So here we have Alice in green
269
678330
2000
Ovde možete videti Alis u zelenom kodu
11:20
and Bob in red.
270
680330
2000
i Boba predstavljenog crvenim kodom.
11:22
We overlay them. This is actual data.
271
682330
3000
Poredimo njihove podatke. Ovo su pravi rezulati.
11:25
And you can see, mostly it overlaps and it's yellow,
272
685330
3000
Postoji puno sličnosti i obeležene su žutom bojom
11:28
but there's some things that just Alice has
273
688330
2000
ali postoje određeni proteini koje ima samo Alis
11:30
and some things that just Bob has.
274
690330
2000
i određeni proteini koje ima samo Bob.
11:32
And if we find a pattern of things
275
692330
3000
I ukoliko pronađemo šablon koji opisuje
11:35
of the responders to the drug,
276
695330
3000
grupu ljudi na koje postojeći lek ispoljava željeni
11:38
we see that in the blood,
277
698330
2000
efekat, mi vidimo to u krvi,
11:40
they have the condition
278
700330
2000
oni imaju uslove koji im
11:42
that allows them to respond to this drug.
279
702330
2000
omogućuju da uspešno odreaguju na tretman.
11:44
We might not even know what this protein is,
280
704330
2000
Mi možda čak ni ne znamo koji je to protein,
11:46
but we can see it's a marker
281
706330
2000
ali znamo da taj protein jeste marker,
11:48
for the response to the disease.
282
708330
2000
koji govori da će određeni tretman biti uspešan.
11:53
So this already, I think,
283
713330
2000
Već ovo saznanje, po mom mišljenju,
11:55
is tremendously useful in all kinds of medicine.
284
715330
3000
jeste od neopisive koristi za različite grane medicine.
11:58
But I think this is actually
285
718330
2000
Ali ja isto tako mislim da je ovo
12:00
just the beginning
286
720330
2000
tek početak razvijanja procedura
12:02
of how we're going to treat cancer.
287
722330
2000
kojima ćemo se boriti protiv raka.
12:04
So let me move to cancer.
288
724330
2000
A sada bih da pričam malo više o raku.
12:06
The thing about cancer --
289
726330
2000
Zanimljiva činjenica o kanceru je ta
12:08
when I got into this,
290
728330
2000
da kada sam ja počeo da se bavim ovim
12:10
I really knew nothing about it,
291
730330
2000
zaista nisam znao ništa o raku,
12:12
but working with David Agus,
292
732330
2000
ali radeći rame uz rame sa Dejvidom Agusom
12:14
I started watching how cancer was actually being treated
293
734330
3000
počeo sam da razumevam kako mi danas lečimo rak
12:17
and went to operations where it was being cut out.
294
737330
3000
i odlazio sam na operacije koje su imale za cilj otklanjanje raka.
12:20
And as I looked at it,
295
740330
2000
I kada sam sagledao tu proceduru,
12:22
to me it didn't make sense
296
742330
2000
to meni i nije baš imalo puno smisla,
12:24
how we were approaching cancer,
297
744330
2000
takav pristup lečenju raka.
12:26
and in order to make sense of it,
298
746330
3000
I kako bih razumeo proces lečenja,
12:29
I had to learn where did this come from.
299
749330
3000
morao sam naučiti kako smo došli do današnjih tretmana.
12:32
We're treating cancer almost like it's an infectious disease.
300
752330
4000
Borimo se protiv raka na način na koji se borimo protiv infektivnih bolesti.
12:36
We're treating it as something that got inside of you
301
756330
2000
Tretiramo ih kao nešto što vas je inficiralo
12:38
that we have to kill.
302
758330
2000
i što moramo da ubijemo.
12:40
So this is the great paradigm.
303
760330
2000
To je velika paradigma.
12:42
This is another case
304
762330
2000
Ovo je drugi primer u biologiji gde se
12:44
where a theoretical paradigm in biology really worked --
305
764330
2000
teorijskom paradigmom zaista došlo do rezultata,
12:46
was the germ theory of disease.
306
766330
3000
a to je "patogen - teorija bolesti".
12:49
So what doctors are mostly trained to do
307
769330
2000
Doktori su u najvećem broju slučajeva obučeni da
12:51
is diagnose --
308
771330
2000
uspostave dijagnozu -
12:53
that is, put you into a category
309
773330
2000
- što znači da vas oni svrstavaju u određenu kategoriju
12:55
and apply a scientifically proven treatment
310
775330
2000
i onda primene naučno odobreni tretman protiv bolesti
12:57
for that diagnosis --
311
777330
2000
za koju su postavili dijagnozu.
12:59
and that works great for infectious diseases.
312
779330
3000
To je odličan pristup u lečenju infektivnih bolesti.
13:02
So if we put you in the category
313
782330
2000
Tako da ukoliko je ustanovljeno
13:04
of you've got syphilis, we can give you penicillin.
314
784330
3000
da bolujete od sifilisa, možemo vas lečiti penicilinom.
13:07
We know that that works.
315
787330
2000
Mi znamo da je to uspešan način.
13:09
If you've got malaria, we give you quinine
316
789330
2000
Ukoliko bolujete od malarije, prepisaćemo vam kinin
13:11
or some derivative of it.
317
791330
2000
ili neki od derivata kinina.
13:13
And so that's the basic thing doctors are trained to do,
318
793330
3000
To je u principu osnovna stvar za koju su doktori obučeni.
13:16
and it's miraculous
319
796330
2000
Tako da je zapravo čudesno
13:18
in the case of infectious disease --
320
798330
3000
kako u slučajevima infektivnih bolesti -
13:21
how well it works.
321
801330
2000
ovi tretmani ekeftivno rešavaju probleme.
13:23
And many people in this audience probably wouldn't be alive
322
803330
3000
Mnogi ljudi u ovoj publici najverovatnije ne bi bili živi
13:26
if doctors didn't do this.
323
806330
2000
da lekari ne rade ovo.
13:28
But now let's apply that
324
808330
2000
Hajde da pokušamo da primenimo ovaj princip
13:30
to systems diseases like cancer.
325
810330
2000
na sistemski tip bolesti kao što je rak.
13:32
The problem is that, in cancer,
326
812330
2000
Problem je što u slučaju raka
13:34
there isn't something else
327
814330
2000
ne postoji strano telo koje treba ubiti,
13:36
that's inside of you.
328
816330
2000
koje je ušlo u vaš organizam.
13:38
It's you; you're broken.
329
818330
2000
To ste vi, vaše ćelije su nefunkcionalne.
13:40
That conversation inside of you
330
820330
4000
Komunikacija koja postoji na sistemskom nivou u vašem telu
13:44
got mixed up in some way.
331
824330
2000
je postala pometena na neki način.
13:46
So how do we diagnose that conversation?
332
826330
2000
Kako možemo da dijagnostikujemo problem u komunikaciji?
13:48
Well, right now what we do is we divide it by part of the body --
333
828330
3000
U ovom trenutku grupišemo rak prema različitm delovima tela -
13:51
you know, where did it appear? --
334
831330
3000
znate, gde se pojavio -
13:54
and we put you in different categories
335
834330
2000
i stavimo vas u različite kategorije
13:56
according to the part of the body.
336
836330
2000
na osnovu dela vašeg tela.
13:58
And then we do a clinical trial
337
838330
2000
I onda sprovedemo klinička istraživanja
14:00
for a drug for lung cancer
338
840330
2000
za lek koji pokazuje efekat na rak pluća
14:02
and one for prostate cancer and one for breast cancer,
339
842330
3000
i za lek koji deluje na rak prostate, rak dojke,
14:05
and we treat these as if they're separate diseases
340
845330
3000
i lečimo ove slučajeve kao da su različite bolesti
14:08
and that this way of dividing them
341
848330
2000
kao da ovaj način na koji grupišemo pod-tipove raka
14:10
had something to do with what actually went wrong.
342
850330
2000
ima ikakve veze sa onim što nije u redu.
14:12
And of course, it really doesn't have that much to do
343
852330
2000
I naravno, to nema baš puno veze sa tim
14:14
with what went wrong
344
854330
2000
šta je pošlo naopako.
14:16
because cancer is a failure of the system.
345
856330
3000
Jer rak je malfunkcionisanje sistema.
14:19
And in fact, I think we're even wrong
346
859330
2000
U principu, ja mislim da je potpuno pogrešno
14:21
when we talk about cancer as a thing.
347
861330
3000
pričati o raku kao o predmetu, stvari.
14:24
I think this is the big mistake.
348
864330
2000
Ja mislim da je to velika greška.
14:26
I think cancer should not be a noun.
349
866330
4000
Ja mislim da rak ne bi trebalo da bude imenica.
14:30
We should talk about cancering
350
870330
2000
Mi treba da pričamo o ovoj bolesti kao o "rakovanju"
14:32
as something we do, not something we have.
351
872330
3000
nečemu što mi sami radimo, a ne nečemu što imamo.
14:35
And so those tumors,
352
875330
2000
Različiti tumori
14:37
those are symptoms of cancer.
353
877330
2000
su simptomi raka.
14:39
And so your body is probably cancering all the time,
354
879330
3000
Tako da vaše telo verovatno "rakuje" sve vreme.
14:42
but there are lots of systems in your body
355
882330
3000
Ali postoji puno sistema u vašem telu
14:45
that keep it under control.
356
885330
2000
koji taj proces drže pod kontrolom.
14:47
And so to give you an idea
357
887330
2000
Da bih vam dao ideju
14:49
of an analogy of what I mean
358
889330
2000
analogije na koju konkretno mislim
14:51
by thinking of cancering as a verb,
359
891330
3000
kada govorim "rakovati" u vidu glagola,
14:54
imagine we didn't know anything about plumbing,
360
894330
3000
zamislite da ne znamo ništa o vodoinstalaterstvu,
14:57
and the way that we talked about it,
361
897330
2000
tako da bismo pričali o tome na sledeći način,
14:59
we'd come home and we'd find a leak in our kitchen
362
899330
3000
došli bismo kući i uočili da je u kuhinji procurela voda
15:02
and we'd say, "Oh, my house has water."
363
902330
4000
i rekli bismo, "Oh, u mojoj kući ima vode."
15:06
We might divide it -- the plumber would say, "Well, where's the water?"
364
906330
3000
Vodoinstalater bi rekao, "Pa, gde je ta voda u kući?"
15:09
"Well, it's in the kitchen." "Oh, you must have kitchen water."
365
909330
3000
"Pa, u kuhinji." "Oh, pa vi onda imate kuhinjsku vodu."
15:12
That's kind of the level at which it is.
366
912330
3000
To je plastični primer nivoa našeg sagledavanja stvari.
15:15
"Kitchen water,
367
915330
2000
"Kuhinjska voda?
15:17
well, first of all, we'll go in there and we'll mop out a lot of it.
368
917330
2000
Pa, pre svega, mi ćemo obrisati dosta vode.
15:19
And then we know that if we sprinkle Drano around the kitchen,
369
919330
3000
Isto tako znamo da ukoliko koristimo "Mr. Musculo"
15:22
that helps.
370
922330
3000
u kuhinji, to će sigurno pomoći.
15:25
Whereas living room water,
371
925330
2000
Dok u slučaju vode u dnevnoj sobi
15:27
it's better to do tar on the roof."
372
927330
2000
bolje rešenje je da popravimo krov."
15:29
And it sounds silly,
373
929330
2000
Znam da zvuči ludo,
15:31
but that's basically what we do.
374
931330
2000
ali u principu to je ono što danas radimo.
15:33
And I'm not saying you shouldn't mop up your water if you have cancer,
375
933330
3000
Ne kažem da ne treba da izbacite vodu ukoliko imate rak.
15:36
but I'm saying that's not really the problem;
376
936330
3000
Ali želim da poručim da to nije uzrok problema;
15:39
that's the symptom of the problem.
377
939330
2000
to je samo simptom problema.
15:41
What we really need to get at
378
941330
2000
Mi zaista treba da tretiramo
15:43
is the process that's going on,
379
943330
2000
proces koji se dešava,
15:45
and that's happening at the level
380
945330
2000
a taj proces se dešava na nivou
15:47
of the proteonomic actions,
381
947330
2000
proteina i njihove komunikacije,
15:49
happening at the level of why is your body not healing itself
382
949330
3000
pitanje je zašto vaše telo ne štiti sebe
15:52
in the way that it normally does?
383
952330
2000
na način na koji se to normalno dešava?
15:54
Because normally, your body is dealing with this problem all the time.
384
954330
3000
Vaše telo se suočava sa problemima ovog tipa svakog dana.
15:57
So your house is dealing with leaks all the time,
385
957330
3000
Vaša kuća se bori protiv prokišnjavanja sve vreme.
16:00
but it's fixing them. It's draining them out and so on.
386
960330
4000
Ali se i odupire prokišnjavanju. Isušuje vodu.
16:04
So what we need
387
964330
3000
Tako da je nama neophodan sada
16:07
is to have a causative model
388
967330
4000
uzročni model
16:11
of what's actually going on,
389
971330
2000
onoga što se zaista dešava.
16:13
and proteomics actually gives us
390
973330
3000
Proteomika nam pruža
16:16
the ability to build a model like that.
391
976330
3000
mogućnost da napokon izgradimo takav model.
16:19
David got me invited
392
979330
2000
Dejvid me je pozvao da održim
16:21
to give a talk at National Cancer Institute
393
981330
2000
govor na Nacionalnom Institutu Izučavanja Raka
16:23
and Anna Barker was there.
394
983330
3000
i Ana Barker je bila tamo.
16:27
And so I gave this talk
395
987330
2000
Tako sam održao taj govor
16:29
and said, "Why don't you guys do this?"
396
989330
3000
i rekao, "Zašto vi ne biste uradili ovo?"
16:32
And Anna said,
397
992330
2000
I Ana reče,
16:34
"Because nobody within cancer
398
994330
3000
"Zato što niko ko se bavi problemom raka
16:37
would look at it this way.
399
997330
2000
ne bi gledao na problem raka na ovaj način.
16:39
But what we're going to do, is we're going to create a program
400
999330
3000
Ali mi ćemo svakako uspostaviti program
16:42
for people outside the field of cancer
401
1002330
2000
koji će okupiti ljude koji se ne bave rakom
16:44
to get together with doctors
402
1004330
2000
i povezaćemo te stručanjake sa medicinarima
16:46
who really know about cancer
403
1006330
3000
koji znaju puno o raku
16:49
and work out different programs of research."
404
1009330
4000
i na taj način ćemo smisliti drugačiji program istraživanja."
16:53
So David and I applied to this program
405
1013330
2000
Tako smo Dejvid i ja konkurisali za pomenuti program
16:55
and created a consortium
406
1015330
2000
i stvorili konzorcijum
16:57
at USC
407
1017330
2000
na Univerzitetu Južne Kalifornije
16:59
where we've got some of the best oncologists in the world
408
1019330
3000
gde smo okupili neke od najboljih onkologa sveta
17:02
and some of the best biologists in the world,
409
1022330
3000
i neke od najboljih biologa sveta
17:05
from Cold Spring Harbor,
410
1025330
2000
iz Kold Spring Harbora
17:07
Stanford, Austin --
411
1027330
2000
Stanforda, Ostina...
17:09
I won't even go through and name all the places --
412
1029330
3000
Ne mogu sada navesti imena svih instituticija -
17:12
to have a research project
413
1032330
3000
kako bismo odradili naučno-istraživački projekat
17:15
that will last for five years
414
1035330
2000
koji će trajati pet godina sa krajnjim
17:17
where we're really going to try to build a model of cancer like this.
415
1037330
3000
ciljem postavljanja modela kancera po opisanim principima.
17:20
We're doing it in mice first,
416
1040330
2000
Radićemo ova istraživanja prvo na miševima.
17:22
and we will kill a lot of mice
417
1042330
2000
Puno ce miševa stradati
17:24
in the process of doing this,
418
1044330
2000
u toku razvijanja ovih eksperimenata
17:26
but they will die for a good cause.
419
1046330
2000
ali će oni umreti za opšte dobro.
17:28
And we will actually try to get to the point
420
1048330
3000
Mi ćemo u principu pokušati da dođemo do momenta
17:31
where we have a predictive model
421
1051330
2000
kada imamo uspostavljeni uzročni model
17:33
where we can understand,
422
1053330
2000
na osnovu kog možemo da razumemo,
17:35
when cancer happens,
423
1055330
2000
kada se rak desi,
17:37
what's actually happening in there
424
1057330
2000
šta se u osnovi dešava u organizmu
17:39
and which treatment will treat that cancer.
425
1059330
3000
i koji specifičan tretman će biti efektan u lečenju.
17:42
So let me just end with giving you a little picture
426
1062330
3000
I za sam kraj bih vam pokazao mali shematski prikaz
17:45
of what I think cancer treatment will be like in the future.
427
1065330
3000
kako ja zamišljam da tretman protiv raka izgleda u budućnosti.
17:48
So I think eventually,
428
1068330
2000
Ja mislim da na kraju,
17:50
once we have one of these models for people,
429
1070330
2000
kada budemo imali ovakav model za ljude,
17:52
which we'll get eventually --
430
1072330
2000
koji ćemo svakako na kraju imati -
17:54
I mean, our group won't get all the way there --
431
1074330
2000
naša istraživačka grupa neće sama doći do cilja
17:56
but eventually we'll have a very good computer model --
432
1076330
3000
ali ćemo na kraju imati veoma dobar kompjuterski model -
17:59
sort of like a global climate model for weather.
433
1079330
3000
nešto kao globalni model vremenske prognoze.
18:02
It has lots of different information
434
1082330
3000
Model će imati puno različitih informacija o
18:05
about what's the process going on in this proteomic conversation
435
1085330
3000
procesima koji se dešavaju u toku komunikacije u
18:08
on many different scales.
436
1088330
2000
proteomu na različitim nivoima.
18:10
And so we will simulate
437
1090330
2000
Na taj način mi ćemo simulirati
18:12
in that model
438
1092330
2000
tim modelom specifičan rak
18:14
for your particular cancer --
439
1094330
3000
od kojeg osoba boluje i taj model
18:17
and this also will be for ALS,
440
1097330
2000
će imati primenu i za amiotrofičnu lateralnu sklerozu (ALS)
18:19
or any kind of system neurodegenerative diseases,
441
1099330
3000
ili bilo koju sistemsku neurodegenerativnu bolest,
18:22
things like that --
442
1102330
2000
bolesti kao te
18:24
we will simulate
443
1104330
2000
mi ćemo simulirati
18:26
specifically you,
444
1106330
2000
Vas posebno, ne neku
18:28
not just a generic person,
445
1108330
2000
generičku osobu, nego baš
18:30
but what's actually going on inside you.
446
1110330
2000
same procese koji se odvijaju unutar vašeg tela.
18:32
And in that simulation, what we could do
447
1112330
2000
I ono što možemo da uradimo u takvoj simulaciji
18:34
is design for you specifically
448
1114330
2000
jeste da specifično dizajniramo
18:36
a sequence of treatments,
449
1116330
2000
za Vas kombinaciju tretmana,
18:38
and it might be very gentle treatments, very small amounts of drugs.
450
1118330
3000
koji mogu biti veoma blagi, veoma male doze lekova.
18:41
It might be things like, don't eat that day,
451
1121330
3000
To mogu biti saveti tipa: nemojte jesti ovog dana,
18:44
or give them a little chemotherapy,
452
1124330
2000
ili primenićemo malu dozu hemoterapije,
18:46
maybe a little radiation.
453
1126330
2000
možda malo zračenja.
18:48
Of course, we'll do surgery sometimes and so on.
454
1128330
3000
Naravno, ponekad ćemo odraditi operativni zahvat.
18:51
But design a program of treatments specifically for you
455
1131330
3000
Ali ćemo dizajnirati poseban program tretmana samo za vas
18:54
and help your body
456
1134330
3000
i pomoći vašem telu
18:57
guide back to health --
457
1137330
3000
da se oporavi - tako ćemo
19:00
guide your body back to health.
458
1140330
2000
usmeravati vaše telo ka zdravom stanju.
19:02
Because your body will do most of the work of fixing it
459
1142330
4000
Jer će vaše telo odraditi najveći deo posla da reši problem
19:06
if we just sort of prop it up in the ways that are wrong.
460
1146330
3000
ukoliko mu mi samo pomognemo u tome.
19:09
We put it in the equivalent of splints.
461
1149330
2000
To bi bio ekvivalent metalnim udlagama.
19:11
And so your body basically has lots and lots of mechanisms
462
1151330
2000
Vaš organizam ima veoma puno mehanizama
19:13
for fixing cancer,
463
1153330
2000
koji se mogu uspešno boriti protiv raka
19:15
and we just have to prop those up in the right way
464
1155330
3000
i mi samo treba da stimulišemo te mehanizme na pravi način
19:18
and get them to do the job.
465
1158330
2000
i pokrenemo ih da ponovo počnu da rade svoj posao.
19:20
And so I believe that this will be the way
466
1160330
2000
Ja sam duboko ubeđen da će ovo biti način
19:22
that cancer will be treated in the future.
467
1162330
2000
na koji ćemo lečiti rak u budućnosti.
19:24
It's going to require a lot of work,
468
1164330
2000
To će zahtevati mnogo, mnogo rada,
19:26
a lot of research.
469
1166330
2000
mnogo istraživanja.
19:28
There will be many teams like our team
470
1168330
3000
Biće mnogo timova koji kao i naš tim
19:31
that work on this.
471
1171330
2000
pokušavaju da razumeju pomenuti fenomen.
19:33
But I think eventually,
472
1173330
2000
Ali ja mislim da ćemo u budućnosti
19:35
we will design for everybody
473
1175330
2000
biti u mogućnosti da dizajniramo
19:37
a custom treatment for cancer.
474
1177330
4000
specifičan tretman protiv raka za svaki pojedinačni slučaj.
19:41
So thank you very much.
475
1181330
2000
Na kraju, mnogo vam hvala.
19:43
(Applause)
476
1183330
6000
(Aplauz)
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7