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Avoiding, Treating & Curing Cancer With the Immune System | Dr. Alex Marson

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Avoiding, Treating & Curing Cancer With the Immune System | Dr. Alex Marson

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3960 segments

0:00

We're living in this amazing moment of

0:01

biology where we can put a gene that

0:03

encodes something on the surface of tea

0:05

cells that will make them programmed to

0:09

search and destroy for cancer cells.

0:11

>> Now this is largely known as CART tea

0:14

cells, chimeriic antigen receptor. This

0:17

is a receptor that was designed in a lab

0:19

does not exist in nature. When those tea

0:21

cells get reinfused into a patient the

0:23

way that you get like a a blood

0:24

transfusion, those cars are directed to

0:27

go against cancers. Welcome to the

0:29

Huberman Lab podcast, where we discuss

0:31

science and science-based tools for

0:33

everyday life.

0:37

I'm Andrew Huberman and I'm a professor

0:39

of neurobiology and opthalmology at

0:42

Stamford School of Medicine. My guest

0:44

today is Dr. Alex Marson. Dr. Alex

0:47

Marson is a medical doctor and scientist

0:49

at the University of California, San

0:50

Francisco. He is developing new ways to

0:52

reprogram the immune system to cure

0:54

cancers. Today we discuss how your

0:57

immune system works, how autoimmunity

0:59

works, and how gene editing and other

1:01

new technologies can be successfully

1:03

leveraged to defeat childhood and adult

1:06

cancers. Dr. Dr. Marson is truly one of

1:09

a kind in his understanding of the

1:10

clinical aspects of cancer treatment,

1:12

the science of the immune system, and as

1:15

you'll soon hear, in explaining the

1:17

things that genuinely increase your

1:19

cancer risk, many of which are

1:20

surprising, and the actionable steps

1:22

that we can all take to reduce our

1:24

probability of getting cancer. In

1:26

addition to the usual factors, smoking,

1:28

UV light, and environmental toxins such

1:31

as pesticides, we discuss the actual

1:33

cancer risks that come from things like

1:35

eating charred meats, airport scanners,

1:37

and food additives, and how to gauge

1:39

your individual level of risk. We also

1:42

explore gene editing for reversing

1:43

diseases, which until recently was

1:45

science fiction, but now is a reality.

1:48

By the end of today's episode, thanks to

1:51

Dr. Marson, you'll have the most

1:52

up-to-date understanding of the

1:54

state-of-the-art science for cancer

1:55

prevention and treatment. Knowledge that

1:58

is certain to impact you or a close

2:00

friend or family member in your

2:02

lifetime. Before we begin, I'd like to

2:04

emphasize that this podcast is separate

2:05

from my teaching and research roles at

2:07

Stanford. It is however part of my

2:09

desire and effort to bring zero cost to

2:11

consumer information about science and

2:12

science related tools to the general

2:14

public. In keeping with that theme,

2:16

today's episode does include sponsors.

2:18

And now for my discussion with Dr. Alex

2:21

Marson. Dr. Alex Marson, welcome.

2:24

>> Andrew,

2:25

>> this is the first time that we're going

2:26

to have a serious discussion about the

2:28

immune system, cancer, and gene editing

2:32

technologies on this podcast. So, I'm

2:34

delighted that you're here. It's also

2:35

great to see you again.

2:36

>> Thank you for having me. Really, really

2:37

good to see you.

2:38

>> It's been a while. Let's start off with

2:41

the big picture.

2:42

>> Uh, how are we doing? How's uh how's

2:45

biology looking? How's medicine looking?

2:47

Are we uh are we on the fast track to

2:49

much better things? Are we going to slog

2:51

along for another 10 years before we

2:53

have cures to the many concerns that

2:55

people have about cancer, Alzheimer's,

2:57

and the rest? Or are you encouraged by

3:00

what's happening right now?

3:01

>> I think maybe there's some some the

3:04

general public doesn't quite know how

3:07

excited biologists are about what's

3:09

possible. And maybe we've overpromised.

3:11

Maybe in the past we've said we're on

3:12

the brink of curing disease and people

3:14

haven't seen it. But something is

3:17

materially different right now. And

3:19

there is a convergence of so many

3:21

different ways of understanding biology

3:25

but then not having that stop at

3:27

understanding but to actually intervene

3:28

and at the root causes of disease. And

3:32

over the course of this conversation, I

3:34

imagine we're going to talk about DNA

3:36

sequencing,

3:38

understanding cells, but going all the

3:40

way to rewriting specific DNA sequences

3:43

inside of the cells of our immune

3:44

system. Doing this not one at a time,

3:47

but testing every gene and understanding

3:49

pieces of DNA throughout our entire

3:51

genome to understand what controls our

3:53

cells. and then being able to take that

3:55

information and actually do something

3:57

about it to boost our immune system to

3:59

go after cancer to balance it for

4:02

inflammation and autoimmunity. And that

4:06

doesn't just have to be sort of

4:07

searching for a pill. All of a sudden,

4:09

we can actually talk to our own cells

4:12

and give them instructions in the

4:13

language of DNA and the language of

4:15

molecular biology. And in some

4:17

instances, this is being done with

4:19

crisper, but it's also being done with

4:21

lipid nanop particles and vaccines. And

4:25

we're still inventing new ways of giving

4:27

these instructions. But all of a sudden,

4:29

medicine

4:31

is programming the behavior of cells in

4:33

a way that's much more directed than was

4:36

ever conceivable before. Like there's

4:38

really a step function in what's

4:40

imaginable and achievable in medicine.

4:43

>> Super exciting. Do you think that

4:46

molecular biology and genetic

4:48

engineering andor AI are the reasons

4:52

that things are on this accelerated

4:54

timeline?

4:54

>> Yes is the answer. All of those things

4:57

>> I think we can do experiments at a

5:00

different level of scale. we can

5:02

generate data and then we have the

5:04

computational tools in including AI but

5:06

we have computational sophistication to

5:09

actually extract insights from massive

5:13

amounts of data and you know I think

5:16

historically biology was we were it was

5:20

an observational science if you

5:21

especially if you wanted to study things

5:22

in in humans there wasn't a way to

5:24

intervene now all of a sudden we're

5:26

taking human cells we're putting taking

5:28

them into the lab and making genetic

5:30

changes is and reading out the

5:32

consequences and directly being able to

5:35

observe the effect. And we have all the

5:38

we have tools to do this with imaging.

5:41

We have the tools to do this with DNA

5:43

sequencing. And we can take this all the

5:46

way into clinical trials and see what

5:48

are the what are the consequences when

5:49

we actually go after targeted DNA

5:52

sequences and make our cells better at

5:55

treating disease.

5:56

>> Would you mind educating us about the

5:58

immune system a bit? the adaptive and

6:01

the innate immune system, some of the

6:02

major cell types, because I think those

6:04

are going to form the kind of building

6:05

blocks of our discussions about cancer

6:08

and and other things today.

6:10

>> Our immune system permeates almost every

6:12

aspect of our health and disease. It is

6:16

a system really in the sense of it it's

6:18

involved in every part of our body that

6:21

has evolved to protect us largely to

6:25

protect us against infections, viruses,

6:28

bacteria, fungus.

6:30

all sorts of foreign invasions and our

6:32

immune system has developed a balance

6:35

that is when it's working properly

6:38

doesn't recognize the cells that are

6:40

supposed to be in the body but is finely

6:43

tuned to recognize signs of things that

6:46

shouldn't be in the body and to

6:48

eliminate them. I mean at at its core

6:50

that's that's the the basic job of the

6:53

immune system

6:54

>> to recognize us versus non us.

6:56

>> Exactly.

6:58

And you you talked about the innate

7:00

versus the adaptive immune system.

7:02

Largely what we're talking about are

7:04

white blood cells. We're we're talking

7:07

about different types of white blood

7:08

cells that are either inside of tissues

7:10

or circulating in our bloodstream that

7:13

go around and play coordinated and

7:16

specialized roles in sensing when

7:18

something comes in that is not us that's

7:21

foreign that shouldn't be there.

7:24

The innate immune system does it as is

7:26

sort of thought of as the the first

7:28

alarm system that something something's

7:30

wrong. And with the innate immune

7:32

system, which consists of cells like

7:35

dendritic cells, macrofasages,

7:38

these are cells that are going around

7:40

and they're looking for patterns of

7:43

things that just generally aren't in

7:45

human cells. some signs of damage, some

7:48

signs of things that are just that

7:49

shouldn't be there in a in a generic way

7:52

in a healthy human. When those first

7:55

alarm systems get triggered, all of a

7:57

sudden these innate immune systems start

7:59

releasing things. They change their

8:01

state and they send off an alarm to

8:03

other cells in the immune system and

8:06

then they often recruit in the second

8:08

arm of the immune system that you

8:10

mentioned, the adaptive immune system.

8:12

We'll talk a lot about the adaptive

8:14

immune system today. And the major

8:16

players in the adaptive immune system

8:18

are a group of white blood cells that

8:21

are collectively known as lymphosytes.

8:24

But we'll talk about B cells and T-

8:26

cells in particular, which are major

8:28

groups of of lymphosytes. We've been

8:31

focused heavily on T- cells. TE- cells

8:34

play a central role in coordinating the

8:37

fine-tuning of the immune response. One

8:39

of the amazing things about the te-

8:40

cells is that each te- cell naturally in

8:43

our body. It's one of the few places

8:45

where each cell will actually have a

8:47

different piece of DNA that's not

8:49

inherited in in our germ line sequence.

8:52

Each tea cell will make its own receptor

8:55

that is generated largely at random

8:59

to go and sense something. And those

9:03

those sensors that get put on the

9:04

surface of tea cells are there to

9:06

engage. And if they're engaged, it's a

9:09

sign that something has has been

9:10

recognized as foreign. And so we have

9:13

this incredible diversity of of

9:16

different T- cell receptors that are

9:18

have developed on our tea cells. Each

9:20

one will have a different unique

9:22

receptor on its surface. Each cell will

9:24

have a different receptor on its

9:26

surface. And the the way to think about

9:28

these receptors is that they're sensors

9:30

for they're when they're engaged, they

9:32

send a signal to the T- cell that okay,

9:34

we found something that that you've been

9:37

programmed to recognize and program is

9:39

recognized as far and if it if the

9:41

immune system is working properly.

9:43

>> And are the genes uh that these tea

9:44

cells make as these receptors uh are

9:46

those based on experience of the of the

9:49

organism? Because you said that it

9:50

doesn't come from the germ line, but we

9:52

should clarify that the germ line is not

9:54

about infectious germs in this context.

9:56

The germline DNA is from the sperm and

9:59

egg that were your parents. It became

10:01

you. There's re combination of those

10:03

genes. And then there's you all um each

10:06

and all. Um and the tea cells are making

10:08

genes that neither your parents

10:10

necessarily expressed nor that you were

10:12

expected to express except based on what

10:15

exposure to particular pathogens. Like

10:17

why do they make certain receptors and

10:18

not others?

10:19

>> Largely random. It actually there's the

10:22

pieces of DNA at this part of the the

10:25

DNA actually recombine and get pasted

10:27

together in in unique ways.

10:31

>> So it's probabilistic.

10:32

>> It's probabilistic and that's what

10:34

allows us to have cells that lying there

10:37

in waiting for things that we've never

10:39

encountered. If a a a bacteria might

10:42

come into existence or a virus might

10:43

come into existence that doesn't even

10:45

exist now in nature, but we might have

10:47

tea cells lying there waiting that could

10:49

be engaged by those proteins on the

10:53

surface that viruses would introduce.

10:55

>> That's incredible. Would you mind

10:56

mentioning the the role of the thymus?

10:58

These days I'm hearing more and more

11:00

about we have a thymus and we lose a

11:01

thymus. Would it be beneficial if we

11:03

could keep our thymus around? So thymus

11:06

is is actually the reason the tea cells

11:08

are called te- cells is the T stands for

11:11

thymus and the thymus is an organ that

11:15

it does sort of shrink as we age but at

11:18

least in childhood it's it sort of lies

11:20

by your heart

11:21

>> and it is the place where tea cells go

11:24

in a key place of their education. So

11:26

they they've have are making these

11:28

sensors at largely at random and then in

11:31

the thymus they get cold they get

11:35

selected and they the ones that by

11:38

accident are generated that recognize

11:40

something that is supposed to be in your

11:42

body if if the T- cell engages a natural

11:46

target in the thymus those cells will

11:48

die and so what emerges from the thymus

11:51

should be and this is not perfect

11:53

process but should be things that have

11:55

are have emerged at random but then are

11:58

selected to remove things that recognize

12:00

your own body targets.

12:02

>> There's sort of a negative selection

12:04

>> of the stuff that's you so that your

12:06

immune system doesn't attack you and it

12:08

knows you from non you.

12:10

>> Yeah, that's exactly right. There's

12:12

actually both a positive selection and a

12:14

negative selection. That's exactly the

12:15

right way to think. The cells get will

12:17

only emerge from the thymus that if they

12:19

have a a receptor on their surface

12:22

that's there. So that's one positive

12:24

selection, but if it engages with a self

12:27

target in the thymus, it gets negatively

12:29

selected. So what comes out are tea

12:31

cells that are there with sensors in

12:33

place

12:34

>> to recognize things that shouldn't be

12:36

there.

12:37

>> Okay. So your thymus and your tea cells

12:39

get educated in childhood. Yeah.

12:42

>> And that's what you're working with

12:44

>> except that the immune system can adapt

12:46

and make antibodies to things it doesn't

12:49

recognize. the antibodies come from the

12:51

from the other type of lymphosy

12:54

lymphosytes. So now now we can talk

12:56

about the B cells. B cells are this

12:59

other type of lymphosy that work in

13:01

coordination with T- cells and they're

13:03

the antibbody producing cells. So they

13:05

actually have a similar process where

13:07

they're generating different antibodies

13:08

at random through a similar kind of

13:10

recombination event. they have their own

13:12

form of selection that they go through

13:14

and then those antibodies can then be

13:17

released into the bloodstream and and

13:19

are the basis for protection against

13:22

infections after we get them. I'd like

13:24

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to get up to 27% off. What um underlies

16:14

the sort of efficiency and functioning

16:17

of the immune system? I I know I and

16:19

many people are thinking, okay, we hear

16:21

like our immune system gets activated or

16:24

our uh our immune system is impaired. Um

16:26

the one thing that I'm certain uh

16:28

supports the immune system is great

16:31

sleep,

16:32

>> right? And we just know this. If we

16:33

don't sleep well or enough, we get sick.

16:36

Is that because there's a a known

16:39

impairment of the immune system?

16:41

>> I I wonder about this too. I mean, I

16:43

agree. I've experienced that so many

16:46

times of being run down and then being

16:48

being feel experiencing that I'm

16:50

susceptible to infection, but I I don't

16:52

actually know the basis of that. I mean,

16:56

it's kind of amazing how much we don't

16:58

know about these determinants of of

17:00

immune health largely because they're

17:02

often variables that are left out of the

17:05

the mouse studies that we're doing.

17:06

We're, you know, we're studying largely

17:08

steady state uh immune responses in

17:12

mice. And I I would say we don't haven't

17:15

done a full exploration yet of all the

17:18

types of ways that general health

17:21

impinges on the immune system. I had a

17:24

someone in my lab a postoc named Sager

17:27

Bapat who came to my lab with an

17:28

interest in in in

17:31

metabolic health and wanted to study the

17:33

effect of metabolic health on on tea

17:35

cells and this there's some subgrowing

17:37

stuff on this but it's another like what

17:39

what are the determinants of it

17:41

>> he did an he did experiments in my lab

17:43

where he exposed

17:47

>> some an allergen something that

17:49

irritated the skin and caused an

17:52

allergic type reaction ction in the skin

17:54

of mice. He did it in mice that were

17:57

eating a normal mouse diet versus a

17:59

highfat diet that caused obesity.

18:03

And what we saw was that it was actually

18:05

not just a qual a quantitative

18:08

difference in the immune system, but

18:09

actually a qualitative difference. The

18:11

actual type of inflammation, the cell

18:12

responses were different in in the mice

18:15

eating a highfat diet. And I think we

18:17

haven't done enough studies like that

18:18

where we actually start playing with the

18:20

variables of life and test them in in a

18:24

mechanistic way to isolate individual

18:27

variants. What was interesting there was

18:29

that the allergic reaction actually

18:32

looked totally different in the obese

18:34

mice and if we used surrogates that are

18:36

for the types of drugs that are being

18:38

used now to treat severe allergy. So we

18:41

gave antibodies that block allergic

18:43

responses. the normal lip diet mice

18:46

would respond favorably to these. It it

18:49

they didn't help the the mice that had

18:51

the obese highfat diet respon response

18:54

to inflammation and in some cases it

18:56

actually maybe made it worse.

18:58

>> So so I think that there are these these

19:00

systemic ways I mean clearly we know we

19:03

our intuition tells us this strongly

19:05

that systemic health can can feed into

19:07

our immune responses but I think it's

19:10

still been underexplored in rigorous

19:13

ways. I realize I'm asking very top

19:16

contour type questions for which there

19:18

probably aren't specific answers, but we

19:20

all know people that um get sick all the

19:23

time. Um and we know people who never

19:27

seem to catch the bugs that everyone

19:28

else seems to catch. Is there any

19:30

understanding of what a more robust

19:32

immune system is at the level? Is it

19:35

more tea cells? Is it um you know are

19:38

the the B cells engaged more quickly so

19:40

they can generate antibodies more

19:42

quickly? What is it?

19:44

>> These are great questions I I that I

19:46

don't think have full full answers.

19:49

>> There are there's been a lot of work on

19:51

genetic determinance and and there's

19:53

extreme cases where people have a

19:54

genetic gap in their immune system where

19:56

they're really

19:58

susceptible to something that healthy

20:00

people should not be susceptible to. And

20:02

you see that there are certain types of

20:03

infections that either happen or happen

20:05

with a different type of severity in

20:07

people with genetic

20:09

deficits in c in certain branches of

20:12

their immune system. And and in some

20:13

cases you can pinpoint that we just

20:15

talked about the innate immune response,

20:17

the adaptive immune response. You can

20:18

see that certain genetic mutations that

20:20

people inherit could influence one or

20:22

multiple branches of that immune

20:24

responses and the consequences that you

20:26

that manifests itself with different

20:28

types of infection. And I suspect that

20:30

there's some spectrum of that that we

20:32

see the the really you can diagnose the

20:33

really strong genetic consequences and

20:35

then there might be a long tail of more

20:37

subtle genetic that might be multi

20:39

multigenic that we don't fully

20:41

understand and then I'm sure that

20:43

there's other determinants of health

20:45

that are just multiffactorial and so

20:49

it's you know it also becomes this

20:50

interplay between the health and then

20:53

what you get exposed to by by your

20:56

environment.

20:57

>> Yeah. Speaking of which, I'm familiar

20:59

with some studies from Stanford, I

21:01

believe, where um kids that have no

21:04

exposure to peanuts get peanut allergies

21:08

and um careful subtle

21:12

>> increasing exposure to peanuts

21:14

essentially um protects them against

21:16

peanut allergies. So, is it true that

21:19

when we're young that exposure to

21:22

pathogens um and different foods uh

21:26

gives us a more robust immune system? I

21:29

think that there's the what we're

21:31

exposed to and what we develop tolerance

21:34

for is is critically important during

21:37

there's some windows of early life that

21:39

I think are we're particularly

21:41

susceptible to becoming tolerant

21:43

>> and I think if we don't get the proper

21:45

exposure to certain things all of a

21:47

sudden our our body can start to be

21:49

hyper sensitive to them which manifests

21:51

as allergies now there's this balancing

21:53

act I think the fear of allergies makes

21:55

people more more hesitant to expose kids

21:57

and I think you can it can get into

21:59

these these dangerous zones of you don't

22:01

want to expose kids who are going to

22:03

have a a dangerous allergic response but

22:06

on the other hand critical early

22:08

exposure is part of how tolerance is

22:10

maintained and I I think peanut

22:11

allergies there there is strong evidence

22:13

that exposure to peanuts can be

22:16

beneficial

22:18

in people who are not yet allergic

22:20

>> what's going on with autoimmune

22:22

conditions

22:24

>> is this that the the B cells and T-

22:26

cells are at probabilistic level that

22:29

tea cells developed um some reaction so

22:32

to speak a binding to um cells that we

22:35

naturally make that they shouldn't have.

22:36

It's just like it happens.

22:38

>> I've always been intrigued by by the

22:40

idea that when the immune system is

22:41

really ramped up

22:43

>> um people will experience autoimmune

22:45

like symptoms. I had experienced that as

22:47

a master's student. I I was working so

22:49

much

22:50

>> and probably not eating enough and

22:53

drinking so much caffeine back then that

22:56

I got some kind of funky skin lesion

22:58

things. I went to the doctor and like,

22:59

"Oh, you're starting to get some attack

23:01

of the deeper layers of of your skin.

23:04

Um, you just need to work a little

23:06

less." And sure enough, did that trick?

23:08

>> It did the trick, you know. But I I was

23:10

just it made me so keenly aware of how

23:13

um the immune system will for lack of a

23:16

better word adapt to conditions and it

23:19

was trying to keep me healthy and it it

23:21

overshot the mark basically.

23:23

>> I sort of walked you through at a first

23:25

principle like how things are supposed

23:27

to work. I told you okay there's this

23:29

process of generating receptors on the

23:32

surface of T- cells. Antibodies get

23:34

generated on B cells. They go through

23:36

this positive selection and negative

23:37

selection. That's a delicate balancing

23:39

act and it doesn't actually work that

23:41

way in practice. In in practice, TE-C

23:44

cells escape from the thymus that do

23:46

recognize our own self antigens and

23:49

there's actually secondary mechanisms

23:51

there to block that. But autoimmune

23:53

diseases emerge when those normal checks

23:57

fail.

23:58

>> This and I think it's a consequence that

24:00

the immune system has two major

24:02

responsibilities. It has to be primed to

24:05

protect us from infections which would

24:07

be fatal and be strong and recognize

24:10

this incredible diversity of potential

24:11

foreign dangerous things that we might

24:13

experience. But it also has to not

24:15

recognize our own cells. And it can miss

24:18

the mark in both ways. And so autoimmune

24:21

disease manifests in different tissues.

24:23

If if you if your immune system starts

24:26

recognizing targets in your joints, it

24:29

can cause rheumatoid arthritis. If it's

24:32

in the cells that produce insulin in the

24:34

pancreas, it causes type 1 or childhood

24:36

diabetes. Um, if it's the my mileinated

24:40

cells in the brain, it's multiple

24:41

sclerosis. So, this is autoimmunity and

24:44

inflammation of different kinds cause

24:47

their own pathology. So, we want to the

24:50

immune system is always these sort of

24:51

two sides of the coin. Making sure that

24:54

we're having strong responses to

24:56

infection.

24:57

We'll talk about cancer where we want to

24:59

also strengthen our responses. But for

25:02

autoimmunity, inflammation, allergies,

25:04

we want to make sure that like our goal

25:06

therapeutically in with drugs is to make

25:09

sure that we make the immune system

25:12

under control

25:14

and ideally do it in a targeted way so

25:16

that you don't have to turn off the

25:17

whole immune system with blanket

25:19

immunosuppression, but to do it in a way

25:21

that just makes you tolerant or not

25:23

reactive against the things that are

25:25

being inappropriately targeted by the

25:27

immune system.

25:28

Two things that I'd love to understand

25:30

about the immune system is uh how is it

25:33

that um an immune response let's say to

25:36

a cold virus is systemic like like where

25:41

is the sort of master uh uh controller

25:44

is it or maybe it's a distributed system

25:46

that says like okay we need to launch a

25:49

a bodywide response as opposed to a

25:51

localized response. I can I can imagine

25:53

like with a splinter, of course, you're

25:54

going to get a localized response.

25:56

>> It's a little piece of wood or metal and

25:58

so you're going to get the innate

25:59

response and you're going to get some

26:00

pus around it and it'll kind of localize

26:02

the wound. But

26:03

>> when it comes to an invasive virus like

26:05

the cold virus, uh it overtakes us,

26:08

right? The production of mucus, we got

26:10

the headache, like the and I think it's

26:11

the systemic effect that um that

26:14

intrigues me so much. like where is the

26:16

signal to to to launch a systemic versus

26:19

a localized response in the immune

26:22

system? How does it determine that? You

26:24

know, I think some of it depends on on

26:25

what virus we're talking about, how

26:27

systemically invasive the the different

26:30

viruses can be, and some of it can be

26:32

that the immune system has different

26:34

levels of, you know, it can have a local

26:36

response, but the immune system, the

26:38

cells that we talked about in the immune

26:39

system, one of their jobs can actually

26:41

be to secrete things into the

26:43

bloodstream, things that are essentially

26:47

chemical signals that something is

26:48

wrong. major ones are they're called

26:51

cytoines and they can act locally but

26:53

they can also have more distributed

26:55

effects and some of the things that that

26:57

that the cytoines can do can influence

27:00

what can cause the development of fever

27:02

right so you you can have these sort of

27:04

cascading effects of something being

27:06

recognized at a particular site in the

27:08

body then sending distributed signals to

27:10

the blood that will make us feel sick

27:12

and you know in some cases there's again

27:14

this balancing act of maybe a fever

27:17

gives us some edge in fighting s some

27:18

some types infection, but it also makes

27:20

us feel lousy. And so the you know the

27:23

the immune system is is always walking

27:24

that I think in sometimes the immune

27:27

system immune system response to

27:28

infections is too strong and a lot of

27:31

the the negative consequence of what we

27:33

experience is the immune system going

27:35

too far and having to come back as as

27:37

the as the as an infection gets under

27:39

control.

27:40

>> Thank you. One of the reasons I asked

27:41

that is well I hate being sick.

27:43

Fortunately I don't get sick too often

27:45

if I take good care which I think is

27:46

like most people. I think about

27:48

antibiotics for instance. Antibiotics

27:50

are amazing.

27:51

>> Yeah.

27:52

>> I've had a few things where I was like,

27:53

"Ah, this thing's bothering me." And uh

27:56

like I had this sinus infection a few

27:58

years back and I was like, "Ah, this is

27:59

definitely not a cold." And then they

28:00

tell you it's not a sinus infection

28:02

unless I was like, "I have a feeling."

28:04

Now, I'm not a physician of course, but

28:06

um it got really bad.

28:08

And I took antibiotics and within a day

28:12

I was feeling substantially better.

28:15

That's great. Many people have such

28:17

experiences with antibiotics. I realize

28:19

they can be overprescribed and you can

28:20

end up with antibiotic resistant

28:22

infections. That's a concern for sure.

28:24

But what is the sort of inherent danger

28:28

of using things like antibiotics the way

28:31

I described like not in a in a life or

28:34

death situation to mitigate the duration

28:37

or the intensity of some sort of

28:39

infection because surely you're

28:41

shortcircuiting your immune system's uh

28:44

ability to eventually just fight that

28:46

thing off. Like is part of building a

28:48

robust immune system across your

28:50

lifespan, allowing your immune system to

28:53

do the work and going through the misery

28:54

of being really sick and infected?

28:56

>> I don't think so.

28:57

>> Great. Okay. Fantastic. Love that

28:59

answer. Love that answer.

29:01

>> I think you probably were exposed and

29:03

had an immune response. Antibiotics when

29:05

they're used for bacterial infections

29:08

that that are susceptible to them are a

29:10

miracle. And you know, we live in this

29:12

amazing sliver of human history where we

29:15

have antibiotics that can cure disease.

29:17

I mean, I think many of us have had

29:20

bacterial infections of different kinds,

29:23

cuts and wounds that would have been

29:25

deadly in other generations. And we're

29:27

we're we're the beneficiaries of having

29:29

antibiotics that work. We are at some

29:31

risk that if we overuse them, that

29:35

window of human history might come to an

29:37

end if we don't continue to replenish

29:38

new antibiotics. But we gain more and

29:41

more bacteria that are resistant to

29:42

antibiotics.

29:43

>> Are people developing new antibiotics?

29:45

>> It's an underfunded area of medicine

29:47

>> because I just hear a moxicil pen. I

29:49

have a friend over in the UK who's been

29:51

having some some eye symptoms that

29:53

>> um from what I'm learning, we're still

29:55

learning is likely an infection uh in

29:58

near the posterior chamber, which just

30:00

simply means his vision is potentially

30:02

at risk. Systemic antibiotics are very

30:04

likely going to save his vision. And so

30:06

people say, well, antibiotics are bad.

30:07

Like a hundred years ago, we probably

30:10

would have just they would have just

30:11

inucleated the eye, which is be blind,

30:13

right? So it's I think they're a

30:15

spectacularly good tool, but it seems

30:17

like there's just a kit of maybe what a

30:20

a five to a dozen very commonly

30:22

prescribed ones. Why aren't people

30:24

developing better, newer, new generation

30:26

antibiotics? Seems like it would be a if

30:29

for no other reason, a trillion dollar

30:31

industry, but also save a lot of lives.

30:34

I don't know whether there's a business

30:35

reason for that or it's but it is an

30:38

underfunded area like it's it's not

30:40

where medicine has has turned enough

30:42

attention and I I do think it's a

30:43

genuine risk.

30:45

>> All right. Well, some entrepreneurial

30:47

young uh guy or gal or both will will

30:50

launch into it.

30:51

>> Um

30:52

>> I want to understand the relationship

30:54

between the immune system and cancer.

30:56

Yeah.

30:56

>> But perhaps first we should talk about

30:58

cancer, what it is and what it isn't.

31:00

>> I think there's a lot of

31:01

misunderstanding out there. um that

31:04

cancer did not exist in uh our

31:08

notsodistant past. I mean you hear this

31:09

like people say oh you know cancer is a

31:11

new thing because of the advent of you

31:13

know all these devices with EMFs and

31:15

radiation. That's certainly not what I

31:17

believe. Has cancer been around a very

31:19

very long time. Do we have evidence for

31:21

that?

31:22

>> Yeah. Yeah. I mean if anyone's really

31:24

interested I I would highly recommend

31:25

this book the emperor of all maladies

31:28

which is a which is really a biography

31:31

of cancer as a disease and talk about I

31:33

mean the long history of going back as

31:37

far as there's records of tumors of

31:39

various kinds and and the misery

31:41

associated with that we have a very

31:44

different understanding of of cancer

31:46

right now right and I think cancer is

31:48

one of the most sophisticated where we

31:49

have one of the most sophisticated

31:51

genetic understandings of disease

31:54

doesn't mean we can always do things

31:55

about it but now we can understand

31:57

mutations that accumulate in in cells

32:00

and all of a sudden so the DNA inside of

32:04

a healthy cell is there programming so

32:07

if you have a skin cell your DNA is

32:09

programming your skin cell to be a a

32:10

skin cell in cancer all of a sudden some

32:14

combination of mutations emerge in that

32:16

cell that

32:19

lose its normal regulation it the skin

32:22

cell is no longer getting the proper

32:24

signals from its DNA to stay in the

32:26

right place and it goes and switches

32:28

into a mode where it's dividing out of

32:30

control and the result is that those

32:32

cells will then transform into cancer

32:34

cells. They'll start dividing. They'll

32:36

lose the normal architecture. The risk

32:38

is that they can disrupt things in the

32:41

in the tissue where they are or that

32:43

further mutations can accumulate and

32:44

they can actually start spreading into

32:46

distant sites in the body and that's

32:48

metastasis. When you when you're when a

32:51

cancer goes from one local site to

32:53

another part of the body and as that

32:55

happens it the those cancerous cells

33:00

it's it's really an evolutionary process

33:01

where those cancerous cells have

33:03

acquired new genetics that are focused

33:06

on their well-being. Those cells are

33:08

dividing. They're growing out of control

33:10

and they're taking the resources.

33:12

They're they're they're growing at the

33:13

expense of the normal coordination of

33:15

the human body. And and that's that's

33:18

really at at its core what what cancer

33:21

is. It's genetic disease where cells

33:23

lose the normal pro uh regulation and

33:27

are dividing out of control in various

33:29

tissues.

33:30

>> I can see the picture in my mind where a

33:33

otherwise healthy cell gets a mutation.

33:36

We can talk about how mutations arise

33:37

but and then starts uh spitting off

33:40

daughter cells as it's referred to.

33:42

>> Yep. Why would the daughter cells

33:44

inherit the mutation necessarily to then

33:47

create more cells because that's the

33:49

prol proliferation of the tumor?

33:51

>> Yeah,

33:51

>> certainly cells propagate their DNA into

33:54

their daughter cells. But um

33:58

I could imagine a situation where every

34:01

day some of our cells get a mutation,

34:03

spit off a couple daughter cells, and

34:05

then those daughter cells are are

34:06

terminal as we say, right? And they

34:08

don't create more cells. Is that

34:10

happening all over the body every day?

34:12

So does this so how is it that a the DNA

34:17

that creates the further propagation

34:19

gets passed from one one cell to the

34:21

next? I do think this is happening

34:23

constantly. It's a process that every

34:25

time a cell is around especially as it's

34:28

dividing there is some imperfection in

34:31

how the DNA the DNA has inside each of

34:34

our cells if that cell is going to

34:36

replicate the DNA has to replicate

34:38

itself. So you end up with two copies of

34:39

DNA that should be the same. Each one

34:42

being passed on to the two daughter

34:44

cells of that dividing cell.

34:47

That process of DNA replication is

34:49

imperfect. And if there's any kind of

34:51

damage during that process, one of those

34:53

two copies might end up different than

34:55

the other one, in which case you end up

34:56

with a mutation now in one daughter cell

34:59

and not the other.

35:01

If that is dilitterious or if it's

35:04

damaging, which probably most mutations

35:06

are, those cells might start to die off.

35:08

Okay. Something got the DNA got messed

35:10

up. Those cells that are carrying that

35:12

DNA die.

35:13

>> Yeah. They can't take up glucose. They

35:15

can't they just can't do cell stuff.

35:17

>> And there's a lot of control mechanisms

35:19

in the cell that say something

35:20

something's wrong. Let's send a a

35:23

programmed cell death signal to that

35:25

cell. And cells will kind of implode

35:27

with with various processes when

35:29

something's wrong. And that that happens

35:31

most of the time. The problem is if if

35:32

if that change all of a sudden starts to

35:36

not be damaging but to actually be a

35:39

signal. Okay, now the cell is is growing

35:42

more. It has some benefit that it's

35:44

accumulated as a result of that

35:46

mutation. Now that cell will start to

35:48

divide more

35:49

>> and that that cell that's carrying that

35:51

first mutation might start dividing

35:53

more. It both of its daughters now will

35:55

pass on this this mutation that's made

35:57

it divide more. And if in subsequent

36:00

rounds it gets a second hit, it that the

36:04

combination may go from just cells that

36:06

are dividing a little bit more to cells

36:08

that take off and become full-blown

36:10

cancer. Now, there's certain processes

36:12

that will accelerate that.

36:14

>> One was exposure to things that cause

36:17

DNA damage, right? The major one is is

36:20

smoking. When smoking causes chemicals

36:24

to go into your lungs, the the lung

36:26

cells get exposed to these chemicals

36:29

that then cause higher amounts of DNA

36:32

damage, more mutations, and just as you

36:34

have more mutations at a higher

36:35

frequency, you're more likely to

36:37

accumulate the set a set of mutations

36:39

that will gradually go on to cause the

36:41

generation of cancer. Another way that

36:44

is that this process can be accelerated

36:46

is that some people carry an underlying

36:48

genetic predisposition to cancer. So

36:51

people you will likely have heard of the

36:54

brocha or the BRCA genes which

36:56

predispose to breast cancer and other

36:58

types of cancer. There people start with

37:00

one copy that's already setting them on

37:03

a road to higher risk of mutations

37:06

accumulating and the whole process on in

37:10

happens with a higher frequency and so

37:12

this this march towards cancer cells is

37:16

more likely to occur in people with that

37:18

type of predisposition. How common is

37:20

the BA mutation? Uh is it equally

37:23

distributed in men and women? Um yeah,

37:27

what can you tell us? And should

37:28

everyone get tested for BA? And there's

37:30

a lot of questions here. I'll ask them

37:32

again one by one. Um and then of course

37:34

we'll talk about things that could be

37:35

protective, not just but certainly

37:38

avoiding smoking would be paramount. So

37:40

how common is

37:41

>> breath? Yeah. So in terms of mut

37:43

mutagens like the big ones are smoking

37:46

>> sun exposure for melanoma. You know I

37:48

know the balancing features of sun

37:50

exposure but

37:50

>> yeah we can talk about that

37:52

>> but but clearly UV is is a risk factor

37:55

for

37:56

DNA damage in the skin.

37:58

>> I mean I'm perfectly happy going on

38:00

record. My the things I've said around

38:01

in sunlight have been contorted so many

38:02

different ways. It's like a pretzel

38:03

twist now. No it's more like one of

38:05

those balloon animals at a party but

38:07

it's not it's a mess. The too much UV is

38:10

bad for for skin cells. It's just bad.

38:13

You need some, but too much is bad. Long

38:15

wavelength light is great uh for and

38:18

therein lies the challenge. But yeah,

38:20

love sunlight, but you don't want

38:21

excessive UV. Don't get avoid getting

38:24

sunburned, folks. Yeah, thank you.

38:26

>> So, yeah, the BA mutation. And I have a

38:29

personal relationship to this cuz I lost

38:31

both my graduate adviser and my

38:33

post-docctoral adviser to bracka

38:35

mutation related cancers 50 and you know

38:38

just a little bit older than 60 and the

38:39

other and you know brutal um especially

38:43

when you you know one of them I know

38:45

they're kids and you know it's um just

38:47

for young people getting cancer and I

38:49

know they're childhood cancers but

38:52

ba seems pretty common.

38:54

>> I don't know the numbers off the top of

38:55

my head. I mean they're not the major

38:58

like numerical causes of of of cancer in

39:01

the scheme of cancers that developed.

39:03

It's it's it's a it's a minority. It's a

39:06

relatively small set number of the full

39:08

set of cancers. The problem is if you

39:10

inherit a broco mutation as an

39:12

individual you have a very high risk of

39:15

developing cancer. So it as an

39:17

individual your risk goes way way up and

39:20

of certain types of cancer in particular

39:23

>> and we can all get tested for it now

39:24

pretty cheaply right.

39:25

>> Yes.

39:26

>> Yeah.

39:26

>> Yeah. That's certainly recommended if

39:28

there's a family history of of cancer

39:30

for broa mutations and a a couple of

39:32

other ones. But you're right it's the

39:35

tests are available. And you asked about

39:37

men and women. Mhm.

39:39

>> It actually was was men were were some

39:43

of the ways that those broco genes were

39:44

identified because it's so rare for men

39:47

to develop breast cancer. The ones who

39:50

did develop it there was a thought well

39:52

maybe there's an underlying genetic

39:53

predisposition and that helped identify

39:55

those genes.

39:56

>> Interesting. Um everyone get tested for

39:59

broa if you know because there are

40:01

lifestyle factors that can reduce your

40:04

cancer risk. I'd like to talk about

40:05

mutagens. Yeah. Um, smoking bad. I'll go

40:09

on record saying vaping bad. Perhaps not

40:12

as bad as smoking, but still way way

40:14

worse than not vaping. Uh, the battle to

40:17

sort of protect vaping is is like beyond

40:20

me. But, um, okay. Uh, to each their

40:24

own. Um,

40:26

environmental sort of and workplace

40:28

hazards, you know, like known mutagens.

40:31

If you work in a laboratory, you're

40:32

working with mutagens, right? You're

40:35

working with things that literally pull

40:36

DNA apart. Yes. This always worried me

40:38

working in a laboratory. There are a lot

40:39

of carcinogenic chemicals in a

40:42

laboratory

40:42

>> for good reason. Yeah. This is the Yeah,

40:44

we're we're trying to study cancer, but

40:46

we're certainly working around a lot of

40:47

things that could cause cancer,

40:49

chemicals,

40:50

>> radiation.

40:52

>> Uh yeah, I don't know if you about you.

40:54

I did a lot of lot of experiments radio

40:56

lababeling cells.

40:57

>> Yeah. I mean we well fortunately we

40:59

worked with

41:01

uh you know radiotagged amino acids with

41:03

radiation that was we were told and I do

41:06

believe was not not as as dangerous as

41:08

some of the others but yeah I mean so

41:11

chemical exposures are a big one. Yep.

41:13

>> And so those those labels on paints and

41:16

thinners and stuff in the garage that's

41:18

real that's a real thing. They mutate

41:20

cells

41:21

>> and there's a you know there's some

41:22

spectrum of stronger and less strong

41:25

ones. And I think oftenimes we're

41:27

operating in an absence of great data,

41:29

but I you know I think there's a lot of

41:31

things are implicated as potential

41:33

mutagens,

41:33

>> pesticides. Yeah, I

41:35

>> you look at cancer rates in in um rural

41:38

areas near where you know crops are

41:40

dusted with pesticides and we've had

41:43

Shauna Swan came on here and she's like

41:45

listen you know the the cancer risks the

41:47

you know endocrine disruptor risks we

41:49

think of as like big cities as as dirty

41:51

and dangerous and they are for certain

41:53

reasons but she said if you really see

41:55

the spikes in uh in these cancers uh

41:59

related to environmental factors it's

42:01

less so bus exhaust than it is

42:04

pesticides.

42:04

>> I mean, it is not evenly or fairly

42:06

distributed. Some people get exposed way

42:09

more to these things and we haven't

42:11

studied them enough. We we need way more

42:13

study to really be able to answer. Okay.

42:15

And and and people shouldn't be left,

42:17

this is my just me just speaking as it's

42:20

kind of amazing to me how much we're

42:22

left on our own to be figuring out what

42:24

the risk of individual products is. And

42:27

I I think it's a place where we should

42:29

be investing a lot more to get clarity

42:32

on where the real risks are.

42:34

>> As many of you know, I've been taking

42:36

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42:39

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42:41

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42:43

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42:45

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42:47

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42:49

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43:07

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43:12

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43:14

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43:15

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43:58

>> I get X-rays at the dentist now and

44:00

again, but I prefer not to get them.

44:02

X-rays cause mutations.

44:04

>> Yeah. Again, there's a tradeoff and the

44:07

dose and I, you know, when you need an

44:09

X-ray, you need an X-ray, but I wouldn't

44:11

do them for fun,

44:13

>> right? Um I mean I have colleagues who

44:16

prefer to do the slower um manual pat

44:20

down at the airport um to going through

44:23

the scanner. It's a low level of

44:25

radiation

44:26

>> is what they tell me. But if you're

44:28

traveling a lot, you're getting multiple

44:31

low-level exposures. And we know pilots,

44:33

and this is for other reasons because

44:35

they're, you know, you can tell us, but

44:37

atmospherically they're exposed to more

44:38

radiation. Cancer rates are higher in

44:40

pilots. Now they're sitting a lot too.

44:42

Prostate kids. Okay. There's a bunch of

44:43

things there, but um do you yourself

44:47

avoid the scanner at the airport?

44:50

>> Honestly, I I do, but I can't say that

44:53

there's data for that. I I feel the same

44:54

way as you. Like if I could avoid it, I

44:56

I try to minimize,

44:58

>> but I that's not based on some inside

45:00

knowledge I have, but I have the same

45:02

>> bias of less seems better.

45:05

>> Yeah. I mean, I'm not out to get the the

45:07

scanner industry. Yeah, just I think

45:09

it's useful for people to hear that that

45:10

you could that one can have no formal

45:13

data but an understanding of mechanism

45:15

that leads them to

45:17

>> to hedge.

45:18

>> Yeah,

45:18

>> it's good to know. Are there any um

45:21

mutagens and

45:23

>> well is a carcinogen and a mutagen the

45:25

same thing?

45:26

>> So they're they're closely related.

45:28

Mutagen I think means that you're

45:31

mutating that you're changing the DNA in

45:32

the cell. That's that's the idea that

45:35

it's those mutations may or may not be

45:37

linked to to cancer, but by virtue of

45:40

the fact that you're causing more

45:41

mutations, almost inevitably you're also

45:43

increasing the risk of cancer and

45:44

carcinogens are things that increase the

45:46

ris rate of cancer.

45:48

>> I love barbecued meat. I don't like

45:50

barbecue sauce because it's sweet, but I

45:52

I like meat with a char.

45:53

>> Yeah. Yeah.

45:54

>> Is the char bad?

45:55

>> I think so. I mean, I like it, too, but

45:58

Yeah. Yeah. Again, these are balancing

46:01

decisions in life. Sure. But yes, there

46:03

there there's some there is I mean meat

46:05

in general has been implicated as a

46:07

potential carcinogen, especially in

46:09

colorectile cancer. There's some data

46:11

around that.

46:11

>> Mhm. Yeah. My read of those data, not

46:14

the char data, but the the me data is

46:16

it's tricky. Um

46:18

>> from my this is just my standpoint. And

46:20

I want to make sure I'm I put you know

46:22

brackets around this that this is my

46:24

read of the literature is that many of

46:26

the studies that looked at

46:28

>> meat rich red meat rich diets versus uh

46:32

plant-based diets. The problem is a lot

46:34

times the red meatenrich diets had a

46:37

bunch of other things in them like

46:39

sourcing wasn't considered. There was

46:40

also a lot of um starches like because

46:44

nowadays you find people who seem to at

46:46

least feel better. Who knows about the

46:48

longevity aspect, but feel better eating

46:50

red meat, fruits, and vegetables,

46:53

limited amounts of starches versus so I

46:55

feel like the nutrition studies are a

46:56

mess. They're kind of a disaster.

46:58

>> I I certainly don't have clarity on

47:01

that. Yeah. Yeah. And they and it seems

47:03

like it changes the the the direction. I

47:06

think some things we have pretty good

47:08

common sense intuition about

47:10

>> fiber.

47:11

>> Yeah. ultrarocessed foods are probably

47:13

bad like you know but I I think the

47:16

balance of exactly what whole foods

47:18

we're eating probably still needs to be

47:20

worked out.

47:20

>> How do you think about the data um on

47:23

like for instance food dyes this is very

47:26

timely um where a certain food dye yeah

47:30

>> at a very very very high concentration

47:32

in laboratory animals creates a

47:34

significantly higher

47:36

>> incidence of of tumors and cancers in

47:38

those animals. But then the amount of

47:41

food dye that's in the human food is is

47:43

is a tiny fraction of that. Um I'm not

47:46

trying to get political here. I just

47:47

think as a framework for people to think

47:48

about

47:49

>> there are many carcinogens I'm sure

47:50

right in this environment. I don't doubt

47:52

that the lacquer on this table in fact

47:54

if that's even what they used um uh if

47:57

ingested could cause um could cause

48:00

cancer. I don't I don't doubt that.

48:02

Right. But I don't know that in its in

48:04

its form here being near it uh for many

48:06

hours a day does that. I I doubt it.

48:08

We're not inhaling the table.

48:09

>> This is what I mean by this this this

48:11

level of confusion. I think we all live

48:13

with this background confusion of things

48:15

some study has been published in in mice

48:18

at whole high concentrations exposure

48:20

does mean anything in our lives. What's

48:22

the relative risk? So that's why I start

48:25

with smoking sunlight and then say

48:28

there's a tail. And I I don't think we

48:29

know fully what that distribution is

48:32

yet. I'm sure there are some combination

48:34

of things that are increasing our risk

48:36

of cancer. We don't really know how to

48:37

weigh uh duration and amount of

48:40

exposure. And this is why I think it's

48:42

really scary to people. People don't

48:43

know, you know, they know smokers who

48:46

don't get lung cancer

48:47

>> and non-smokers who do

48:48

>> and non-smokers who do. And so I think

48:50

people go well like what they it

48:52

actually has caused I I believe a lot of

48:55

um damage in the faith in in medicine

48:57

unfortunately because the messaging is

48:59

all uh is mixed up.

49:01

>> Yeah. I think that nowadays people are

49:03

trying to do what they can to protect

49:04

themselves, but people still get cancer.

49:06

You can do everything right and still

49:08

get cancer. Is that

49:09

>> even if you don't have a bracket

49:10

mutation?

49:11

>> Absolutely. I mean, absolutely. You

49:14

know, I think the last thing you ever

49:16

want to do is like attribute someone's

49:19

actions to to cancer. I mean, it is it

49:22

is a probabilistic disease where some

49:24

set of mutations occur that cause a

49:26

really devastating disease. And so I

49:29

yeah I mean I we don't know the answers

49:32

and I think we have to be humble about

49:33

that. Now what I I think we can also

49:36

talk about is well like how how do we

49:38

handle how do we treat cancer when it

49:39

comes up and this is where these two

49:41

conversations that we've been having

49:42

really come together of when talking

49:45

about the immune system. We went through

49:46

a lot of I think I mean actually we went

49:48

through a lot of sort of detailed

49:49

mechanism thinking about the different

49:51

cell constituents of our immune system.

49:54

I will tell you that when I went to

49:56

medical school, which wasn't that long

49:58

ago, I graduated in 2010,

50:02

the dogma was don't waste time thinking

50:05

about cancer immunology.

50:07

Cancer immunology is a field that's

50:09

going nowhere.

50:10

>> I mean, I think I I I was in Boston. I

50:13

think that was a maybe there was some

50:14

local bias in that direction, but this

50:16

was not the mainstream of thinking about

50:18

how we would treat cancer

50:20

>> at that point. that the way the cancer

50:21

was being treated was chemotherapy,

50:24

which you know is something that's been

50:25

around for decades. And it's basically

50:27

give toxins to the body that will be

50:30

more toxic to the cancer cells than to

50:32

the healthy cells. And ask people to

50:35

endure all the side effects because they

50:38

have to to get rid of the cancer cells.

50:39

And that's still the mainstay of of of

50:42

cancer treatment. We all want to do

50:45

better than that.

50:46

>> It's very unpleasant. Very very

50:48

unpleasant.

50:48

>> Unpleasant and and worse. I mean I mean

50:50

people endure hor you know it's it's we

50:53

put put we put people through horrific

50:55

things because it's the best we can do

50:57

>> and then there was a wave of thinking

51:00

okay well let's try to make drugs that

51:02

are targeted to the mutations that we

51:04

talked about and that was that was the

51:06

hot thing that was the promising avenue

51:08

when I was in medical school of like

51:10

okay now we we've really measured that

51:12

these are mutations that accumulate

51:13

inside of cancer cells this is what's

51:15

causing cancer let's let's make drugs

51:17

that go after those things And turned

51:20

out that that was although a lot of good

51:23

has come from that people have extended

51:25

lives, cancer has a way of working

51:28

around that. And

51:29

>> so these are cell cycle inhibitors.

51:31

>> So signaling thing various mutations

51:34

affect this these growth properties of

51:36

of cells and there's targeted drugs that

51:39

have been designed to go after some of

51:41

those pathways that are making the cells

51:42

divide out of control. Yeah, I think

51:46

that benefit has come but cancer has

51:48

ways of mutating around that and become

51:50

developing resistance. The same way we

51:51

talked about resistance in bacteria to

51:53

antibiotics if they're exposed you can

51:56

cancer cells are can evolve quickly and

51:58

can become resistant to these targeted

52:00

modifications.

52:02

What has emerged as a whole new way of

52:05

thinking about going after cancer is

52:08

using the power of the immune system

52:09

that we talked about at the beginning

52:11

and redirecting that against cancer

52:14

targets.

52:15

This has changed how we think about

52:17

cancer treatment. It's the hope is that

52:20

all of we tal we we talked all of us

52:22

have this immune system that goes

52:23

through every organ in our body. It

52:24

circulates. We have white blood cells

52:26

that are constantly going around and

52:27

looking for things that shouldn't be

52:28

there.

52:30

Can we unleash that immune system

52:33

against cancer?

52:35

And the hope would be that the cells

52:37

that our immune system, we've talked

52:38

about how they're really exquisitly

52:39

evolved to make a determination of this

52:42

is a healthy cell, this is not a healthy

52:44

cell, this this cell should be here,

52:45

this should not.

52:46

>> If we could get that level of precision

52:49

where we could have a durable immune

52:51

response that gets rid of the cancer

52:52

cells but leaves the healthy cells

52:54

intact, that is what we want. Mhm.

52:57

>> Now that is not science fiction and has

53:00

is is now approved and used to treat a

53:03

number of different cancers. The first

53:05

place where this happened was in a class

53:08

of medicines called checkpoint

53:10

inhibitors.

53:11

>> Um or amunotherapy drugs uh a lot of a

53:15

lot of people will have heard of these

53:17

things. PD1, CTLA4 are some targets

53:20

where there are drugs that get infused

53:23

that hit these things that are on the

53:25

surface of TE-C cells and they actually

53:28

are natural breaks to the TE- cells.

53:31

Te-E cells might be in our body there

53:34

but turned off or not turned on enough

53:37

to be strong enough against cancer. And

53:39

for certain types of cancer, it's been

53:41

absolutely miraculous that if you make a

53:44

drug that hits the break on the on the

53:46

tea cells, the tea cells go stronger and

53:49

they can be unleashed against cancer

53:50

just by taking the brakes off of them.

53:53

>> What sorts of cancers has it been

53:54

successful for?

53:55

>> The poster child for this has been

53:57

melanoma. Mhm.

53:58

>> One of the big success cases was was

54:01

Jimmy Carter who had a melanoma which is

54:03

a skin cell aggressive skin cancer that

54:06

had already gone to his brain which was

54:08

thought of as a death sentence and he

54:10

got treated with checkpoint inhibitors

54:12

and basically was cured.

54:15

>> Amazing.

54:15

>> Um and so you know they saw these tumors

54:18

just shrink away and in and not just him

54:20

but in a in a large fraction of of

54:22

melanoma patients now respond to these.

54:25

And so that that has changed how

54:27

melanoma is treated. It's and other

54:28

cancers to varying degrees because some

54:32

types of cancers can respond to this.

54:34

That's taking the a drug that unleashes

54:37

the tea cells that are already in our

54:38

body. The focus of my research in is

54:40

well

54:42

the first thing I said was we're living

54:44

in this amazing moment of biology where

54:45

we can we can do things to cells in our

54:47

body that with incredible precision and

54:51

and we're often just limited by our

54:53

imagination. And what we can see now is

54:56

that we don't actually have to just be

54:57

limited to the cells that the tea cells

54:59

that are natural in our body that

55:00

already have this random distribution of

55:02

sensors. We can actually genetically

55:05

make a a one of these sensors for tea

55:10

cells and put it into te- cells. We can

55:13

put in put a gene that encodes something

55:16

on the surface of tea cells that will

55:19

make them programmed to search and

55:22

destroy for cancer cells.

55:24

>> Now, this is this is largely known as

55:28

chimeriic antigen receptor tea cells.

55:30

That's a long term. They're known for

55:33

short as CART cells, chimeriic antigen

55:35

receptor. And what that means chimeic is

55:38

that these are stitched together. This

55:39

is a receptor that was designed in a

55:41

lab, does not exist in nature, but can

55:44

be put into a piece of DNA, delivered

55:47

into a TE-C cell, and when that DNA goes

55:50

into the genetic code of the T- cell,

55:52

all of a sudden the T- cell will start

55:54

making proteins that go on its surface

55:56

and act as these artificial sensors. And

55:59

those cars then when those tea cells get

56:02

reinfused into a patient the way that

56:04

you get like a a blood transfusion

56:07

those cars are directed to go against

56:08

cancers. This has been done for certain

56:11

types of leukemia and lymphoma. And

56:13

there's been these amazing success

56:15

stories. The thing that woke up me and

56:19

the world was in 2012

56:22

there was a young girl who was the first

56:25

pediatric patient to be treated with a

56:26

cartis cell for for cancer. So she she's

56:30

become a heroic figure uh Emily

56:32

Whitehead. She was I think eight at the

56:34

time and she had a form of leukemia that

56:38

hadn't resp it just was for some reason

56:40

whatever reason it failed all the

56:42

treatments and it just nothing worked.

56:46

She was going to be sent home on

56:47

hospice. She had exhausted all the

56:50

possibilities at the age of eight and

56:52

she got enrolled in a at that time

56:55

highly experimental treatment to get

56:56

these CAT tea cells. So her blood cells

56:59

were taken out in a big blood donation.

57:02

her own tea cells were genetically

57:03

modified and we could talk about how

57:05

that was done. It's actually done with

57:06

like a pretty crude technique that's

57:08

been around actually used viruses,

57:11

lentiviruses. These are sort of modified

57:13

HIV viruses to deliver this extra piece

57:16

of DNA that encoded the car. And this

57:20

was done on her cells. And then after

57:22

that extra gene was put into the tea

57:25

cells, the tea cells were reinfused into

57:27

her body. And it was not a

57:31

straightforward course. She she ended up

57:33

in the ICU. The immune system had to we

57:35

people in real time people had to figure

57:36

out how to control the immune systems

57:38

and the side effects. But as that was

57:41

controlled, all of a sudden the her

57:43

cancer cells disappeared.

57:45

>> Amazing. And the lentivirus itself

57:46

didn't uh didn't spark a an immune

57:49

reaction that was

57:50

>> that outweighed the benefits of of the

57:52

cargo.

57:53

>> No, amazingly it really hasn't. I mean

57:55

there there's been some discussion about

57:57

the risks of using these lentiviruses

57:59

and we we'll talk in a second about how

58:01

we can do better now.

58:02

>> Yeah. People are going to hear uh

58:04

putting viruses into cells and putting

58:05

them into humans and a bunch of people

58:07

will freak out. But I I promise you that

58:08

things like adeno, which is like a cold

58:10

virus, or lenti, which is similar to

58:12

HIV. And of course, they didn't give her

58:14

HIV. They changed the virus, so they're

58:16

not delivering HIV. These viruses are

58:19

incredible because they can create

58:22

longlasting expression of genes that you

58:24

deliberately put into them. They're a

58:26

shuttle.

58:27

>> It's an amazing application of

58:28

biological understanding, right? that

58:30

all of a sudden we've been studying

58:32

viruses because of the risk that they

58:34

have, but we've learned that they can

58:35

deliver that that viruses have evolved

58:38

to be very good shuttles

58:39

>> and to deliver their genetic material

58:41

into cells.

58:42

>> The way I think of it uh that is the

58:45

viruses have evolved to take advantage

58:48

of our biology and our genes. And so we

58:51

did the ultimate touch in these

58:53

instances like you're so good at at

58:55

hijacking our cell's DNA and

58:57

proliferating. All right, we'll leverage

59:00

you to help us as opposed to hurt us.

59:02

Right.

59:02

>> That's exactly right.

59:04

>> And so that was done in 2012. Emily

59:07

Whitehead was eight.

59:09

It was done as an experimental treatment

59:11

at the University of Pennsylvania. And

59:13

the story now is that now all these

59:17

years later, Emily White is not only

59:19

cured of her leukemia, she's premed at

59:21

the University of Pennsylvania.

59:23

>> So awesome.

59:24

>> And so no one could ignore that. You

59:26

know, this was this wasn't this was just

59:28

all of a sudden this dogma that I had

59:30

just been taught a couple of years early

59:31

in medical school that we should ignore

59:33

cancer amunotherapy. It was just we were

59:35

just wrong.

59:36

>> And all of a sudden the field woke up

59:38

and said, "Okay, the immune system is

59:40

not just limited to treating viruses and

59:43

bacting us from viruses and bacteria.

59:45

The immune system can be exploited and

59:47

potentially re-engineered to protect us

59:49

from cancer and maybe other diseases."

59:52

So that was 2012.

59:54

2012 also was the year that a paper got

59:58

published in science by Emanuel

60:00

Sharpantier and Jennifer Dana that

60:03

introduced this new technology called

60:04

crisper

60:06

and we can we'll talk about this but

60:09

crisper

60:11

fundamentally is a tool to rewrite DNA

60:14

sequences that came out in 2012

60:17

and on a personal level 2012 was also

60:20

the year that I moved to San Francisco

60:22

to start a lab studying tea cells and

60:25

how genetics influences te- cells. I was

60:27

looking around and trying to figure out

60:29

what my lab would do and all of a sudden

60:31

I was arriving with a empty lab space at

60:34

exactly the same moment that that the

60:37

world was shown that te- cells could

60:38

cure cancer and that we had a tool that

60:42

could potentially rewrite DNA sequences

60:43

and that we wouldn't be limited to these

60:45

lentiviruses which are kind of clunky

60:47

the best tools we had at the time but

60:49

pretty clunky and non-precise in how

60:50

they insert genetic material. All of a

60:52

sudden, we could imagine that we could

60:54

take tea cells and use crisper to

60:57

actually pick individual places in the

60:59

genome and make targeted changes to

61:02

program exactly how cells behave. And

61:04

that is the basis for my ongoing work.

61:07

We've put a lot of work over the years

61:09

into being able to now take crisper

61:12

technology, get it to work in TE-C cells

61:15

to learn the rules about what are the

61:16

genetic changes that will be most

61:19

effective at making TE- cells into

61:22

into amunotherapies that cure patients

61:24

for with different diseases and then to

61:27

go all the way and then actually use

61:29

crisper to make tea cells that can be

61:33

input into patients with new levels of

61:35

precision and power and that's that's in

61:38

clinical trials now. We're now in

61:40

clinical trials with these crisper

61:42

engineered CARTT cells and we're not

61:45

just going after leukemias where these

61:48

CARTT cells have historically worked but

61:50

we're also thinking about can we make

61:53

these work for the really common causes

61:55

of cancer deaths solid tumors and that's

61:59

been a challenge and we can talk about

62:00

that but getting tea cells to find the

62:03

right targets in tumors and then work

62:05

inside of tumor environments which are

62:07

inherently imunosuppressive

62:09

requires figuring out additional gene

62:11

edits that are now possible with crisper

62:13

to try to beat the cancer at its own

62:16

game. If cancer is evolving to to make

62:18

itself cloaked from the immune system,

62:20

now with crisper, we can think about

62:22

getting one step ahead and making tea

62:24

cells that are able to be resist all the

62:26

tricks that cancers throw at it to be

62:28

more and the I think we're on the brink

62:30

of having precise crisper engineered

62:33

cells that will I I hope start to melt

62:37

away cancers without the side effects of

62:39

chemotherapy.

62:41

>> Amazing. Uh just amazing. And the story

62:44

of this young woman is spectacular. Um,

62:48

>> I have two questions before we talk

62:50

about crisper technology. The first one

62:52

is, is it true, I believe it is, but is

62:55

it true that cancer risk goes up as we

62:58

get older?

62:59

>> And if so, why? Um,

63:03

so that's the first question. And then

63:05

uh the other question has to do with how

63:08

the the amunotherapy that you described

63:11

um was able to target the cancer and and

63:14

not cause problems elsewhere which is

63:16

kind of the major issue of chemo and

63:18

radiation therapy. But the first

63:19

question um again was you know why more

63:23

um mutations as we get older. So I think

63:25

there's there's a few cancers that that

63:27

peak in childhood and there's risk as as

63:30

the body's developing of certain cancer

63:31

childhood cancers and there's childhood

63:34

leukemas for example then that like when

63:36

we talk about Emily Whitehead but most

63:38

cancers as you said exactly as you said

63:40

that there's this sort of increase and

63:42

they're largely disease of later stages

63:44

of life. I think that the reason for

63:47

that is remember when we talked about

63:49

what causes cancer it's this evolution

63:52

where c cells start to accumulate

63:54

mutations numerically a lot of the cells

63:56

that have the mutations will die off and

63:58

it's just a game that unfolds over time

64:01

and the more time you have cells

64:02

dividing and sticking around in the body

64:04

they're accumulating more damage and

64:06

eventually you're more likely that that

64:07

damage would actually transform the

64:09

cells into a cancer cell. So time is is

64:12

is is a big factor here. time and just

64:15

accumulated damage.

64:16

>> And the other question was, you know,

64:18

how is it that the lentivirus knows to

64:21

um the lentiviral

64:24

uh cargo carrying tea cells uh know to

64:28

attack the cancer and not something

64:31

else.

64:31

>> So this is a key question for the field,

64:33

right?

64:34

And I think one of the things that

64:36

worked incredibly well was a brilliant

64:39

choice by a group of scientists in

64:40

different a few different places that

64:42

converged on the target that was used in

64:44

the first CARTT cell. And what the

64:47

target is known as as is is a protein

64:50

called CD19.

64:52

>> That's just the name of this thing

64:53

that's found on a lot of different types

64:56

of B cells. So this brings us back to

64:58

this discussion. the the leukemas

65:00

themselves are a disease, a cancer of

65:03

the immune cells. So they're cancer of B

65:05

cells and CD19 is is found on the on the

65:09

surface of many a large number of

65:12

different types of B cell leukemas and

65:15

lymphas.

65:15

>> I see.

65:16

>> I think one of the things that turns out

65:17

to be serendipitous here is that B cells

65:21

themselves natural healthy B cells

65:23

actually also have CD19 on their

65:25

surface. What just turns out to be

65:28

serendipitous is that the body can

65:29

tolerate those cells going away. And so

65:33

what has made this a particularly

65:34

effective and safe and relatively well

65:37

tolerated treatment for cancer is that

65:40

the collateral damage is actually not

65:42

that damaging. That te- cells in this

65:44

case are not strictly distinguishing

65:46

between cancer and health. They're not

65:48

just getting the leukemia cells. They're

65:50

they are getting collateral B cells. But

65:53

by and large to a first approximation,

65:55

people can live without those cells. And

65:57

so that side effect has just been

65:59

tolerable.

66:01

Finding that balance gets harder and

66:03

harder for more cancers. Right? If you

66:06

start to think about pancreatic cancer

66:09

or brain cancer, finding targets that if

66:12

you hit the healthy pancreas or the

66:15

healthy brain are not toxic, it's it's

66:18

harder and harder. So people are

66:19

thinking about more and more

66:20

sophisticated ways to look for these

66:23

targets that are selectively found on

66:25

the cancer cell and not on the healthy

66:26

cell or to think about ways that you

66:29

might actually make the cell depend on

66:31

recognizing multiple features so that

66:34

you can have what's sometimes talked

66:35

about as like a two-factor

66:36

authentication like the T- cell will

66:39

only kill cancer if it finds this and

66:41

this and that combination of things are

66:43

not found on healthy cells even if one

66:46

or the other might be. So people are

66:48

thinking about how do we

66:50

>> get more sophisticated about building

66:52

these discrimination systems into tea

66:54

cells. The building blocks are there but

66:56

the specifics for each cancer have to be

66:58

invented but but we have the tools to do

67:01

that.

67:02

>> Awesome. Before we talk about crisper

67:04

there was one other question that I know

67:05

many people will be thinking about. Uh a

67:08

few years back, maybe five, ten years

67:10

back, there was a a lot of discussion,

67:12

maybe even some enthusiasm about

67:14

ketogenic diets to treat or prevent

67:18

cancer. And my understanding from

67:21

looking at that literature was that for

67:23

some cancers it perhaps, I want to bold

67:27

uh underline and and capitalize perhaps

67:29

um might help, but for other cancers it

67:33

could make things worse. And then uh I

67:36

also more recently started hearing about

67:38

uh low glutamine diets. Um so and of

67:41

course this is the way the internet

67:42

works but um but I did see some papers

67:44

in some decent journals you know uh that

67:48

at least we're exploring this. So are um

67:52

low they're just low carb let's call it

67:54

what they are ketogenic diets um have

67:56

they been shown to be useful for

67:58

treatment or avoidance of cancer?

68:00

>> I have to defer to you. I actually I

68:01

don't I don't know the answer to that.

68:02

Yeah.

68:03

>> Okay. My my guess is that um people are

68:05

still looking at this, but you know

68:06

there was also the idea that they could

68:07

be useful for um certain forms of

68:09

dementia. There was an effort to call

68:11

dementia, you know, type three diabetes,

68:13

but my understanding from talking to the

68:15

experts in this is that um it might help

68:17

through indirect mechanisms, but that

68:19

it's not going to solve the problem. Um

68:22

okay. Well, thanks for entertaining that

68:24

little uh culde-sac that I created.

68:27

>> Crisper, tell us the story of Crisper.

68:30

Uh because I think crisper is one of

68:32

those funny things in biology and

68:34

medicine that almost everybody has heard

68:36

about in the general population. Most

68:39

people know it has something to do with

68:41

changing genes, but it's sort of like

68:43

AI.

68:45

>> Yeah,

68:45

>> it's here. Uh it's powerful. It scares

68:48

certain people. It excites other people.

68:51

Um but most people don't know how it

68:54

works because there's really no

68:55

incentive to. But I think the story of

68:58

Crisper is actually also a story about

69:01

uh how science works

69:04

>> and that's important too.

69:05

>> I think it's exactly true. I think it is

69:08

a perfect illustration of something

69:11

where a discovery happened that no one

69:14

was planning

69:15

>> but changed biology. Um

69:19

let me tell this story in two separate

69:21

arcs. One arc is the arc of

69:23

understanding DNA. You know, if you go

69:25

back to Watson and Crick, it's

69:27

understanding the double helix to

69:29

understand the structure of the DN what

69:31

a DNA sequence is that mature as we

69:33

learn how to sequence to understand the

69:36

to be able to measure a row of ATS and

69:39

C's and G's that in whatever combination

69:41

they are will start to be the building

69:43

blocks for programming which proteins

69:46

get made inside a cell. And then around

69:49

2000, we get to the first draft of the

69:51

human genome, which is this

69:53

multi-billion dollar project across the

69:55

world to come up with a draft of one

69:58

human genome sequence

70:00

milestone for for biology and medicine.

70:04

And then DNA sequencing technologies

70:06

continue to improve and cost comes down.

70:09

We're getting to the point where we can

70:10

start to measure big chunks of our DNA

70:13

at increasingly affordable costs. And

70:16

people were starting to understand the

70:18

differences between people with DNA at

70:21

the level of at least statistics. Okay,

70:23

people with this disease are more likely

70:25

to have this this gene than that. But

70:28

we're getting to some limit of what we

70:30

can do just by sequencing DNA. All of a

70:33

sudden, you you're observing the DNA

70:34

sequence that's in someone's cells, but

70:37

you don't really know what those effects

70:39

are. Just as the sequencing world is is

70:42

maturing,

70:44

we're desperately looking for a tool to

70:46

say, well, now we want to as we have all

70:48

the sequences, we want to be able to see

70:50

what happens if you change a sequence.

70:52

And people were stumbling around looking

70:54

for

70:56

different tools. There were there were

70:58

there was a range of these things. There

71:00

were zinc fingers. that people

71:01

lentivirus was another one that we just

71:04

talked about that with different degrees

71:06

of efficiency and people were trying to

71:09

to be able to change DNA sequences and

71:11

cells and it had been a long-standing

71:13

effort.

71:15

Out of nowhere emerges crisper as the

71:18

answer to this problem. crisper was

71:21

being studied as an an

71:25

interesting and unusual set of DNA

71:28

sequences that were found in certain

71:30

types of bacteria.

71:32

There were these repeated sequences and

71:34

no one knew what they were. And people

71:36

out of real basic curiosity about what

71:38

was happening in bacteria started

71:40

studying these repeat sequences and what

71:42

they were doing. And little by little by

71:45

little it was worked out that these

71:47

repeat repeat sequences actually ba

71:49

formed the basis of a kind of immune

71:52

system for bacteria.

71:54

>> Now we talked about the human immune

71:55

system. Bacteria are just an individual

71:57

cell but they're also susceptible to

72:00

infections which is a sort of a strange

72:01

idea. Bacteria cause infections in us

72:03

but there's this arms race between

72:05

organisms.

72:06

>> Everyone's trying to kill everyone else.

72:07

>> And so bacteria are constantly being

72:09

bombarded by certain types of viruses.

72:12

They're called bacteria phagee viruses

72:15

and they've evolved a series of bacteria

72:19

have evolved a series of defense

72:20

mechanisms to protect themselves from

72:22

from these viruses. Crisper turns out to

72:25

be a bacterial defense mechanism against

72:27

viruses

72:29

which is kind of amazing that this that

72:31

this thing that has entered into popular

72:33

culture is a bacteria protection against

72:36

bacteria phage. Now why has this caught

72:40

the world of biology by storm? Well,

72:42

what was realized was that the way that

72:45

that crisper works to protect against

72:47

itself

72:49

um the protect bacteria from viruses is

72:52

that it can recognize particular

72:54

sequences of DNA which are virus

72:58

sequences and discern discriminate

73:00

whether it's a virus sequence or its own

73:02

bacteria sequence

73:04

>> and it actually does that by scanning

73:07

across the DNA and finding something

73:09

that's recognized as a virus target and

73:12

not a bacteria target. And when it finds

73:14

it, it makes a cut.

73:17

Okay, now this sounds technical obscure,

73:22

but what was recognized and this became

73:25

the basis for a Nobel Prize of of with

73:28

Jennifer Dow and Emanuel Sharpentier.

73:30

Many people around the world have

73:31

contributed to this field. Um what was

73:34

realized was that this could be

73:36

repurposed

73:38

as a tool. If we take it out of

73:40

bacteria, we could actually exploit this

73:42

with this crisper system that had

73:44

evolved to protect bacteria. And the

73:46

same rules that allowed bacteria to to

73:50

scan across DNA and find a virus

73:52

sequence and cut it could be used to

73:55

scan across any DNA and cut at a

73:57

particular sequence.

74:00

That's the power of crisper. Now, why do

74:02

we care so much about being able to cut

74:03

a particular sequence? If you can cut,

74:05

you can also start pasting. You can cut

74:07

out genes that are limiting the that you

74:09

don't you don't want to be in a cell.

74:11

You can start pasting in sequences to

74:14

replace mutations that cause disease. We

74:16

can start pasting in big sequences like

74:19

the sequence for cars or other types of

74:21

things that will make TE- cells more

74:22

powerful. So, and this is I'm I'm

74:25

focused on TE-C cells, but this is in

74:27

now in every aspect of biology. People

74:30

are studying this in plants and to make

74:33

crops that will be drought resistant.

74:36

People are studying this in in in every

74:38

organ system to understand every type of

74:40

disease and to build new new types of

74:42

molecular medicines.

74:45

There's one other feature of crisper

74:47

that's that's really important in this

74:48

story. It's not just that this crisper

74:51

can cut at a specific sequence that it's

74:53

evolved to cut at virus sequence. It's

74:55

the way that it cuts that has made it

74:57

really catch on in a way that none of

74:58

these earlier technologies do. So

75:01

crisper, if you think of it as a it's an

75:03

enzyme that can cut DNA

75:06

and it it can cut essentially almost any

75:09

sequence of DNA. So how does it decide

75:12

which sequence to cut? It does it by

75:15

actually pairing with an RNA molecule.

75:18

So crisper

75:20

sometimes called cast 9 which is a

75:22

particular type of crisper system um is

75:25

a is a combination of a protein which is

75:28

a scissor and then an RNA that sticks to

75:31

it and the RNA is what actually programs

75:35

where that scissor will cut. Okay. So

75:38

this and and what's so special about

75:40

that is that we actually know with

75:42

perfect nearperfect precision the rules

75:46

of how an RNA will recognize any DNA

75:49

sequence. There's a complimentarity

75:51

where you you can match up and know

75:54

exactly which RNA you want to design. So

75:57

you can now cut DNA sequences at will.

76:00

And it's gotten to the point where now

76:02

if we want to cut a piece of DNA, we

76:05

order a piece of RNA off the internet.

76:08

It shows up in in in the lab in a matter

76:10

of days. We mix it with cast 9 protein

76:13

and then that's going in tea cells the

76:15

next day and we're able to introduce a

76:18

cut into any DNA sequence. So now you go

76:21

back to the genome sequence that was

76:24

came out in 2010 and all of a sudden you

76:26

can go on the internet, pick a place in

76:28

the genome that you're interested in

76:29

studying, order a piece of RNA, make

76:32

your your targeted crisper molecule and

76:34

make a cut or a cut and a paste at that

76:37

particular site and then in a very

76:40

tangible way read out the consequences.

76:42

you're going into the source code of DNA

76:46

inside of a cell and you can when you

76:47

make that change you can say what what

76:50

happens to the cell. Does it is is it a

76:52

stronger response? Is it a different

76:53

response? We can test it in test tubes.

76:56

We can test it in models of disease and

76:59

then as we learn the rules we can

77:01

actually take those crisper modified

77:03

cells all the way and infuse them into

77:06

patients.

77:07

>> Incredible. and thank you for that

77:08

incredibly clear and detailed um

77:12

explanation of the crisper cast 9

77:14

system. A couple of questions. How

77:17

precise is the cut? Are you damaging

77:21

adjacent nucleotides or can you home in

77:24

exactly on the site that you want to

77:27

cut? And then if the related question is

77:29

if you're going to introduce a gene

77:32

sequence there um how do you ensure that

77:35

there aren't downstream effects? I mean,

77:37

I think what you're getting at with both

77:39

these questions are unintended

77:40

consequences and that's always present,

77:43

right? I think this has been a major

77:46

concerted effort for the field of

77:47

crisper. How do you get more and more

77:49

precise and it's come a long way, but

77:53

nothing's perfect, right? So, I think

77:55

we've done a lot the field has done a

77:57

lot of work to test offtargets, right?

78:01

If you're programming to cut on one

78:03

place on chromosome 6, do you actually

78:06

evidently accidentally ever cut anywhere

78:08

else? And there's a range. Sometimes

78:10

some sequences are a little bit more

78:11

promiscuous than others. But we've

78:13

gotten quite good at getting more and

78:15

more precise to say, okay, we're making

78:17

these high fidelity cuts that at at one

78:20

place.

78:22

There are still the second risks of

78:25

bystander effects. Okay, you make a cut.

78:27

What does the DNA get chewed back? And

78:30

at the neighboring part, there's been in

78:31

some extreme places pieces of

78:33

chromosomes actually falling off. I all

78:35

these things can happen. And I think

78:39

what we're kind of at a place in a field

78:40

where now we're thinking about for each

78:42

disease a risk benefit of okay, there's

78:45

going to be there's always a risk for

78:47

any medicine of some unintended

78:48

consequences. We have to be on the

78:50

lookout for them. We have to know what

78:52

what they are. Most cells, as we said,

78:54

that get a mutation don't have a

78:57

problem. They just die off. So if you

78:59

have an unintended consequence, most

79:00

will die. But there is always the risk

79:02

of the unintended consequences. And I

79:04

think as a field, we have to be humble

79:06

about that.

79:07

>> That said, the the the crisper world is

79:09

not static. And what I what I the story

79:12

I told you was like the building block

79:14

of crisper. It's a protein scissor that

79:18

can be targeted to any piece of DNA with

79:20

an RNA molecule. people

79:24

are appropriately thinking well scissors

79:26

can cause damage.

79:28

>> Maybe that that crisper molecule should

79:31

actually be re-engineered not to be a

79:33

scissor but to do other things. And now

79:35

people have started engineering it to

79:37

say well let's not make it a scissor.

79:38

Let's make it a thing that just

79:39

introduces a more predictable mutation

79:42

at a site. David Louu at Harvard has

79:44

created these things called crisper base

79:45

editors that doesn't introduce a

79:47

doublestranded break but actually

79:49

changes nucleotides in a more

79:51

predictable way at that site by

79:53

recruiting a damnase domain something

79:56

that will change DNA nucleotides when

79:59

it's recruited to a particular place and

80:00

you use crisper just to recruit that

80:01

enzyme that makes that mutation at a

80:04

targeted place other people have

80:06

actually started using epigenetic

80:08

enzymes that DNA doesn't just get

80:11

enacted by DNA sequences but can

80:14

actually pieces of it can be active or

80:16

inactive and this is called epigenetics

80:18

where there can be a stable program of

80:21

things getting turned on or off without

80:22

any change in the A's and T's and C's

80:24

and G's and now we and other others are

80:28

using crisperbased

80:30

epigenetic editing it's called

80:32

epiediting where we don't make any cut

80:35

in the genome but we just turn on or off

80:38

and it's in a large part to think about

80:40

mitigating some of these risk risks that

80:42

might come with the scissor function.

80:44

Instead, all of a sudden, we're thinking

80:45

about we're using the same building

80:46

block of recruiting an enzyme to a

80:48

particular place in the DNA code, but

80:51

using the full set of things that we

80:53

might do at that DNA site to program

80:55

cells in the most precise possible way.

80:58

I'd like to take a quick break and

80:59

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82:16

to claim a free sample pack. I'm curious

82:18

about getting crisper into the cells of

82:22

interest. Yeah,

82:23

>> you know the lentivirus example that you

82:25

gave before um my understanding is it

82:28

involved harvesting some tea cells um

82:31

introducing the lentivirus with the you

82:34

with the cargo that you want putting

82:37

that back into circulation and the tea

82:39

cells know where to go and know what to

82:41

do. uh for a lot of cell types like

82:44

neurons in the brain, uh liver cells,

82:47

pancreatic cells, um

82:50

I could imagine a surgery where you

82:52

inject directly into those organs, but

82:55

uh wouldn't it be wonderful if you could

82:57

um get the cells of interest from, you

83:00

know, without having to be so invasive?

83:02

Um so what's being done there in terms

83:05

of trafficking um

83:08

crisper 2 appropriate cell types or

83:10

andor or organs and then that uh sort of

83:13

seeds another question that I'll I'll

83:15

hold off on about whether we should be

83:16

banking uh cells or or uh for what's

83:20

coming.

83:21

>> First of all, I just want to pause for

83:22

this this is this is great. I love this

83:24

conversation.

83:24

>> No, I do too. I mean, you're taking us

83:27

to the the

83:28

>> I don't like the phrase bleeding edge.

83:30

sounds of violent, but you're taking us

83:32

to the cutting edge of molecular biology

83:34

and medicine and we are peering over

83:37

into what's next like what your children

83:40

and my children and are probably our

83:42

parents also will uh be able to benefit

83:45

from in the next 10 years maybe sooner.

83:48

>> Yeah, we're really talking about things

83:49

that are happening now and and happening

83:51

at an accelerating rate. So you asked

83:54

part of what just got made me have that

83:56

reaction was I think you asked one of

83:57

the key questions for this field of how

84:00

is this being delivered into cells. So I

84:03

told you let me go backwards and then

84:05

I'll go forward. I told you that in 2012

84:08

I sort of was sitting there thinking

84:10

about I wanted to study tea cells the

84:11

genetic control of tea cells. I saw the

84:13

power of carti cells. They saw the power

84:15

of crisper, which at that time was being

84:17

only used in highly artificial

84:20

immortalized cell lines that grow easily

84:22

in the in the lab. And it just wasn't

84:25

clear that there would be a way to get

84:26

crisper to work in real tea cells that

84:29

you would take out of a human blood

84:30

sample that are not immortalized that

84:32

can only stay in a dish for a short

84:34

amount of time and still retain their

84:36

function. And I put a I I sort of

84:40

tripled down on this is what my lab was

84:42

going to do. if we were going to figure

84:44

out a way and we went through a long

84:45

list of different ways that we might

84:47

deliver and it wasn't obvious actually a

84:50

key collaboration early in my career was

84:54

another serendipitous runin with I met

84:56

Jennifer Dana through some persistence

84:58

of my own and Jennifer Dana and I sat

85:00

down and started thinking about how

85:02

could we team up to take her expertise

85:04

in crisper biochemistry and get it to

85:07

work in T- cells and we settled on this

85:09

this thing that was not at the top of my

85:12

list of things that would work but ended

85:13

up opening up the field. We actually

85:16

purified the the crisper protein. So we

85:18

had protein and RNA that would we we

85:21

could make in a test tube. Now now we

85:23

order it off the internet. We can mix

85:26

them together and we could make these

85:27

protein RNA complexes and we could

85:29

suspend that in liquid. And then what we

85:32

did is we actually incubated TE-C cells

85:35

from a blood sample in that liquid. And

85:38

then the question was how do you get

85:39

these protein RNA complexes into the

85:41

cells? And we use this trick that's been

85:43

around for a long time. No one even as

85:45

as long as it's been around. Sounds

85:47

magical and no one quite understands how

85:49

it works. We put the cells into a device

85:52

that gives a small electrical current to

85:54

the tea cells.

85:54

>> Electroparation.

85:55

>> Electroparation.

85:56

>> Oh man, I I

85:58

during my graduate career, I

86:00

electroparated a lot of Well, I can just

86:02

say it now because I don't do it

86:04

anymore. Um, electroparate a lot of

86:06

brains of of intact animals.

86:09

>> Yeah. You inject DNA. It's floating

86:11

around in the in the local tissue. You

86:14

pass some square wave current.

86:16

>> Yep.

86:17

>> And the assumption is that it creates

86:19

little transient pores in the cell

86:21

membrane and it gets in and sometimes

86:23

you end up with four cells transfected

86:26

and sometimes you end up with 40,000

86:28

cells transfected. It's a wildly useful

86:31

technique, but it's a little bit hit or

86:32

miss.

86:33

>> That's perfect description. And so we we

86:36

my first posttock in my lab Katherine

86:39

Schumann sat there and tested different

86:41

electroparation conditions altering

86:43

these little pulse

86:44

>> pulse 12 pulses long pul you're taking

86:46

me back to my graduate and and to some

86:48

extent my post-doal years it's unclear

86:50

for given tissues for given uh sequences

86:53

what's going to go into cells what's

86:55

going to not kill the cells

86:57

>> we were walking this tight rope of how

86:59

do you make these pores big enough that

87:01

crisper will get in but that the cells

87:03

don't

87:05

And we did it, you know, and we did it.

87:07

And we've we've optimized this. And it

87:10

was one of those things you when it

87:12

happens, you you see it and you just

87:14

realize it's it's binary. Like all of a

87:16

sudden, you're you're editing DNA inside

87:18

of of TE- cells. And you know, we got

87:20

our foot in the door with some level of

87:21

efficiency. We've gone through the roof.

87:23

This is now used by labs widely and it's

87:28

incredibly efficient. And some cells

87:30

die, but overwhelmingly you end up with

87:32

cells that that are gene edited.

87:35

>> She figured out the protocol.

87:36

>> Yeah, she really did. And it's been

87:37

optimized. And then another grad student

87:39

in my lab came in, this guy, amazing

87:41

grad student Theo Roth, and realized

87:43

that he didn't have to stop there. That

87:45

we thought we were limited to just

87:46

putting crisper in and these very small

87:48

pieces of DNA called oligoucleotides

87:50

that were just change a couple of

87:52

nucleotides at a time. Our mindset was

87:54

like, maybe we can fix a mutation, an

87:55

individual mutation. Theo said, let's

87:57

not stop there. let's put big pieces of

87:59

DNA in. And we've pushed this boundary

88:01

of being able to say, let's pick a site,

88:03

make a cut, and introduce hundreds or up

88:06

to thousands of different nucleotides to

88:09

be able to really write a piece of DNA

88:11

code that doesn't even have to exist in

88:12

nature. But then we have the precision

88:15

using crisper to put it into a

88:16

particular place in the DNA. We started

88:19

a company when that when that technology

88:20

worked, a company called Arsenal

88:23

Biosciences that's now in clinical

88:25

trials. It's actually it's in its clin

88:27

third clinical trial right now for solid

88:30

tumors. It's in a clinical trial for

88:32

prostate cancer that's about to start

88:33

enrolling patients. And that company can

88:36

now do this at industrial scale. It

88:38

takes patient cells, electroparates

88:40

them, and has now written a long piece

88:44

of like 10 10,000 nucleotides of DNA

88:47

code that put in a sequence of a

88:50

combination of different receptors,

88:53

including a car and additional gene

88:56

enhancements that will make these tea

88:58

cells more powerful in in in a tumor

89:00

micro environment.

89:01

>> And then they go into the bloodstream,

89:03

they navigate to the prostate

89:05

>> and they start fighting the cancer

89:06

cells. And I imagine you can also put it

89:09

sounds like you're putting some um kind

89:10

of resilience genes in there as well to

89:13

bolster the healthy cells

89:14

>> to bolster the the tea cells that carry

89:17

these receptors to make them persist

89:19

longer and be able to fun. Exactly.

89:21

>> Awesome.

89:22

>> That's happening. And you know that that

89:23

the way that that happens is that a

89:27

patient will be selected will go in for

89:29

a blood donation, give a rather large

89:32

blood donation, but those cells are then

89:34

shipped to a facility that Arsenal

89:36

maintains. The the electroporation

89:39

happens in the centralized facilities.

89:40

The cells get grown up for a couple of

89:42

days and tested. They get frozen down

89:44

and then sent back to the patient where

89:46

there the cells are then thawed and they

89:48

get it's the equivalent of a blood

89:49

transfusion. Now their own cells have

89:52

been supercharged to allow them to

89:55

recognize cancer but also to have as you

89:57

said added resilience, added strength in

90:00

that battle against cancer.

90:01

>> The cells that have been modified by the

90:03

crisper castine, they're sitting in this

90:05

bag um that get infused. Are they

90:10

designed is the crisper designed to to

90:14

only go after the prostate cancer cells?

90:17

Um, or is there some version of this

90:20

where you can inoculate against a number

90:22

of different cancers? In other words, if

90:25

I'm understanding correctly, if there

90:27

are sort of um canonical

90:30

>> mutation

90:32

sequences, yeah,

90:34

>> that occur in all cancerous cells. Yeah.

90:36

Is there a version of this where I give

90:38

some blood

90:40

>> you or a company probably a company

90:42

electroporates them with uh the crisper

90:44

cast 9 system brings in resil resilience

90:48

uh genes for the te- cells from my te-

90:51

cells um plus some attack genes right so

90:57

that are going to destroy the cancer

90:58

cells and then I get an infusion of

91:01

these when I turn I'm 50 now so like 52

91:04

and then it protects against all cancers

91:06

that probably are forming at multiple

91:08

sites throughout my body. Low mutations

91:09

here, low mutations there. Hopefully

91:12

they don't, you know, proliferate. But

91:15

is there a way to just short circuit

91:16

cancer bodywide?

91:18

>> I think that's a hope that all of us

91:20

have to some extent. I think these

91:22

technologies get proven out in patients

91:25

who where the risk benefit of the an

91:28

unproven technology

91:30

>> is tolerated. And you know, I think that

91:32

that in reality that means that patients

91:36

who have exhausted other treatment

91:37

opportunities get treated and often

91:39

those are the sickest patients. And I

91:41

think there's good reasons for ethics

91:43

that that's where we start.

91:45

>> But our hope is that these technologies

91:48

eventually will be proven to be safe.

91:50

They'll get more and more precise. I

91:52

hope the cost would go down. And I don't

91:54

know, you know, you you talk about the

91:56

other extreme of doing it

91:57

preventatively, but at least we should

91:59

start marching earlier and earlier in

92:01

the course of diagnosis. And the hope is

92:04

that, you know, there'll be there we're

92:07

already seeing improved tools for early

92:08

diagnosis of cancer where we're

92:10

detecting the earlier signs of cancer.

92:12

It'd be nice if we have the ability to

92:14

start treating those early cancers that

92:17

might be the ones that are the most

92:18

responsive to the immune system. And

92:21

then beyond that, preventative would be

92:23

even better. Um, I think to get there,

92:27

if we really want to scale up, I think

92:30

we also have to think about you sort of

92:32

going back to your last question about

92:33

delivery, maybe it's not always going to

92:36

be these cells getting shipped to a

92:37

centralized factory and electroparated.

92:40

>> Um, although that's been incredibly

92:41

powerful and it's not stopping now.

92:44

We're actually starting academically in

92:46

my in an institute that I run the

92:48

Gladstone UCSF Institute of Genomic

92:50

Immunology. We're starting a

92:51

philanthropically funded crisper trial

92:54

for multiple myyoma where we're using a

92:56

different genetic program. So we we

92:58

there's a huge number of diseases where

93:00

we are thinking about what can we do

93:02

with existing technologies. We're also

93:04

starting to look for ways that the that

93:06

the deliveries of the future will happen

93:08

and different people are are coming up

93:11

with different solutions. But one

93:12

emerging trend is that rather than

93:14

taking the cells out of the body and

93:17

then exposing them to crisper in these

93:19

targeted ways with electroparation. What

93:21

if we could put crisper into the body

93:23

and just send it and address it

93:25

>> just to the cells that we want to

93:27

modify? We're interested in the tea

93:29

cells.

93:30

>> Someone else might be interested in

93:31

modifying

93:33

or heart or neurons right

93:35

>> for different diseases.

93:37

>> Um and that is a field that is now

93:40

exploding

93:41

>> thinking about technologies. It's

93:43

another area where there's just tools

93:45

that are are happening so fast.

93:47

>> You know when I was a posttock there was

93:49

it was all about it seemed for a few

93:52

years like different ways to get genes

93:54

into cells. Um, so there's

93:56

electroparation, there are lentiviruses,

93:57

there adnoiruses, there calcium

94:00

phosphate transfaction, there was and on

94:02

and on. One of the things that was kind

94:04

of interesting, but at the time didn't

94:06

really go anywhere was um customized

94:09

little uh liposomes like little fatty

94:12

bubbles. Yeah.

94:13

>> Cuz fatty stuff can get onto and through

94:15

cell membranes. So it makes good sense.

94:17

but with some sort of zip coating so

94:19

that you could inject these fatty

94:21

bubbles um or swallow them even get them

94:24

into the bloodstream and then those

94:26

fatty bubbles would go to the very

94:27

specific type of liver cell or brain

94:29

cell that you wanted. Has that

94:31

technology moved forward at all? The

94:32

liposome technology

94:33

>> dramatically.

94:34

>> Oh great dramatically.

94:36

>> Relieved to hear and relieved to hear I

94:38

wasn't the one that had to do the work

94:39

because I knew a lot of very frustrated

94:41

people working on liposomes. Fortunately

94:42

for me, electroparation adn noiruses

94:45

worked spectacularly well for my

94:48

experiments, but a lot of people needed

94:51

cell type specific in um transfaction.

94:54

>> Yeah.

94:54

>> Through a a vein injection.

94:56

>> So all of these things have gone under

94:59

rapid progress. The vir let's talk about

95:02

the viruses. We talked about viruses as

95:04

a tool to as a shuttle of DNA.

95:07

>> They naturally each one will have some

95:09

range of what cells it would infect.

95:11

This is for a virus. This this is called

95:13

tropism. What is what cells are

95:15

susceptible to infection with any virus?

95:17

Those would be the cells that you would

95:18

be able to deliver genetic material to

95:20

with an engineered virus. People have

95:23

really advanced engineered tropism.

95:26

Engineering what cells a virus will

95:29

deliver material to. And that can be

95:31

dialed in quite precisely now in a

95:33

number of different ways. So people are

95:34

working on engineered viruses that

95:37

>> trying there's still problems. trying to

95:39

make sure that they don't trigger immune

95:40

responses. But they're getting more and

95:42

more precise, both viruses and things

95:45

that have virus-like properties that are

95:47

sometimes called virus-like particles

95:48

that are essentially viruses that can

95:50

just deliver either DNA or protein to a

95:53

cell that's specified by what that virus

95:56

tropism is. And that and people are

95:58

working on engineering these tropisms

96:00

with a lot of technologies

96:01

>> because you could put drugs in them too.

96:03

I mean, we talk about, you know, like

96:05

SSRIs have all these side effects. Well,

96:07

that's because you're getting serotonin

96:10

uh, you know, increases at locations you

96:12

don't want it. Like you could imagine

96:14

only getting drugs to certain cells.

96:16

It's it's super to me it's super

96:18

exciting and just seems so fundamental.

96:20

So, I'm relieved to hear that there's

96:21

there's progress being made.

96:23

>> Anything that can be genetically

96:24

encoded, you can start imagining these

96:26

types of targeting. Now, you asked about

96:27

lipid liposomes.

96:29

>> Now, liposomes have kind of come up with

96:32

our new name is lipid nanoparticles. the

96:35

banana particles that kind of rolls off

96:37

the tongue nicely.

96:38

>> And you know the abbreviation we use is

96:40

L&Ps but a billion people around the

96:43

world have now been injected with L&Ps.

96:45

L&PS are the technology that delivered

96:48

mRNA vaccines.

96:49

>> Ah okay that'll raise some eyebrows.

96:53

Yeah. No, we're going to talk about

96:54

vaccines. Listen, we're going every

96:56

we're we're going into it all today.

96:58

They were liposome bound.

96:59

>> These essentially these are lipids that

97:01

can deliver genetic material to cells.

97:03

This was done locally for the co

97:06

vaccine, but people are now engineering

97:08

them with the targeting molecules that

97:09

he described so that they go to

97:10

particular cells. If you inject them

97:12

into the body, lipid nanop particles

97:15

naturally tend to go to the liver. So

97:17

people are using these already to cure

97:19

genetic diseases that where the genetic

97:21

burden is affecting the cells in the

97:23

liver because you can deliver crisper to

97:25

cells in the liver pretty robustly with

97:27

these.

97:28

>> I have my strong view on on the COVID

97:30

vaccine. I think it was a miracle that

97:32

we were able to develop something on a

97:35

short timeline to address a pandemic

97:37

that was killing killing people. But

97:41

I understand there's controversy.

97:43

Leaving that aside, lipid nanoparticles

97:45

are it's amazing that we were able to do

97:48

this that we took something that was an

97:50

idea. Most people thought it would be an

97:53

obscure technical thing like you talked

97:56

about like it would would it ever work?

97:58

All of a sudden it could be manufactured

97:59

at scale. could deliver a synthetic

98:01

piece of of mRNA to give a temporary

98:05

instruction to cells to make a protein

98:08

to protect us. And whether that's for CO

98:10

or for other things, all of a sudden

98:12

we're again I just keep coming back to

98:15

this theme where there's more and more

98:16

ways that we can not only understand

98:18

biology, but that we can intervene in it

98:20

to treat disease. And so now we're

98:22

talking about something totally

98:23

different. We're talking about

98:24

delivering crisper. not the an mRNA

98:27

vaccine, but we're talking about how

98:28

would we get crisper into cells or how

98:30

would we get extra pieces of genetic

98:32

material which might be an mRNA so into

98:35

a T- cell. All of this can now be done

98:38

even beyond the vaccine world with the

98:40

same kind of building blocks of

98:42

technologies like lipid nanoparticles.

98:44

Actually, there's a company out of the

98:46

University of Pennsylvania

98:48

that actually developed recently a

98:51

technology to make lipid nano particles

98:53

that could be injected into the

98:54

bloodstream. Think of them as these

98:56

little fat bubbles exactly as you said,

98:58

but in them they they included a protein

99:03

that would recognize something on the

99:04

surface of tea cells. So that as these

99:06

lipid bubbles were going through the

99:08

blood, they would stick preferentially

99:10

to tea cells and deliver mRNA to TE-

99:13

cells. And you could actually put in an

99:16

mRNA into TE- cells that would

99:18

temporarily make a gene that it would

99:21

encode a CAR, these artificial receptors

99:24

against cancer. And they've done this

99:27

now in testing in a number of models.

99:29

that can actually make these CARTT cells

99:31

by inject injecting lipid nanop

99:33

particles into the body without ever

99:35

taking the tea cells out of the

99:37

bloodstream. And I think we're going to

99:38

see more and more things like that. The

99:41

farm industry is all of a sudden saying,

99:42

"Oh, there's more ways that we can make

99:44

drugs. Things don't have to just be

99:46

pills anymore. They can be engineered

99:49

proteins or lipid nano particles or

99:52

viruses or engineered cells. Whatever is

99:54

going to be most effective at getting to

99:56

the root cause of disease. I want to

99:58

just talk about the COVID vaccine

100:01

briefly. Yeah. Um because in my role as

100:04

a public health educator, um I was

100:08

exposed to a lot of voices.

100:11

>> Um and I can't speak for everybody. Um

100:14

certainly, but I think that at least

100:17

three of the things that caused a lot of

100:20

divide around um the the mRNA vaccines

100:24

were first of all um the difference

100:28

between mandates versus optionality. We

100:32

don't have to go there, but I think that

100:33

that that was a that was a major player,

100:35

right? People, especially Americans,

100:39

don't like to be told what to do.

100:41

>> That's just I've noticed that. Okay.

100:43

Second of all, um it was closely related

100:47

to um notions of the shutdown which

100:51

differentially impacted people. Um and

100:55

that's an understatement, right? Some

100:57

people maintained paychecks, some people

100:59

didn't. Some people could work, some

101:00

people couldn't. So, there was that. I

101:02

just I I'm not trying to uh you know,

101:06

soften anything here, but I think that

101:07

the the vaccines were were nested in a

101:09

bunch of other issues. Um again at least

101:12

three this is not exhaustive. And then

101:14

the other one and I actually had this

101:16

concern myself which was how is it that

101:20

it gets turned off right like I I can

101:23

imagine a situation where I would want

101:25

to put uh an mRNA into me um to do

101:30

something biologically but then I don't

101:33

want it to continue to do that after a

101:35

period of time. So what in the design of

101:38

that vaccine allowed it to be targeted

101:41

to the cells of interest and then not

101:44

continue to express in all other cells

101:46

in perpetuity?

101:47

>> I'll answer the specific question but I

101:49

think that the context that you give is

101:50

also a really important part of this and

101:52

I I'll take one second to talk about

101:54

this. I think to to to answer your first

101:57

question we talked about DNA as the the

102:00

sort of source code. We talked about

102:02

proteins as what the DNA is ultimately

102:04

encoding. Let's just talk for a second

102:06

about what mRNA is. mRNA is the sort of

102:10

temporary intermediate between those

102:12

things. DNA will get what's called

102:16

transcribed into mRNA which is a another

102:20

nucleic acid but doesn't stick around

102:22

permanently. It is the temporary

102:24

instruction which will then go to the

102:27

ribosome and become the template the

102:29

template for a particular protein.

102:32

The idea of an mRNA vaccine is that

102:34

you're using this temporary template so

102:36

that the cells that will take this up

102:39

will make proteins from this temporary

102:42

template for some period of time. Now,

102:44

there could be some I you can always

102:46

imagine the extreme outliers of ways

102:49

that this could last longer or not, but

102:51

fundamentally this is you're you're

102:54

putting in an mRNA that gives a

102:57

temporary instruction to the cell to

102:58

make a small part of the COVID vaccine.

103:01

Now we have the co virus very small part

103:03

right now just by comparison if you get

103:06

infected with covid you're also going to

103:08

get co mrna is transcribed in your cells

103:12

and you know that that that so there's

103:16

we're talking about genetic material

103:17

making mRNA either way whether it's the

103:20

mRNA from the covid or a designed small

103:24

part of that co vaccine that of that co

103:26

genome that we're using as a vaccine. So

103:29

I think it's important to think about

103:30

the risks in the context of the virus

103:33

versus what we're doing with a with a

103:35

vaccine. So I got the COVID vaccine

103:37

enthusiastically and I and I actually I

103:40

think overwhelmingly my imun I mean I

103:43

know overwhelmingly my immunology

103:44

colleagues did the same in people who

103:47

live in this world of immunology a a

103:49

great enthusiasm that this could be done

103:51

and built. Now what that doesn't answer

103:55

what you said about the cultural

103:57

phenomenon. I'm talking just as a person

104:00

not as an immunologist but

104:02

>> I think we probably haven't done enough

104:05

to talk about the trauma that we went

104:07

through as a nation during co of

104:11

>> being fractured by people dying on one

104:14

hand and all the negative consequences

104:16

as you said of of shutdown shutdown of

104:19

economic life shutdown of social life. I

104:22

I I think it was a period of major

104:24

dislocation and we're still feeling the

104:26

trauma and the people's different

104:30

relationships with things like vaccine

104:33

but of science even more generally were

104:35

dislodged or accentuated by this trauma

104:38

that I think we all collectively went

104:40

through and we don't talk enough about.

104:42

>> Um I'll just give one anecdote. Well, I

104:46

I spent a lot of time isolated during CO

104:50

and was disheartened by the fact that on

104:52

one hand I was watching the sort of

104:54

scientific like speed race. That was,

104:58

you know, actually, I think, one of the

104:59

one of the the highlights of of the

105:01

first Trump administration, Operation

105:03

Warp Speed, to to streamline and get

105:06

coordination both on the science and the

105:08

the regulatory side to get vaccines

105:11

approved in an extraordinary timeline,

105:14

taking advantage of a number of

105:15

technologies and making them all. So, I

105:17

was watching this this science unfold

105:19

with some some optimism, but also

105:21

watching the trust in science being

105:24

eroded. I developed it aside hobby um

105:27

which is I've been I've gone back and

105:30

I've been reading I've been reading

105:31

presidential biographies sequentially

105:34

this is this is it's just a side hobby

105:37

now in this in reading in thinking about

105:39

this sort of frustration with with how

105:42

science was sort of tearing things apart

105:44

I found this sort of strange relief in

105:47

reading about early American history in

105:50

1793

105:52

there was a yellow fever epidemic in in

105:55

in u in Philadelphia and actually the

105:58

early parties that were forming the the

106:01

Federalists and the Democrats actually

106:03

took like wildly dissenting views of how

106:06

to deal with an epidemic. They they had

106:09

different views of what caused it whe

106:10

whether it was outside contagion or

106:13

those or sanitation. And the the

106:15

Democrats at that time, the Jeffersonian

106:18

Democrats were in favor of like really

106:20

extreme uh bloodletting techniques and

106:24

the and the Hamiltonians, the

106:26

Federalists had it had a totally

106:27

different set of techniques of baths and

106:30

and more gentle treatments and they just

106:32

couldn't see to eye to eye. Why am I

106:34

saying all this? I think it's not new

106:36

territory that in in that that these

106:40

discussions of how we deal with

106:42

infections which are inherently societal

106:45

diseases unear the societal tensions and

106:48

we deal with them in different ways and

106:50

we come to them from different

106:51

perspectives and there there's a lot of

106:55

things that are simultaneously being

106:56

balanced in any decision of how we deal

107:00

with thinking about the trade-offs that

107:02

we're willing to make in the face of of

107:05

an of a pandemic or an epidemic.

107:07

>> I really appreciate that and I'm also

107:09

impressed that you're reading these

107:10

biographies. How do you know which

107:12

biography to select because there are

107:14

many of them and unfortunately Walter

107:16

Isacson hasn't written them all. I love

107:18

his books. So, how do you select uh the

107:21

author of each biography?

107:22

>> This is this is an this is a a project

107:25

that I spend a lot of time each one I I

107:27

go through a period of indecision about

107:29

which one I I should read.

107:31

>> I can share my list. I'm not I'm not

107:34

done yet. This has been over several

107:36

years. I've been I'm now up to World War

107:38

II.

107:38

>> You should do a podcast someday. Just

107:40

know in your copious amounts of spare

107:42

time, not as a husband, father running a

107:45

giant lab, etc. and physician, uh you

107:48

could do a podcast and and teach us what

107:50

you learn. Anyway, awesome. I'd like to

107:52

take a quick break and acknowledge one

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to get early access to function. I have

109:40

a question related to technologies to

109:43

killing or altering cells that we didn't

109:46

cover but since uh we've touched on a

109:48

number of them the uh lip lipid nano

109:50

particles um lenty viruses since we're

109:54

um

109:55

in a previous lifetime I used uh in my

109:59

experiments and I was excited by

110:00

immunotoxins so an antibbody against you

110:04

generally need a cell surface protein

110:06

and then you attach to it in our our

110:08

case we Saporin toxin, which uh I think

110:11

is most infamous uh because it was put

110:14

on the tip of an umbrella and used to

110:16

assassinate somebody on a bridge

110:18

someplace in some sort of uh

110:20

international spy warfare in the last 20

110:23

years or so. Saporin will kill you if it

110:26

goes systemic. But the idea there is

110:28

that you take the Saporin toxin and you

110:30

tether it to an antibbody that then

110:32

finds a cell surface protein and then

110:34

kills that cell and only cell. and it

110:37

works remarkably well in experimental

110:39

conditions if certain things are right.

110:41

It doesn't always have the specificity

110:43

you would like or the thoroughess. Um

110:46

has that been tried in cancer um

110:49

directing toxins towards uh cancer

110:51

cells?

110:52

>> The short answer is yes. It's a it's a

110:54

really interesting area and and and what

110:58

that toxin is can almost be thought of

111:01

as like modular that you can put put a

111:03

different that you can think of it as

111:05

two components, right? You have a

111:06

targeting component. You have in an

111:09

antibbody is a natural one where an

111:11

antibbody is evolved to recognize one

111:15

particular type of protein that can be

111:17

the thing that targets something on the

111:19

surface of cancer cells.

111:21

Um people have then developed what's

111:24

called antibbody drug conjugates where

111:28

basically a drug or a tox something

111:30

that's going to kill the cell gets

111:31

appended to that antibbody and so it's

111:35

selectively delivered. You don't have to

111:37

deliver the drug at systemic doses but

111:39

you can actually increase the local

111:41

concentration by delivering it

111:42

preferentially to the cancer cells that

111:45

will be recognized by that antibbody.

111:48

>> Doesn't have to be drugs. People are

111:49

thinking about other things. we were one

111:51

people are now trying to attach

111:55

uh radioactive isotopes there's radioan

111:58

therapies that to the that can be

112:00

attached to these things um and I think

112:02

in an extreme that's essentially what

112:05

we're doing with these T- cell therapies

112:07

too

112:08

>> we're also using the the when I I've

112:10

talked about this CAR the chimeic

112:12

antigen receptor the outside of it that

112:14

is the sensor that's being used is also

112:16

an a part of an antibbody and so

112:19

essentially what we're doing is now

112:20

using the antibbody to target, but

112:22

instead of dra dragging along a drug,

112:25

it's dragging along a cell.

112:27

>> And so when that's engaged, the T- cell

112:30

is there and the T- cell becomes the

112:32

killing module. But the the cell not the

112:34

T- cell not only kills the cancer cell,

112:35

but could potentially be used to amplify

112:37

that response, could recruit re-release

112:40

things and recruit other things. So I

112:42

think this general way of thinking about

112:45

designing things um to drag something to

112:49

a cancer site is something that people

112:51

are thinking a lot about. There's even

112:53

another flavor of this that are called

112:55

T- cell engagers. So I talked about okay

112:57

we can genetically put an antibbody

112:59

fragment on a T- cell and use that to

113:01

direct a T- cell to a cancer. People are

113:04

also making antibodies that are

113:06

antibodies on both ends. Okay. So this

113:09

is sometimes I think this is a

113:12

proprietary term but it can be called a

113:13

bispcific or a bite. The bite is a

113:17

proprietary term. Um but basically these

113:19

are two-headed antibodies. One side will

113:22

recognize a cancer cell and the other

113:24

side will recognize a T- cell and

113:26

essentially bring these things together

113:28

so that you get the T- cell action

113:30

locally to the cancer cell without

113:32

having to do any genetic mod

113:33

modification to the T- cell. You

113:35

actually just take advantage of TE-

113:36

cells that are already in the body. So

113:38

all of these things are now under very

113:41

active developments and and some of them

113:43

are approved, others are still in

113:45

development.

113:46

>> Very cool. I'm sure people are catching

113:49

on to this, but basically if you can

113:51

understand the structure of things,

113:53

including very very small things, you

113:55

can Lego them. Yeah. and you can um put

113:59

all sorts of interesting cargos and play

114:02

matchmaker between cells and um it's

114:05

kind of infinite what what you can do um

114:08

once you start to understand things at

114:11

that scale. That's really what it's

114:13

about.

114:13

>> I'll push it one step further. I'm

114:16

actually uh helping to organize a cancer

114:18

amunotherapy conference here in in LA.

114:21

I'm I'm simultaneously here for for this

114:23

and for that. I was at the conference

114:26

yesterday and there was a talk by Amgen

114:29

big pharma company I should disclose I'm

114:31

I'm an adviser to Amgen but this this

114:34

talk was and Amjen's been one of the

114:36

leaders in these bites I think they

114:39

actually trademarked this idea of bicep

114:40

specific T- cell engager um these are

114:45

antibbody fragments but one of the

114:48

leaders at Amgen talked yesterday about

114:50

how looking forward these aren't being

114:53

used as just traditional antibodies that

114:55

come out of of animals, but they're

114:57

actually being used as AI designed

115:00

protein engagers of any target you want.

115:03

So essentially now it's getting to the

115:04

point where if you know that something's

115:06

on the surface of a cancer cell, people

115:09

are increasingly using AI models to

115:12

design a synthetic protein that doesn't

115:14

even exist in nature that is designed to

115:19

recognize and stick to something on the

115:21

surface of cancer cell. And that could

115:23

be of one of these Lego blocks for these

115:25

modular multi multiaceted in cell

115:29

engagers or drug engagers or any of

115:31

these other things. So this

115:35

is another area where the the cross talk

115:37

between experimental capabilities and

115:39

computational exper capabilities is

115:42

further accelerating what's possible.

115:45

>> Incredible. Um would you mind if I asked

115:48

a couple of questions about the kind of

115:50

science, sociology and uh ethics around

115:54

crisper?

115:55

>> No, I I would love it.

115:56

>> I'll keep this brief. Um a few years

115:59

back uh we all learned meaning the

116:02

entire world learned that uh a scientist

116:05

in China had done a crisper cast

116:08

experiment on babies.

116:10

>> Yeah.

116:11

>> I don't know when he did the

116:12

modification. My guess is it was in

116:13

uterero. you'll tell us what exactly he

116:15

did. This hit close to home for me

116:17

because he and I were postocs at the

116:19

same time at Stanford different labs and

116:23

the way it the news hit the world was

116:26

very interesting. One of the things I

116:28

benefit from now as a podcaster and not

116:30

just a professor is that I can talk

116:32

about the stuff that perhaps pure

116:35

professors wouldn't be willing to. Um,

116:37

so I'll say it. It was very interesting

116:40

because the world kind of braced but

116:42

didn't make a decision as to whether or

116:44

not they were upset that he had done

116:45

this like put him in front of an ethics

116:48

board, maybe even throw him in a cell or

116:51

give him a Nobel Prize. It was like

116:52

there was this kind of moment where no

116:53

one really knew what to do.

116:55

>> Yeah.

116:55

>> Like do you reward him? Do you punish

116:57

him? Do you do nothing? And it

116:59

circulated back to Stanford because

117:03

there was a question of, you know, what

117:05

he had learned at Stanford, what was

117:06

done at Stanford. And and the stance, as

117:09

I recall, was everyone just kind of

117:11

waited to see how the world treated him.

117:14

This is not a disparagement of any of my

117:16

colleagues. I think we didn't understand

117:18

how to react to this. And then the

117:20

decision was quickly made

117:23

at large that he had done a bad thing.

117:27

And that's kind of the last we ever

117:28

heard about him were those kids. The

117:31

Chinese government condemned it

117:33

publicly. Uh I think they said he was

117:35

going to be punished, but it wasn't

117:36

clear if he was going to be punished by

117:38

being put in a jail cell, being fined,

117:40

or um given a larger laboratory and more

117:42

resources. It was very unclear.

117:45

>> It's playing God at some level, right?

117:48

It's not the same as deciding to not

117:52

implant some embryos that were created

117:55

through IVF because they carry an extra

117:58

chromosome. It's different than that.

118:00

It's taking healthy children in this

118:03

case and making a change to try and make

118:07

them quote unquote super people. So I

118:10

would love your thoughts on that

118:12

particular instance, your awareness if

118:15

any that um crisper in in otherwise

118:18

healthy humans has continued and where

118:20

you think this is all going.

118:22

>> Yeah, I think you capture a lot of that

118:24

moment. I'm I wasn't there but there was

118:28

a international crisper conference that

118:30

was being held I believe in Hong Kong at

118:32

the time and the the scientist um got up

118:36

and announced with extraordinary pride

118:40

in in in one of these sessions in this

118:41

conference that he had done it he had

118:44

done genetic modification of embryos and

118:47

my understanding of what what had

118:49

happened was that there were two twins

118:53

um who were There there was were parents

118:56

who wanted to have kids and the father

118:59

was HIV positive

119:02

and the modifications that they decided

119:04

to try to make were to delete a gene

119:09

that is if it if it's deleted can confer

119:13

resistance to HIV.

119:15

>> This is a gene called CCR5. there's

119:18

people who naturally have a certain

119:20

mutation in this certain at some

119:21

frequency and mutations in this gene

119:24

confer resistance to HIV if they're

119:26

naturally occurring. So that was the

119:28

supposed rale.

119:29

>> So there was a disease um aspect to it.

119:31

Okay. I wasn't aware of that. Thank you

119:33

for that clarification.

119:34

>> It was a prophylaxis against this

119:36

potential risk of HIV. Now

119:39

>> there were a lot of troublesome features

119:41

from what I understand. First of all,

119:43

there's state-of-the-art methods to

119:46

reduce the risk of HIV if through sperm

119:49

washing and things that can be done that

119:50

would from my understanding essentially

119:53

reduce the risk to near zero of

119:55

transmission through from a father to an

119:57

embryo. So I think it was a bit of a

119:59

manufactured need but there was this

120:02

supposed justification.

120:04

Second of all, it was done um so they

120:08

actually ended up generating two twins

120:10

and my understanding of how it was done

120:13

and I don't think that this was ever

120:15

published. There was some some publicity

120:18

that was released. So I'm sort of

120:19

piecing this together from what was

120:21

public at that time, but I don't think

120:23

any journal ever published this in any

120:25

peer-reviewed context. Um they did this

120:29

in concert with essentially IVF

120:31

techniques. So they were fertilizing

120:34

embryos with this with this father's

120:37

sperm as the mother's the mother's eggs.

120:39

They created multiple embryos and then

120:42

they delivered crisper into these

120:44

embryos and trying to create mutations

120:47

in the CCR5 gene.

120:50

There was some variability. It was

120:51

pretty early in days of crisper and as I

120:53

said there's an unpredictability of what

120:55

happens when you make a double stranded

120:56

break in the genome.

120:58

It was a stretch to say, okay, they

121:00

didn't exactly get the mutations that

121:02

they wanted, but they proceeded

121:04

nonetheless to implant these embryos.

121:07

And I know less about this, but there

121:09

were also serious concerns about the way

121:12

that consent was done on this, like how

121:14

much was informed about what the actual

121:17

benefits would be to these patients. My

121:20

understanding is that he got up and I

121:22

wasn't in the room, but I do think that

121:23

there was some degree of immediate

121:26

horror that this was being announced and

121:28

that that it was unfolding in this way

121:30

and that it hadn't been considered. It

121:32

it was it was not ready. In the wake of

121:35

that, the Chinese government then

121:37

announced that they were going to punish

121:40

this and I don't know the details, but I

121:41

believe that he unders underwent some

121:43

period of house arrest.

121:44

>> Okay. He he was punished. I believe so

121:47

after I I think after there was some

121:50

degree of scientific outrage at this

121:53

point.

121:53

>> Yeah, there was this pause moment that

121:55

lasted maybe a week or two. Um

121:58

>> Okay. Well, you're clarifying a lot of

122:00

the the detail important details,

122:02

>> but my understanding again

122:05

is that he's now free and I think is is

122:08

restarting a lab. I don't think in

122:10

China. I think somewhere else. Um so the

122:13

story might not be over yet. Mhm.

122:15

>> So that's my understanding of of the

122:17

facts.

122:18

>> Let me I'll tell you now what I think.

122:20

>> Yeah, please.

122:21

>> I actually have a pretty hard line

122:24

position on this which I'm not sure all

122:26

my colleagues would agree with, but I

122:28

think that we should have a line in the

122:30

sand where we do not introduce genetic

122:33

edits that will be passed on to the next

122:35

generation.

122:37

You know, I I I told you I've dedicated

122:39

my life now to creating crisper

122:40

technologies to engineer individual

122:43

cells in the immune system. But these

122:45

are what we call sematic edits. These

122:47

are making edits to the DNA in

122:50

individual cells where those genetic

122:52

consequences will be passed on to the

122:54

daughter cells but not to the next

122:56

generation of human because those ed

122:58

we're not making genetic edits in sperm

123:01

or in eggs.

123:03

If you do it in an embryo, all of a

123:05

sudden every cell in the developing

123:07

embryo will will have it, including

123:09

sperm and egg. And now you've not only

123:10

made a genetic change to treat a disease

123:12

or in this case to prevent a disease. As

123:15

you said, in some cases it'll be imagine

123:17

to make an enhancement. People have

123:19

talked about you know maybe you want to

123:21

add we know genes that would make people

123:23

be more muscular or will there be a rush

123:25

to you know

123:26

>> or enhanced memory. I mean many years

123:27

ago there was a paper I mean it had some

123:30

issues with replication down the line

123:32

but where I think it was Joe Chen at

123:36

Princeton um introduced maybe a mutant

123:39

or an extra I've forget now it's been a

123:42

while um case in point I clearly don't

123:45

have this receptor uh to uh the NMDA

123:47

receptor which is involved in plasticity

123:49

and a sub region of the hippocampus the

123:50

idea was they were trying to make super

123:52

smart mice

123:53

>> I remember that that made quite a splash

123:55

at the time I forget where that went and

123:57

may maybe Joe followed up on that. I

123:58

don't know. But um but that would be the

124:01

sort of thing that people are both

124:03

excited about and concerned about. You

124:05

know, could you confer your offspring

124:07

with better um memory genes?

124:11

>> Yeah.

124:11

>> But of course, we have no idea if that's

124:13

a good or a bad thing. Forgetting

124:15

certain things is very useful as well. I

124:17

completely agree with you and I and I

124:19

think the point you made is a key one

124:20

that we do have a we we do live in a

124:23

world where people do IVF and we do

124:26

pre-implantation genetic testing and we

124:28

select in people opt people have the

124:30

option to select non-implant embryos

124:33

that have certain mutations that's

124:34

already a level of like avoiding disease

124:38

in in a next generation if there's a

124:39

severe mutation I think it's not it's

124:43

it's a qualitatively different step to

124:46

then not to select but to actually make

124:48

a genetic change. All of a sudden now

124:50

you're really hampering you're you have

124:53

the ability to

124:55

make some kind of mass- prodduced

124:58

genetic edit in many embryos. I worry a

125:01

lot about what this means for our

125:04

offspring if they are designed rather

125:06

than just born by by chance. I worry

125:09

about fads. You know, when when you

125:12

think about like the Pinterest culture

125:14

that we live in where people see

125:16

something on Pinterest and want to

125:17

follow on, I worry deeply about losing

125:21

human diversity if we see fads in what

125:25

genes are popular for our offspring and

125:27

people can order those in in concert

125:30

with IVF. And I I don't think we gain

125:33

enough to to come close to what we would

125:36

lose as a society if we embark on that

125:39

journey of of editing offspring.

125:44

>> Appreciate the clear stance and and

125:45

answer. Uh as long as we're there, I'd

125:48

love your thoughts on some of the newer

125:50

technologies uh that are only available

125:52

to those that can afford them. So that's

125:54

an important caveat for deep sequencing

125:57

embryos from IVF. So typically with IVF

126:00

check to see that they're chromosomally

126:01

normal, that they're uploid as they say,

126:03

and they'll do some sequencing in the of

126:05

the parents, maybe of the of the embryos

126:08

as well for certain mutations. But

126:10

there's this whole other um industry

126:12

now, I believe a company in the Bay

126:14

Area, Orchid, um is is probably the most

126:16

popular uh one or well-known one uh

126:19

where

126:20

>> if you pay a certain amount of money,

126:21

they'll um deep sequence. If you pay

126:25

more, they'll deeper sequence. Um, and

126:27

so you're getting some additional

126:30

readout of potential disease genes and

126:32

and I I've looked at that technology and

126:35

they're very clear that they at some

126:37

point they can't draw a causal

126:38

relationship between say like a

126:40

neurolyan mutation and autism but there

126:42

are these implications based on the

126:44

animal data or and so it it starts to

126:47

become this it's not gene editing.

126:50

>> Yeah. But it is a deeper and deeper uh

126:54

gene sequencing based selection of

126:56

embryos.

126:57

>> Yeah. First of all, I'm I'm sympathetic

126:59

to the idea, right? Like we we we want

127:01

to protect our kids from from from

127:04

suffering and from disease, right? And I

127:07

understand the idea of doing

127:08

pre-implantation genetic testing if you

127:10

want to avoid a mutation or a

127:12

chromosomal abnormality that would

127:15

really impair lifespan or quality of

127:17

life for your offspring.

127:20

I the imp impulse that we know that's

127:22

this the sort of straightforward

127:25

chromosomeal testing that's done at from

127:27

the first level does will miss a lot of

127:30

mutations. So people I understand the

127:32

idea of trying to fill that in with more

127:34

deep sequencing or comprehensive

127:35

sequencing of the genome. The problem is

127:38

there are some mutations that if we know

127:40

if we see them we will know that they

127:42

can be cause severe disease but there's

127:45

a lot that are become probabilistic and

127:47

statistical and I think we're

127:49

overpromising what can be delivered.

127:52

>> So all of a sudden you're using an

127:54

algorithm to determine

127:57

which embryos are more desirable than

127:59

others. And I think the fact is there's

128:02

just a it's not an access that actually

128:05

exists. there aren't categorically more

128:07

desirable or less desirable. We want

128:09

diverse diverse people for and you know

128:14

how successful you're going to be as a

128:15

interplay of like how your genes inter

128:18

come around and influence your community

128:20

your your environment those are

128:22

unknowable

128:24

from just looking at a DNA sequence

128:26

alone. So I think that there's it

128:29

introduces a false axis. There's another

128:32

book that I I would would recommend here

128:34

that I read years ago and I actually I'm

128:36

probably overdue to go back and and

128:38

reread this. This predates crisper

128:41

technology, but there's a Harvard

128:42

philosopher Michael Sandell who years

128:45

ago wrote a short book called The Case

128:47

Against Perfection. And it's a really

128:50

beautiful meditation on what's lost when

128:54

we enter into this illusion of thinking

128:56

that we can engineer towards some access

128:59

of perfection rather than embracing the

129:02

beauty of chance chance and happen

129:05

stance which is like a part of our

129:07

relationship with with our kids with

129:09

ourselves of thinking like okay this is

129:11

this is the human experience of you're a

129:13

product of some degree of chance and and

129:16

circumstance.

129:17

I'll definitely check out the book. Um I

129:21

I know the whole point of life is not to

129:23

be a quote unquote high performer, but I

129:25

I'll just say as an example, um I know

129:28

of no single very successful person that

129:31

doesn't have some thing about themselves

129:35

that um that initially they disliked or

129:38

felt that they had to overcome which led

129:41

them to pursue certain things hopefully

129:43

in a healthy way. um and that they

129:45

eventually came to embrace and is now

129:48

and are now grateful for. I I know of no

129:51

exception to that. It's just kind of it

129:54

it's sort of the story of of humans in

129:56

many ways. It's a story of humans and in

129:58

fact uh uh people who perhaps are told

130:02

that they're perfect in every dimension

130:03

their entire lives. Um they I can only

130:06

imagine the amount of pressure they must

130:09

feel. In fact, before today's

130:10

discussion, we were talking about people

130:11

that we knew that perhaps had been told

130:13

that and some of the fragility that that

130:15

can introduce to the psyche.

130:17

>> I think that's really well said. I think

130:19

it goes in both ways. I think things

130:20

that we think are hardships or or

130:24

disabilities often end up being the

130:26

things that that make us who we are and

130:29

and you know, make us more sympathetic,

130:32

give us added depth as humans. And the

130:34

things that we think are the things that

130:36

make us perfect are the things that are

130:39

really holding us back or creating all

130:41

sorts of false ideas that limit us.

130:43

>> I couldn't agree more.

130:45

I'd love to know what right now you're

130:49

most excited about for your own

130:52

intellectual enrichment and in your lab

130:55

and and like what you really feel is

130:57

like the the thing that has the most

130:59

electricity for you. and and if you're

131:01

willing to also give us a a hint of

131:04

what's just right over the edge in terms

131:07

of what you think will be the next big

131:09

therapeutic breakthrough um that we can

131:13

look forward to.

131:14

>> Thanks for asking that. So I'm going to

131:16

give a little bit of a long and

131:18

meandering answer that

131:19

>> I mean listen when it comes to me you

131:21

don't have to succinct is not something

131:23

that sort of like exists in my neural

131:25

circuitry although I try. So I see this

131:28

this moment I talked about clinical

131:30

trials where that are already filling me

131:33

with hope. I talked about a a biotech

131:36

trial that I'm associated with for

131:39

prostate cancer. I talked about an

131:40

academic trial that I've put a lot of

131:42

work in with my colleagues over many

131:44

years to open for multiple myyoma. And

131:46

we have a pipeline that we're

131:47

developing.

131:50

We didn't even talk today about we we

131:52

haven't fully talked yet about the idea

131:55

of CARTT cells for autoimmunity. We left

131:57

that open a little bit, but that's an

131:59

amazing moment that we're at right now

132:01

that the same CARTT cells that are being

132:02

used to get rid of B cell leukemas are

132:05

also getting rid of B cells which are

132:07

contributing to autoimmune disease. So

132:08

without making any change, people are

132:10

already starting to see incredible

132:12

responses in the early trials for lupus

132:14

and other autoimmune diseases with tea

132:17

cells engineered to eliminate B cells.

132:19

Oh,

132:19

>> fantastic. Could you just mention a few

132:21

other disease targets? I I know a few

132:22

people with fibromyalgia. Um they suffer

132:25

tremendously.

132:26

>> Fibromyalgia is a disease that we just

132:29

don't understand. Like that is that is

132:33

>> talk about underststudied diseases. is I

132:35

think fibromyalgia is something that

132:37

gets bucketed in a certain way and we

132:39

just have not figured out what what is

132:42

what it really is what what causes it

132:44

and so my that that is its own thing but

132:47

for autoimmune diseases these are

132:49

diseases where we do know that there are

132:51

immune cells going after our own tissue

132:54

in various ways lupus people are talking

132:57

about various engineered te- cell trials

132:59

for rheumatoid arthritis for childhood

133:02

diabetes for multiple sclerosis

133:05

um and on and on but those are a number

133:08

that people are thinking about different

133:09

types of immunotherapies including gene

133:12

and edited tea cells to treat these

133:14

autoimmune diseases. So I'm already I

133:17

guess what I'm saying is excited about

133:19

the near future of things that have come

133:22

out of decades of lab work from labs

133:26

around the world already starting to be

133:28

assembled into things that are advancing

133:30

through clinical pipelines. But the next

133:34

wave of what's coming up behind that is

133:37

just as exciting if not more. So I think

133:41

that one of the things that makes me

133:42

feel like I I have one of the great jobs

133:44

out there is I there's about 30 people

133:48

in my lab.

133:50

I get the joy of ideas bubbling up. They

133:52

don't the idea of the lab don't come top

133:55

down from me. They come from grad

133:57

students and postocs who have come

133:59

filled with energy to bring their own

134:00

ideas and progress is being made through

134:04

this conversation of people in the lab

134:06

reading papers going to conferences

134:08

talking late at night in the lab and I

134:11

can't believe the surprises that are

134:13

that are coming. So I I want to give you

134:15

a couple of these. So I just look

134:19

looking backwards to 2013

134:22

2014 we were struggling to see if we

134:23

could get crisper into with

134:25

electroparation to make one cut in a T-

134:27

cell. We could barely do it. Now if a

134:30

grad student comes into my lab within a

134:34

month or two they can routinely do a

134:38

crisper experiment where we do crisper

134:41

where we deliver a set of thousands up

134:44

to tens of thousands or hundreds of

134:45

thousands of different crispers into a

134:48

population of tea cells from a blood

134:50

sample. So each cell will get a

134:52

different crisper modification and then

134:54

we can essentially race these cells

134:55

against each other. So we can put them

134:57

into a tumor environment and see which

134:59

ones continue to grow, which ones have

135:01

markers that seem like they're going to

135:03

be favorable and giving them

135:04

characteristics that are going to be

135:05

strong against cancer. So we are able to

135:08

do the the type of genetics that was

135:11

possible in fruit flies but unimaginable

135:15

in human cells we're doing directly in

135:16

the human cells that will be the

135:18

therapies of the future. We're directly

135:20

learning what are the genetic

135:21

modifications that will make tea cells

135:23

do exactly what we want. And one of the

135:26

things that we just made publicly

135:28

available is that we used to do these

135:30

experiments and race these cells against

135:32

each other and read it see race them

135:34

against each other for one

135:36

characteristic which ones would start to

135:38

make one cytoine. I talked about these

135:41

signals that immune cells can make. Now

135:44

what we can do is we can for each

135:49

genetic modification we can do a

135:51

complete measurement of the state of

135:53

each individual cell. We this is a

135:56

technology called single cell RNA

135:58

sequencing. So we measure now

135:59

simultaneously all of the the RNA that's

136:02

in that cell telling us giving us a

136:03

snapshot of what that cell is now able

136:05

to do. And we can also simultaneously

136:08

measure which crisper was put into that

136:10

cell. And so now we can essentially

136:12

inactivate every gene in the genome in

136:14

T- cells and read out the consequences

136:17

on the overall state of the cells. And

136:20

this is technology that was developed by

136:21

a number of labs around the world. We've

136:23

now deployed this at a massive scale

136:26

directly in primary human immune cells.

136:28

We just released 22 million cells where

136:32

each one has a different crisper gene

136:33

inactivated. And we get a map of this.

136:36

And I think of this not just what we're

136:39

doing in T- cells, but what other labs

136:40

are doing around the world, using

136:42

crisper to read out the consequence of

136:44

every gene in different cell types, in

136:47

different conditions as a sequel to the

136:50

genome project.

136:51

>> You know, we talked about the genome

136:53

giving us this draft of the DNA

136:54

sequence. Now, we can actually read out

136:56

the function of every gene and see how

137:00

each gene contributes to the behavior of

137:02

every cell. And this is being used with

137:06

in as a basis for massive computational

137:08

analysis. It's providing us a a real

137:12

road map of how cells are wired. That

137:15

will be the instruction manual for the

137:18

next generation of T- cell

137:19

amunotherapies. That the lessons that we

137:21

learn about how every gene behaves are

137:23

now going to be actionable. And these

137:25

are going to be genes that we tune or

137:27

epigenetically edit or inactivate or add

137:30

to genes that we will now have a recipe

137:33

book for what what do we want an immune

137:35

cell to do? What do we want it to

137:37

recognize? What where do we want it to

137:38

go? And we'll have a cheat sheet

137:42

>> that tells us, okay, here's here's what

137:44

we should be adding or subtracting from

137:46

that cell genetically to endow it with

137:48

the powers that will give it precision

137:51

and endurance against some disease that

137:53

we want to go after.

137:55

>> Amazing. I mean, truly amazing. Um,

137:58

should I be banking tea cells?

138:00

>> Well, I think the good news is that

138:04

that's a I never know what the answer

138:05

is.

138:07

I was going to say the good news is that

138:08

we largely have tea cells. Now there are

138:11

are there exceptions to that? Yes. You

138:14

know there are patients who are getting

138:15

treated for certain types of cancer and

138:17

the the chemotherapy that they're

138:19

getting depletes their tea cells.

138:22

I it's hard to know, you know, I guess I

138:26

I can't say that there would never be a

138:27

use, but I think we're getting better

138:29

and better at being able to take

138:32

whatever tea cells are there and and I

138:34

hope reactivate them, re endow them with

138:37

powers.

138:38

I would be disappointed if in the future

138:42

we would need to go back and take bank

138:44

tea cells and not be able to re-engineer

138:47

cells that are already there. Are there

138:49

edge cases where it might be? It's not

138:50

something that I would tell people to go

138:52

out and do. I It's not something I'm

138:54

doing.

138:54

>> I Yeah, I would only do it if you told

138:56

me to. uh a colleague of yours um

138:59

Yamanaka won a Nobel Prize for

139:02

essentially showing that you can take a

139:03

skin cell put in a dish give it Yamanaka

139:06

factors as it were for

139:08

>> in some cases only three transcription

139:10

factors and essentially revert that cell

139:11

to a stem cell and then give it some

139:13

other transcription factors and turn it

139:15

into I don't know a neuron or a

139:18

pancreatic cell.

139:20

>> Should we be banking

139:22

fibroblasts and putting them into that

139:25

ready state? um reverting them to the

139:27

stem cell state. I in my mind I always

139:30

thought well if I ever need more cells

139:31

of a given organ I can always assuming

139:34

I'm I'm alive they you know they can

139:36

take a skin cell and they can do all

139:38

that but I could imagine that there

139:42

would be use for a cell bank not a

139:45

tissue bank where there are a bunch of

139:47

these pur potent

139:50

>> huberman in my case Marson in your case

139:53

obviously uh cells that if uh you know

139:56

god forbid I needed a bunch of

139:57

pancreatic eyelet cells Boom. They could

139:59

have those within a week.

140:00

>> This field is is something that's been

140:03

amazing to watch. It's it's there's been

140:05

ups and downs of it of this induced pur

140:07

potent stem cell field that Shiny

140:09

Yamanaka opened up. Um, one of the

140:13

interesting areas is actually imagining

140:15

how these IPS cells could be made into

140:17

tea cells which would essentially create

140:19

a limitless supply of T- cells.

140:21

>> That's what I was thinking. You know, I

140:22

don't you don't have to even draw blood.

140:23

>> Exactly. which would negate the need for

140:26

banking if you had your so I don't know

140:28

if again it's probably not something

140:30

that I would be cost effective for

140:32

everyone to have their their IPSLs are

140:35

ready to go I understand from in

140:38

conversation from from with Sheny

140:40

Yamanaka that one of the things that he

140:42

has been involved with is actually

140:44

building sort of a bank of IPS cells

140:46

that would be compatible immune

140:49

compatible with broad sets of different

140:51

people so that it could essentially be

140:53

used as a transplant bank which would

140:55

might be a way to be like an

140:56

intermediate step that there would be

140:58

IPSLs available that could be

141:00

transplanted with various degrees of

141:01

ease into different people

141:03

>> and then I do think that I hope it gets

141:06

easier and easier to make IPS cells that

141:08

are matched to any patient when they're

141:10

needed. So, but I mean again like this

141:14

these different threads of things of

141:16

being able to make endless

141:18

supplies of any cell, direct them to any

141:21

tissue type and then being able to

141:23

program them when the language of

141:24

crisper actually it's worth some moment.

141:28

I in 2020 I moved my lab from the main

141:32

branch of UCSF to a separate research

141:36

institute in San Francisco called the

141:38

Gladstone Institutes. It's a nonprofit

141:41

research institute. My grad students

141:43

still come from UCSF at University of

141:45

California, San Francisco, but my lab's

141:48

at Gladstone.

141:50

And one of the reasons that I moved my

141:53

lab to Gladstone was a conversation when

141:55

they when they were recruiting me, they

141:57

brought me into the president's office.

141:59

And in in the president of Gladstone's

142:01

office was Shina Yamanaka, who maintains

142:04

a lab at Gladstone, and Jennifer Dana,

142:07

who also maintains a lab at Gladstone.

142:08

you had to say yes. They're very clever

142:10

that you had some psychologist uh inform

142:12

that they got your number so to speak.

142:15

>> I described this and I think this not

142:17

just a cliche. I actually remember kind

142:19

of like that feeling of hair sticking up

142:21

in the back of your head of like oh all

142:23

of a sudden these are the technologies

142:25

that the these two humans have made

142:27

possible and and others. But we can now

142:31

program the what the epigenetic state of

142:33

a cell is. Thanks to the Yamanaka

142:34

factors, you can dial between skin and

142:37

embryo and and then back to anything

142:40

else and then not only epigenetically

142:42

program a cell, but take the power of

142:44

crisper and genetically program. And

142:46

when you put these things together, all

142:47

of a sudden we have this ability to

142:49

imagine

142:51

programmable cells that we can dial in

142:54

and direct their behavior to either

142:56

regenerate or to in the case of the

142:58

immune system survey the immune the body

143:01

and get to the root cause of disease.

143:03

And I my imagination still lies at that

143:06

intersection of what's possible when we

143:08

combine that with immunology.

143:11

>> I love it. I one question I don't expect

143:14

you to answer, but uh your enthusiasm

143:17

for this uh is tangible. I'm excited. I

143:20

know people listening are and the

143:22

question is how do you sleep at night?

143:23

Like it's so exciting. Like the tools

143:26

are are they're here. Um and mostly I

143:30

want to say thank you. Um, thank you for

143:32

coming here today and giving us a

143:34

absolute master class on the immune

143:37

system, on cancer, on the technologies

143:41

to improve the immune system, combat

143:43

autoimmune diseases. I mean, we got into

143:46

molecular biology with some considerable

143:49

degree of depth and thanks to you, it

143:51

was incredibly clear. I know people

143:52

learned a ton. I know I learned a ton

143:55

and I'm super excited about what you're

143:56

doing. Also, just the the heart and

143:59

soul. There are no other words really.

144:01

Um I think those are are apt. The heart

144:04

and soul that you put into your work is

144:06

so clear. Um and you are definitely in

144:08

the right job. So just uh one request is

144:11

that you come back and talk to us again

144:13

um when the next advancements are made.

144:15

We'd love to have you back.

144:16

>> I'd be honored. And I just I just really

144:18

want to thank you. There are not enough

144:20

forums that are dedicated really to the

144:23

depth to talk about science. the so much

144:26

of the joy of science is in the details

144:29

and you do such a great job of letting

144:31

those details really come through and

144:34

sharing them broadly. So, it's it's an

144:35

honor to be here.

144:36

>> Oh, well, thank you. Um, it's a labor of

144:38

love and I've loved this. So, come back

144:41

again.

144:41

>> Thanks.

144:42

>> Thank you for joining me for today's

144:43

discussion with Dr. Alex Marson. To

144:46

learn more about his work, please see

144:47

the links in the show not captions. If

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Interactive Summary

Dr. Alex Marson, a medical doctor and scientist at UCSF, discusses the revolutionary advancements in reprogramming the immune system to combat diseases, particularly cancer and autoimmunity. He highlights the current excitement in biology and medicine due to the convergence of molecular biology, genetic engineering (including CRISPR), and AI, which allows for unprecedented intervention at the root causes of disease. The conversation delves into the intricacies of the immune system, differentiating between innate and adaptive responses, and the roles of T-cells and B-cells. Dr. Marson explains the genesis of cancer as a genetic disease driven by accumulating mutations and explores various carcinogens and mutagens. A significant portion of the discussion is dedicated to the evolution of cancer treatments, from chemotherapy to targeted therapies and the groundbreaking field of immunotherapy, including checkpoint inhibitors and CAR T-cells. The episode elaborates on the discovery and mechanism of CRISPR gene-editing technology, its current applications in engineering immune cells for cancer treatment, and its potential for other diseases. Ethical considerations surrounding germline editing are also addressed, along with emerging delivery methods like lipid nanoparticles and the future of personalized, programmed cellular therapies.

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