>> From the Library of
Congress in Washington, D.C.
>> Sandra Charles: Okay.
Good morning, everyone.
And welcome to this Joint
Health Forum with Science
and Technology Division of
the Office of Health Services.
I'm very pleased with this
collaboration with Tomoko.
And this is the second of
two that we've done recently.
And thank you all for coming.
Today in honor not only but
particularly because this is October
and breast cancer awareness month,
we're having an esteemed speaker
who will be introduced by
Tomoko -- Dr. Tomoko Steen.
And we're waiting with baited breath
to hear all the new
developments from you, Dr. Clark.
But it is -- it is a subject that we
certainly address on an annual basis
because it is still the number
two cancer killer in women --
and probably the number one
skin cancer -- that exists.
So I just wanted to welcome you and
to thank you for coming and hope
that you will get as much
out of it as we hope you will
and that we expect you will.
And without further ado, I'm
going to ask Tomoko to come
to the podium to introduce
Dr. Clark.
Thank you very much.
>> Tomoko Steen: It's
my great pleasure
to introduce today's
speaker, Dr. Clark.
And he's a senior colleague of mine.
Today's talk is actually part of
the translational medicine series.
We started with two Nobel laureates.
Jim Watson and Carol Greider came.
In fact, Professor Clark was one
of the speaker was supposed to be,
but the schedule didn't work out.
And I'm so glad to be able to
invite him back for this topic.
Professor Clark is dean for research
at the Georgetown University
Medical School and also Professor
of Oncology and Core Director
of the Breast Cancer Program
at Lombardi Comprehensive
Cancer Center.
And he has done the
DSc and PhD at Belfast,
actually, University of Queens.
And also, he has done the
post-doctorate research
at National Cancer Institute.
And I have bio in the back.
You can pick it up.
And we have books on
the -- basic books --
on breast cancer back there.
So if you have time,
please take a look.
And before I go into
the further ado,
I should just introduce
Professor Clark.
Thank you so much.
[ Applause ]
>> Robert Clarke: Well, thank you.
This is a great pleasure to be here.
This is maybe going to be a little
different today because I'm going
to tell you about some of
the research that's going on
and how we've begun
to think differently
about understanding
several different cancers
but with a specific
focus on breast cancer.
Okay. Hands up if you know anyone
-- yourself, anyone in your family
or extended family -- who's ever
had a diagnosis of breast cancer.
Look around.
Sadly, one in eight women --
I'll show you the statistics
in a minute --
are likely to experience a diagnosis
of breast cancer in their lifetime.
We made significant strides
in managing this disease,
and we do cure breast cancers; we
just don't cure all breast cancers.
We will get there.
We probably won't get
there as quickly
as everyone would like,
but we will get there.
Today I'm going to give you an --
some insight into what the
statistics are for breast cancer,
who it affects, some of the drugs.
I'm going to focus mostly
on estrogen-receptor-positive
breast cancer,
which is about 70 percent
of all breast cancers.
And tell you how we've begun
to take a different approach
to understanding the biology of that
disease and how that might lead us
to think very differently about
how we might treat that disease
and ideally, eventually prevent it.
Now, I've got a little bit
of science in my slides.
And probably none of you are
breast cancer researchers.
So please, if you don't
understand anything, just stop me.
I'm happy to take time and try
and explains things
to you as we go along.
And if you see something
that you don't understand,
just make sure that we don't panic.
Really, this is here to have
as much conversation with you
as I am to tell you what we do.
I'd like you to learn something
about breast cancer from today
and go away with it
and think about it.
Because we all have a
responsibility to do something
in whatever way we can to
eradicate this terrible disease.
So don't panic if you see data, or
crazy words, or symbols that sound
like they're a foreign language.
They probably are a foreign
language; they're science language.
But most of those you
don't actually need
to follow; just follow the idea.
Don't worry about the
details because it's the sort
of big picture I'd like to
get across to you today.
So let's start by telling
you something about cancer,
just in case you don't know much.
You might think that it's
a disease of modern man
in some way, shape, or form.
But actually, it is one of
those unfortunate side effects
of just being alive.
We've known cancer has been
around for a very long time.
And the dinosaurs got cancer.
You might wonder how
do we know that?
Well, some cancers come up in bone.
And so when fossils are created
and the bones are left behind,
you can actually see evidence
that there was a cancer
in the bone, in that fossil.
And it turns out this is an example
of one, apparently, who knew --
Hadrosaurus were particularly
cancer-prone.
Dinosaurs -- plants can
get types of cancer.
So it's really a very
common disease.
And I'm going to explain
to you what cancer is.
And then we're going to go and
look at what breast cancer is.
And I'm going to tell you
something about some of the drugs
that we have and how they work.
And then we'll talk about how
breast cancer cells get [inaudible].
And that's the key.
We need to understand how to
stop cancer cells escaping
from when we're trying to kill them.
So most cancers --
all cancers, really --
start with the DNA mutation, a
change in the sequence of DNA
that encodes for eventually
the proteins
that allow our cells
to perform functions.
And sometimes when those changes
occur, it screws up the ability
of the cells to function properly,
and in some cases it
leads to cancer.
So it starts with a mutation.
That doesn't mean that we know
what that mutational event is
in all cancers -- we clearly don't.
In some cases breast
cancer would be an example.
We know that some are caused by
a mutation in a particular gene,
like the BRCA1 gene
or the BRCA2 gene,
which you've probably heard of.
Those are mutations that
lead to more mutations
that build up in the cell.
And eventually we get cancer.
And -- and to all intents and
purposes, cancer is really a disease
where there's loss of
the normal controls
on proliferation and growth.
It's where cells start to
make copies of themselves
when they shouldn't and in places
where they don't belong is probably
the easiest way to think of it.
There's a wonderful set of
slides which I have borrowed
from that the National
Cancer Institute has made
that you can download and look at in
your own time if you want to see --
learn a little bit more
just about the basics.
But this is -- and this is
one of them, for example.
So you can see at the top
you've got these cells that go
through normal division
because as cells get old or die,
they need to be replaced.
Or if they get damaged,
they need to be replaced.
So that's a natural process.
It's when that goes wrong,
the control of that goes wrong
and you start to get growth of
cells where they don't belong
and it's no longer controlled.
We usually call that a tumor.
And they come in different types.
They can grow in one place
and never go anywhere else.
They can grow in one place and
stop and do very little harm.
But the ones that are the
biggest problem and for
which breast cancer is
an example are the ones
that find -- that don't stop.
They don't stop in the breast, they
don't stop in that little place
where they started and they start
to spread into the tissues around.
And eventually they get into
the lymphatic system or they get
into the blood system and
they go all over the body.
And some of them will stick in other
parts of the body and start to grow,
and then you have what's
called metastasis.
And you get spread of the
disease all over the body.
That's usually the process
that kills most women
and the small number of men
who get breast cancer --
that process of metastatic
advanced disease.
So this is what the breast looks
like when you're thinking
conceptually.
The breast, of course, is there
for one purpose only: To make milk.
And we wouldn't be here
as a species if it wasn't
for the milk that's
produced in the breast.
And it's made in these little --
in these glandular structures here.
And then it gets expelled
into these ducts
and comes out through the nipple.
That's the natural process
that occurs during what we
call lactation, after pregnancy
when a woman has given birth and
she's making milk in her breast.
Sometimes things go wrong in
the cells that line these ducts
and you end up with a tumor.
And you can see here this is an
example of a tumor that began here
in this quadrant of the breast.
Sometimes it will get
out of the breast
and end up in the lymph nodes.
So there are lymph nodes
that are in the breast --
that's often call the
sentinel lymph node.
And there are the ones
turned the arm in the axilla.
And so often when there's an
initial diagnosis of breast cancer,
the doctor will want to know
is it in the lymph nodes,
either in the breast
or under the arm?
And that tells us a lot about --
just knowing whether it's there
or not tells us a lot
about the potential
of that cancer to be
in other places.
So often if it's confined
to the breast,
if we can have the surgeon remove
it and the radiotherapist come along
and use radiation to burn
away and kill any few cells
that the surgeon might have
missed, that woman can go away
and she's completely cured.
But many women, as you know,
that cancer has already got
to the lymph nodes, or to the
lungs, or the brain, or the skin,
or the bone, or the liver.
And then it's a much more
difficult disease to manage.
That's the sort of natural
history of breast cancer from sort
of soup to nuts, if you like.
So let's look at the incidence
and what we think we know
about what might cause
breast cancer.
So in this top panel
here where it says --
that circle there where
there's known risk factors,
most women who get a diagnosis
of breast cancer have none
of these risk factors.
We really still don't know what
causes most breast cancers.
We know a number of things
that can increase the risk
on a population basis.
If we look at those women,
we can say that if some
of these women have been
exposed to one, two,
or threes of these things,
their risk is higher.
But that doesn't mean that we can
go in and say "And you're the one
that has a risk that's twice as high
as anybody else's as an individual
and you're the one
that's going to cancer."
We can't do that.
We can only look at large numbers
of women and draw broad conclusions
or associations about what is this
correlated with breast cancer?
The panel below, the circle,
shows you the age distribution
of breast cancer.
It doesn't arise in
children before puberty.
It's extremely rare
in very young women.
The incidence increases with age.
And the highest increase, as you can
see from that middle chart is just
around the age when women
go through menopause.
So it is a disease of
getting older primarily
but not obviously exclusively.
In terms of why is that the
case, the longer you live,
the more cells you have in your body
that go through and are replaced.
And every time you replace a
cell, there's a risk that the DNA,
when it's replicated,
makes a mistake
and you get a mutation
by chance increases.
So it simply increases with age.
That's one explanation, probably
the simplest way to think of it.
It's obviously a little
more complicated.
But that's enough for now
to get the basic idea.
If you inherit a BRCA1
or BRCA2 mutation --
and that's shown in
the table at the top --
the risk of getting
breast cancer is very high.
But the percentage of women
who inherit mutated BRCA1 is
fortunately relatively low.
So it doesn't explain most
breast cancers, it explains some.
And we can find out from looking at
family histories who's likely to be
in a family that might have
a BRCA1 or BRCA2 mutation,
and we can identify those women
if someone in their family,
for example, comes in with a breast
cancer and we take their history.
And we can sequence from just
a buccal swab, for example.
We can sequence that BRCA1 gene and
determine whether they're in one
of these breast cancer families.
And that allows that family to make
decisions as to who else wishes
to get screened and what they might
want to do with that information.
We have a whole set of folks
called genetic counselors
who will help people work
through that issue if they find
that they're a carrier of this.
One in eight women
is a lot; men, too.
But not so many largely because the
amount of breast tissue in men is --
is much smaller than it is in women.
There's a small residual piece
of breast epithelial tissue
where the cancers arise
present in men also.
But it's so small that -- and there
are so few cell there are relative
to women, that probably explains
why the risk is much lower to men.
On the panel that shows the young
woman, breast cancer is caused
by the interaction of
genes in the environment.
It's wonderful to say that.
So what genes and what
in the environment?
That's a mess -- that's much harder
to figure out because we have tens
of thousands of genes, and they
make proteins in different forms.
We don't always know
what they all do.
And then there are so many
things in the environment.
And if it's a combination of
things and not a single exposure
in the environment, it's very,
very, very difficult to figure
out what it is that's
actually causing that.
So for most people,
we really have no idea
if they didn't inherit
a BRCA1 or BRCA2.
We only know a few things that
might elevate their risk slightly,
and almost none of those are
anything you can do anything about.
So if someone says, "I
just got a diagnosis.
Why me, what did I do wrong?"
You probably didn't
do anything wrong.
Almost certainly you did nothing.
There is very little that you can do
to fundamentally change
your lifetime risk.
There are things that
you can do that are --
that can moderate that to some
degree: Exercise, a healthy diet --
the things that everybody keeps
telling you to do for a whole series
of different diseases can help
to keep your risk of
breast cancer down.
But fundamentally, what is it that's
driving it is still something we
still have a long way
to go to understand.
And these are the numbers.
Now, they are kind of scary.
230,000 new cases every year.
230,000 families will get a
diagnosis of breast cancer
because it's not just the woman who
gets it, everybody in the family
and friends in the
circle are affected
by a diagnosis of any cancer.
That's 231,000.
And at 41,000 women dying
of breast cancer every year,
that averages out if you just do the
simple math of one every 13 minutes.
We will be here 45
minutes to an hour.
So you get a sense of the impact
that has across the country.
It is still a terrible,
devastating disease.
And it has tremendous implications
for public health, for economics --
not just the human condition.
We have to do much better than this.
Now, interestingly, 70 percent
of those breast cancers express a
protein called the estrogen receptor
that binds to that
female hormone, estrogen.
And we've known that
if you target that,
it has a significant survival
advantage for most women.
And we've known that
since the 1970s.
First ever molecular-targeted
therapy
for any cancer was
tamoxifen for breast cancer.
This shows you that the
importance of the estrogen receptor
because it shows you
that estrogen-receptor-positive
breast cancers
and estrogen-receptor-negative
breast cancers don't behave exactly
the same -- the risk of the
breast cancer coming back,
which is distant recurrence
in that panel,
or the risk of dying
from breast cancer.
The patterns of those over a woman's
lifetime are really quite different
-- the risk of dying
from estrogen-receptor-negative
breast cancer is higher
than estrogen-receptor-positive
breast cancer
in those first few
years after diagnosis.
After that, the risk
begins to get higher
for estrogen-receptor-positive
breast cancers.
And although those women often live
much longer, they actually have
on an annualized basis a higher risk
of their breast cancer coming
back the longer they live
than those women who've
managed to survive that long
with an estrogen-receptor-negative
breast cancer.
So I said we can target the estrogen
receptors; how do we do that?
And there are basically
two types of drugs
that target the estrogen receptor.
There are some that will bind there
and stop estrogen binding there,
and those are called anti-estrogens.
And tamoxifen is a
good example of that.
And that's shown in
this bottom part.
So it's binding to
the estrogen receptor
so estrogen can't sit there.
The other group are
called aromatase inhibitors
because they block the ability
of the body to make the estrogen
that would otherwise bind
to the estrogen receptor.
So you either block that
protein that binds estrogen
or you block the ability
to make estrogen.
And those two classes of drugs
have been really quite remarkable
in reducing the risk of
recurrence and death.
And that's shown here on
this particular table,
that the risk of recurrence is cut
almost in half and the risk of dying
from breast cancer if you have
estrogen-receptor-positive disease
is reduced by about a third.
That's pretty good, but
it's not good enough.
Because you can see on that
graph at the bottom here,
you can see the survival
advantage --
the overall survival advantage
of taking tamoxifen --
but you can still see
that there are plenty
of women who don't survive still.
Now, they may live longer and
still die of their breast cancer,
which is a fabulous thing to do.
If you think about that top bar for
the incidence is highest for women
who are 50 to 60 years of age,
if you could shift
their survival 20 years,
they get to see their
kids get married,
they get to see their grandkids
grow up, they may even get
to see their grandkids
graduate from college.
Even if they still
died of breast cancer,
you have transformed the lives of
those women and their families.
If we could make breast cancer
a disease you died with,
not a disease you died from,
that alone would be
utterly transformational.
So think in your own minds
how you might choose --
how you might choose to define cure.
Because if you die of something
else and you've had a good life,
if we can get that far,
that's a great step.
Curing it is the last step, then.
So think of it that way.
So here's some basic questions.
I'm going to speed up a
little bit, and don't worry
if you get left behind because I'll
bring it all together at the end.
And if you want me to -- if you
get lost and you need to stop,
just raise your hand
and ask your question.
So I posed a couple of
questions here because I'm going
to give you some insight
into how we think about them.
So I showed you that
recurrence curve
that some breast cancers can
come back 20 years later after --
when there's been no
evidence of disease at all
and you think you're done.
Are the ones that come back 20
years out the same as the ones
that come back three
or four years out?
We don't know.
So maybe we can begin
to ask that question.
And if we could find
that they were different
and we could understand
how they were different,
maybe we could take all those ones
that recur in three and four years
or five years and not have
them recur for 20 years.
And for many women, as I just said,
you'd basically have cured
breast cancer for those women
because they die of old
age or something else.
So how you define where the finish
line is frames the way you ask the
questions, the questions that you
ask and where you look for answers.
So if we could learn something from
any differences that we might find,
we might have different ways of
identifying the women who were
at the highest risk of recurring
early and we might be able
to finds ways of not having them
recur at all or having them recur
to light that they would
hopefully never experience --
have that experience.
And the fundamental question
is: If these drugs are so good
for a high proportion
of those women,
why aren't they good for everybody?
What is it about some breast cancers
that have that estrogen receptor
that we know we can hit and
hit hard that still come back?
Because if we could
understand that difference,
we might be able to cure them.
So there's some of the
questions I want to sort of pose.
And then I want to show you
where research is going.
We can talk about the clinical
implications in the questions.
I can only answer those vaguely
because I'm not a clinician.
So let's ask the question,
first of all,
are all tamoxifen failures the same?
Are those tumors that
come back late different
from those that come back early?
And there are different
ways to do this.
And I wanted to give you a
sense of the power of the tools
that we have today that we didn't
have 10 or 15 or 20 years ago.
Because this is where the hope is.
We can ask and answer
questions in ways today
that when I was a student getting
my PhD I could not have dreamt
of in one lifetime.
And I'm not done yet.
Don't think so.
I've seen a transformation and
an acceleration of our ability
to create knowledge and turn that
knowledge into actionable outcomes
that can make a difference
in the lives of people.
I've seen that change so quickly and
so much in the last 10 or 15 years.
This is the most exciting
time to be trying
to find a cure for breast cancer.
And it's the best time we've
ever had to get there quickly.
So this is an example of
one of those technologies.
This is a technology that
allows us to take a little piece
of a breast cancer and
look at the expression
of every gene that's
present in that piece
of breast cancer, in one experiment.
So we can measure the
expression of 40,000 genes
in one biopsy from a woman.
And if we can do that,
maybe we can take biopsies
from those breast cancers that will
recur early and those breast cancers
that will recur late
and see if they're --
there's a pattern of gene
expression in those two groups
that predefines the outcome.
So we'd be able to say which
women are at the greatest risk
of recurring early or late.
And then we could ask
why are they different
and why do they recur early
or late and learn something
about the biology that
would allow us to look
at new ways of creating treatment.
So this is a study we did
where we did exactly that.
We took breast cancers
at the time of diagnosis
but we had 20 years
of clinical follow up.
So we knew which women recurred
early and which women recurred late.
And we measured those 40,000 genes
in each one of those breast cancers.
What this shows you -- and
you don't need to be able
to understand the figures --
if you look at those
two boxes in the middle,
you'll see there's a red
line and a blue line.
So the red line --
each line tells you
when that breast cancer
recurred or that woman died.
And you can see that the red line
is very separate from the blue line
and that the ones on the red line,
their breast cancers came back early
and the ones in the blue
line came back late.
So we were able to find a pattern
of genes that told us whether
that breast cancer was going
to come back early or late.
And we were able to
find another set of data
that was completely
unrelated to our data --
this is a scientific question --
and show that we could
do the same thing.
So for us that told us -- our
interpretation was, "Well,
there's something different about
breast cancers that recur early
and breast cancers that recur late."
Now, I'm not going to
tell you that this is --
this tool is useful
for telling any one
of you whether your breast
cancer is early or late
because we didn't ask
the question that way.
We asked the question
just to learn something
about the biology this disease.
So they're -- they
seem to be different.
That's good, we've
learned something.
So now we do what scientists
do: We set up hypotheses.
We say, "Well, if that's the case,
what might explain those differences
and how would we ask that question?"
And so we took a different
approach from others.
We had 40,000 measurements
on 140-odd breast cancers.
And we said well, what do
we really want to know?
And rather than look
for a single gene --
because we've always
looks for single genes.
And the best we could come up with
was BRCA1 and BRCA2 mutations,
and that's less than ten
percent of all breast cancers.
We have to think differently.
And you think about what
the estrogen receptor is,
it controls everything that
breast cancer cell wants to do.
You take it away and
those breast cancers --
some of those breast cancers die.
It's that important.
So what is different between those
where you take it away and they die
and those you take it
away and they don't?
So we're going to think
of this as a system.
It's called systems biology.
We're not going to try and
find one gene or one pathway;
what we're going to try and find
out is how does these breast
cancers cells work as a system?
How do they coordinate
everything that they do
to survive the stress
of these drugs?
And will that teach us
about breast cancer?
And so we have a network idea,
that concept doesn't matter so much
as where do you start looking?
I mean, you've got 40,000
genes, you've got all the things
that cells do; what do
you really care about?
Well, this is cancer.
So we thought let's not ask all
of the questions that we could,
let's just figure out what it is
that makes cancer cells live or die.
Because if they die, we can go home.
We're not there yet, obviously.
But if they don't die and they never
made another copy of themselves,
that would be a case
where a woman would die
with breast cancer,
not of breast cancer.
So then we want to know if
they're going to not die,
what is it that makes
them make copies
of themselves when they shouldn't?
So let's not worry
about the other things,
which are very important
questions to ask about biology --
how do they spread, how do they
get to other parts of the body,
how do they live in other
parts of the body --
let's just ask alive or dead
or making a copy of yourself
or not as a place to start.
And so that's -- so that then
constrains where you look in all
of the data for the answers
because you already know
what some of these genes do.
And they're not doing what --
anything that's related
to being alive or dead
for the cell or making a copy of it.
So you can ignore those.
And it gives you a place to look in
a focused sense to learn something
about the biology of the disease.
So I've shown you that we could --
we had all these breast patients'
tumors and we had all of this data.
And we knew we could separate them.
So now we knew which were
early and which were late.
So what are the genes that
are different between early
and late recurrences, and
do they teach us anything
about why they may be different?
So you don't need to know
the tools that we used.
We used a computational modeling
tool that basically said, "Okay,
we know the estrogen
receptor's important.
Let's first find out all the genes
that we think or all the proteins
that we think are likely to
interact with the estrogen receptor
or interact with the
protein that interacts
with the estrogen receptor."
And we're not worried
about anything else.
We'll just say what is that
close in that data space
to the estrogen receptor?
And then when we find those, and
there's about 50 of them that are --
no matter how you look --
keep coming up as being related
to the estrogen receptor.
We just look and see how
are those expressions
for those genes different between
breast cancers that come back early
and breast cancers
that come back late?
So once you have a focused
question and you have the data,
you can begin to look
at it in different ways
and answer a very focused
specific question.
So that's kind of what we did,
and this is what we found.
Basically, it's complicated.
You kind of knew that
was coming, didn't you?
But also, it suggests that
there are some relationships --
some genes that are always up,
some genes that are always down,
some that are always
probably talking
to each other no matter what
estrogen-receptor-positive breast
cancer you look in that would allow
us to think if we were to knock
down one of those,
maybe we could stop all
of this signaling from happening.
So now it gives us a place to
think about where we want to look
to understand the biology and
how we might want to think
about where we want to
look for new treatments.
This is one way of looking at one
dataset -- one or two datasets.
So that's something.
Now we've got some genes and
some ways they talk to each other
that tell us that we
think that's important.
So what if we take cells
-- breast cancer cells --
and culture that we know can be
killed by an endocrine therapy
like tamoxifen or [inaudible]
and we treat them and we look
at the changes in genes at
expression over time and we can look
at how genes -- how
cells respond quickly
when they're first treated
with an anti-estrogen.
And that gives us another model.
And what we find is some of
the things that are present
in the patient's tumors
that seem to talk
to each other also
happening very quickly --
literally within hours of those
breast cancer cells being exposed
to the drugs.
So are any of those
hard wired later?
Does the cancer learn how to
use some of those to survive?
So yeah, they kind of do.
Because if you take the same cells
and you treat them long enough
so that a small number of
them survive and they grow out
and they're resistant, you can ask
"How are the resistant cells
different from the sensitive cells?"
So what's now hard wired into
those breast cancer cells
that now are surviving the drug?
And it's some of same genes
that predict from early
or late recurrence that
are changed very early
when the breast cancer cells
are exposed to the drugs.
They're now wired in hard.
The cells have adapted
their biology,
their signaling to survive the drug.
They've learned.
We have to learn how they learn
and what they learn to
be able to stop that.
So we know what some
of these genes do.
We know what functions they control
within the cell that might allow
that cell to survive, or die,
or make a copy of itself or not.
And when we start to put
that information together
in a systematic way,
we begin to get insight
into how the breast
cancer cell works.
And I'm going to tell you one
way that we think it works.
So these words on the
far right in red
and blue represent
functions that cells perform.
So apoptosis is a process
of cell death.
We like that in cancer cells.
We want them to do more of that.
Autophagy is a fascinating process.
That's the cell's recycle plant.
So when bits of it
get old or damaged,
it eats them up so they can be
replaced and the cell can continue.
But it doesn't waste the
byproducts of what's chewed up;
it uses those to live off.
Because nature and
life is very careful
in how it uses its resources.
So there's something going
on here about alive or dead,
whether that apoptosis
piece is switched on or not,
and whether that recycle
plant is activated.
And that UPR -- I'm going
to tell you what that is
in a minute, so just hold on.
It doesn't get too complicated.
So what we're really looking for now
is how does the cell coordinate all
of the things it needs
to do to survive
and to make a copy of itself?
What all does it need to do
just to do those two things?
We -- that's the piece
we care about.
We know that when we give
these drugs, they are --
the cells become stressed
and some cells can't deal
with that stress and die.
This is good.
But some cells are stressed by
these drugs and they don't die.
And that's bad.
And, again, we're trying
to understand the difference
between those two.
Now, we know that to do
anything the cell needs energy.
We all need energy.
So one of the places we want
to look is how the cell --
the breast cancer cell --
controls its cell metabolism.
Because without energy,
it can't do anything.
We've known a lot about
cell metabolism
for a very, very long time.
But we've always studied yeast,
or simple cells, or normal cells.
So a lot of what we know is how
normal cells do what they're
supposed to do.
But these are cancer cells --
though don't do what
they're supposed to do.
So can we learn something about
how they manage their metabolism
so they have the energy
to make a copy
of themselves in order to survive?
Hang in there.
This is going somewhere.
I -- I assure you.
So we can do that, too.
We can actually measure thousands
of metabolites at the same time
on a single specimen, just like we
could measure all of those genes,
we can measure all
of the metabolites.
And we can look at which metabolites
are being used more frequently
and which aren't, and that
will tell us which processes
and pathways the cell
is preferentially using.
And so some of these are listed
here -- glutamate and glutamine.
You see, we've actually
known for a very long time
that cancer cells are addicted to
glucose -- the sugar glucose --
and to the amino acid glutamine.
We've actually known that --
I'll show you in a minute --
for even longer than I've been here.
That's how -- age-wise
on this planet.
That's an example of some things
we've known for a long time.
And we haven't known
what to do with it.
So the bottom tells you some of
the functions that are changed.
And you've got cell
death, that's good.
Cancer, well, we knew that.
Glucose metabolism.
So we know that there's so much --
that glucose metabolism
must be important
in how these cells become resistant
and evade the anti-estrogens.
And autophagy, that process,
that recycle plant process,
that's also been upregulated
in these cells.
So now we have to think
"How are they connected?
And what way does that connection
allow the cells to survive
and make copies of itself?"
And I've shown you that we've got
-- we can measure the metabolites
and we can measure the
genes that are expressed.
Well, we can take those two types
of data and map them onto each other
and begin to understand how
the cells uses its proteins
and its genes to regulate
its metabolism.
Now we can begin to understand
how it functions as a system
and how it makes choices.
And we find things like cell
survival, we find insulin and IGF,
which would regulate glucose
metabolism normally are
also changed.
They do other things.
And we see that some of the
high-energy metabolites,
the levels of those are
different in the cancer cells
that are sensitive and resistant.
So this is what we've known
since about the 1930s.
So when my mom was born,
this guy, Otto Warburg,
was figuring out that cancer
cells are addicted to glucose.
And they metabolize glucose in a
way that's very, very different
from most -- but not all
-- but most normal cells.
Because cancer cells -- cancers
don't have a proper blood supply.
So they don't have all of the
nutrients and oxygen and all
of the bits and pieces
they need as easily.
It's not as easy for them to get
as it is for the rest of our body.
And so there's not enough oxygen.
And normally that would change the
way cells would metabolize glucose,
but cancer cells don't care.
They've learned to do this
whether there's oxygen --
enough oxygen present or not.
And they just love glucose.
And glucose gets broken
down naturally
to produce the chemical energy that
the cells use to build everything.
One of those molecules
is called ATP.
And you don't really
need to know much more
than there's a chemical that's made
from glucose, that's a byproduct
of breaking up glucose, that
the cells use to store energy,
and then they can release
it to build other things.
So we looked at whether the glucose
levels are changed in sensitive
or resistant cells and
whether that's effected
by the anti-estrogens.
Because that's fundamentally --
if we're changing their ability
to make energy, maybe that's one
of the reasons they're dying.
It turns out that that's the case.
But what's really interesting
is actually
on that ATP graph on the right.
You -- I'll tell you what it
says so you don't have to worry
about whether you can read it.
It says if you give an
anti-estrogen to sensitive cells,
they take up less glucose
and they have less ATP.
They don't have enough
energy to do everything.
And what that normally does
is first that causes the cells
to stop making copies of themselves.
And if you can hold that
glucose levels low enough
and the ATP levels low enough,
some of those cells will die.
They -- they just can't
survive any longer.
The resistant cells have figured
out how to take up glucose and make
that APT even though they still
have the estrogen receptor present
and the drug is present.
They don't care anymore.
They've figured out a
way to get around that.
So we don't quite know
yet how they've done that,
but we know that they've done it.
But the other thing that told us
we needed to look elsewhere, too,
was -- and that's these
panel on the far right --
the cells that are resistant and
are growing happily at the same rate
as the cells that are sensitive
when they're not being
inhibited actually have less ATP.
They don't need as much energy.
Well, why do resistant cells that
are doing all the same things
as sensitive, normal cells are,
why do they need less energy?
That's where the recycle
plant begins to come in.
So they're clever little suckers.
So what happens in a cell if
you don't have enough energy?
Well, the first thing is
you actually can't make
and fold your proteins properly.
You need proteins through all of the
business that the cell needs to do.
And cells have across
evolution been exposed
to very different environments
when their nutrient supplies
and their ability to make
energy was constrained.
But they still survived because
they developed a system to deal
with not having enough
energy to fold your proteins.
It's called the unfolded
protein response --
that's that UPR thing I
promised I would tell you about.
And you can find this
in yeast cells.
It's a little different in mammalian
cells, but it's not that different.
And it's a damnably clever
system, as you would imagine.
Because if you don't have enough
energy to fold your proteins
and you want to survive first --
survive first, grow second is a sort
of priority for the cells.
Normal cells have that priority
just like cancer cells do.
And if normal cells
are able to do this,
why couldn't cancer cells
use this as a way to survive?
And what the unfolded
protein response does
in this cell is it
says "I have a problem,
I can't fold my proteins properly.
Let's make less protein, figure
out how to get everything back
to normal, and then we'll
make a copy of ourselves."
In the process it doesn't
want to die.
So it also sends a signal
out to the mitochondria,
the energy piece in the cell.
It says "Wait a minute,
we've got a plan here.
I know we have a problem;
we're not going to die yet.
So signal, just don't die yet
because we're going to fix this
by making less protein, making only
what we need until we can survive.
And then we're going to
go off and we're going
to make a copy of ourselves."
And that unfolded protein
response coordinates all
of those decisions in the cell.
And cancer cells can
use the same thing.
And that takes us back to this
little model that I briefly went
over and told you none
of the details.
Because what that model
from our study said was
that seems to be important here.
Of all the things that this -- that
the breast cancer cells could do
to survive the drugs
that we're giving them,
they seem to be using this
unfolded protein response.
And we learned that one of the
coordinating signals that comes
out of from the unfolded protein
response also coordinates the
recycle plant signal.
So now we're beginning to see how
what the cell's doing doesn't have
enough energy, so it's not
trying to make copies of itself.
It's going to survive first.
To do that, now it doesn't need as
much energy because it doesn't have
to make a whole other
cell to make a copy.
So it can live with a lot less.
And at the same time it's sending a
survival signal to allow it to see
if this is going to work or not.
And that's what these
resistant cells do.
They upregulate at the same
time that recycle plant
because there they were happily
going along, making lots and lots
of copies of themselves,
and now they don't need to.
So all the machinery that they had
to make another copy is superfluous.
They don't need it anymore,
so they just recycle it.
And they kind of live off
their little bit of belly fat,
if you like, and find
a way to survive even
when all their metabolism
is being shut down.
And some of the cells next
door haven't figured this
out and they die.
And what happens to the
bits of the dead cell?
The one that's alive
just sucks them in.
So they start to feed each other.
So they start to feed themselves
off what they don't need anymore,
and they start to pull in
the nutrients from the cells
that are dying next door.
So it's really an ecosystem.
It's a whole system where all the
cells are talking to each other
and working together
and some are dying.
And because they're dying,
they're actually helping some
of the other ones to live.
Cancer is smart.
And this simply shows --
so I'm just about done.
And I'm going to live you an
analogy of how we've come to this
to understand just these basic
principles and why that's beginning
to change the way we think
about dealing with breast cancer
and dealing with particularly
this drug-resistant --
type of drug-resistant
breast cancer,
which is in effect
ultimately up to 70 percent
of all breast cancer patients.
Imagine a car.
Okay. You could have Mini,
you could have a Maserati.
I know which one I want.
But it doesn't matter.
The basic principles of the
internal combustion engine
that drives the Mini and drives
the Maserati are exactly the same.
What's different is all
the bells and whistles
in the Maserati that's
not present in the Mini.
But all the control systems -- the
brakes, the engine, getting the fuel
in -- all of those things
are basically the same.
And that's kind of a little bit like
looking at cancer and normal cells.
The cancer cells are using
what they've inherited
as from their having been once
normal to allow them to survive
when they're cancer and
we're trying to kill them.
So think of where we are on a car.
So we kind of know where
to put the key in the car.
And it's like the estrogen receptor.
It's kind of like the switch
that turns on everything.
And if we turn it off, notice
that car's not going anywhere.
It's stopped.
If you leave it stopped long
enough, it rusts away and it dies.
So we know where the key goes and we
know that if we mess with that key,
we can cure some breast
cancer patients.
So it's a great place to start.
What happens, then, when
that key gets broken
and turned on all the time?
So what it's doing is it's
turning on the engine.
It's firing up the engine and it's
going to make a copy of itself.
Now, we know how cells
make copies of themselves.
We know how yeast cells do it.
We know how normal
cells in humans do it.
So that piece of what happens in
cancer is often very much the same.
What's not the same is the signal
between the switch and the engine.
That's what's got changed in cancer.
So that now begins to tell us
where to look to understand
in more detail, a much
finer place to start looking
to understand how these
cancer cells are different.
We know, like, the car ain't going
anywhere without gas in the engine.
And the cancer cell
isn't going anywhere
without the same gas in the engine.
It makes it differently.
It's like it's got a different
grade of fuel, if you like.
But it's still ultimately the same
energy source, the same fuel source.
If we could understand how that
was different, we might be able
to stop it from making its energy.
And in a sense that's what these
anti-estrogens do when they work:
They turn off the switch
and they take away the fuel.
The real thing is how
does that happen?
Now we know where we
really need to focus.
And the basic principles,
when you think of it that way,
are on my last -- or
my almost last slide.
So this is how we think
it works as a system.
This is where it all comes together.
You give an anti-estrogen, you don't
take up enough glucose or glutamine,
fatty acids, but you don't have
what you need to have enough energy
so you can't fold your proteins.
You can't fold your proteins,
that activates the
unfolded protein response.
And that coordinates the don't
die yet signal and lets turn
up the recycle plant because we're
going to live off that for a while.
And maybe we can pull some
other things in from outside.
That's the way the
integration works.
That's where if you look
at it as a whole system,
you see a very different
picture than if you just try
and find a single gene
or a single mutation
that you think might
drive the whole system.
Because the estrogen receptor gets
mutated in some breast cancers.
And that's not the whole answer.
It's when you look at it
as a system that you begin
to see now there are
some vulnerabilities.
There are vulnerabilities in
how the cell makes metabolism.
There are vulnerabilities
in how it coordinates
that -- that recycle plant.
We could turn the recycle plant off.
We could turn that off, we could
turn down the cell metabolism,
and we might get a completely
different response using drugs we've
never thought of using before.
So that's kind of the bottom line.
And what have I told you today?
Because I've covered
a lot of ground,
and I've probably talked too long.
We have to fix this problem.
We have to understand
how this works.
The cancer doesn't
exist as a single cell;
it exists as an organism
almost within the patient.
It talks to itself.
The cells talk to themselves.
They use the host's response
in some cases to survive.
At the same time the host is trying
to eliminate the cancer
with its immune system.
Why hasn't that worked?
That's another piece of the puzzle
that we haven't cracked open yet.
Because if the immune system
worked, you'd never have cancer.
They would just be identified
as being foreign or screwed up
and eaten up and removed.
That's obviously another
piece of the problem.
So there's a lot more to think of.
But if you start thinking of it as
a system, you begin to ask "Well,
what is it that's in the
immune system that's talking
to the breast cancer?"
You know, just think
why does it not work?
You look at the question
in a different way
and you see different
parts of the jigsaw puzzle.
With one woman dying
every 13 minutes
and 70 percent having this
biology when they start,
we need to do something that's
fundamentally different.
We have drugs that work for some
women, we have drugs that kind
of work for some more women, and we
have the same drugs that don't work
at all for another group of women.
We need to be able to do better.
And there are drugs coming along
that are playing in this area
that are probably going
to be very helpful.
We have drugs now that are
called CDK/46 inhibitors.
What that means is they're very good
at also turning off the
proliferation signal.
So when the anti-estrogens come
along and shut down some but not all
of the cells, these other
drugs come can come in
and shut the rest of them down.
Don't know if they'll cause them
to die, but maybe if they're shut
down long enough, they will.
We have the tools -- and I've given
you just an example of a couple --
to ask the questions
of these systems
in ways we could never do before.
Our ability to generate data
first, and then translate that data
into knowledge, and from
that knowledge identify the
actionable items that can lead us
to better preventions
and better treatments
for breast cancer is
moving very quickly.
And it's very exciting.
And the potential for making a
big difference is greater now
than it's ever been in
any time in the past.
Those are tremendously
exciting things to think about.
We have the ability to do this.
Now is the time to do it.
We shouldn't wait any longer.
We shouldn't constrain the resources
that we put to curing this disease.
This is a time to do the opposite
because now we have the tools
that will allow us to
answer this question
in ways we could never
have done before.
Obviously, what I've told you
involves a lot of different people,
and it's nice that I'm able
to put their names up there.
And you're welcome to read them.
But there are names
that are not up there.
And they will never be up there
because I'll never know their names.
I'm not allowed to know
their names, and that's fine.
It's fine that I don't
know their names;
it's not fine I can't thank them.
Those are the women who gave us
the tissue in the first place,
some of them 20-odd years ago.
They're not here anymore.
Some of them died of
their breast cancers
because they had early recurrences.
Some of them died of
their breast cancers later
because they had late recurrences.
Some of them probably I'm
certain are still alive.
I don't know their names.
I can't thank them.
Without what they did, we
could not have got even started
on this pathway.
So the people that are most
important are the patients
who contributed to the
study in the first place.
Thank you.
It is so important to hear from
patients what their experiences are,
what their needs are,
what their questions are.
It's not just about the research.
And it's just lovely to
see someone say "I had it
in the 1970s and I'm still here."
Because we'd love that to
be the story for everyone.
Now, can we take what we've
learned and make it --
and turn it into new treatments
for prevention, or to eliminate
that cancer, or make
it never come back?
I think we can.
But we started to think about
how we do that very differently.
So the way that -- I use
the example of a car.
So the same way of thinking
is the way we're beginning
to change how we -- I
think we should be thinking
about how we combine drugs to get
a better effect than just randomly
or following a logical
linear way of thinking.
This is a non-linear
way of thinking.
If you really wanted to stop
the car, you'd break the switch,
you'd take out the battery,
you'd drain the fuel tank.
We've kind of thought of different
ways of breaking the switch,
but we never thought of "Okay, I
should really take the battery out
and drain the fuel tank
as well because, you know,
we want to make darn sure
this cell can't function."
So in the past -- and it
was a fine way to go --
and the CMF therapy that you got is
a good example of we took drawings
that had different
mechanisms of action
and didn't have the same toxicity so
we could give them in combinations
at the highest doses we could.
And that's fine, but it's --
it's a practical, pragmatic
but not hypothesis-driven approach.
It's what you can do.
It doesn't mean it's
what you should do.
Sometimes it is.
Sometimes there's better ways.
So we're trying to
think differently.
So let's not just take
three drugs like that
because they have different
mechanisms of action.
They're not -- not that different.
[Inaudible] are similar in a sense.
But we want to now target
different parts of the whole system.
The more pieces of the system
that we can knock out at once,
the less chance that cell has
to figure out how to survive.
And that's a different way
of thinking because we had
to understand what those functions
were, how they might be wired,
and talk to each other
before we could even think
of doing it this way.
And we still don't know enough
to do this rationally yet.
But it's taking -- it's allowing
us to begin to think differently.
And sometimes that's just enough.
You think differently, you may get
to a place you never
thought you'd get to,
but it's still the right place.
We do know that there are
different types of breast cancer.
We know
that estrogen-receptor-positive
is different
from estrogen-receptor-negative.
We know that -- that a
mutation in a gene called HER2
or ERBB2 also creates a special
group of cancers that we can target
by targeting that growth
factor with drugs
like [inaudible] as
you probably heard.
So at the very least there are
those that have the expression
of the estrogen receptor,
those that have expression
that mutated oncogene HER2, and
those that don't have any of those.
And the other one that goes
with the estrogen receptor is
progesterone receptor.
And that's why that last group is
sometimes called triple negative
because it doesn't
have estrogen receptor,
progesterone receptor,
or mutated HER2.
At that level there's
at least three.
Once you start asking "Are
there other groups within that?"
then is opens a whole can of worms.
There are, depending
on what you look for.
Different mutations you'll find
are scatter in a different way.
Other pathways that
are differentially --
you'll find that as subgroups.
Ultimately, for the moment
the type of treatment
that a woman gets is
determined by whether
or not there's the estrogen
receptor there to target,
whether there's HER2
there to target,
or whether there's
neither of those to target.
And that's the triple negative,
and they unfortunately have the
highest risk of recurrence and death
in the shortest period
of time since diagnosis.
And we only have chemotherapy
for the moment for those.
And they seem to be a
quite heterogeneous group
of breast cancers.
And it's about 12 to 15
percent of all breast cancers.
The subgrouping is useful
in my personal view --
and this is only my personal view --
if it teaches us something about the
biology we didn't know that leads
to an actionable outcome
that allows us to identify
which women should be
treated with which treatments
because that's the best for them.
I'm not sure we've quite
got there yet with a lot
of these subtype analyses.
We can say from some of them
that this woman has a
worse outcome likely
or a really good outcome likely.
So some of the tools are
good in a prognostic sense.
And the real value there
is who not to treat.
Because some of the very
early stage breast cancers
like I described [inaudible]
if the surgeon gets in
and the radiotherapist gets in and
it's gone, you don't need chemo.
So why would you take it?
It's not a very pleasant experience.
So the real goal there is if your
risk of recurrence is so low,
why would we use chemo
at this point?
So those are the sort of questions
that we're able to do better at.
But which chemo should you get?
We're not there yet.
What new drugs, what combinations
of current drugs would give us the
best outcome for you versus you?
We're not there yet.
But those are exactly the
directions that we want to go in.
We'd like to be able to say that --
that your cancer is unique in
some way, and we understand
that uniqueness, and that
uniqueness is a vulnerability
in that cancer that we can target.
That's the sort of
precision medicine concept --
one way of expressing the
precision medicine concept.
I think we will find better ways
of using the existing
drugs first, I suspect.
And we'll see the benefits of that
earlier simply because we don't have
to wait for a single drug to be
approved and sure that it's safe
and efficient, and then identify
the patients that need to be used,
and then figure out how to use it
in combination with other drugs.
That's a long process.
And we need to keep doing that
because we need to find drugs
that hit different parts of
that machinery more effectively.
From where I sit, we have
drugs that target metabolism,
we have drugs that
target proliferation,
we have drugs that target survival.
We've never understood
how we should use those
or whether they're the right drugs
to hit those targets if we were to.
But now we can build mathematical
and computational models
with the data that allow
us to ask those questions.
And those questions
because they're done
in the computer can be asked
hundreds of thousands of times
and very quickly and
make predictions
as to what we can do quickly to
test first in cell culture models
and then in preclinical
animal models to see --
make sure that those drug
combinations are safe effective
and then quickly get them into women
because the drugs are approved.
That is -- so that's
a drug repurposing
or redesigning the cocktails.
And there are some really
interesting clinical trial designs
that I won't go into today
because I'm not a clinician
and I wouldn't be able
to answer your questions.
But there are some really
powerful new clinical trial designs
that are beginning to try and get
at that, where women can come in
and they can get treated
with one set --
series of drugs, and then upon
recurrence they automatically get
into a different box.
We think that there might
be ways of better selecting
when a woman gets what drug
and what box to go into next.
And so these new designs which
are using existing drugs --
and a small number -- will probably
teach us how to do that better.
And we'll be ready, then,
to do those experiments --
to do those trials in women once
we've completed the experiments
that tell us how to mix and match.
So my prediction?
I -- I make this as a
prediction for my lifetime,
and since when it's over, I won't
be here to know I was wrong,
I think we will make
estrogen-receptor-positive a disease
that women die with but not
of in my lifetime -- I think.
Triple negative?
A little longer.
If there was a BRCA12 mutation,
the risk of ovarian cancer is also
increased along with breast cancer.
So that's the Angelina Jolie story.
So -- and that's -- I mean, again
that's a very personal choice
for every woman in consultation with
her physician, removing the breasts
and then removing the ovaries to
eliminate the risk of both breast
and reduce -- greatly reduce -- the
risk of breast and ovarian cancers.
So, again, that's -- we have -- we
have professionals who help women
and families work through those
and find what is the
right solution for them.
So that's probably the
rationale for that.
So HER2 is a protein that
sits in the membrane of --
of breast cancer cells, and
it's mutated in a way that means
that it's constantly
sending a growth signal,
a proliferation signal, a survival
and proliferation signal
to the breast cancers.
And they are -- a significant
proportion of the ones that have
that are depending on that
signaling in a way that's similar --
conceptually similar -- to being
driven by the estrogen receptor,
not as being driven by HER2.
And so if you come along with
drugs that block that signaling,
the cells can't survive
and they can't proliferate.
And about half of those have no
estrogen receptor and about half
of those have estrogen receptor.
The ones that don't usually get
a chemotherapy at some point.
The ones that do can still
take tamoxifen or letrozole --
an anti-estrogen aromatase
inhibitor --
and they will sit gel some benefit
from that even though
they've also got
that driver mutation
in the HER2 gene.
So it's an interesting
intermediate biology in one sense
and a completely different
biology in another.
>> Tomoko Steen: Please join
me thank you for [inaudible].
[ Applause ]
>> Robert Clarke: Thank you.
>> This has been a presentation
of the Library of Congress.
Visit us at loc.gov.