cc
>> Welcome, everyone, to
Wednesday Nite at the Lab.
I'm Tom Zinnen.
I work here at the UW Madison
Biotechnology Center.
I also work for UW Extension
Cooperative Extension, and on
behalf of those folks and our
other co-organizers,
Wisconsin Public Television,
the Wisconsin Alumni
Association, and the
UW Madison Science Alliance,
thanks again for coming to
Wednesday Nite at the Lab.
We do this every Wednesday
night, 50 times a year.
Tonight, it's my pleasure to
introduce to you Paul Clark.
He was born as my father was in
Milwaukee, and he grew up as my
father did south of Milwaukee
in Cudahy.
Although, my dad grew up
in Racine.
Close enough.
Paul got his bachelor's degree
in biomedical engineering from
the Milwaukee School of
Engineering.
And then he got his PhD in
bioengineering at the
University of Illinois
at Chicago.
And then he came here as
a postdoc.
Since then, he's been promoted
to be assistant scientist.
He's in the Department of
Neurological Surgery.
Tonight he's going to talk with
us about cancer stem cells as a
model to develop novel brain
tumor treatments.
Please join me in welcoming
Paul Clark to Wednesday Nite
at the Lab.
[APPLAUSE]
>> Thank you very much, Tom.
[APPLAUSE]
Excellent.
Thank you, everybody.
Thank you, Tom, for that great
introduction, and thank you all
for having me.
I'm very honored to be able to
give this talk to you today.
As Tom mentioned, my name is
Paul Clark, assistant scientist
in the brain tumor research
laboratory of Dr. John Kuo over
at the UW Hospital.
And today I'm going to talk
about cancer stem cells and sort
of how we're using these to
develop new approaches and new
treatments to brain tumors and
the such.
So just a very general
beginning.
Of course, cancer is a
widespread and a really bad
disease in the US as well as
worldwide.
Millions of new cases each year
and hundreds of thousands of
deaths.
In the US, it is the second most
common cause of death right now,
and soon this will be overtaken
and cancer will soon be the
number one killer within the US.
Just kind of, the picture here I
just sort of wanted to point out
that cancer can pretty much
occur anywhere throughout the
body.
It's sort of preferable in some
areas, but it can come up
anywhere and, for the most part,
it can kill from anywhere.
Now sort of jumping from this
population, as a biologist, I
look at this as a molecular
disease.
And so, overall, cancer at its
very base is a disease of
mutations.
So DNA being the genetic sort of
code of life within every single
cell of the body built all the
way up to functioning to the
organism or human, and so when
this DNA is mutated or changed
from its normal base sequence,
if it's changed in the wrong
spot, this can induce cancer and
can lead to cancerous growths in
the body.
And so through many groups for
many, many years now, they've
identified specific genes that
they think are responsible for
this sort of thing.
So oncogenes are genes that
drive cancer, sort of like
pushing the gas pedal on a car,
to drive them forward so that
cells start accelerating too
fast and become cancerous.
Conversely, tumor suppressor
genes are like the brakes on a
car.
So when these are cut by
mutations, these lead to cancer
as well.
And, in general, these mutations
in DNA are pretty random.
So just normal cell division and
as you go age and progress
through life, as good as cells
are when they divide and
proliferate, they do make
mistakes every once in a while.
So these mutations accumulate.
Other environmental toxins have
been found as well, and when
they occur at these certain
oncogenes or tumor suppressor
genes, they can induce cancer.
So kind of from the lowest level
molecularly, this is what
cancer is.
And so because of this random
nature of these DNA mutations,
sort of the traditional view of
cancer has been that it arises
from a clonal evolution sort of
paradigm or a random process.
So some normal cell in your body
accumulates a mutation in its
DNA that gives it some sort of
growth advantage.
That cell grows a little bit but
can't quite be a full blown
cancer, and then as you progress
in age or as this cell survives
and passes on this mutation to
its progeny, it eventually
accumulates more mutations until
it finally sort of outdoes all
the checks and balances of the
body and becomes this full blown
tumor.
But as these mutations
accumulate, this is seen as a
random or stochastic process.
And kind of the other important
point is that at the end that
every tumor cell with this model
is seen as pretty much the same
thing.
They all have the same random
chance to become a full blown
cancer and a full blown tumor.
And so what I'm going to begin
with tonight is sort of
describing that as science
usually goes, this is not the
whole story, and there might be
a little bit more to it.
It may not be a completely
random or stochastic thing.
So this began a couple decades
ago with researchers that were
looking at leukemia, or blood
cancer, and who were just kind
of trying to answer the simple
question of how many cells
within a cancer can actually
sort of transmit that cancer or
regrow the entire cancer in a
new organism.
And so for this, they used the
good old laboratory mouse.
And an immunodeficient mouse
they could put cancer cells and
regrow human cancer within a
mouse model.
And just sort of the simple
setup was they just took these
leukemia cells, withdrew them
from patients, these single
cells, and just sort of diluted
them down in attempting to find
out how prevalent cancer cells
are, even in a full blown
cancer, to reform an entire
cancer in these mice, and they
found that about one in 250,000
cells are sort of by this random
process, I guess you could say,
lucky enough to form this new
cancer and survive into a new
organism.
And so, according to this sort
of random or stochastic process,
this wasn't a huge finding, but
what this group then started to
do is they had expertise in
looking at normal stem cells of
the blood known as the
hematopoietic stem cells.
And so they were experts in the
techniques and technology and
things like that to define the
entire hierarchy of blood stem
cells.
So starting with the stem cell
on top and then how a blood stem
cell progresses all the way down
to the different cell types of
blood.
The immune system, white blood
cells, red blood cells, things
like that.
And so, importantly, the way
they were able to do this was by
looking at these protein surface
markers that at that time were
being developed and really
defined for these different cell
types.
So they are proteins on a cell
surface known as cluster of
differentiation or CD proteins,
and this group as well as other
groups at the time were trying
to sort of define almost like
barcodes for cells.
So in the examples up here, this
sort of CD 34 positivity, if
that is present on a blood cell,
it is very indicative of a blood
stem cell.
Whereas, when this cell begins
to differentiate to more mature
cell types, they take on these
sort of different proteins and
lose this CD protein.
So using this barcode then, they
could sort of derandomize their
initial experiments, and
actually they were interested in
if for some reason there were
subsets of these leukemic cells
that could drive the cancer,
whereas other subsets might not
be able to.
So taking that a step further,
they used these surface makers,
these leukemia cells.
So the setup being the same,
that they would get leukemic
cells from patients, look at
this population, and now using
this technique called flow
activated cell sorting, they
could actually, cell by cell,
pick the cells that express
these different surface markers.
The example I'm going to use
here is a CD 34 or stem cell
marker, and they could actually,
using this technology, pick
these specific cells, these CD
34 positive cells, inject those,
and then separate all the other
cells or all the other
subpopulations and look at how
cancerous or how aggressive
these cells were.
And kind of surprisingly, only
the CD 34 positive cells from
this leukemia were able to
induce the full blown cancer in
these new mouse recipients.
So kind of what this said is
that cancer may not be an
entirely random process anymore.
There might be definable subsets
that drive the cancer and then
are responsible for cancer both
sort of initially as the cancer
grows, and then for cancer
treatment, these might be the
cells responsible for regrowing
after treatment of patients.
And as I mentioned, the CD 34
was a stem cell marker within
the blood.
So they wanted to kind of
explore this a little further.
And so with the stem cell angle
in mind, I just want to sort of
take a step back and define kind
of how some functional
definitions of what we think a
stem cell is sort of from the
research side of things.
So, stem cells have a couple
properties that have to be shown
to sort call them stem cells.
One of these being what's called
self-renewal or the ability of
these cells to pretty much
divide but remain stem cells.
So in my mind, this is almost a
stem cell remaining immortal.
It can always keep its identity
and either create a clone of
itself or just divide or almost
bud off a daughter cell that
then becomes a more
differentiated, specialized cell
type.
So that's the self-renewal
property of stem cells.
The second being the ability of
stem cells to sort of
differentiate and become
different tissues of the body or
different cells within whatever
tissue they come from.
So this is known as potency.
And so just kind of show what
these terms, how they sort of
relate within this cartoon.
Sort of the penultimate stem
cell is the embryonic stem cell.
So these are the cells that
build every cell and become
every cell and tissue within the
body.
So these embryonic stem cells
have this ability of
self-renewal that they can stay
stem cells pretty much as long
as they're needed.
But they also produce cells that
can differentiate.
So they differentiate sort of
from the top of this hierarchy
beginning as embryonic stem
cells, they become cells with a
little less self-renewal known
as adult stem cells, and then
these are a little more
specialized in that they can
only become certain tissues of
the body, and then finally
becoming every tissue, all the
mature cell types of the human
body.
Sort of apart from these
definitions, what's important
when calling a cell a stem cell
in a dish when you get it is the
ability of the cell not just in
a dish to have these two
properties I just described but
to also be able to produce all
these tissues when put back into
an in vivo system.
So, in general, back into this
immunodeficient mouse.
So following this example of
embryonic stem cells, if we put
the embryonic stem cells back in
the mice, they become all the
tissues, you can see all the
different tissues of the
organism such as cartilage in
bone, intestine and brain cells
and neural and things like that.
So just these three sort of
defining properties of a stem
cell, of self-renewal,
multi-potency, and the ability
to recapitulate all the tissue
in vivo.
So this group was, like I said,
blood stem cell people, and they
knew how to identify and how to
call something a stem cell.
So taking this CD 34 cell that
they had got from a cancer, they
subjected these cancer cells to
these different stem cell
assays, and sure enough, they
found that they satisfied all of
these different stem cell
properties.
So the CD 34 expressing cell
that they could get from blood
was able to exhibit
self-renewal, so make copies of
itself, potency to different
multiple types of specialized
cells, so using the same
techniques they used for normal
stem cells, these cells could
also lose this CD 34 or stem
cell identity and become the
more differentiated cells of the
blood, or at least express the
markers.
So it was probably a cancerous
differentiation, but they were
able to differentiate.
And then finally, as I was
saying, they would inject these
back into mice, and only these
CD 34 positive stem cells from
this cancer were able to
recapitulate the entire tumor in
the mouse.
So even in the mouse they would
form cancer, but they would also
form all these sort of
differentiated and subtypes
found within the patient's
cancer as well.
And so all together this made
them sort of start calling
these, as a term and as a sort
of context, as cancer stem
cells.
So now kind of shedding light
that the subpopulation, as I
mentioned, cancer might not be a
completely random thing anymore.
There might be subsets of these
cancer stem cells that induce
cancer, drive cancer, and lead
to cancer regrowth after
treatments.
So just sort of a comparison.
Like I said, kind of the most
important thing is that it's no
longer completely random.
Whereas, this clonal evolution
predicts that mutations gather
in sort of a linear fashion
until just any kind of random
cell can form this tumor in
which each cell is the same.
This cancer stem cell model has
sort of this hierarchy, this
linear hierarchy of cancer cells
instead where the cancer stem
cell is on top, this is the cell
can pretty much infinitely make
copies of itself as well as
follow this kind of cancer
differentiation, this aberrant
differentiation to all the cell
types found within this cancer.
So with the general cancer stem
cell model there and then kind
of how this fits as I started
with kind of the basic idea of
molecular biology is that cancer
is a disease of mutations, and
so molecular biology, of course,
too has come very far within the
last couple decades as well and,
with most sort of general first
ideas, that this has got much
more complex.
So cancer at its base is still a
disease of mutations, but a lot
can happen and a lot does happen
from DNA to protein.
So between transcribing this
mutated DNA to controlling how
the MRI is shuttled around the
cell and how it eventually
becomes these proteins that
drive cancer, a lot can happen.
So kind of how this fits with
this cancer stem cell model is
that the cancer stem cells are
possibly the only subset within
this cancer that know how to
manipulate all of this to still
form cancer and drive cancer.
And as they kind of
differentiate down this path,
these non-cancer stem cells that
form the bulk piece of the
cancer cannot manipulate these
well enough and, thus, do not
drive the cancer and cannot
proliferate enough to be
cancerous.
So that is the general cancer
stem cell model, and I want to
now move on to what my specific
lab does.
So the cancer, I work in
neurological surgery, the cancer
we look at is malignant brain
tumors.
And, not surprisingly, these
brain tumors are an incredible
clinical challenge because of
the location and how important
the brain and nervous system are
to the functioning human as a
whole.
And they are estimated about
20,000 new cases of these
primary central nervous system
tumors each year and about
14,000 of them are deadly.
And within children, these brain
tumors actually represent the
most common form of solid tumor
and second more cancer that
comes up in kids.
And what's up there now, I just
want to sort of say that there's
a sort of large breadth of
different types of cancers and
tumors that can arise in the
nervous system that are each
kind of named for the different
parts of the brain or nervous
system that they arise in as
well as kind of what the cells
look like in the tumor to a
pathologist or histologist.
So there's a long list here, and
the ones we look at specifically
within the lab are what are
known as gliomas.
And so from this long list, the
way the cell biology of the
brain works is there's three
kind of main cell types in the
brain, the neuron being the data
transmitter and sort of the
workhorse of the brain that
organizes and does all of that
sort of thing within the nervous
system, but there's also these
support cells, both these
oligodendrocytes and these star
shaped astrocytes, and these
cells are constantly always in
the brain helping the neurons to
work at an optimal level.
And so since they're glial
support cells, when they go bad
and become cancer, they're known
as these gliomas.
And then the specific subset of
these gliomas that we look at in
lab is the glioblastoma
multiforme or GBM.
And this GBM is about half of
all gliomas that come up in
patients, and it is
unfortunately inevitably a very
deadly and fast acting disease
and the most aggressive and
deadly glioma and potentially
the most deadly and aggressive
brain tumor you can get.
The way these are detected are
using non-invasive imaging in
the clinic.
So over here you can, this is an
example of a magnetic resonance
imaging.
So this is an entire human brain
here with the sort of normal
brain tissue here shown by MRI,
and then this part that enhances
here is the glioblastoma
multiforme part.
So this is how a clinician
actually visualizes and detects
this in the clinic.
And how this looks sort of
cellularly and on a macroscopic
level just normally is shown by
this sort of whole brain mount
of an autopsy in which the
glioblastoma is over here.
So indicative of this disease,
it grows so fast that it ends up
sort of dying within itself so
there's a lot of necrotic
tissue.
It's a reddish tissue because
it's really good at inducing
blood vessel and vascularization
to feed itself.
And, like I said, just a high
proliferative index that sort of
makes it grow out of control
and, of course, eventually,
unfortunately, kill the patient.
And, as I mentioned, this is a
highly aggressive, highly deadly
disease, and despite all the
state of the art in both imaging
to detect the tumor and the
common treatments of surgery,
radiation, and chemotherapy,
like I said, with all the state
of the art, the overall survival
for these patients with these
glioblastomas remains incredibly
poor.
So I usually put this survival
curve up because it kind of is
indicative of the big problem of
these glioblastomas.
So in survival curves like this,
this was a clinical trial on
human patients done to test the
ability of this chemotherapy
Temozolomide to improve patient
survival.
So in these survival curves,
100% survival on top, and then
each patient that passes during
this timeline on the bottom is
charted onto this slide.
So a right shift means the drug
is at least working a little
bit, and with this specific
clinical trial, the Temozolomide
was approved as sort of the new
gold standard along with
radiation treatment and of
course -- resection, safe
resection surgery.
But if you actually look at the
numbers, it was only with an
increase of two months of
survival from just a 12-month
average to a 14-month average.
Extra survival for people with
this disease is fantastic of
course, but to me it says that
we sort of need new approaches
or some new treatment needs to
be attempted and tried to make
significant gains in the
survival of this glioblastoma
multiforme.
So that's pretty much where our
lab then comes into play.
So we are trying to use this
cancer stem cell system and
approach within and apply it to
this glioblastoma brain within
patients.
So us as well as other groups
have now shown that these cancer
stem cells can be isolated from
glioblastoma, and sort of the
work through of this looks like
starting from a patient GBM, so
again this is looking down on a
patient brain, and the enhancing
region is the tumor.
So if we can get a piece of this
tumor from the surgeon and then
we analyze this either two
different methods that are used
either using a similar surface
marker approach with this
specific CD 133 protein or a
cell culture approach developed
for normal neural stem cells
known as the neurosphere assay.
So in this assay the potential
stem cells are cancer stem cells
in this case in red are able to
grow in very specific conditions
that we give it or as
differentiated cells are not.
So with either of these
approaches now, us as well as
many other groups have
demonstrated that these cancer
stem cells can be isolated from
glioblastoma.
And so once we have them, of
course the final test is that
they still induce tumors within
these immunodeficient mice so we
orthotopically inject them into
the brain of these mice and they
do grow these tumors.
And kind of the final validation
is that the tumors that grow, so
this is a histological high
magnified slide.
Each one of these dark dots is a
cell within the brain.
And so just high cellularity,
like I said, dying tissue,
disorganization, but the cancer
that grows in this mouse after
it's injected from these cancer
stem cells recapitulates pretty
much exactly what is seen in the
initial tumor, initial patient
tumor.
And, thus, cancer stem cells
from glioblastoma.
And so, conversely to that, if
we take this non-cancer stem
cell population, tumors do not
form within these mice.
And so this is what these cancer
stem cells actually look like
when we grow them in lab.
So, as I mentioned, we grow them
at these sort of aggregates of
cells, like little soccer balls
floating in cell culture medium,
and so this is one of those
tumorspheres, or neurospheres as
they're known.
And this is a couple thousand
cells here.
So pretty much how these work is
these cells stick together and
continue to grow kind of on top
of each other.
And the way you can kind of
think about this is almost like
growing a little, each of these
spheres represents a little
tumor with highly enriched
cancer stem cells but also other
pieces of the tumor as well.
And so, again, this was borrowed
from the normal neural stem cell
culture which uses this
neurosphere system to derive and
propagate these neural stem
cells, and thus, again, sort of
parallels between these
cancerous stem cells and the
normal neural stem cells.
Following that same logic again,
as I mentioned, one way we look
at these in trying to call them
stem cells is if they act like
normal stem cells.
So they express the same surface
stem cell markers, and if we
either label these cancer stem
cells for this CD 133 surface
marker, so in this case the
green is expression of this
marker and it's very prevalent
both throughout the cancer stem
cells as well as throughout
normal stem cells.
Nestin is another marker for
these neural stem cells as well.
And similar here, green is this
nestin stain within this sort of
clump of cells, each blue dot
being a single cell within this
sphere culture.
Similar expression between the
cancerous stem cells and normal
neural stem cells.
So kind of establishing the fact
that they act like stem cells.
And then the second thing to
test is that they, again, retain
this potency to become these
different lineages within the
brain.
So sure enough, if we put these
stem cells, cancerous stem cells
under different conditions, they
stick to a plate and extend
processes and begin to look like
neural cells, similar to the
normal neural stem cells when we
put these under the same
differentiating conditions.
And so analyzing specific neural
lineages, the cancer stem cells
begin to express proteins
indicative of both neurons, so
green here is the protein beta
III Tubulin, again similar to
the neural stem cells, as well
as this red stain here for
astrocyte specific protein known
as GFAP.
So these cancerous stem cells
that we isolated in this fashion
now satisfy sort of the first
two definitions of what a stem
cell is with almost eerie
parallels with the normal neural
stem cell counterpart.
And then sort of, again, the
final validation is when we
actually put them back in the
humans or when other groups have
done this that they recapitulate
the patient tumor very closely
and almost exactly.
So on the left side here is
magnified patient tumors that
this group, sort of the original
group to isolate these stem
cells got and then resulted in
xenografts that were grown in
the mice.
So whether it be just a general
stain known as HNE for
histology, it looks very
similar.
This nestin stain again.
So brown is what's called an
immunohistochemical staining is
positive staining for this
protein that labels stem cells.
So very similar nestin staining
between these two.
MIB one, brown positive again,
as a proliferation marker.
So, as I mentioned, these are
very highly proliferative tumors
that grow so fast they almost
grow on top of each other.
And in this case well, similar
staining between patient and
mouse.
And then as well for this
astrocyte specific protein known
as GFAP similar as well.
So I'm just kind of pushing,
again, that these functional
definitions of a stem cell can
all be satisfied from a cell
that we got in cancer.
And so now that we know kind of
that a subtype exists that we
can define or that we can easily
obtain, people began studying
these biologically.
So they're important, for one,
because they seem to be the
cells that drive the cancer and
potentially drive the cancer
after treatment, but further
than that, little was known.
So now biologically groups began
to look at how these cancer stem
cells behave when sort of
threatened by these current
treatments that are used against
brain tumors, specifically
radiation and chemotherapy.
So the group, this picture that
I'm showing here now is a group
that looked at how cancer stem
cells respond to radiation.
And they seem to be resistant to
this radiation in that these CD
133 positive cells, as the
cancer stem cells from
glioblastoma, there's a lot
percentage in these untreated
mice when they inject them, but
radiation actually seems to
purify for these cancer stem
cells, suggesting that the
cancer stem cells are the
resistant population within this
brain tumor.
And then they went on to show
many other tests and experiments
to show that yes, the cancer
stem cells are better at
surviving this common radiation
application, this radiation
treatment that patients even get
for glioblastoma.
Additionally, other groups now
have shown that these cancer
stem cells are also resistant to
common chemotherapy known as
Temozolomide.
And this is a survival curve
testing these cells with 100%
cells surviving on the top, none
at the bottom, like all dead at
the bottom, and then across
varying doses of this
Temozolomide chemotherapy.
So in this case, the CD 133
cells, fewer die when exposed to
this chemotherapy versus the
non-cancer stem cell, or CD 133
minus population, that rapidly
perishes when this chemotherapy
is given.
So kind of wrapping this all
together, it sort of presents a
new model to us so that these
cancer stem cells, really the
fact that they potentially drive
the cancer, can recapitulate the
cancer, as well as being
resistant to common treatments
within a tumor really tells us
that these must be the cells
that must be eradicated for
successful cancer treatments.
So just in cartoon form from our
original tumor, if we give these
common cancer treatments, the
cancer stem cells survive in
red, and then they are sort of
one of the only cells within
this tumor that are able to then
regrow the tumor as a whole.
So eradication--
>> Question.
>> Mm-hmm, yep.
Yeah, go for it.
>> So maybe you're gong to
answer this next, but what would
the reason be that these stem
cells are more resistant to
chemo and radiation than other
cancer cells?
Why are they such harder cells?
[INAUDIBLE]
>> Yeah, they try to...
>> Can you repeat the question.
>> Oh, yeah.
So just asking why these cancer
stem cells might be more
resistant to these common
chemotherapies and sort of more
hardy than the other tumor cells
as a whole.
And people are definitely
looking into that right now, but
they're kind of overall relating
it back to normal stem cells as
well that are usually pretty
resistant to therapies as well.
It's one of those things that
when your body gets injured, it
needs those stem cells to be
able to regrow tissue.
If you cut you skin, you need
your stem cells and skin cells
to proliferate.
So kind of just evolutionarily
these sort of became the more
resistant and more tougher cells
within the body.
Second to that, common
chemotherapies in general attack
proliferating cells, and by sort
of disrupting DNA and breaking
DNA, that kills cells when they
proliferate.
And even though it really hasn't
been shown, one of the other
theories is that the cancer stem
cells just proliferate slowly.
They're pretty much only called
upon when needed.
So just like normal stem cells,
they stay quiet, acquiescent,
don't proliferate until you kill
everything else.
So with the mix of all those
different things is how they are
hypothesizing right now that
these are more resistant, but
definitely a case that needs to
be ironed out.
There's no real simple answer to
it yet, unfortunately.
So kind of moving on now from
these sort of general cancer
stem cell sets, I'm going to
move into a few approaches that
we're using in lab about how we
use now this hypothesis to sort
of make novel or new cancer
treatments.
And I'm just going to talk about
three projects being done in our
lab right now.
One about kind of the obvious
way of specifically targeting
these stem cells so that we can
kill that subpopulation as well
as the normal chemotherapy to
kill the rest of the tumor,
what's known as differentiation
therapy.
As a second point, sort of using
the normal stem cell hierarchy
and applying it to these cancer
stem cells as well.
And then finally end up with
kind of the brute force approach
that now that we know these
cancer stem cells exist, we want
to develop and make novel new
drugs that attack both the
cancer and cancer stem cells.
So starting with specifically
targeting cancer stem cells, we
have adopted an antibody based
approach.
So antibodies of the immune
system, when they were first
identified, were described as
the magic bullets against
disease.
So antibodies are part of the
immune system that are highly
specific and bind tightly to
pretty much for our immune
system what is considered
foreign invaders, and then they
start the immune system and
immune response to get rid of
any foreign invasion into the
body.
And so these antibodies now,
this is kind of the cartoon of
what an antibody looks like, and
so they have these two arms, and
these arms are the antigen
recognition sites.
So these antigen recognition
sites bind incredibly tightly to
very specific proteins.
Like I said, naturally in the
body it would be a foreign
invader, but they can now be
engineered to kind of attack any
protein that we want them to.
And so it's kind of not quite as
simple as this cartoon depicts
but, as shown by this x-ray
structure here, was still kind
of the same Y shape with an
antigen recognition site out on
the side here.
And how these antibodies are
currently being used in cancer
treatment and how we hope to use
them is kind of, so you can see
there's many different ways that
people are attempting to use
them, the two we mean to focus
on is if we can find a protein
that is specific to the
glioblastoma cancer stem cells
and not in normal tissue around
the body.
For one, this antibody may bind
it and initiate an immune
response to sort of detect the
cancer as a foreign body and
destroy it, or another
alternative route we might be
able to do is if it's specific
enough we can bind an antibody,
if we find it, with a poison
that can specifically attack the
tumor cells and not normal
tissue, eradicating the tumor
as well.
And so this was the project of a
PhD student that just graduated,
Mike Zorniak, and he used what's
called yeast display technology.
So this was working with a group
in chemical engineering and
pretty much using yeast to
create and entire sort of human
immune system outside that we
can use in a dish.
And the way they did that is
using these antigen recognition
fragments known as single chain
variable fragments, or scFvs,
they actually could engineer the
microbes of yeast to display
these scFvs on their cell
membrane, and they could
actually be used to bind with
the cancer stem cells or kind of
any substance that you are
interested in.
So kind of moving on from that,
and yeast are really nice
because since they bind and even
in a dish we can see the yeast
binding and determine which
antibody fragment scFvs are
successful and which ones
are not.
And so, of course, we didn't
want to do that one by one, and
they took this a step further
and pretty much made this almost
entire human immune system.
So they developed enough scFvs
fragments within these yeast to
look like 500 million different
antibodies.
So this is going to be pretty
much a fishing or kind of
shotgun approach that we throw
this whole pool of 500 million
antibodies and try to find one
or a couple that detect
specifically our cancer stem
cells.
And so these 500 antibodies in
yeast and then we can use this
in what's called a biopanning
approach.
So pretty much like panning for
gold, we biopan for a very
beautiful and gold antibody, I
guess.
So, much like gold panning, you
start with a big chunk of mud or
a sift and sort of through many
different rounds you can
actually find little gold
pellets.
And in a similar approach here,
through multiple rounds of sort
of sifting out the garbage and
finding the antibodies that
bind, we can detect or find a
very specific antibody,
hopefully, to our cancer stem
cells.
And so with our cancer stem
cells in a dish, we can throw
this whole original library on
top of there.
Some stick, some don't.
So we remove the ones that don't
and then keep the recovered ones
that do, grow this library up
again of the yeast displaying
our antibody fragments of
interest, and then through
multiple rounds of this sifting
and recovery and amplification,
so second round and Mike did it
all the way to a ninth round
until he was confident they were
very tight binders to these
cancer stem cells, we can then
find this enriched pool of CFC
binders.
So with this shotgun approach,
we don't know exactly what's
there or how many sort of unique
antibody fragments we had.
So over a year or two, he
started looking at all these
different types of scFvs that we
obtained that tightly bound
cancer stem cells.
And so this is sort of figure of
sort of the entire, all the
unique antibodies and antibody
fragments that he found.
So this is related to DNA
fingerprinting for humans.
So just like different streaks
on this gel can identify
different humans, it can
identify different antibody
fragments, in this case, as
well.
So doing this for over a
thousand of these clones, he
found 62 unique antibody
fragments that we hypothesize
would specifically bind these
cancer stem cells.
And through a bunch of other
further purifications and
further testing, he determined
that this specific 9.7 was going
to be kind of the highest, best
candidate to develop further.
So, sort of moving with just
this one scFv that he found,
scFv 9.7.
And so to sort of ensure that
this was scFv selected, we
further kind of modified the
yeast.
And so instead of actually
presenting it on their surface,
there's a different, we can
modify them to make the yeast
produce it and release it.
So to make them little factories
and little manufacturers of our
scFv or antibody fragment of
interest.
And so Mike did this with these
yeast, and these little
splotches here represent
purified protein.
In this case, this is our
antibody fragment of interest
right here.
And then what I'll talk about in
a few of these experiments is
this 4420 scFv which will be a
negative control for all of our
experiments in that it does not
bind any known protein to be
expressed by humans.
And so the way we tested this is
across many different patient
glioblastoma lines, against
normal cells, as well as the
non-cancer stem cell population.
So up on top here are sort of
the same techniques they used
with the leukemic cells, this
flow cytometry, to define single
cell bases if whatever protein
this antibody fragment was
attaching to it was present on
these cancer cells.
So the way these are set up is
on this X axis is sort of how
bright or how much of that
protein is expressed, if at all,
on these cancer cells.
And then these curves, as they
shift to the right, means
positivity against with this
scFv 9.7 antibody fragment.
So with the cancer stem cells,
it was very good to see.
Even when we get this soluble
form of it, it's still specific
to cancer stem cells.
And this was our first time
testing it against normal cells,
which it did not bind which was
very good for us.
And then taking just, from these
two cells lines across many
different cell lines, we saw
similar results, or Mike saw
similar results, so that in
normal cells, either astrocytes
or stem cells, there was very
low binding of this cancer stem
cell specific antibody fragment.
And then across five different
cancer stem cell lines we saw
enhanced binding and a lot of
binding.
And then the non-cancer stem
cell groups as well, we did not
see binding of this antibody to
these non-cancer stem cell
populations.
And so how this is kind of
visualized with this 9.7 is in
the normal human astrocytes,
this is just two cells next to
each other, the blue dots being
cell nuclei again, and the cell
membrane no staining on the
astrocytes, but with the 33
cancer stem cells now, the
specific patient line, we see
littered positive staining all
over the cell membrane.
And so it's very exciting that
this might be some sort of
cancer stem cell specific
antigen that this antibody is
detecting, and we're sort of
moving forward to try to figure
out exactly what that is.
And so, moving on even a little
bit forward, we want to test it
again in animals and see if this
antibody is as good at hunting
down and detecting a tumor in
animals as it is in a cell
culture dish.
So animals were injected again
with these brain tumors, allowed
to grow, and then we gave them
this antibody through the blood.
And so in this case, the glowing
spots here are where the tumors
are, and it detected them very
well.
So this is an entire kind of
cross-section of a mouse
harboring one of these brain
tumors, and the tumor is kind of
on this side right here.
And so the tumor lights up very
nicely.
Whereas, if we use a control
antibody, again this 4420, that
doesn't detect any proteins,
there's no non-specific binding
within, which is nice.
So no binding here, and if no
tumor is present, this specific
antibody fragment does not bind
to normal tissue either.
So very exciting, and we're sort
of pushing these results
forward.
And how we kind of envision
using this now, sort of along
this cancer stem cell
hypothesis, is, as I mentioned,
a conventional chemotherapy
seems very good at eradicating
and getting rid of the
non-cancer stem cell population,
and then we can sort of
supplement any therapies with
this specific antibody.
And either the antibody alone,
potentially or by attaching it
to some sort of poison or toxin,
to specifically sort of kill
these cancer stem cells in here,
and hopefully when we put
everything together, we can get
rid of the glioblastoma as a
whole.
So we'll definitely be pushing
this forward and trying to get
further results on this antibody
fragment study.
Secondarily, what kind of got me
into this field, being sort of a
normal stem cell person, was
this idea of differentiation
therapy for cancer stem cells.
So, as I mentioned, these cancer
stem cells do kind of seem to
want to follow the same sort of
differentiation pattern or same
kind of hierarchy that normal
stem cells follow, but somehow
they get blocked along the way
to then form cancer and lose the
ability to control themselves.
And so one of the ways that
normal stem cells regulate this
sort of path from stem cell to
differentiated cell is through
growth factors.
And these are specific proteins
released by cells that either
can keep a cell a stem cell or
induce the cell to become
further differentiated.
And so, biologically, what I've
been looking at within the lab
for these cancer stem cells are
what's known as the epidermal
growth factor, this protein that
binds cellular receptors.
So on the surface of the stem
cells and then through
intracellular signaling, it
tells these cells to remain a
stem cell.
So this is one of those that
keeps a cell a stem cell, and
the receptor for this protein
EGFR has been implicated within
brain tumors as well as other
cancers of the body as being
kind of overactivated and might
be a key component that's
keeping these cells as stem
cells and keeping the cancer
alive and keeping the cancer
growing.
So, looking at these two
cultures, and within the cell
culture conditions that we use,
we commonly give these two
growth factors to preserve that
cancer stem cell phenotype.
Whereas, similarly, again, to
the normal neural stem cell
culture.
And with neural stem cells, they
definitely need these two
proteins to survive and remain
stem cells versus if they're
taken away, the cells sort of
die and/or differentiate.
And so when we started studying
how these growth factors affect
these stem cells, again the
neural stem cells, when they are
given the self-renewal promoting
protein, form these neurospheres
in culture that renew and
propagate, but when taken away,
they differentiate and/or die
away.
Cancer stem cells, on the other
hand, not surprisingly, I guess,
when we form these spheres again
in culture with the
self-renewing growth factors,
but when taken away, unlike
normal stem cells, they do
maintain this sphere forming
ability and this self-renewal
ability even though the
differences in sphere formation
here definitely suggest some
sort of change in cell type.
And then when we injected these
cells again into this mouse
model that we use, we saw that
they remained tumorigenic.
So they didn't differentiate
all the way down, but what we
did notice is that the tumors
that grew from these cells were
very different from sort of when
we injected the cells that did
have these growth factors.
So plus this EGF and FGF, this
is, again, a mouse cross-section
and a tumor over here.
It forms a very sort of
delineated and very focal tumor
within the mouse.
And the star here represents our
injection site within this
brain.
So the cells don't really go
anywhere.
They're not a very mobile cell
when they're cultured with this
EGF and FGF.
Whereas, when we take it away,
they all the sudden do become
very infiltrative and very
mobile.
So these high magnification
pictures here are on a
contralateral hemisphere.
And these pictures on the
bottom, the brown staining is
for a human specific stain.
So looking for the cells that we
injected.
And again, with this
self-renewing promoting protein,
they don't really infiltrate
normal brain too much.
Whereas, they're littered all
the way throughout, even the
contralateral absolute opposite
side of the brain, without these
growth factors when we establish
these cultures.
So really suggesting that the
didn't quite mature all the way
but they did become something
different.
And so if they followed, again,
kind of this normal stem cell
hierarchy, they should become
kind of more differentiated
cells.
So we started using these
proteins and surface markers
again.
We did look at exactly that.
And so these are what's called
western blots.
So the protein is present, if
there is the blots on these, the
little splatters on these
pictures here.
And so this neural stem cell
marker from plus EGF, these are
three different patient derived
tumor cancer stem cell lines,
and the minus EGF is on the
right.
So nestin goes away, whereas
these three different
differentiation markers all go
up.
So it seems like, again, they
are sort of following a normal
stem cell hierarchy that when we
remove these growth factors,
they move a little bit of the
way down the line, just
something's blocking them from
final differentiation.
So since they still form tumors,
we were a little frustrated with
this, but if we sort of look
back then to one of those
correlates of the cancer stem
cell theory that therapy
resistance is also related to
sort of how stem-like these
cancer stem cells are, if we
applied this, we wanted to test,
okay, did we push the cells far
enough to become sensitive now
to these chemotherapies?
And for this line, it was really
fantastic to see that we did.
So these are, again, cell
survival curves, 100% survival
on top, no survival at the
bottom, across varying doses of
this common chemotherapy
Temozolomide.
So for the ones with with EGF,
FGF, so the ones with more
stem-like phenotype, the cells
almost 100% survived until very
high doses of Temozolomide.
And then if we sort of just
pushed these cells even just a
little bit down this stem cell
hierarchy, we could sensitize
these cells to these common
treatments.
So it was very exciting, and
sort of where we hope to maybe
apply this is that, like I
mentioned, this EGF signaling
and EGFR signaling through many
different cancer types is very
important.
So there are these clinical EGFR
inhibitors available, and
potentially, through careful
timing of administration of
these different drugs, we could
sort of use EGFR inhibitors
first to stop these stem cells
from self-renewing, become sort
of a tumor type sensitive to
radiation and Temozolomide.
So definitely moving forward
with that as well.
And now kind of this third
approach, we're working with a
group, as I mentioned, using
stem cell hypothesis.
So any new drug or novel drug we
develop, we definitely have to
test if it targets both cancer
and cancer stem cells.
So for this, we are working with
Dr. Jamey Weichert, part of the
radiology department at the UW
Hospital, who has developed
these alkylphosphocholine, or
APC, analogs as cancer targeting
agents.
So here's a little cartoon of
what these drugs look like, and
it's really neat how they're set
up.
So this portion of the drug
right here is a targeting drug.
At least what they've done up
until now, they've shown that
this drug can very optimally
target tumors but does not label
normal tissue.
So this targeting piece of this
drug, as long as it stays the
same, it always specifically
labels and specifically targets
many a broad range of cancers.
And now, interestingly, what
they can do then is this side of
the drug, on the other hand, is
very versatile, and they can put
on different pieces here,
whether it be radioactive
substances or fluorescent
molecules for visualization.
So I'm going to cover a couple
of different ways that they've
modified there analogs to be
useful against these cancer stem
cells and against tumors in
general.
So, for instance, when they put
this highly radioactive iodine
molecule onto this APC analog,
they create a molecule,
radiotherapeutic molecule, so
pretty irradiating and baking a
cell from the inside to kill it
since it's so specifically
targets the cancer.
Similarly, they can put a
different radioactive molecule
for positron emission or a very
specific visualization technique
used within a clinic right now.
Then I'll touch a little bit
upon the fluorescent versions of
this as well for real-time
visualizations of cancer versus
normal tissues.
And so, as I mentioned, these
APC analogs selectively label
cancer stem cells.
And here are a couple examples
up right now.
So in a skin cancer melanoma, if
we use this green version of the
drug, it labels the cancerous
cell, or melanoma, very
strongly.
So all the green is strong
staining within the melanoma.
Whereas, normal skin cells take
up very little, if any, of this
drug comparatively.
So making it cancer targeting,
cancer selective.
And then even if we have a
cancer cell right next to a
normal cell, again cancer cell
green positive signal takes up a
lot of the drug compared to the
normal human fibroblast.
And sort of moving on from these
first examples, the Weichert
group as well as our group have
now tested 55 different cancer
and cancer stem cell lines, and
in almost every case we've seen
this sort of specific labeling
of cancer with minimal labeling
of normal tissue counterparts.
Moving on from cell culture,
they've also shown this across a
broad range of cancers in
animals as well.
So these are examples using that
positron emission or
visualization.
And in these images, the very
bright spots are the drug
attaching to the tumor actually
within an animal, showing us
where the tumor is.
And it's very specific to tumor
and doesn't really show up in
the normal tissue of the animal.
As I mentioned, it was
impressive that it works across
a broad range of cancer types.
So brain tumors, this is a rat
brain here, and then the glowing
is where the drug localized to
within the tumor.
That sits right over the tumor,
where it is in the animal as
well.
And then colon cancer, sort of
injected under the skin of these
animals in many different forms.
And then even not just the
primary tumor but this can
identify metastatic lesions that
are sort of secondary cancer
from the primary tumor as well.
So in this example right here,
the initial tumor was set up
here, it metastasized in the
lungs, and this drug picked out
both of these sites and showed
us both of these tumor sites
while being gotten rid of or
removed from all the normal
tissue of the body.
Specific to our lab, we wanted
to look at this within brain
tumors, of course.
So we used our cancer stem cell
derived models to form GBNs in
these mice again, and sure
enough, this sort of green
fluorescent version also was
able to label these brain tumors
as compared to the normal brain
tissue as well.
So this, again, is an entire
cross-section of a mouse brain
with the brain tumor over here,
and the drug just shows up
incredibly bright green and
actually really well kind of
shows where the tumor is focally
in this brain with very minimal
labeling of the sort of normal
brain tissue or contralateral
side of this brain.
And then kind of, of course we
wanted to make sure, as I
mentioned, that this drug
targets the cancer stem cells as
well as the cancer as a whole.
So for that, we started looking
into this tumor sort of at a
higher magnification or digging
a little bit deeper into the
tumor.
So looking at just a small piece
of the tumor, we could actually
look at this tumor on a cellular
level, and using specific
staining again for this stem
cell or cancer stem cell marker
nestin, shown in purple here as
positive staining.
So all the purple cells
correlate with the green cells
and they overlay quite nice.
So this, along with some other
experiments that we performed,
showed us and convinced us that,
yes, this drug does target the
cancer stem cells as well as the
cancer as a whole.
So it was very exciting results
for us.
And then working with these
collaborators as well as the
company that's sort of begun
moving this drug into clinical
trials, it's really exciting
that they can begin to show this
labeling of tumors in humans as
well.
So in this case, this was a lung
cancer patient that received
this APC analog, and so why this
one is impressive is that when
this patient came in, they
didn't even know that she had
metastatic disease to the brain.
So this is one of these PET scan
images of the entire head
showing these three lesions
here.
And so they could see the lung
tumor but they also saw these
spots in the brain as well that
was unbeknownst to the
clinicians.
So kind of on this plain right
here, looking down, again with
this --, so PET visualization
form of this APC analog, very
little uptake in normal brain,
but they did see this dark spot.
And in this case, the dark spot
is positive signal from this
drug that they injected.
And so from this sort of
clinical trial result,
unbeknownst to them, they sent
this patient back to the
doctors, they did sort of the
classical imaging, this MRI, and
indeed did show enhancement
within this metastatic disease
from this tumor.
And in this, as well as many
other cases that the company and
our collaborators have now
performed, it does seem pretty
impressively selective for human
cancer.
Question?
>> Yeah, question.
>> Mm-hmm.
>> You said this woman had lung
cancer.
>> Yep.
>> How could they tell that the
cancer on the brain had
metastasized from the lung
rather than been grown in the
brain?
>> Yeah, this is just sort of
the initial thing of it.
The surgical way to approach
this is to actually take these
out and then the doctors,
pathologist, actually confirms
that, yes, these are lung cancer
cells and not brain cells.
So yeah, that was performed
after but definitely verified
that, yes, this came from the
lung cancer and was not tumors
growing primary within the
brain.
>> It was a biopsy not an
autopsy?
>> I don't know how it ended up,
but I sure hope so too.
So, moving on from just general
cancer then.
Of course, our lab is interested
in glioblastoma and brain
tumors.
And similarly, when these APC
analogs are injected, they also
identify and target these brain
tumors as well.
So sort of again, the
traditional MRI detection for
these brain tumors shows some
enhancement around this area
right here that identifies the
glioblastoma.
Secondarily, with this other
sort of parallel MRI imaging
shows a similar pattern.
And with this APC analog shows
tumor location and
localization of this APC analog
into the exact same tumor.
And so they're now kind of doing
the same verification that
everything that this drug
targets is definitely tumor.
So one of the things that I did
find showing that this isn't
going to replace anything
currently used, it can sort of
get stuck in the blood pool and
show these positive signals here
are actually veins within the
body in which this drug can get
stuck before localizing to the
tumor.
But overall, being able to use
this visualization technique
along with traditional MRI could
be very powerful in helping
surgeons plan and pretty much
see the entirety of the tumor
and not just kind of what shows
up on one imaging modality
versus another.
Sort of further on from that, as
I mentioned, they could also put
a different isotope,
radioisotope onto this drug as
well that is radiotherapeutic
and can actually kill cancer
cells.
So in this case now, our
collaborators have tested this
in eight different cancer forms
where they can inject the cancer
in mice, let the tumor grow, and
then inject this APC analog with
this radiotherapeutic, this very
powerful radiation that targets
the tumor.
So in these cases, whether it be
as a tumor grows, so tumor
volume, so if untreated, of
course the cancer just keeps
growing and eventually kills the
animal.
When they inject this
radiotherapeutic version of this
APC analog, it targets the
cancer and suppresses growth,
potentially even gets rid of it,
and then the animal continues to
survive.
Seen on this survival curve as
well that 100% of the animals
survived with this
radiotherapeutic version of this
drug compared to this control
version in which every animal
succumbed to the disease.
And sort of one last thing now,
one last analog of this
alkylphosphocholines that I want
to talk about is used
fluorescent analog that you can
actually see in real-time.
So I've been showing a lot of
these MRI pictures and PET, but,
for one, these take a pretty
fair amount of time for a
clinician to get, so somewhere
between 30 minutes to an hour to
actually get these images back,
and then, for two, these are
just sort of overall looks of
within the brain.
So the whole human head, but
when a surgeon actually goes in
to take these tumors out, it's a
very different view that they
get.
They can definitely not see what
the MRI or PET sees.
So they can use these to plan,
but once they get in there, it's
a whole different world kind of
exemplified by, this is one of
our tumors that grew in mice.
So, again, when a surgeon gets
in there, it's not incredibly
clear exactly where the tumor
is.
So because I know where I
injected this into the mouse and
such, I know the tumor is
growing right here, and I could
kind of wave my hands and say
it's a little bit more of a
reddish tissue and things like
that, but on top of even just
where the tumor is in general,
where does it end, and where
does normal tissue begin.
So, of course, surgeon wants to
take out all the tumor possible
that is safe for the patient and
wants to take out, of course,
minimally all the normal tissue
that they can.
But this is very difficult, as
sort of seen here.
It's not incredibly easy to tell
what's tumor and what's not.
And so, with this, sort of one
of these final APC analogs is a
fluorescent analog.
So a drug that we can shine a
specific light on and that it
actually glows that we can see
coming out as a different color
of light.
And so this was work done by the
neural surgical resident in our
lab, Kyle Swanson, who looked at
this as a potential way in
real-time to assist the surgeon
to decipher and determine what
is tumor and what is not.
So kind of with that same
picture, we really don't know
where the tumor is within the
brain tissue here, but when we
inject this APC analog with the
fluorescent output, the tumor is
very evidently glowing right
here.
And there is some sort of
background in the skin and such,
but I'll kind of show some
better pictures later.
And then even sort of showing
where the tumor ends.
So the border or margin with
normal brain that could assist
these surgeons in better
removing and better safely
removing more of this tissue
while sparing normal tissue.
And sort of moving on by this,
the neural surgical resident
Kyle actually sort of did some
mock surgeries of these tumors.
So using fluorescence as a
guide, he could actually take
the tumor out of this mouse
brain.
So, again, this tissue looks
very similar to this normal
brain, but once you turn on the
correct light, shown by these
pictures, the tumor glows white,
and the normal brain has very
little of this tumor selective
APC analog uptake.
And then kind of the final
verification is that, is this
actually tumor?
So if we stain this with this
general histology stain again
and look at it in a magnified
view, we can see that the tumor
cells, this is what the tumor
looks like traditionally when we
inject this specific cell line.
Whereas, in this adjacent that
we're calling not tumor, looks
like normal tissue as well.
So with very minimal cancer
cells in the normal tissue.
So successfully kind of using
this fluorescence as a guide to
removing these tumors and to the
surgical approach.
And then just one last thing I
wanted to show you talking about
the real-time.
So Kyle actually took a video of
how quickly and how nicely he
could see this within the
animal.
So this is a mouse harboring a
brain tumor...
Ah, man.
[LAUGHTER]
Is this going to work this time?
Okay, good.
Again, in real-time the mouse is
moving around, but you can
already see through the brain,
through the skull, through the
skin a spot in here where this
APC analog is localizing and
kind of defining where the tumor
is located.
And so apart from this
real-time, when this animal sort
of again this mock surgery that
this animal is going to undergo,
as Kyle gets in there and
actually starts the surgery, he
can peel away the skin.
And as he takes away skin which
does cause a little bit of
background, as he gets deeper
and deeper, you can detect a
very definite sort of tumor
location for this APC analog,
this fluorescent version.
And then finally ending up, once
he actually gets within the
brain, again the brain has
incredibly low uptake of this
drug and very low signal
compared to the tumor in here.
So we're hoping to sort of, as a
proof of principle here, use
this as, push this into the
clinic to help assist the
neurosurgeons actually within
humans to better resect and get
more tumor and take less normal
brain.
And so, in general now, these
APC analogs are very exciting in
that they are incredibly
versatile in these different
sort of ways they can help these
brain tumor treatments.
So kind of starting again, one,
to help in the planning stage.
This radioactive version that
can be seen by this PET scanning
can be used alongside MRI to
better plan, better visualize
all the tumor within so that a
surgeon and his team can better
plan what to take out.
During the actual surgery, they
can inject this fluorescent
analog so that the surgeon can
actually see the tumor that he's
taking out and spare normal
brain.
And then when that is all done,
this therapeutic version can be
injected.
And since we've shown that this
drug gets at cancer stem cells
as well as the cancer as a
whole, it will hopefully kill
all the cells within this tumor
and then leading to hopefully,
probably overoptimistic, but
hopefully total tumor
eradication for these brain
tumors and glioblastomas in
people.
So just as a very, then, end
summary, I hope I've sort of
persuaded you that going to be a
key element in future cancer
treatments to eliminate these
cancer stem cells if we hope to
have kind of any long-term
success.
Particularly against this
glioblastoma multiforme, this
highly aggressive form of brain
tumor.
And what I like is this cancer
stem cell hypothesis just
doesn't tell us what we can't
do, but it actually offers new
avenues to drug development and
to technique and treatment
development for these tumors.
And that sort of shows us that
we can define, since we know the
stem cells for the most part, we
can define that population, we
can find ways to specifically
target and kill them.
We can use what we know of
normal development in normal
stem cells against these cancer
stem cells to sort of push them
out of the stem cell state and
become no longer tumorigenic.
Or we can develop new drugs and
novel new drugs that attack both
the cancer stem cells as well as
the cancer as a whole.
So some acknowledgments here, of
course.
As I mentioned, this work was
done by me as well as many other
people within lab and with help
from many, many different
collaborators.
So kind of specifically wanted
to point out Michael Zorniak
here performed that scFv
antibody fragment development
against our cancer stem cells.
And that was in collaboration
with Dr. Eric Shusta of Chemical
and Biological Engineering.
Kyle Swanson was the neural
surgical resident, unfortunately
not in this picture, but who
performed the APC analog
fluorescent project.
And then all that APC analog
work was in collaboration with
Dr. Jamey Weichert of radiology.
And then, of course,
Dr. John Kuo, right here, the
neurosurgeon scientist head of
the lab that kind of always
keeps us inspired, keeps showing
us that this is what we're
working for.
We're not just playing with
cells in a dish.
We're sort of hoping to move
this and help people in the
future against these horrible
cancers.
And then a list here of all the
different people that have come
and gone from lab that have all
been part of these projects and
really, really helped out in
keeping them moving and keeping
them alive.
And then a thanks to many other
people we've worked with as
well, particularly the Selecta
Biosciences, like I mentioned,
for these APC analogs actually
starting to develop these and
trying to start clinical trials
or have gotten clinical trials
started with these analogs and
were very good at supplying us
with the drug as well as kind of
teaching us how to correctly
administer them, etc.
And then just finally,
of course, nothing can get done
without cash.
So thank you to the federal
government, National Institutes
of Health for the many grants
we've held, and then a special
thanks to our private funders as
well, this HEADRUSH and
Roger Loff, the things that
they've funded to our lab have
been critical for keeping us
going through many years.
And then as well as the
UW Madison as a whole who's
supported our lab throughout the
whole time we've been here and
given us money to perform these
experiments and pushed these
treatments along as well.
So thank you, and with that, are
there any questions?
[APPLAUSE]