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While she's writing that up,
I also wanted to clarify a point

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that was raised by a TA last time at
the end of last lecture.

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Some of you might have thought
about this fact,

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00:00:27,000 --> 00:00:32,000
and it's important to clarify at
least as best we can.

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00:00:32,000 --> 00:00:36,000
I told you last time that people who
inherit a defective copy of the RB,

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00:00:36,000 --> 00:00:41,000
retinoblastoma tumor susceptibility
gene are highly predisposed to the

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development of retinoblastoma,
a tumor of the eye.  Actually, these

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00:00:46,000 --> 00:00:50,000
patients end up getting bilateral
retinoblastoma,

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00:00:50,000 --> 00:00:55,000
affecting both eyes,
and typically have about a dozen

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00:00:55,000 --> 00:00:59,000
tumors, independent tumors.
And, if you recall,

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00:00:59,000 --> 00:01:03,000
those tumors arise through the loss
of the normal copy of the RB gene in

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the cells that give rise to these
tumors.  And I also told you that

13
00:01:07,000 --> 00:01:11,000
the RB gene is a critical regulator
of cell cycle progression.

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00:01:11,000 --> 00:01:15,000
And so you might have wondered why
don't these people get all sorts of

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tumors?  Why are they predisposed
only to retinoblastomas?

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Why not breast cancer,
lung cancer, pancreatic cancer and

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00:01:23,000 --> 00:01:28,000
so on?  We don't actually know in
complete detail why that is,

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but we suspect that there's a
fundamental difference between

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00:01:33,000 --> 00:01:38,000
retinal cells and other cells with
respect to their requirement for RB

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00:01:38,000 --> 00:01:43,000
gene function.
So I told you previously that RB is

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a regulator of the cell cycle.
Specifically it regulates the entry

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00:01:47,000 --> 00:01:52,000
of cells from the G1 phase of the
cell cycle into S phase.

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It blocks.  And it has to,
itself, be inactivated for tumor

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development.
Or rather for normal cell cycle

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00:02:02,000 --> 00:02:06,000
progression.  An we think that in
retinal cells this is the key

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00:02:06,000 --> 00:02:10,000
regulator of S phase progression,
of S cell cycle entry, so that if

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00:02:10,000 --> 00:02:14,000
you get rid of it you now have
deregulated cell cycle control and

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00:02:14,000 --> 00:02:18,000
tumor development.
And we suspect that in other cells

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00:02:18,000 --> 00:02:23,000
where RB is almost certainly
important --

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00:02:23,000 --> 00:02:30,000
-- there are probably other factors,

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00:02:30,000 --> 00:02:34,000
let's call them X, which can also
regulate cell cycle progression.

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00:02:34,000 --> 00:02:38,000
So that even if the cell were to
lose RB, there are other factors

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00:02:38,000 --> 00:02:42,000
that can, in a sense,
back it up.  And in these cells,

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00:02:42,000 --> 00:02:46,000
in most of your cells, although RB
loss might contribute to tumor

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00:02:46,000 --> 00:02:50,000
formation, it's not sufficient.
In these cells other events must be

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00:02:50,000 --> 00:02:54,000
necessary to inactivate,
one way or another, these X

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00:02:54,000 --> 00:02:59,000
functions.  OK?  So hopefully
that helps clarify.

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00:02:59,000 --> 00:03:03,000
Now, I told you last time,
the last two times that we now think

39
00:03:03,000 --> 00:03:07,000
of cancer as a clonal progression
from normal cells to tumor cells.

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00:03:07,000 --> 00:03:11,000
The acquisition of mutations in
cellular genes,

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00:03:11,000 --> 00:03:15,000
oncogenes, tumor suppressor genes,
and collectively these give rise to

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00:03:15,000 --> 00:03:19,000
cells that are malignant and
potentially life-threatening.

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00:03:19,000 --> 00:03:23,000
This is interesting information
from a scientific point of view,

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00:03:23,000 --> 00:03:27,000
but is it useful?  Why do we want to
understand these cancer-associated

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00:03:27,000 --> 00:03:32,000
genes?
Why do we want to understand these

46
00:03:32,000 --> 00:03:36,000
mutations?  Well,
there are a variety of reasons why.

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00:03:36,000 --> 00:03:41,000
We're going to focus today on
therapy which is directed against

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00:03:41,000 --> 00:03:45,000
the mutations that arise in cancers.
But there are other purposes that I

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00:03:45,000 --> 00:03:53,000
just want to mention to you.

50
00:03:53,000 --> 00:03:57,000
Early detection.
Cancer is most easily treated when

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00:03:57,000 --> 00:04:01,000
caught early.  If we know somebody
has cancer, before the cancer has

52
00:04:01,000 --> 00:04:05,000
spread, they have a much better
chance of curing that individual.

53
00:04:05,000 --> 00:04:10,000
And so it's desirable to have tests
for early detection.

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00:04:10,000 --> 00:04:16,000
And increasingly there are
PCR-based tests looking for cancer

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00:04:16,000 --> 00:04:21,000
cells in bodily fluids.
Sometimes the blood, urine or other

56
00:04:21,000 --> 00:04:27,000
tissues.  PCR-based tests looking
for mutations in the

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00:04:27,000 --> 00:04:32,000
cancer-associated genes,
looking for cells that have a Ras

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00:04:32,000 --> 00:04:38,000
mutation or have a p53 mutation or
have an RB gene mutation and so on.

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00:04:38,000 --> 00:04:44,000
So this is not commonplace,
but there are now tests,

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00:04:44,000 --> 00:04:50,000
commercially available tests that
are based on PCR looking for such

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00:04:50,000 --> 00:04:56,000
mutations.  There are also blood
tests for what we call

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00:04:56,000 --> 00:05:01,000
cancer markers.
You've probably heard of the PSA

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00:05:01,000 --> 00:05:05,000
test for prostate cancer.
There are certain other tests for

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00:05:05,000 --> 00:05:08,000
other types of cancer.
These are blood tests that detect

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00:05:08,000 --> 00:05:11,000
inappropriate levels of something,
often something produced by the

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00:05:11,000 --> 00:05:15,000
cancer.  And, again,
increasingly, as we understand what

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00:05:15,000 --> 00:05:18,000
happens in cancer cells,
we'll have more and more precise

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00:05:18,000 --> 00:05:21,000
cancer makers that will be
detectable in the blood in a very

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00:05:21,000 --> 00:05:25,000
simple screening test so that you
can go to the doctor every year,

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00:05:25,000 --> 00:05:28,000
go through one of these tests and
know whether or not you have an

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00:05:28,000 --> 00:05:32,000
early form of one or another
type of cancer.

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00:05:32,000 --> 00:05:36,000
That's not, again,
happening today, at least in a

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00:05:36,000 --> 00:05:40,000
widespread way,
but it will happen in the years to

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00:05:40,000 --> 00:05:44,000
come.  And when it does,
we will be in a position to do what

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00:05:44,000 --> 00:05:48,000
we call cancer prevention.
Rather than waiting until somebody

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00:05:48,000 --> 00:05:52,000
has a full-blown tumor and trying to
treat it, which is difficult,

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00:05:52,000 --> 00:05:56,000
we will hopefully detect those
tumors at a very early stage and

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00:05:56,000 --> 00:06:00,000
then prevent their progression.
So this is not treating cancer

79
00:06:00,000 --> 00:06:05,000
really, but treating the
hyperplasias I told you about.

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00:06:05,000 --> 00:06:11,000
Or early lesions,

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00:06:11,000 --> 00:06:15,000
benign lesions before they progress
to true cancer.

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00:06:15,000 --> 00:06:19,000
And we think that this will be
easier to do because those cancer

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00:06:19,000 --> 00:06:23,000
cells will have acquired fewer
mutations.  And,

84
00:06:23,000 --> 00:06:27,000
therefore, it will be easier to
design very specific agents that

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00:06:27,000 --> 00:06:31,000
will effectively limit their
proliferation or possibly

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00:06:31,000 --> 00:06:35,000
even kill them.
OK.  Today we're going to focus on

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00:06:35,000 --> 00:06:41,000
the use of this information for
better therapies,

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00:06:41,000 --> 00:06:47,000
ways to design more effective,
more specific anti-cancer agents.

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00:06:47,000 --> 00:06:52,000
And I'll come towards the end to
using this information and related

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00:06:52,000 --> 00:06:58,000
information to do better diagnosis
to try to distinguish two people who

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00:06:58,000 --> 00:07:03,000
have clinically similar tumors.
But those tumors might actually be

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00:07:03,000 --> 00:07:08,000
quite different at the molecular
level, and we'd like to understand

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00:07:08,000 --> 00:07:13,000
that.  OK.  Before we get into sort
of the New Age cancer treatments,

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00:07:13,000 --> 00:07:18,000
I thought I should at least mention
to you conventional therapies.

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00:07:18,000 --> 00:07:34,000
Right now, if you have to have

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00:07:34,000 --> 00:07:38,000
cancer treatment,
you might get one of the drugs that

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00:07:38,000 --> 00:07:42,000
I'm going to tell you about later in
the lecture, but more likely you're

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00:07:42,000 --> 00:07:46,000
going to get what we call a
conventional anti-cancer treatment.

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00:07:46,000 --> 00:07:50,000
And these anti-cancer treatments
have actually been around for quite

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00:07:50,000 --> 00:07:54,000
some time, and they do work.
They do work, but they don't work

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00:07:54,000 --> 00:07:58,000
as well as we need them to work.
Radiation is a very common

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00:07:58,000 --> 00:08:02,000
anti-cancer agent, as you
probably are aware.

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00:08:02,000 --> 00:08:07,000
And there are a variety of drugs
that we list along with radiation

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00:08:07,000 --> 00:08:13,000
like Adriamycin,
Cisplatin.  And there are a variety

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of other chemical agents,
which together are grouped because

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they cause DNA damage.
These are DNA damaging agents,

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and they're also effective
anti-cancer agents.

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00:08:30,000 --> 00:08:34,000
There's another category of
anti-cancer agents which is

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exemplified by a drug called Taxol,
and there is a series of

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Taxol-related compounds.
And these are microtubule

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00:08:43,000 --> 00:08:48,000
inhibitors.  Microtubule inhibitors.
And these therefore, microtubules

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00:08:48,000 --> 00:08:53,000
are important in mitosis,
if you'll remember the mitotic

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00:08:53,000 --> 00:08:58,000
spindle.  So these are
anti-mitotic drugs.

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And these drugs do work.

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00:09:06,000 --> 00:09:10,000
And we think that they work in part
because cancer cells are rapidly

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00:09:10,000 --> 00:09:14,000
dividing cells compared to most
normal cells in your body.

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00:09:14,000 --> 00:09:18,000
And, therefore, if you damage their
DNA or you block their ability to

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divide you'll more effectively block
cancer growth compared to

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normal cell growth.
Now, overall, in the context of

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00:09:26,000 --> 00:09:31,000
cancer, what we're looking for,
and actually in the context of other

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diseases as well is something called
a therapeutic window.

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A therapeutic window is defined as
a difference in the concentration of

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a drug necessary to kill the cell of
interest versus normal cells in the

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body.  These drugs,
anti-mitotics and DNA damaging

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agents will kill normal cells.
So if you look at a graph of percent

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00:10:00,000 --> 00:10:10,000
killing versus drug concentration,
normal cells will eventually die.

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00:10:10,000 --> 00:10:21,000
The hope is that cancer cells will
die sooner.  And this difference is

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defined as the therapeutic window.

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And that does exist for many of
these drugs for many different types

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of cancer.  And so these agents will,
in fact, give initial responses.

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Unfortunately, they tend not to be,
tend not be durable.  That is

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patients tend to relapse.
Not always but tend to relapse in

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response to these agents.
This slide just makes the same

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point that many of the drugs that we
know about affect the cell cycle

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either in S phase during DNA
synthesis or in M phase

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00:11:03,000 --> 00:11:08,000
during mitosis.
And this also points out that many

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00:11:08,000 --> 00:11:12,000
of these agents cause the death of
cancer cells by inducing apoptosis,

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inducing the death of cells.  In
contrast to most,

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00:11:17,000 --> 00:11:21,000
but not all, most normal cells in
the body, which in response to that

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00:11:21,000 --> 00:11:26,000
same concentration of drug,
will not die.  And instead those

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00:11:26,000 --> 00:11:30,000
cells will arrest at some point in
the cell cycle and repair

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00:11:30,000 --> 00:11:34,000
the damage.
And the difference,

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00:11:34,000 --> 00:11:38,000
what makes up the therapeutic window
in many cases,

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00:11:38,000 --> 00:11:41,000
is that the cancer cells are dying
at a given concentration,

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00:11:41,000 --> 00:11:44,000
the normal cells are staying alive
and simply arresting.

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00:11:44,000 --> 00:11:48,000
However, there are other cells in
the body that in response to the

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same drug at the same concentration
will undergo apoptosis.

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00:11:51,000 --> 00:11:54,000
And you actually know what those
cells are if you've thought about

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00:11:54,000 --> 00:11:58,000
cancer chemotherapy before.
It's the cells that support the

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00:11:58,000 --> 00:12:02,000
hair follicles.
Those cells die in response to these

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00:12:02,000 --> 00:12:06,000
drugs.  And that's why cancer
patients lose their hair.

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00:12:06,000 --> 00:12:10,000
It is cells in the blood,
in the bone marrow which will die in

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00:12:10,000 --> 00:12:14,000
response to these concentrations.
And that's why cancer patients get

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00:12:14,000 --> 00:12:19,000
anemic.  And in cells of the lining
of the stomach and intestine which

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will die in response to these drugs.
And that's why cancer patients feel

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00:12:23,000 --> 00:12:27,000
sick, feel nauseous.
So there are side effects in

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response to these drugs.
And that's because many cells,

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00:12:32,000 --> 00:12:36,000
some cells in your body will also
die by apoptosis.

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00:12:36,000 --> 00:12:40,000
Now, we've learned,
actually my lab has participated in

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00:12:40,000 --> 00:12:44,000
this process, that the p53 tumor
suppressor gene that I've told you

161
00:12:44,000 --> 00:12:49,000
about is actually quite important in
guiding the responsive cells to

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00:12:49,000 --> 00:12:53,000
these drugs.  Many normal cells turn
on p53 in response to this damage

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00:12:53,000 --> 00:12:57,000
and arrest.  Those other cells that
I just told you about will

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00:12:57,000 --> 00:13:01,000
turn on p53 and die.
And cancer cells,

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00:13:01,000 --> 00:13:05,000
likewise, if they have a functional
p53 gene will turn it on.

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00:13:05,000 --> 00:13:09,000
And this will induce apoptosis.
And it's the difference between

167
00:13:09,000 --> 00:13:13,000
cancer cells turning on p53 and
dying compared to normal cells

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00:13:13,000 --> 00:13:16,000
turning on p53 and resting,
it gives the therapeutic window.

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00:13:16,000 --> 00:13:20,000
Unfortunately, as I've mentioned to
you, about 50% of human cancers

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00:13:20,000 --> 00:13:24,000
carry p53 mutations.
And given that p53 is important in

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00:13:24,000 --> 00:13:28,000
this response,
if you don't have p53 then you won't

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00:13:28,000 --> 00:13:32,000
die, or won't die as effectively,
and that limits the therapeutic

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00:13:32,000 --> 00:13:35,000
window.
And this is one of the reasons why

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00:13:35,000 --> 00:13:39,000
cancer therapy is not as good as it
should be and why cancer cells will

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00:13:39,000 --> 00:13:43,000
sometimes come back,
because they're now no longer

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00:13:43,000 --> 00:13:47,000
responsive to the drug,
at least especially responsive to

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00:13:47,000 --> 00:13:51,000
the drug.  So we'd like to do better,
and we think we can do better by

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taking advantage of the information
that we've gained over the last 30

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00:13:55,000 --> 00:13:59,000
years about cancer-associated
mutations.

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00:13:59,000 --> 00:14:02,000
And I'm going to review for you in
detail the first three of these new

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00:14:02,000 --> 00:14:05,000
agents, all three FDA approved in
the last five years or so for the

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00:14:05,000 --> 00:14:09,000
treatment of one or another type of
cancer.  And I'll also mention

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00:14:09,000 --> 00:14:12,000
anti-Ras therapies,
although we don't have an FDA

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00:14:12,000 --> 00:14:16,000
approved drug for those.
If there's time I'll mention

185
00:14:16,000 --> 00:14:19,000
inhibitors of an enzyme called
telomerase, as well as

186
00:14:19,000 --> 00:14:23,000
anti-angiogenesis.
There are other therapies,

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00:14:23,000 --> 00:14:26,000
not drug-based therapies but other
therapies that are under

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00:14:26,000 --> 00:14:30,000
consideration, and in
some places in use.

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00:14:30,000 --> 00:14:34,000
Gene therapy, replacing cancer
mutation genes.

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00:14:34,000 --> 00:14:39,000
Immunotherapy, trying to convince
your immune system to attack your

191
00:14:39,000 --> 00:14:43,000
cancer.  And also cancer prevention
strategies, which I mentioned

192
00:14:43,000 --> 00:14:48,000
actually last time,
trying to make vaccines against

193
00:14:48,000 --> 00:14:53,000
viruses that are associated with
certain types of cancer including

194
00:14:53,000 --> 00:14:57,000
human papillomavirus and cervical
cancer.  So Ras is the first one

195
00:14:57,000 --> 00:15:02,000
that I'd like to mention to you.
And it's an example of where we

196
00:15:02,000 --> 00:15:06,000
haven't done enough.
We don't know enough.

197
00:15:06,000 --> 00:15:10,000
Even though we know that Ras is
mutated in 30% of human tumors,

198
00:15:10,000 --> 00:15:14,000
30%, 90% of pancreatic cancers carry
Ras mutations.

199
00:15:14,000 --> 00:15:18,000
Pancreatic cancer is one of the
worst killers in the cancer category.

200
00:15:18,000 --> 00:15:22,000
If you get pancreatic cancer,
of a particular type at least, it's

201
00:15:22,000 --> 00:15:26,000
a very, very, very serious disease.
We know that these tumors carry

202
00:15:26,000 --> 00:15:30,000
mutations in the Ras gene but we
cannot do anything about

203
00:15:30,000 --> 00:15:36,000
it at the moment.
So, as I've told you,

204
00:15:36,000 --> 00:15:43,000
Ras proteins are involved in
signaling proliferation.

205
00:15:43,000 --> 00:15:50,000
And this takes place through kinase
cascades, phosphorylating enzymes

206
00:15:50,000 --> 00:15:56,000
that phosphorylate other enzymes in
a cascade.  When you have a mutation

207
00:15:56,000 --> 00:16:03,000
in Ras, it turns the protein on in a
constitutive fashion leading to

208
00:16:03,000 --> 00:16:10,000
increased signaling down these
pathways and increased

209
00:16:10,000 --> 00:16:16,000
proliferation.
We know some of these enzymes.

210
00:16:16,000 --> 00:16:21,000
I've told you about Raf and MEK and
MAP kinase.  And so many drug

211
00:16:21,000 --> 00:16:26,000
companies are now trying to find
inhibitors that might block those

212
00:16:26,000 --> 00:16:31,000
enzymes, small molecule
inhibitors, drugs.

213
00:16:31,000 --> 00:16:42,000
And because these are kinases,

214
00:16:42,000 --> 00:16:47,000
the approach is to try to find ATP
analogs.  Drugs that look like ATP,

215
00:16:47,000 --> 00:16:53,000
can get into the active site of the
enzyme and compete for ATP,

216
00:16:53,000 --> 00:16:58,000
and thereby block enzyme function.
Some of these drugs work, at least

217
00:16:58,000 --> 00:17:02,000
in cells in culture.
There's a bit of a fear that these

218
00:17:02,000 --> 00:17:06,000
pathways are so commonly used in
normal cells that the drugs might be

219
00:17:06,000 --> 00:17:10,000
highly toxic and therefore not
tolerated.  And,

220
00:17:10,000 --> 00:17:14,000
importantly, we don't understand
what these arrows mean well enough.

221
00:17:14,000 --> 00:17:18,000
We have some basic ideas, but we
don't have enough detail to know

222
00:17:18,000 --> 00:17:22,000
exactly which kinase to inhibit in
exactly which type of tumor.

223
00:17:22,000 --> 00:17:26,000
So this is in progress but it's not
quite there yet.

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I'll come back to another couple of
stories related to ATP analogs that

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do work and are now in use
in cancer treatment.

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Before I do, I want to mention
another class of inhibitors,

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00:17:38,000 --> 00:17:50,000
and these are antibodies.

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00:17:50,000 --> 00:17:54,000
Antibody-directed therapy.
Cancer cells often up-regulate

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proteins on their surface.
I mentioned one last time in the

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context of breast cancer.
It's a protein called HER2.

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00:18:02,000 --> 00:18:07,000
I mentioned the fact that 30% of
breast cancers have an amplification

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of the HER2 gene and,
therefore, make more of this HER2

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00:18:12,000 --> 00:18:17,000
receptor on their cell surface.
So, in contrast to normal cells

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00:18:17,000 --> 00:18:22,000
which will have a certain
concentration of this receptor on

235
00:18:22,000 --> 00:18:27,000
their surface,
cancer cells, breast cancer cells

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00:18:27,000 --> 00:18:32,000
that carry this amplification will
have a much higher density.

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00:18:32,000 --> 00:18:37,000
Maybe ten times or a hundred times
the level of this receptor on their

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00:18:37,000 --> 00:18:42,000
surface.  And they are using that
increased level of receptor to

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00:18:42,000 --> 00:18:47,000
increase the signal downstream of
that receptor to promote

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00:18:47,000 --> 00:18:52,000
proliferation.
Now, the receptor is responding to

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00:18:52,000 --> 00:18:57,000
ligands as it would normally do.
And therapy is based on the fact

242
00:18:57,000 --> 00:19:02,000
that the ligand has to bind to the
receptor in order to activate it.

243
00:19:02,000 --> 00:19:07,000
And so what was done by a company
called Genentech out in California

244
00:19:07,000 --> 00:19:12,000
was to make antibodies that block to
the receptor, that bind to the

245
00:19:12,000 --> 00:19:17,000
receptor and block the binding of
the ligand to the receptor.

246
00:19:17,000 --> 00:19:22,000
So these are anti-HER2 antibodies.
And this drug, which is now

247
00:19:22,000 --> 00:19:28,000
approved by the FDA, is
called Herceptin.

248
00:19:28,000 --> 00:19:34,000
And it works.  For those breast

249
00:19:34,000 --> 00:19:38,000
cancer patients who have
amplification,

250
00:19:38,000 --> 00:19:41,000
too much of this receptor on their
surface, Herceptin works and can

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00:19:41,000 --> 00:19:45,000
give them months,
sometimes years of symptom-free

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00:19:45,000 --> 00:19:48,000
survival.  It's not curative,
unfortunately, but it does extend

253
00:19:48,000 --> 00:19:52,000
life.  And it's therefore an
extremely important drug.

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00:19:52,000 --> 00:19:55,000
This is just a blocking antibody.
There's nothing attached to the

255
00:19:55,000 --> 00:19:59,000
antibody.  It's just blocking the
binding of the receptor to its

256
00:19:59,000 --> 00:20:03,000
ligand and thereby blocking the
function of the receptor.

257
00:20:03,000 --> 00:20:09,000
But antibodies can also be linked to
toxins or radionuclides,

258
00:20:09,000 --> 00:20:15,000
and thereby deliver bad stuff to the
tumor cell, either a toxin or

259
00:20:15,000 --> 00:20:21,000
something that will irradiate this
cell.  And these are being tested

260
00:20:21,000 --> 00:20:27,000
currently.  There are no FDA
approved versions of this,

261
00:20:27,000 --> 00:20:34,000
but I suspect that will change in
the years to come.

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00:20:34,000 --> 00:20:37,000
So Herceptin is an effective
antibody-based therapy.

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00:20:37,000 --> 00:20:40,000
There are a couple more now,
but it was the first.  And this is

264
00:20:40,000 --> 00:20:43,000
actually from the Genentech website
which gives you a little bit of

265
00:20:43,000 --> 00:20:46,000
information about Herceptin and
shows you a bottle of Herceptin as

266
00:20:46,000 --> 00:20:49,000
you would see in the pharmacy.
And this diagram is just a

267
00:20:49,000 --> 00:20:52,000
reiteration of what I've told you
already.  Normal cells have low

268
00:20:52,000 --> 00:20:56,000
levels of the receptor on their
surface, cancer cells have higher

269
00:20:56,000 --> 00:20:59,000
concentrations of the receptor on
their surface,

270
00:20:59,000 --> 00:21:02,000
and the antibody binds to the
receptor thereby blocking

271
00:21:02,000 --> 00:21:06,000
its function.
OK?  So this is a clear example.

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00:21:06,000 --> 00:21:10,000
We learned that Herceptin was
over-expressed in cancer,

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00:21:10,000 --> 00:21:14,000
breast cancer and ovarian cancer.
The company made an antibody and it

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00:21:14,000 --> 00:21:24,000
works.

275
00:21:24,000 --> 00:21:29,000
Another story,
my favorite story relates to a

276
00:21:29,000 --> 00:21:34,000
disease called chronic myelogenous
leukemia --

277
00:21:34,000 --> 00:21:51,000
-- or CML.  CML is a disease that

278
00:21:51,000 --> 00:21:57,000
affects young adults,
adults and children.  Child patient

279
00:21:57,000 --> 00:22:02,000
shown here.
It is leukemia so it's a disease of

280
00:22:02,000 --> 00:22:06,000
the blood.  It affects both the
blood, as well as the bone marrow.

281
00:22:06,000 --> 00:22:10,000
And we've learned a lot about this
disease over the years.

282
00:22:10,000 --> 00:22:14,000
It's not a very common disease.
It only affects about 4,000 or 5,

283
00:22:14,000 --> 00:22:18,000
00 people in this country per year.
And it falls in stages.  Initially

284
00:22:18,000 --> 00:22:22,000
the person is diagnosed with CML
based on relatively low

285
00:22:22,000 --> 00:22:26,000
concentrations of,
low levels of white blood cells in

286
00:22:26,000 --> 00:22:31,000
their circulation.
And then they progress with that

287
00:22:31,000 --> 00:22:36,000
phase in what's called the chronic
phase where there are still

288
00:22:36,000 --> 00:22:40,000
relatively low levels of white blood
cells, higher than normal but lower

289
00:22:40,000 --> 00:22:45,000
than are dangerous.
However, this can progress over

290
00:22:45,000 --> 00:22:50,000
time through an accelerated phase
where there's even higher levels of

291
00:22:50,000 --> 00:22:54,000
white blood cells in the blood to
the final phase which is called

292
00:22:54,000 --> 00:22:59,000
blast crisis where the levels of
white blood cells really shoot up.

293
00:22:59,000 --> 00:23:04,000
And this is lethal.
And these patients invariably

294
00:23:04,000 --> 00:23:08,000
progress through these stages and
eventually died.

295
00:23:08,000 --> 00:23:12,000
So what have we done?
This is a picture of what the blood

296
00:23:12,000 --> 00:23:17,000
cells look like in a normal
individual.  This is a white blood

297
00:23:17,000 --> 00:23:21,000
cell you could see in a CML patient.
There are higher levels, and they

298
00:23:21,000 --> 00:23:25,000
can be even higher than this.
This disease has been studied for a

299
00:23:25,000 --> 00:23:30,000
very long time.
And we now know that there's a

300
00:23:30,000 --> 00:23:34,000
signature mutation,
a mutation that takes place in

301
00:23:34,000 --> 00:23:38,000
almost all CML cases.
It's a translocation that

302
00:23:38,000 --> 00:23:43,000
rearranges two genes called BCR and
ABL and places them together on a

303
00:23:43,000 --> 00:23:47,000
translocated chromosome.
There's a swapping of genetic

304
00:23:47,000 --> 00:23:52,000
information from chromosomes 9 and
22 such that there's production of a

305
00:23:52,000 --> 00:23:56,000
new gene called BCR-ABL that results
in a new protein,

306
00:23:56,000 --> 00:24:00,000
a fusion protein that has a little
bit of this BCR protein and a little

307
00:24:00,000 --> 00:24:04,000
bit of this ABL protein.
And you can see in the karyotypes of

308
00:24:04,000 --> 00:24:07,000
these individuals that they have an
abnormal chromosome 9 which is a

309
00:24:07,000 --> 00:24:11,000
little shorter,
sorry, a little longer than it

310
00:24:11,000 --> 00:24:14,000
should be, and an abnormal
chromosome 22 which is a little

311
00:24:14,000 --> 00:24:17,000
shorter than it should be.
And when you look at cancer cells of

312
00:24:17,000 --> 00:24:21,000
CML patients you always find that
translocation.

313
00:24:21,000 --> 00:24:24,000
It's called the Philadelphia
translocation because it was

314
00:24:24,000 --> 00:24:28,000
discovered by researchers
in Philadelphia.

315
00:24:28,000 --> 00:24:39,000
And it's sometimes referred to as

316
00:24:39,000 --> 00:24:43,000
the Philadelphia chromosome.
And, again, it's a translocation

317
00:24:43,000 --> 00:24:48,000
involving chromosome 9 which has a
gene called ABL which is

318
00:24:48,000 --> 00:24:56,000
a tyrosine kinase.

319
00:24:56,000 --> 00:25:03,000
And so it's a signaling protein.
And chromosome 22 which has a

320
00:25:03,000 --> 00:25:11,000
separate gene called BCR.
And, in the development of CML,

321
00:25:11,000 --> 00:25:19,000
breaks take place on these two
chromosomes leading to a

322
00:25:19,000 --> 00:25:27,000
translocation and the formation of a
new chromosome that has a fusion

323
00:25:27,000 --> 00:25:33,000
gene composed of both BCR and ABL.
And this gives rise to a fusion

324
00:25:33,000 --> 00:25:38,000
protein with a piece of BCR and the
kinase domain of ABL.

325
00:25:38,000 --> 00:25:43,000
And this leads to increased
proliferation,

326
00:25:43,000 --> 00:25:48,000
as well as increased survival of the
cells that carry that translocation,

327
00:25:48,000 --> 00:25:53,000
more cells in the blood and
eventually leukemia.

328
00:25:53,000 --> 00:25:58,000
And the hope is, the hope was,
as this was being worked out,

329
00:25:58,000 --> 00:26:03,000
actually important experiments done
at MIT in the early 1980s here.

330
00:26:03,000 --> 00:26:06,000
As this was being worked out that
maybe, because it's such a common

331
00:26:06,000 --> 00:26:10,000
mutation in this disease,
if you could find an inhibitor --

332
00:26:10,000 --> 00:26:18,000
-- maybe you could block the

333
00:26:18,000 --> 00:26:21,000
proliferation of these cells or
perhaps induce their death.

334
00:26:21,000 --> 00:26:25,000
This just gives you a little a bit,
a sort of cartoon version of BCR-ABL

335
00:26:25,000 --> 00:26:28,000
signaling.  I don't want you to
literally pay great attention

336
00:26:28,000 --> 00:26:32,000
to this.
Suffice it to say BCR-ABL as a

337
00:26:32,000 --> 00:26:36,000
signaling protein stimulates many of
the pathways that you've learned

338
00:26:36,000 --> 00:26:40,000
about already in this class and
causes cells to proliferate,

339
00:26:40,000 --> 00:26:44,000
as well as to survive better.
So, again, can you find an

340
00:26:44,000 --> 00:26:49,000
inhibitor that blocks the activity
of this enzyme and thereby blocks

341
00:26:49,000 --> 00:26:53,000
the proliferation of these cancer
cells?  This was undertaken by

342
00:26:53,000 --> 00:26:57,000
probably many drug companies in the
world, but a drug company now called

343
00:26:57,000 --> 00:27:01,000
Novartis, which has its research
headquarters here in Cambridge,

344
00:27:01,000 --> 00:27:06,000
succeeded.
They generated this drug which goes

345
00:27:06,000 --> 00:27:10,000
by the name Gleevec.
It has a trade name,

346
00:27:10,000 --> 00:27:14,000
the name of which I can never
remember, but everybody called it

347
00:27:14,000 --> 00:27:18,000
Gleevec when it was being developed.
It was also called STI571 but

348
00:27:18,000 --> 00:27:23,000
Gleevec is the common name.
They found this drug through a

349
00:27:23,000 --> 00:27:27,000
screen looking for small molecules
that look a little bit like ATP,

350
00:27:27,000 --> 00:27:31,000
although it doesn't look much like
ATP anymore, that can specifically

351
00:27:31,000 --> 00:27:36,000
bind to and block the kinase
activity of this particular kinase.

352
00:27:36,000 --> 00:27:39,000
And this drug is successful.
It does bind to the kinase and

353
00:27:39,000 --> 00:27:43,000
blocks its kinase activity.
And importantly in cell lines,

354
00:27:43,000 --> 00:27:47,000
as well as in mouse models, it was
found to be effective in killing CML

355
00:27:47,000 --> 00:27:51,000
cells.  It was then used in
treatment of CML patients and found

356
00:27:51,000 --> 00:27:55,000
to be effective there,
too.  So the number of white blood

357
00:27:55,000 --> 00:27:59,000
cells in these patients dropped
dramatically and the number of

358
00:27:59,000 --> 00:28:03,000
Philadelphia chromosome positive
cells likewise.

359
00:28:03,000 --> 00:28:18,000
So if you were to plot the number of

360
00:28:18,000 --> 00:28:23,000
white blood cells in a normal
patient it would be low.

361
00:28:23,000 --> 00:28:29,000
In a CML patient, in the early
phase of the disease it would be

362
00:28:29,000 --> 00:28:34,000
down here, and then it would go up
in the accelerated phase and then it

363
00:28:34,000 --> 00:28:40,000
would go up still further
in blast crisis.

364
00:28:40,000 --> 00:28:51,000
And, as I said,

365
00:28:51,000 --> 00:28:55,000
this could take years,
several years to progress.

366
00:28:55,000 --> 00:28:58,000
And at this stage, late-stage
disease, this person might have

367
00:28:58,000 --> 00:29:02,000
hundreds of thousands of white blood
cells per mill.

368
00:29:02,000 --> 00:29:06,000
But when treated with Gleevec the
white blood cell counts dropped to

369
00:29:06,000 --> 00:29:11,000
mere normal.  And amazingly the drug
is extremely well-tolerated.

370
00:29:11,000 --> 00:29:16,000
So even though all of your cells
have this same ABL kinase,

371
00:29:16,000 --> 00:29:20,000
not fused to BCR but the same ABL
kinase unfused,

372
00:29:20,000 --> 00:29:25,000
and it's probably doing stuff in
your cells, those cells

373
00:29:25,000 --> 00:29:30,000
don't need it.
But the cancer cells,

374
00:29:30,000 --> 00:29:34,000
in the context of this BCR-ABL
fusion, are totally dependent on it.

375
00:29:34,000 --> 00:29:38,000
And if you inhibit it now the cells
will not proliferate anymore.

376
00:29:38,000 --> 00:29:42,000
And, indeed, as you can see how
precipitous this fall is,

377
00:29:42,000 --> 00:29:46,000
the cells will actually die,
undergo apoptosis.  So the drug is

378
00:29:46,000 --> 00:29:50,000
extremely effective.
As I said, clinical tests were done.

379
00:29:50,000 --> 00:29:54,000
Sorry.  This just illustrates a
cartoon version of what we've been

380
00:29:54,000 --> 00:29:59,000
talking about.  Here's
the BCR-ABL protein.

381
00:29:59,000 --> 00:30:03,000
Here it's in its normal state
binding to ATP and transferring a

382
00:30:03,000 --> 00:30:07,000
phosphate to some substrate protein
in the context of signaling.

383
00:30:07,000 --> 00:30:11,000
And what Gleevec does is binds to
the ATP pocket and blocks the access

384
00:30:11,000 --> 00:30:16,000
of ATP to the enzyme and,
therefore, blocks the kinase

385
00:30:16,000 --> 00:30:20,000
activity.  And this is actual
clinical data provided by Novartis

386
00:30:20,000 --> 00:30:24,000
in this case.  And what you're
looking at here is the number of

387
00:30:24,000 --> 00:30:29,000
Philadelphia chromosome positive
cells in the blood.

388
00:30:29,000 --> 00:30:33,000
And what percentage reduction you're
seeing, either somewhat or

389
00:30:33,000 --> 00:30:38,000
completely, looking at the accepted
therapy before Gleevec came along,

390
00:30:38,000 --> 00:30:43,000
which was not very effective, only
12% of patients showed any response,

391
00:30:43,000 --> 00:30:48,000
or rather a major response, and only
3% showed a complete response.

392
00:30:48,000 --> 00:30:53,000
That is when you looked in their
blood by PCR you could find no more

393
00:30:53,000 --> 00:30:58,000
Philadelphia chromosome
positive cells.

394
00:30:58,000 --> 00:31:02,000
But now with Gleevec,
75% of patients showed a major

395
00:31:02,000 --> 00:31:06,000
response.  And 54% of patients
showed a complete response,

396
00:31:06,000 --> 00:31:10,000
you could not find Philadelphia
chromosome positive cells by PCR in

397
00:31:10,000 --> 00:31:14,000
the blood of these patients.
So it really worked extremely well.

398
00:31:14,000 --> 00:31:26,000
It gave what we call clinical

399
00:31:26,000 --> 00:31:32,000
remissions.  Clinical remissions.
And these patients survived, had,

400
00:31:32,000 --> 00:31:38,000
you know, dramatically extended
lifetimes.  This would go on for in

401
00:31:38,000 --> 00:31:44,000
some cases as little as a half a
year, in other cases up to ten years

402
00:31:44,000 --> 00:31:50,000
increased survival,
especially if the patients were

403
00:31:50,000 --> 00:31:56,000
treated early in the disease.
But unfortunately for all the

404
00:31:56,000 --> 00:32:08,000
patients the numbers went back up.

405
00:32:08,000 --> 00:32:12,000
Clinical relapse.
An all too familiar problem in

406
00:32:12,000 --> 00:32:16,000
cancer therapy.
You might see initial treatments,

407
00:32:16,000 --> 00:32:20,000
they might even last a while, but
too many patients undergo relapses

408
00:32:20,000 --> 00:32:24,000
where their disease comes back.
So what's going on here?  These

409
00:32:24,000 --> 00:32:28,000
patients are continuing to receive
Gleevec throughout this course,

410
00:32:28,000 --> 00:32:33,000
and yet the tumors are returning.
Why?  What might be going on?

411
00:32:33,000 --> 00:32:39,000
Remember that cancer cells acquire
mutations?  Cancer cells are always

412
00:32:39,000 --> 00:32:45,000
acquiring mutations.
So what kind of mutation might be

413
00:32:45,000 --> 00:32:52,000
taking place in these cells that
would lead them to be Gleevec

414
00:32:52,000 --> 00:32:58,000
resistant?  Well,
maybe they're acquiring mutations

415
00:32:58,000 --> 00:33:04,000
within the BCR-ABL gene,
that fusion gene, which blocks their

416
00:33:04,000 --> 00:33:10,000
ability to bind the drug.
So Charles Sawyers,

417
00:33:10,000 --> 00:33:15,000
investigator at UCLA,
took the cancer cells from these

418
00:33:15,000 --> 00:33:20,000
relapsed patients,
PCR-ed up the BCR-ABL gene,

419
00:33:20,000 --> 00:33:25,000
sequenced it, and lo and behold he
found a bunch of mutations.

420
00:33:25,000 --> 00:33:30,000
Individual tumors had one or
another of these point mutations

421
00:33:30,000 --> 00:33:35,000
within the ABL kinase.
And the consequence of those

422
00:33:35,000 --> 00:33:40,000
mutations was that the drug Gleevec
could no longer bind.

423
00:33:40,000 --> 00:33:45,000
And that's illustrated here.
So this is, again, a cutaway view

424
00:33:45,000 --> 00:33:50,000
of the BCR-ABL kinase.
Here's Gleevec where it normally

425
00:33:50,000 --> 00:33:55,000
sits, but that red dot is a mutation
that sticks an amino acid side chain

426
00:33:55,000 --> 00:34:00,000
right in the way of where
Gleevec binds.

427
00:34:00,000 --> 00:34:05,000
So now it cannot bind anymore.
The drug cannot bind, it cannot be

428
00:34:05,000 --> 00:34:10,000
effective, cancer cells come back.
OK?  So that's a problem.  What are

429
00:34:10,000 --> 00:34:15,000
you going to do about it?
What can be done?  What would you

430
00:34:15,000 --> 00:34:24,000
do?

431
00:34:24,000 --> 00:34:30,000
Maybe we could find a drug that will
bind even if there is a mutation

432
00:34:30,000 --> 00:34:37,000
there.  And that actually works and
that's why this Gleevec fits nicely

433
00:34:37,000 --> 00:34:43,000
into that pocket and blocks the
activity.  So this enzyme is

434
00:34:43,000 --> 00:34:50,000
inhibited.  The problem is that
apparently invariably mutant

435
00:34:50,000 --> 00:34:57,000
BCR-ABLs arise which are
Gleevec resistant.

436
00:34:57,000 --> 00:35:08,000
So you can have Gleevec around,

437
00:35:08,000 --> 00:35:13,000
but it cannot get in there, the
enzyme still functions,

438
00:35:13,000 --> 00:35:19,000
it still causes proliferation.
But working with a different drug

439
00:35:19,000 --> 00:35:24,000
company, Charles Sawyers screened
new drugs.  And he found a drug

440
00:35:24,000 --> 00:35:29,000
which has a similar but slightly
different shape than Gleevec,

441
00:35:29,000 --> 00:35:35,000
and it's able to bind to the mutant
BCR-ABLs.

442
00:35:35,000 --> 00:35:43,000
This drug is called BMS-354825
produced by Bristol-Myers Squibb.

443
00:35:43,000 --> 00:35:51,000
And just in December of this past
year Charles Sawyers reported the

444
00:35:51,000 --> 00:35:59,000
first clinical trial with this drug
in patients who had failed Gleevec

445
00:35:59,000 --> 00:36:07,000
therapy who had relapsed.
And 31 out of 36 responded.

446
00:36:07,000 --> 00:36:11,000
And to my knowledge they are still
in remission.  And the five who

447
00:36:11,000 --> 00:36:15,000
didn't respond had a particular kind
of mutation that actually also

448
00:36:15,000 --> 00:36:19,000
blocked the binding of this drug.
But the majority of mutations, even

449
00:36:19,000 --> 00:36:23,000
though there are several mutations
that will affect Gleevec resistance,

450
00:36:23,000 --> 00:36:27,000
the majority of them are still
sensitive to this new drug.

451
00:36:27,000 --> 00:36:32,000
So this is smart and smart again.
Smart, understanding how cells can

452
00:36:32,000 --> 00:36:36,000
be sensitive.  Then smart again,
finding out how they become

453
00:36:36,000 --> 00:36:40,000
resistance.  And then smart for a
third time, finding new drugs that

454
00:36:40,000 --> 00:36:44,000
will bind even in the presence of
those resistance mutations.

455
00:36:44,000 --> 00:36:48,000
And this, I suspect, is the future
of cancer treatments.

456
00:36:48,000 --> 00:36:52,000
Understanding the molecular
signature mutations,

457
00:36:52,000 --> 00:36:56,000
finding specific drugs,
and then being prepared to find

458
00:36:56,000 --> 00:37:00,000
second-generation drugs that will
still work even if resistance

459
00:37:00,000 --> 00:37:04,000
arises.
A very similar story,

460
00:37:04,000 --> 00:37:09,000
which I'll have to tell you quickly,
comes from the world of lung cancer.

461
00:37:09,000 --> 00:37:14,000
In this case,
several drug companies were trying

462
00:37:14,000 --> 00:37:19,000
to find drugs that would block a
different tyrosine kinase.

463
00:37:19,000 --> 00:37:24,000
This time a receptor tyrosine
kinase by the name of epidermal

464
00:37:24,000 --> 00:37:30,000
growth factor receptor,
EGF receptor.

465
00:37:30,000 --> 00:37:36,000
They were motivated to do so because
this receptor is over-expressed,

466
00:37:36,000 --> 00:37:42,000
there is too much of it in many
types of cancer, including

467
00:37:42,000 --> 00:37:50,000
lung cancer.

468
00:37:50,000 --> 00:37:55,000
And so different companies made
different drugs.

469
00:37:55,000 --> 00:38:00,000
One of them is called Iressa which
goes by the trade name Gefitinib.

470
00:38:00,000 --> 00:38:05,000
Another made by Genentech is called
Tarceva.  And these do function as

471
00:38:05,000 --> 00:38:10,000
EGF inhibitors,
anti-EGF receptor inhibitors.

472
00:38:10,000 --> 00:38:15,000
They work.  They work in the
test-tube.  However,

473
00:38:15,000 --> 00:38:20,000
when tested in clinical trials they
were a spectacular failure.

474
00:38:20,000 --> 00:38:25,000
Even for patients who had high
levels of EGF receptor on the

475
00:38:25,000 --> 00:38:31,000
surface of their cancer cells,
the drug didn't do anything.

476
00:38:31,000 --> 00:38:35,000
And they were almost not going to be
FDA approved for that purpose,

477
00:38:35,000 --> 00:38:40,000
except that a very small number of
lung cancer patients responded

478
00:38:40,000 --> 00:38:45,000
extremely well to the drug.
about 10% of lung cancer patients

479
00:38:45,000 --> 00:38:50,000
showed responses like the one I'm
showing you here,

480
00:38:50,000 --> 00:38:55,000
where this, and outlined in red,
is a lung tumor where the tumor is

481
00:38:55,000 --> 00:39:00,000
basically filling the entire
lobe of the lung.

482
00:39:00,000 --> 00:39:04,000
Six weeks after treatment with this
drug Iressa, you can see massive

483
00:39:04,000 --> 00:39:08,000
resolution of the tumor.
The tumor is almost all gone,

484
00:39:08,000 --> 00:39:12,000
and that white stuff is probably
just fibrotic tissue.

485
00:39:12,000 --> 00:39:17,000
The tumor cells are practically
gone.  A dramatic response.

486
00:39:17,000 --> 00:39:21,000
What's going on?  Why do those 10%
of patients respond so well?

487
00:39:21,000 --> 00:39:25,000
Well, it turns out that those 10%
of patients carry a mutation in the

488
00:39:25,000 --> 00:39:30,000
EGF receptor gene.
In those 10% of patients,

489
00:39:30,000 --> 00:39:35,000
one of the ways the cancer cells are
growing and surviving is that they

490
00:39:35,000 --> 00:39:39,000
have a mutation that activates this
gene making those tumor cells highly

491
00:39:39,000 --> 00:39:44,000
dependent on that particular protein
in the same way that these cancers

492
00:39:44,000 --> 00:39:49,000
are highly dependent on BCR-ABL.
And if you deprive those cancer

493
00:39:49,000 --> 00:39:53,000
cells of that activity by using
these drugs, the cells will die.

494
00:39:53,000 --> 00:39:58,000
So this is a good example of what
will come in the future of

495
00:39:58,000 --> 00:40:03,000
individualized medicine.
If you're a lung cancer patient,

496
00:40:03,000 --> 00:40:07,000
you shouldn't just indiscriminately
take Iressa because 95% of the time

497
00:40:07,000 --> 00:40:11,000
it won't do anything for you.
But if you're one of those 10% who

498
00:40:11,000 --> 00:40:15,000
has a mutation in this gene,
you would benefit dramatically from

499
00:40:15,000 --> 00:40:19,000
having it.  And that will happen
more and more in cancer and other

500
00:40:19,000 --> 00:40:23,000
diseases.  Your tumor will be
molecularly typed to find out

501
00:40:23,000 --> 00:40:27,000
exactly what mutations it has to
find out which of a collection of

502
00:40:27,000 --> 00:40:31,000
targeted therapies you
should be taking.

503
00:40:31,000 --> 00:40:34,000
These patients,
just so you know,

504
00:40:34,000 --> 00:40:38,000
tend to be women, non-smokers,
and tend to be Asians for reasons

505
00:40:38,000 --> 00:40:42,000
that we don't understand.
Any of those three we don't

506
00:40:42,000 --> 00:40:46,000
understand, but the percentage of
EGFR mutant lung cancer patients are

507
00:40:46,000 --> 00:40:50,000
higher in those categories of people.
And so they have a greater

508
00:40:50,000 --> 00:40:54,000
likelihood of being responsive.
But, in fact, nowadays if you have

509
00:40:54,000 --> 00:40:58,000
lung cancer you get your EGFR gene
sequenced.  And if it has a mutation

510
00:40:58,000 --> 00:41:02,000
you take this drug.
And it will work.

511
00:41:02,000 --> 00:41:08,000
It will resolve your tumor.
Unfortunately, your tumor will come

512
00:41:08,000 --> 00:41:13,000
back.  The same story but faster.
These patients tend only to get

513
00:41:13,000 --> 00:41:18,000
three months, six months,
maybe a year, two years, three years

514
00:41:18,000 --> 00:41:24,000
extra survival,
and then their tumors come back.

515
00:41:24,000 --> 00:41:29,000
Same story, the receptors that are
now insensitive to the drug carry a

516
00:41:29,000 --> 00:41:35,000
new mutation that blocks access of
the drug to the receptor.

517
00:41:35,000 --> 00:41:39,000
Fortunately, just last month there
was a paper that described a new

518
00:41:39,000 --> 00:41:44,000
drug that will still work even if
the receptor carries such a

519
00:41:44,000 --> 00:41:48,000
resistance mutation.
So there's hope that we'll see a

520
00:41:48,000 --> 00:41:53,000
story similar to this one emerging
for lung cancer.

521
00:41:53,000 --> 00:41:57,000
Now, I've told you three of,
just a handful of molecularly

522
00:41:57,000 --> 00:42:02,000
targeted agents for
therapy in cancer.

523
00:42:02,000 --> 00:42:06,000
There are more to come.
Telomerase is an enzyme that cancer

524
00:42:06,000 --> 00:42:10,000
cells need, that normal cells or at
least most normal cells don't need.

525
00:42:10,000 --> 00:42:14,000
We won't go into the details of
that, but suffice to say this is a

526
00:42:14,000 --> 00:42:18,000
promising area for therapy as well.
Angiogenesis, I've mentioned to you

527
00:42:18,000 --> 00:42:22,000
before.  Tumors,
solid tumors need a new blood supply.

528
00:42:22,000 --> 00:42:26,000
If you can block the ability of the
tumor to recruit a blood supply,

529
00:42:26,000 --> 00:42:30,000
you might be able to block the
development of the tumor.

530
00:42:30,000 --> 00:42:34,000
And there has recently,
Genentech once again, been an FDA

531
00:42:34,000 --> 00:42:38,000
approved anti-angiogenesis drug that
blocks, that prevents progression of

532
00:42:38,000 --> 00:42:42,000
colon cancer, and also they just
reported breast cancer.

533
00:42:42,000 --> 00:42:47,000
So anti-angiogenesis is a viable
therapy strategy as well.

534
00:42:47,000 --> 00:42:51,000
Gene therapy, putting lost genes
back.  Cancer cells have mutations

535
00:42:51,000 --> 00:42:55,000
in tumor suppressor genes,
p53, RB I've told you about,

536
00:42:55,000 --> 00:42:59,000
and others.
Perhaps you could just put the gene

537
00:42:59,000 --> 00:43:03,000
back in, the gene that got lost.
Make a virus that expresses that

538
00:43:03,000 --> 00:43:07,000
gene and put it back.
This is being tried.  I'm not super

539
00:43:07,000 --> 00:43:11,000
enthusiastic about whether it will
work because I don't know that we

540
00:43:11,000 --> 00:43:14,000
can get the virus carrying the good
gene into all the cancer cells.

541
00:43:14,000 --> 00:43:18,000
But, nevertheless, it's something
to consider.  Immunotherapy is also

542
00:43:18,000 --> 00:43:22,000
a promising area.
It's possible that we can convince

543
00:43:22,000 --> 00:43:26,000
your immune system to detect the
abnormal proteins that cancer cells

544
00:43:26,000 --> 00:43:30,000
make by virtue of the mutations
that they carry.

545
00:43:30,000 --> 00:43:33,000
You can make antibodies or T cells
that eliminate those,

546
00:43:33,000 --> 00:43:37,000
and that's underway.  And I've
mentioned already the cancer

547
00:43:37,000 --> 00:43:41,000
prevention approaches with vaccines.
I want to draw your attention to

548
00:43:41,000 --> 00:43:45,000
the fact that the Cancer Center here
at MIT will have a symposium in June.

549
00:43:45,000 --> 00:43:49,000
Many of you will have gone home for
the summer, but some of you may not

550
00:43:49,000 --> 00:43:53,000
have.  June 24th.
This is free to MIT students,

551
00:43:53,000 --> 00:43:57,000
and actually features many alums of
MIT.  Two of these people were

552
00:43:57,000 --> 00:44:01,000
undergraduates here at MIT,
including Dan Heber, the guy who did

553
00:44:01,000 --> 00:44:05,000
the EGF lung cancer story
that I just showed you.

554
00:44:05,000 --> 00:44:08,000
This is a very great group of people
who will be telling you the latest

555
00:44:08,000 --> 00:44:12,000
and greatest about the new science
of cancer therapy,

556
00:44:12,000 --> 00:44:16,000
an extension of what I've told you
about today.  All right.

557
00:44:16,000 --> 00:44:20,000
Before we finish I want to just
briefly mention that in addition to

558
00:44:20,000 --> 00:44:24,000
tracking mutations in
cancer-associated genes,

559
00:44:24,000 --> 00:44:28,000
we can also track the expression
patterns, the levels of expression

560
00:44:28,000 --> 00:44:32,000
of all the genes in a cancer cell.
And this is done using a technology

561
00:44:32,000 --> 00:44:36,000
called array technology where all of
the genes of a cell,

562
00:44:36,000 --> 00:44:41,000
the 30,000 genes of a cell can be
assessed based on how much RNA is

563
00:44:41,000 --> 00:44:45,000
being produced in those cells at any
given time or at any given sample.

564
00:44:45,000 --> 00:44:50,000
This is called a GeneChip or a gene
expression array.

565
00:44:50,000 --> 00:44:54,000
And increasingly it's being used to
diagnose cancers.

566
00:44:54,000 --> 00:44:59,000
Cancer is typically diagnosed by
histopathology.

567
00:44:59,000 --> 00:45:02,000
You look at the tumor,
or the pathologist looks at the

568
00:45:02,000 --> 00:45:06,000
tumor in a histological section and
says it's a this or it's a that.

569
00:45:06,000 --> 00:45:10,000
The problem is that many cancers
look very similar to the histologist

570
00:45:10,000 --> 00:45:14,000
or the pathologist,
but in the underlying molecular

571
00:45:14,000 --> 00:45:18,000
level they might be quite different.
Some of them might be fairly benign.

572
00:45:18,000 --> 00:45:22,000
Others might be really dangerous.
And maybe you cannot tell that

573
00:45:22,000 --> 00:45:26,000
apart by looking at the cells,
but looking at the activity of the

574
00:45:26,000 --> 00:45:30,000
different genes inside those cells
you may be able to get to that.

575
00:45:30,000 --> 00:45:33,000
So this is done by comparing,
on a glass slide, the levels of

576
00:45:33,000 --> 00:45:37,000
expression of all the genes from the
cancer cell compared to some

577
00:45:37,000 --> 00:45:41,000
reference RNA,
let's say the normal cell of that

578
00:45:41,000 --> 00:45:45,000
tissue.  And then the signal that
you read out by looking at labeled

579
00:45:45,000 --> 00:45:48,000
RNAs, the cancer cell being labeled
red, for example,

580
00:45:48,000 --> 00:45:52,000
the normal RNA being labeled green,
the signal that you read out from

581
00:45:52,000 --> 00:45:56,000
each of those spots using a laser
and a CCD camera to detect the

582
00:45:56,000 --> 00:46:00,000
signal coming off of the chip,
the signal that you see can be

583
00:46:00,000 --> 00:46:03,000
quantified.
And a red signal would mean there's

584
00:46:03,000 --> 00:46:07,000
more RNA in sample one for that
particular gene,

585
00:46:07,000 --> 00:46:11,000
a green signal more RNA for sample
two, and a yellow signal roughly

586
00:46:11,000 --> 00:46:15,000
equal.  And the pattern that you get
from these chips can then give you

587
00:46:15,000 --> 00:46:19,000
information about the state of those
cells, and that information might be

588
00:46:19,000 --> 00:46:23,000
extremely important clinically.
And in the last two minutes I'll

589
00:46:23,000 --> 00:46:27,000
just tell you a brief story about
how it is being used.

590
00:46:27,000 --> 00:46:30,000
This is a collection of 75 breast
cancer specimens,

591
00:46:30,000 --> 00:46:34,000
early stage breast cancers,
node negative, lymph node negative

592
00:46:34,000 --> 00:46:38,000
breast cancers.
These patients,

593
00:46:38,000 --> 00:46:42,000
before this technology,
all would undergo removal of the

594
00:46:42,000 --> 00:46:45,000
tumor and then chemotherapy.
But it turns out that only some of

595
00:46:45,000 --> 00:46:49,000
them will actually go on to progress.
These patients were followed for

596
00:46:49,000 --> 00:46:53,000
ten years after that sample was
taken.  And it was known that some

597
00:46:53,000 --> 00:46:57,000
of them progressed,
and those fall over here,

598
00:46:57,000 --> 00:47:01,000
progressed in the sense that they
developed metastatic tumors.

599
00:47:01,000 --> 00:47:05,000
And others didn't progress.
And so what was done was is to take

600
00:47:05,000 --> 00:47:09,000
RNA from these samples at this early
stage, RNA from these samples and do

601
00:47:09,000 --> 00:47:13,000
one of these GeneChips and ask,
is the pattern of expression of

602
00:47:13,000 --> 00:47:17,000
genes correlative to the outcome,
the eventual outcome?  It might take

603
00:47:17,000 --> 00:47:21,000
some years for it to happen.
And what they found was that indeed

604
00:47:21,000 --> 00:47:25,000
--
And you can probably see it from

605
00:47:25,000 --> 00:47:29,000
where you're sitting,
that this collection of genes in red

606
00:47:29,000 --> 00:47:33,000
over here is highly expressed in the
guys who actually do pretty well and

607
00:47:33,000 --> 00:47:36,000
is relatively lower expressed in the
guys that don't do well.

608
00:47:36,000 --> 00:47:40,000
And this collection of genes is
highly expressed in the ones who

609
00:47:40,000 --> 00:47:43,000
don't do well compared to the ones
who do.  And so now there's a

610
00:47:43,000 --> 00:47:47,000
clinical test.
You can have your early-stage

611
00:47:47,000 --> 00:47:51,000
breast cancer typed by this analysis
and it will tell you with some

612
00:47:51,000 --> 00:47:54,000
degree of certainty,
not complete, whether your tumor

613
00:47:54,000 --> 00:47:58,000
will eventually,
maybe five year down the road

614
00:47:58,000 --> 00:48:02,000
progress into a metastatic tumor.
If you get the signal,

615
00:48:02,000 --> 00:48:06,000
if you get the answer yes,
then you have it removed and you

616
00:48:06,000 --> 00:48:11,000
undergo therapy.
If you get the answer no,

617
00:48:11,000 --> 00:48:15,000
you have a choice.  Perhaps you get
the tumor removed,

618
00:48:15,000 --> 00:48:20,000
but you don't undergo what is in
fact quite difficult and sometimes

619
00:48:20,000 --> 00:48:24,000
damaging therapy.
So this is an example of,

620
00:48:24,000 --> 00:48:29,000
again, stuff to come, molecule
medicine, specific patient-oriented

621
00:48:29,000 --> 00:48:32,000
medicine.