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Exponential proliferation is rare
1 month
2 months
9 months
3 months
20
3A Cancer (continued)
21
Some big scary numbers
Number of cells in your body ≈ 60,000,000,000
Number of cell divisions in a lifetime ≈ 1016
Mutation rate ≈ 10-9/base pair/cell division
Times any mutation occurs = 10-9 x 1016 = 10,000,000
This calculation should bring home how important it is to control where and
when our cells grow and proliferate and how easily cancer cells that have lost
this control can overwhelm us. This thought leads in turn to two others. The
first is that because mutations that allow cells to grow and proliferate at the
wrong time and place can cause cancer, somatic cells, like germ cells, want to
have a very low mutation rate, and measurements suggest that the mutation
rate of somatic cells is similar to that of germ line cells. The second thought is
that since there will be roughly 1016 cell divisions during your lifetime, any
given mutation will have occurred about 1016 x 10-9 = 10 million times in your
life, and the cellular cooperative must have evolved sufficiently strong
defenses against mutant cells that no single mutation can give rise to cancer.
In fact, the defenses are so good that it takes at least 5 mutations to convert a
normal cell into a malignant cancer cell.
22
Problems with cell division: Cancer
At least 5
mutations
Normal Cell
Cancer Cell
Obeys strict rules
Divides only when told to
Dies rather than misbehaving
Stays close to home
Disobeys rules
Divides at will
Bad behavior doesn’t kill
Wanders through body
Careful with chromosomes
Careless with chromosomes
A simple analogy is that our somatic cells resemble prim, Victorian ladies. They obey strict rules,
grow and divide only when told to, live and die close to where they were born, and would rather
die than do something to endanger their community. In contrast, tumor cells are the original
rebels without a cause. They disobey all the rules, grow and divide uncontrollably, migrate
throughout the body, and avoid social sanctions when they misbehave. We can list the specific
defenses that cancer cells have to escape as they accumulate mutations. We list the steps
sequentially, but you should be aware that for most cancers we do not know which order they
occurred in.
1) A cell has to mutate so that it can grow and divide under conditions where its normal
counterparts would not, and this is one of the steps that we will discuss in detail because the target
of Gleevec is an enzyme that regulates cell growth and proliferation.
2) Cancer cells have to ignore signals that tell a cell that is behaving inappropriately to commit
suicide by a process known as apoptosis or programmed cell death.
3) If a tumor is going to grow beyond a diameter of about 1mm, its cells have to be able to
induce new blood vessels to invade the tumor.
4) With the exception of cancers involving blood cells, the cells from the tumor have to acquire
the ability to crawl into blood vessels, be carried by the circulation , crawl out of the vessels
somewhere else, and establish a new, metastatic tumor.
5) The cancer cells have to become genetically unstable, that is they have to increase the rate at
which they accumulate genetic changes relative to normal, somatic cells.
23
Cancer: Required genetic changes
1) Grow and proliferate under conditions were normal cells do neither
2) Ignore signals telling badly behaving cells to kill themselves (apoptosis)
3) Induce the growth of new blood vessels
4) Enter and exit blood vessels and form tumors at new sites (metastasis)
5) Become genetically unstable (increased mutation rate)
This last feature helps to explain two confusing things. The first is how cancer
can be so prevalent when the human mutation rate is so low and so many
different types of mutations must accumulate to produce a malignant tumor.
The second is why so many cancers initially respond to therapy but then later
become resistant to it. Increasing the rate at which cells make mutations,
makes it easier for them to accumulate all the mutations they need to become
fully malignant, and just as it does for HIV, having a high mutation rate allows
the offending objects to escape the slings and arrows of medical intervention.
24
Cancer is an evolutionary disease
Evolution leads to imperfection: selecting for increased growth
and proliferation is eventually suicidal
A few genetic changes can drastically alter cell behavior
Prolonged, strong selection selects for mutators
I conclude this section by reminding you that like AIDS, cancer is an
evolutionary disease. There are three reasons for doing so. The first is to pop
the anthropomorphic bubble that says that evolution is progressive, leading to
things getting bigger and better in every possible way. Cancer cells are
selected because they proliferate and survive better in our bodies than the
normal cells they are derived from, but their success ultimately destroys the
body that houses them, and thus kills them as well. The second is to show that
evolution can lead over a very short time and through a small number of
mutations to the dramatic changes in cellular behavior, composition, and
appearance that distinguish cancer cells from normal cells. The last is to point
out that strong selections, like the ones on cell proliferation, migration, and
survival in cancer, can select for mutations that increase the rate at which cells
and organisms accumulate subsequent mutations. An interesting and important
question in evolution is identifying the circumstances under which such
mutator strains are selected for and determining how important they have been
in organismal evolution.
25
Cancer: Epidemiology
Cancer results from multiple mutations
Environmental contributions to cancer
Genetic contributions to cancer
4 THE EPIDEMIOLOGY OF CANCER
This section deals with three questions about cancer:
1) Since it kills so many people, why hasn’t it been eliminated by natural
selection?
2) How many mutations must we accumulate to get cancer?
3) What causes these mutations?
26
Why natural selection hasn’t eliminated cancer
2500
Incidence, cases per
100,000 US women
2000
1500
UK life expectancy
1750
1000
500
0
0
10
20
30
40
50
60
70
80
90
Age at detection, years
If cancer is so prevalent, why hasn’t natural selection rooted it out. The
answer is that it has for people who were likely to be reproductively active
under the conditions that have existed for the vast majority of Homo sapiens’
existence. From our origin roughly two million years ago, until the invention
of public health in the 19th century, the average human lifespan has been less
than 35 years. As a result, things that happened after the age of 50 affected
only a small fraction of the human population and therefore contributed little to
the selective pressure on the human population, especially when compared to
the need to resist starvation, parasites, and infectious diseases, challenges
whose effects are strongest on infants and children. Just as importantly,
evolution worries not about you but about your progeny and by the age of 50
essentially all women and most men have stopped reproducing, an effect that
was much stronger when a majority of the population died of other causes by
the age of 50 and the age of menopause in women was likely much lower.
Plotting the incidence of cancer against age reveals that cancer is a disease that
almost exclusively affects those over 50. Although the deaths of children and
young adults from cancer are poignant, they are rare. For example, the number
of deaths from colon cancer for patients below 50 is less than 5% of the total
number of colon cancer deaths in the US.
27
Multiple mutations: the dice analogy
Dice have one hundred sides and get thrown once a year
One dice: need to throw a hundred once to win
Two dice: need to throw a hundred on each dice, but not in
the same year
Probability of winning in
1st year
2nd year
3rd year
One dice
1%
2%
3%
Two dice
0.01%
0.04%
0.09%
How many things have to go wrong to cause cancer? As I mentioned earlier,
one answer comes from genetically analyzing cancer cells and tracking down
and counting important mutations that change their properties. Another,
earlier, and complementary approach was to look carefully at the statistics of
cancer, in particular by examining the details of how the incidence of cancer
changes with people’s age. To understand how, we will think about throwing
dice in a game of chance. Imagine a dice that has hundred faces, that you are
allowed to throw the dice once a year, and you need to throw a hundred to win.
Your chance of winning in the first year is 1%, your chance that you won
sometime in the first two years is 2%, your chance that you won sometime in
the first three years is 3%, and so on. Now imagine that you have two dice,
that as soon as you have thrown a hundred with a particular dice you need not
throw it again, and that you have to have thrown a hundred with both dice in
order to win. Now the chance of winning in the first year is 1% of 1%, or
0.01%, of winning during the first two years is 2% of 2% or 0.04%, of winning
during the first three years is 3% of 3% or 0.09%, and so on.
28
Cancer requires multiple mutations: the dice analogy
Log scales
Linear scales
0
0.12
-1
One Dice
Two Dice
Three Dice
Four Dice
0.08
-2
Log(p(Success))
Winning Probability
0.1
0.06
0.04
-3
-4
-5
-6
One Dice
-7
0.02
Two Dice
Three Dice
-8
Four Dice
-9
0
0
2
4
6
Years
8
10
0
0.2
0.4
0.6
0.8
1
Log(Years)
We draw two conclusions from this argument. The first is that if you have to throw a
hundred on two dice, your chances of winning fall dramatically. The second is that as time
goes on, the probability of winning goes up more steeply when you have to throw two dice,
or speaking more mathematically, that with two dice, the chance of winning rises as the
square of the number of years, rather than linearly with the number of years as it did when
we were only throwing one dice. You can extend this argument to higher and higher
numbers of dice, and you can convince yourself that the more dice you need to have turn up
showing a hundred, the less likely you are to win, and the more steeply the chance of
winning goes up with time, so much so that for three and four dice the chance of winning is
so small as to be hard to see on the graph. One way of seeing these points more clearly is
to plot the logarithm of your chance of winning against the logarithm of time, where each
unit on the y axis corresponds to a ten-fold greater chance of winning. Now all the lines are
clearly displayed, each one is straight and the larger the number of dice that need to be
thrown, the steeper the corresponding line is, and if you don’t know the number of dice
beforehand you can deduce it from measuring the slope of the line on this logarithmic
graph.
It is exactly this strategy that epidemiologists used to determine how many mutations are
needed to cause cancer. By plotting cancer incidence, that is the number of new cases that
arise each year in a particular age group, against age they deduced that between five and
six distinct genetic events are needed to produce this cancer, an answer that gibes nicely
with the five different types of mutation we listed above as needing to occur to create a
malignant tumor.
29
Cancer rates vary widely
Cancer
Skin
Stomach
Region with
highest rate (per
1000)
Region with
lowest rate (per
1000)
Queensland,
Australia
Bombay, India
>200
<1
Japan
Uganda
110
5
After Cairns, J., Cancer: Science and Society, W.H. Freeman, 1978
Our third question is what causes the mutations that cause cancer? The
answer, as it does for so many human conditions, reflects the interplay between
environment and genes. We begin with the contribution of the environment.
A simple way of looking at this is to look at the global variation in the
incidence of particular forms of cancer. For example the incidence of skin
cancer in Queensland, Australia is 200 times higher than it is in Bombay,
India, and the incidence of stomach cancer in Japan is 10 times higher than it is
in Uganda. These differences can be explained in two ways, either by genetic
differences between the populations in the two locations that make them more
or less susceptible, or by environmental differences that lead to more mutations
in one location than the other. For example, the Japanese population could be
genetically more susceptible to stomach cancer than the Ugandan one, or there
is something different about the way in which people in the two countries live
that exposes the their populations to different levels of mutation causing
chemicals (mutagens) in their food.
30
Cancer rates vary widely
Cancer
Skin
Stomach
Region with
highest rate (per
1000)
Region with
lowest rate (per
1000)
Queensland,
Australia
Bombay, India
>200
<1
Japan
Uganda
110
5
After Cairns, J., Cancer: Science and Society, W.H. Freeman, 1978
For an animal population, you should be able to think of experiments that can
rule out one of these two hypotheses, but you should quickly come to the
conclusion that such definitive experiments are not allowed on humans.
Fortunately, there are natural experiments, and the most striking of these are
provided by large scale population migrations. For example, there has been
extensive immigration from Japan to the United States over the last 100 years.
This allows us to compare the incidence of stomach cancer in people of
Japanese origin who live in Japan, with those who migrated to the United
States, and with the migrants’ children. The incidence of stomach cancer is
highest in Japan, intermediate in the immigrants from Japan to the US, and
lowest in their children. In this case, the incidence of stomach cancer is
strongly correlated with how much pickled and fermented food the various
populations eat, likely reflecting the production of carcinogenic compounds by
the organisms used to prepare these foods. Rates for prostate and colon cancer
show the opposite trend, with low rates in native Japanese, higher rates in
immigrants, and rates that are indistinguishable from the Caucasian population
in their sons. Studies like this suggest that the vast majority of the global
variation in cancer rates reflects differences in environment rather than genes,
although there are some noticeable exceptions like skin cancer where there are
both environmental factors (exposure to sunlight) and genetic ones (skin
pigmentation).
31
Indirect association: migrations alter cancer
Cancer
Rate in Japan
Japanese
immigrants to
California
Sons of
Japanese
immigrants
Stomach
6.5
4.6
3
Colon
0.2
0.8
0.9
Prostate
0.1
0.5
1.0
All rates relative to white Californian males.
After Cairns, J., Cancer: Science and Society, W.H. Freeman, 1978
The knowledge that factors in the environment play an enormous role in
determining which population gets which sort of cancer prompts the interesting
thought that most cancer is in principle preventable. If we knew what the
dangerous features of our environment were, we could modify people’s
behavior and dramatically reduce their risk of cancer. Unfortunately, life is not
so simple. For at least two widespread cancers, those of the skin and lungs, we
know that the predisposing factors are sun and tobacco smoke. In both cases,
although the links between behavior and cancer have been clear for more than
50 years, efforts to modify people’s behavior have been poorly financially and
politically supported and only modestly successful.
32
Smoking causes lung cancer causes death
The case of lung cancer is particularly striking. By comparing the increase in
smoking amongst men and the increase in deaths from lung cancer it is clear
that the two are strongly correlated with cancer deaths rising roughly 20 years
after the increase in smoking. Women started smoking in large numbers so as
the other graph shows their incidence of deaths from lung cancer are still rising
whereas those from breast cancer are steady. Remarkably, this almost entirely
avoidable form of cancer will kill 90,000 men and 70,000 women in the US in
2005, almost twice as many people who will die from breast and prostate
cancer combined which rank as the second worst killers in women and men.
The message to you should be clear: SMOKING CAUSES CANCER
CAUSES DEATH.
33
Rare mutations can cause cancer
Subject
Chance of
colorectal cancer
Average age of
occurrence
Normal
0.04
65
HNPCC mutant
(0.2% of population)
0.8
44
APC mutant
(0.01% of population)
1
39
Just because some of the factors that induce cancer are environmental, we
cannot exclude the idea that genetic differences between individuals help to
determine who gets which sorts of cancer. Our evidence on this point is of two
sorts. The first is that there are rare genetic disorders that enormously increase
cancer incidence in the very small fraction of the human population that is
unlucky enough to bear a crucial mutation. Collectively, these strong genetic
predispositions probably account for only 1% of human cancers, but they have
been enormously useful for identifying genes that are commonly mutated by
environmental carcinogens in a wide variety of patients. The second is more
complicated and more controversial evidence that suggests that there are
common genetic variations that have much more modest effects on an
individual’s chance of getting a particular cancer. This latter topic will be
discussed in more detail in LS1b, but we mention the former here because it
helps to confirm that cancer is caused by mutations.
34
Rare mutations can cause cancer
Subject
Chance of
colorectal cancer
Average age of
occurrence
Normal
0.04
65
HNPCC mutant
(0.2% of population)
0.8
44
APC mutant
(0.01% of population)
1
39
One of the rare conditions that strongly predisposes individuals to cancer is called hereditary nonpolyposis colorectal cancer or HNPCC for short. Patients who are unlucky enough to inherit a
mutant gene, have an 80% chance of getting colorectal cancer and are diagnosed at an average
age of 44, as opposed to the general population which has a 4% chance of developing the disease
and an average age at diagnosis of 65. Human geneticists tracked down the gene that is mutated
in patients with HNPCC and it turns out to be one of the proteins involved in mismatch repair.
Yeast or bacterial cells that have mutations in their versions of the same gene have a mutation rate
that is 100 times higher than that of normal cells, and the same difference is seen when colon
cancer cells from HNPCC patients are compared to those of normal individuals.
A final question we can ask about cancer is how many different diseases it is. In principle we can
answer this question in three ways. The first is to ask pathologists who look at cancer biopsies
how many different appearances cancer can have, and the answer is frighteningly large [ask
Russell for details]. A second is to take cancers that appear identical to the pathologist and then
look for molecular markers that differentiate between them. Again the result is scary, since in
almost every study of this sort, cancers that appear the same to a pathologist can be differentiated
into at least two distinct classes by looking at differences in levels of particular proteins and
mRNAs. Last but not least, we can ask how many distinct genes can be mutated to cause a high
risk of cancer, and once more the answer is uncomfortably large with over 30 different genes
having been identified and the true number almost certainly at least twice this large[31 = 2002
number].
35
Rare mutations can cause cancer
Subject
Chance of
colorectal cancer
Average age of
occurrence
Normal
0.04
65
HNPCC mutant
(0.2% of population)
0.8
44
APC mutant
(0.01% of population)
1
39
One example of how very different mutations can cause similar cancers comes
from colorectal cancer. We have already met mutations in the HNPCC gene,
which elevate the frequency of point mutations, but there is another, commoner
form of familial colon cancer called adenomatous polyposis coli or APC for
short. In patients who have this syndrome, the rate of mutation in the tumor
cells is exactly the same as it is normal cells, but instead of having 46
chromosomes as every somatic cell does, the tumor cells have far more
chromosomes, and the number varies from cell to cell in the tumor because
chromosomes are constantly being lost and gained during cell division. In
contrast, the tumors in HNPCC patients all have the normal 46 chromosomes,
showing that the two different tumor syndromes become genetically unstable
in different ways, HNPCC cells by dramatically elevating the frequency of
point mutations and APC cells by losing and gaining chromosomes at a
prodigious rate. The important lesson here is that tumors of the same organ,
that look similar to pathologists can have completely different molecular
causes.
36
Different cancers destabilize genomes in different ways
HNPCC: 46 chromosomes, no major rearrangements
Familial APC: 71 chromosomes
The vast number of different molecular paths that can produce cancer has
important implications for trying to cure this disease. One approach, which
has been practiced for roughly 80 years is to treat cancer patients with
draconian regimes which are designed to kill all dividing cells, for example by
irradiating them with X-rays or treating them with chemicals that damage
DNA. Here the goal is to take patients to the very edge of death, and hope that
the cancer cells are easier to kill than the normal cells whose constant division
is required to renew the lining of our GI tract, replenish our immune system,
and perform many other essential functions. For the most aggressive tumors,
these therapies typically provide only a brief respite, and the differences
between the details of different cancers matter only if they make the tumor
cells more or less sensitive to these blunt instruments that the oncologist
wields. The second approach is to exploit the fact that different tumor cells
have become outlaws by different paths and try to match sophisticated
therapies to the molecular profile of a patient’s disease. As we will see later,
the story of Gleevec illustrates the strengths and weaknesses of this approach.
37
3C: The cell division cycle
1
3B: The cell division cycle
1.
2.
3.
4.
Introduction
a.
The cell cycle
b.
Challenges: order and coordination
The cell cycle engine
a.
Early embryonic cells cycles are stripped down
b.
Cyclins and cyclin-dependent kinases make an oscillator
c.
Proteolysis regulates the progress of the cell cycle
d.
The cell cycle engine in mammalian cells
Cell cycle checkpoints
a.
Cell cycle arrests
b.
Damage repair
Mitosis and the cytoskeleton
a.
Phosphorylation controls cellular architecture
b.
The cytoskeleton: roadways & scaffolding
c.
Microtubules are dynamically unstable
d.
Chromosome capture by exploration with selection
To understand more about what goes wrong in cancer we need to start by understanding the
basics of cell growth, cell division, and cell death. Cancer is caused by too much growth, too
much division, and too little death, but these processes are also central to all of biology from the
replication of single celled microorganisms to the growth and development that converts a single
starting cell into the elaborate and specialized structures of multicellular animals and plants, and
the physiological regulation that allows organs to grow and shrink as conditions change.
In this section of the course, we begin with a general description of cell division, as it occurs in a
typical human cell. We then introduce the challenges cells need to solve in order to grow, divide,
and leave the genetically identical descendants that will form well behaved members of the
cellular cooperatives that are our bodies. We will continue by introducing the cell cycle engine,
the biochemical machine that drives progress through the cell cycle and show how the
combination of protein synthesis, protein degradation, and positive feedback can produce a
molecular clock. Next, we will discuss how cells make sure they finish one task before starting
the next, a behavior that is critical if they are to avoid handing mutations on to their daughters.
Finally, we will talk about mitosis, the part of the cell division cycle where cells segregate their
chromosomes into two identical sets, as a way of introducing the cytoskeleton, the cells internal
scaffolding and the motors that move objects along it, and the concept of self assembly, which is
how most biological structures form.
2
Cell cycle learning objectives
Understand the challenges to producing genetically
identical daughter cells
Understand how a simple biochemical oscillator can drive
the cell cycle
Understand how protein phosphorylation can be used to
regulate protein activity
Understand why regulated protein destruction is a major
mode of biological regulation
Understand how cell cycle checkpoints protect the
integrity of the genome
The process that converts one newly born cell into two daughter cells is called
the cell division cycle or cell cycle for short. Most of the cells in your body
are neither growing nor preparing to divide. Those that are typically divide
about once every 24 hours, and this cycle is conventionally regarding as
starting when a cell finishes dividing. When we think about the cells genetic
information, there are three things that have to happen in each cell cycle: cells
have to replicate their chromosomes, then they have to segregate the replicated
chromosomes into two identical sets, one for one daughter cell, and the other
set for the other daughter, and finally the cell must divide in two. In most, but
not all, cells must also grow during the cell cycle so that when the mother
divides, her daughters are the same size as she was when she was born, a point
we will return to later on. These processes are shown in their simplest form on
this slide.
3
A minimalist view of the cell cycle
Cell
Growth
There are two ways of classifying where a cell is in the cell cycle. The first is
based on appearance and dates back to the 19th century, when the first cell
biologists examined the process of cell division. Based on the appearance of
cells they described two parts of the cell cycle, interphase, when the nucleus
was intact, and mitosis, when it broke down to reveal the chromosomes. We
now know that DNA replication occurs during interphase and that once the
chromosomes have been replicated, two sister DNA duplexes are associated
with each other as sister chromosomes or chromatids, as they are sometimes
called. The second classification comes from the 1950s when the availability
of radioactive isotopes made it possible to figure out when during interphase
DNA replication was occurring. The period when DNA was being replicated
is called S (synthesis) phase, and the period when chromosome segregation
takes place is call mitosis. We will also come back for a detailed study of the
remarkable changes in the cell’s architecture that occur in mitosis, but for now
its key feature is that after the nucleus breaks down, the replicated pairs of
chromosomes are arranged on a mechanical device called the mitotic spindle
whose structural elements are called microtubules. Once the chromosomes
are properly aligned, the linkage between the two copies is broken down and
the cell divides.
4
Mitosis segregates chromosomes
5
The standard cell cycle
G0
Cells rest in G0
The relationship between S phase and mitosis divides the standard cell cycle
into four parts or phases. A gap called G1 lasts from the birth of a cell to the
start of S phase is called G1 and a gap called G2 lasts from the end of DNA
replication to the beginning of mitosis is called G2. In a typical animal cell
cycle G1 lasts for 12 hours, S phase for 6 hours, G2 for 6 hours and mitosis for
about 30 minutes. These phases describe the orderly progress of the cell cycle
in cells that are actively proliferating. But the vast majority of cells, whether
they be in multicellular or unicellular organisms and whether they be bacterial
or eukaryotic, are neither growing or dividing. These cells are not making
progress through the cell cycle but are stuck in specialized resting phase, which
in eukaryotes is named G0 (G zero). These cells are metabolically active, and
some cells, such as neurons can remain arrested in G0 from well before birth
until their owner dies. They make mRNA and the mRNA catalyzes the
production of proteins, but for most cells in G0 the rate at which new
components are made is precisely balanced by the rate at which old ones are
degraded, so that the cells turn over many of their components without getting
either bigger or smaller. Cells leave the active cell cycle from G1 to enter G0,
and when they start proliferating again, they return to G1.
6
Cell Cycle Challenges
The cell cycle engine
DNA replication
Chromosome segregation & cell division
Coordinating growth and proliferation
Finishing tasks
Before we go on to discuss the cell cycle in more detail, I will introduce the
different aspects we would like to understand.
1) The cell cycle engine. What is the nature of the biochemical machine that
induces DNA synthesis in and interphase cell, then drives it into mitosis, sends
the signal to separate the sister chromosomes and start cell division, and finally
pushes the cell into interphase of the next cell cycle?
2) What is the machinery that induces DNA synthesis? We have talked about
the basic mechanism of DNA replication, in which the two strands of the DNA
duplex separate from each other and act as the templates for the synthesis of
two new strands by DNA polymerase. There are a number of other important
questions such as whether DNA replication starts at specific places on the
chromosomes and how the cell makes sure that every part of the genome is
replicated once and that none of them are replicated twice. We will come back
to consider one aspect of the latter problem, but most of the details of how
cells solve it are beyond the scope of this course.
7
Cell Cycle Challenges
The cell cycle engine
DNA replication
Chromosome segregation & cell division
Coordinating growth and proliferation
Finishing tasks
3) How do cells assemble a mitotic spindle, align their chromosomes on it and
then break the linkage between the sister chromosomes?
4) How do cells coordinate cell growth and proliferation so that over many
cells cycles these processes are carefully enough balanced that the average size
of the cells stays constant?
5) How do cells make sure that they finish one task before starting the next?
8
The cell cycle engine
a. Early embryonic cells cycles are stripped down
b. Cyclins and cyclin-dependent kinases make an oscillator
c.
Proteolysis regulates the progress of the cell cycle
d. The cell cycle engine in mammalian cells
The early embryonic cell cycle
The cell cycle I have just described is the one that is most relevant for
understanding cancer but most of our knowledge about the basic mechanism of
the cell comes from two other sorts of cells. One is the bakers and brewers
yeast, Saccharomyces cerevisiae. This organism is often referred to as the
budding yeast and has been widely used for studying the cell cycle and every
other aspect of cellular behavior. The other are the first few cell cycles of
various embryos, most notably those of the South African clawed frog,
Xenopus laevis.
The rationale for using early embryos is that they are cells that are specialized
for cell division and if you want to study a ubiquitous biological processes, the
best place to start is with a cell that is specialized for the process you want to
understand. Thus many cells use the difference in electrical potential across
the plasma membrane to accomplish important tasks, but the principles were
first understood by studying nerve cells which exist to transmit electrical
signals across time and space. Likewise, every eukaryotic cell contains
motors that can move along the structural fibers of the cytoskeleton, but the
identity and mechanism of these motors was first understood in muscle cells
and sperm both of which are specialized for rapid and directed motion.
9
The frog egg is specialized for cell division
Fast cycles
LOTS of eggs
Natural synchrony
The cells that are most specialized for cell division are the eggs of creatures
who lay countless eggs that are fertilized outside the mother and then left to
fend for themselves. Before they turn themselves into creatures that can swim
or wriggle away, these eggs are easy prey for a variety of predators, placing a
high premium on getting from egg to moving creature as fast as possible. This
logic applies to amphibia, fish, and a wide variety of marine invertebrates such
as sea urchins, starfish, and clams. These creatures offer three other important
advantages. The first is that because so many of their progeny get eaten, they
produce eggs and sperm in prodigious quantities. The second is that because
egg and sperm meet outside the female, scientists can start a large number of
eggs proceeding synchronously through the cell cycle by simply mixing eggs
and sperm. Finally, the eggs start out by just dividing to make smaller and
smaller cells, rather than requiring that each cell grow bigger before it divides.
This is a crucial point. These eggs already contain all the proteins that are
needed to make more chromosomes and to segregate them, such as tubulin,
histones, DNA polymerase, all of which have been stockpiled during the long
slow cell cycle that produced the egg. As a result, we shall see that the role of
protein synthesis is restricted to producing a small number of proteins that are
intimately involved in regulating passage through the cell cycle. The embryos
of early frog eggs have one further advantage, the biochemical engine that
drives their cell cycle continues to run even if there are problems with DNA
replication or chromosome segregation.
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The frog egg is specialized for cell division
Fast cycles
LOTS of eggs
Natural synchrony
For simplicity, we refer to the first few cell cycles of the these types of eggs as
the early embryonic cell cycle. This movie shows one of the simplest of all
cell cycles, that of a fertilized frog egg. The egg is 1.6 mm in diameter and
after it has been fertilized it divides after 90 minutes and then again every 30
minutes for a total of 12 rounds of cell division which convert one cell into a
ball of 4000 much smaller cells.
Because the dividing egg doesn’t have to grow, these early embryonic cells are
highly simplified, and have been stripped down to three processes, DNA
replication, chromosome segregation and cell division.
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Watching eggs cleave
This movie shows six frog eggs cleaving. You should notice that they all show
a weird convulsion before they divide for the first time, that they divide in
almost complete synchrony with each other, and that they keep dividing and
getting smaller and smaller without growing any bigger. Like many things in
biology, this progressive reduction in cell size is an exception that draws
attention to a general rule. In this case the rule is that cell growth and cell
proliferation are tightly coordinated so that cells double in size in the interval
between birth and division so that the daughter cells are born at the same size
as their mother was.
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Coordinating Cell Growth & Division: reproduction
Typical somatic cells double
in size in each cell cycle
This coordination between growth and proliferation is deliberately suspended
to produce eggs. Over roughly 6 months, the 1.6 mm diameter frog egg grew
without dividing from a normal looking, roughly 10 um diameter germ cell,
thus increasing a million fold in volume, and then over the first five days of
development, division without growth produces a tadpole with a roughly a
million cells, on average 10 um in diameter . After this stage, cell size stays
roughly constant demonstrating that growth and proliferation are now being
tightly coordinated. In unicellular organisms like budding yeast, scientists
have shown that this coordination is due to the cell cycle arresting in early G1
until cells achieve a critical size, implying that cells actually know how big
they are and set the size they wish to achieve based on the conditions they are
experiencing!
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An autonomous oscillator drives the cell cycle
Time in minutes after activation
The cell division cycle depends on the orderly succession of DNA replication,
chromosome segregation, and cell division. As we will see later in this
section, if the order of these events was altered, or if one started before its
predecessor had finished, dead or genetically damaged cells would be
produced. We have already argued that large stores of the proteins that carry
out replication, segregation, and division have been bequeathed to the egg by
its mother, so in principle any of these events could be happening at any time.
Thus there must be a regulatory machine that switches the biochemical
activities of these proteins on and off so that the right events occur in the right
order.
We call this machine the cell cycle engine and the goal of this section is to
learn about its components and the interactions between them that allow it to
produce a regular cycle of activities which in turn drive the regular progress of
the cell cycle. In most cells, the cell cycle engine is a complex machine that is
subject to many forms of regulation, which use two sets of signals from the
cells immediate environment to control whether cells grow and proliferate.
The first are external signals that tell a cell whether it should be growing and
proliferating or resting quiescently in G0. The second are internal signals that
let the cell know whether crucial events like DNA replication have been
completed yet.
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An autonomous oscillator drives the cell cycle
Time in minutes after activation
Important as these controls are, they make the engine difficult to dissect and
analyze. In this regard it resembles a modern automobile, which must fulfill
several functions at once, making it hard for a naïve owner to understand,
much less work on their car. In contrast, the early embryonic cell cycle is the
equivalent of a dragster, with a huge engine, the minimum set of controls, no
video screens for the kids in the back, and a single, brutal purpose, to get from
here to there as fast as possible. In the case of the early embryo, a simple, twostroke, biochemical oscillator drives the events of the cell cycle.
The first hint of this oscillator came from making movies of frog eggs that had
been tricked into thinking they were fertilized but contained no DNA. These
eggs never divide, but they show rhythmic waves of contraction that precisely
mimic when their normally fertilized counterparts would be dividing,
suggesting that it is an oscillator in the cytoplasm of the eggs that is driving the
nuclei through the different parts of the cell cycle, and that the period of this
oscillator is unaffected by the removal of nuclei. The slide shows stills from
the movie and the movie follows. The first bulging up of the cell corresponds
exactly to the convulsion that preceded the first cell division in the movie of
the eggs that had been genuinely fertilized.
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Embryonic oscillator conclusions
The oscillator does not require a nucleus or DNA
The oscillator is unaffected by interfering with mitosis
or DNA replication
The oscillator depends on post-translational
modification, and protein degradation
NOTE: First two conclusions are not valid for the
standard cell cycle
This experiment and its successors leads to three crucial conclusions. The first is that in these
cells the engine runs independently of the events it normally controls, that is that engine keeps
running even if there is no DNA to replicate or chromosomes to segregate. The second is that
even if the eggs are allowed to keep their nucleus, drugs that interfere with DNA replication
or mitosis do not slow down the engine. Third, if the engine can run for many cycles in a cell
that lacks DNA, the basic oscillation must depend on the ability of proteins to modify each
other’s behavior, rather than changes in that rate at which genes are transcribed into mRNA
and mRNA is translated into protein. This is an important point for you to take away. Most
introductions to modern biology focus heavily on the basic mechanisms that control where
and when particular genes are expressed and from this emphasis it is easy to get the
impression that most of biological regulation occurs by regulating which genes a particular
cell transcribes into mRNA. In reality, more, faster, and more subtle regulation occurs by
controlling protein degradation, the chemical destruction of proteins, and by controlling
how proteins chemically modify each other to regulate their location and activity. These
chemical changes are collectively referred to as post-translational modification, and form an
important part of the remainder of this course. It is important to remember that these early
embryonic cell cycles are atypical and the first two conclusions do not apply to the standard
cell cycle. The third does, although for standard cell cycles regulating when cells express the
genes that encode the proteins of the cell cycle engine controls its progress along with posttranslational modifications and protein degradation.
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The discovery of cyclin
Tim Hunt,
discoverer of cyclin
But what is the oscillator? The answer is surprisingly simple; the
accumulation and destruction of a single protein called cyclin is the core of the
oscillator. Like many of the most important biological discoveries this one
was made by accident. Tim Hunt, a British scientist, had worked for many
years on how protein synthesis was controlled and had become increasingly
interested in early embryos, where protein synthesis seemed to have an
important role in driving the cell cycle engine, since even in these cells that did
not have to grow in order to divide, drugs that blocked protein synthesis
arrested the cell cycle by keeping the embryonic cells from leaving interphase
and entering mitosis.
Tim was testing an idea that others had proposed, namely that eggs that had
really been fertilized and those that had been chemically tricked (a process
known as parthenogenetic activation) into thinking they had been fertilized
made different proteins. He took eggs treated in these two ways, incubated
them in radioactively labeled methionine, collected a fraction of the eggs every
10 minutes, lysed them, and then separated the proteins according to their
molecular weight and used photographic film to detect those that were
radioactive, since the particles emitted when a radioactive element decays can
expose film. The key to this experiment is that the only proteins being detected
were the ones the eggs were making after they had been fertilized, so that all
the proteins that the mother sea urchin had deposited for her progeny were not
labeled.
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The discovery of cyclin
Tim Hunt,
discoverer of cyclin
When Tim developed the film, the result was striking. In this picture the
largest proteins form horizontal bands at the top of the image and the smallest
ones form bands at the bottom. Most of the bands simply got darker and
darker as the samples were taken later and later after fertilizing the eggs. But
one did not. It got brighter for the first 45 minutes after the egg was fertilized
and then abruptly disappeared, and then reappeared later, repeating this
behavior over several cell cycles. As Pasteur said “Fortune favors the prepared
mind”. Although Tim had not intended to look for this protein, he instantly
made three intuitive leaps: because the protein accumulated during interphase
and then disappeared at the end of mitosis it must represent an activity that
catalyzed entry into mitosis, its abrupt and specific disappearance meant there
must be ways of very selectively degrading a small number of proteins at
particular points in the cell cycle, and the simplest way of explaining its
disappearance was that when cyclin reached some critical level it activated the
machinery that would lead to its own destruction. All three ideas proved to be
completely right, and other experiments that I don’t have time to describe both
confirmed Tim’s brave leaps of faith and showed that the fundamental
structure of the cell cycle engine was evolutionary conserved over the roughly
billion years since frogs and budding yeast last shared a common ancestor.
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Cyclin oscillates through the cell cycle
19
A cyclin-based cell cycle
Cyclin binds to and activates
Cyclin-dependent kinase 1
One of the subsequent discoveries was that cyclin binds to and activates a
protein called cyclin-dependent kinase 1 (Cdk1). Kinases are a class of
enzyme that catalyze the transfer of a phosphate group from ATP to another
molecule. Protein kinases are the subclass of kinases that transfer the
phosphate from ATP to the hydroxyl group of one of three amino acids, serine,
threonine, or tyrosine, and because Gleevec attacks cancer cells by interfering
with a protein kinase, you will hear a good deal more about the chemistry and
biochemistry of this reaction later in the course. But for now, the key point is
that the addition of the phosphate group modifies the protein that receives it in
one of a variety of ways: activating or inhibiting the catalytic activity of an
enzyme, encouraging or discouraging the binding of the modified protein to
other molecules, altering its stability, or changing its localization within the
cell. The stability of proteins is usually expressed in terms of their half life,
the time it takes for their concentration to fall by a half after you have
prevented the synthesis of any new protein.
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Protein kinases add phosphates to other proteins
We can now make a simple model for the cell cycle engine. We begin just
after mitosis, with Cdk1 molecules that are inactive as protein kinases because
the cell has just destroyed all its cyclin. As cyclin accumulates it binds to
Cdk1, activating the protein kinase activity of this enzyme and the active
protein kinase activates machinery that destroys cyclin, thus inactivating Cdk1
and returning the cell cycle engine to its original state.
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Phosphorylation regulates protein activity
Phosphorylation ACTIVATES
OR
Phosphorylation INACTIVATES
Also regulates:
Inter-molecular binding
Protein degradation
Protein location
This simple viewpoint has two problems., If the binding of cyclin to Cdk1 was
enough to activate the protein kinase activity of Cdk1, the amount of protein
phosphorylation catalyzed by Cdk1-cyclin complexes would go up gradually
interphase as more and more cyclin accumulated. But we have seen that the
transition between interphase and mitosis is an abrupt one, suggesting that we
should look for an explosive way of activating Cdk1-cyclin complexes to
explain it. More importantly, if the synthesis of cyclin and the rate of cyclin
destruction were each constant throughout the cell cycle the cell would simply
reach a steady where the concentration of cyclin led to exactly equal rates of
synthesis and destruction.
This would be a disaster, since the whole purpose of the cell cycle engine is to
act as an oscillator. This highlights why we often need a careful understanding
of the kinetic and regulatory details of biological reactions to explain what
their biological purpose is. The gory details of the cell cycle engine lie beyond
the scope of this course and I will only summarize them here.
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Phosphorylation regulates protein activity
Phosphorylation ACTIVATES
OR
Phosphorylation INACTIVATES
Also regulates:
Inter-molecular binding
Protein degradation
Protein location
The basic idea is that Cdk1-cyclin complexes control their own activation and
inactivation. They control activation through a positive feedback loop, a
device that makes an initial change amplify itself. What this means is that
when cyclin and Cdk1 first bind to each other, the complex is not active as a
protein kinase. Other reactions, which add and remove phosphate groups from
Cdk1 itself to convert it to its catalytically active form, are stimulated by the
active Cdk1-cyclin complex. Thus when cyclin is first made, there is little or
no active Cdk1, so cyclin-Cdk1 complexes are inactive. As time goes on, a
little bit of activated complex appears. This stimulates the reactions that
activate Cdk1, leading to the production of more active Cdk1, further
accelerating the activating reactions. As a result the reaction keeps getting
faster and faster leading to the very rapid conversion of all the Cdk1-cyclin
complexes into their active form. Positive feedback is widely used in biology
amplify small input signals into dramatic outputs.
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Positive and negative feedback produce a cell cycle
Fast
Slow
To inactivate Cdk1-cyclin complexes, the oscillator uses negative feedback,
the principle that tends to return a system to its original state after it has been
perturbed. There are two types of negative feedback. The first is fast and its
effect is to keep a part of biology working at the same level in the face of
external changes. A classic example is your blood pressure. If it falls,
receptors in your arteries send signals that increase your heart rate and produce
other changes that tend to restore it to the normal range. If it goes up, an
opposing set of signals is sent telling your heart to slow down.
The second type of negative feedback is delayed, and it allows a biological
system to get to a state very different from the starting one, but then returns it
to something resembling its initial state. This is exactly what happens in the
cell cycle engine. Active Cdk1-cyclin complexes turn on the anaphase
promoting complex (often abbreviated as APC), the regulated part of the
machinery that destroys cyclin molecules, but they do so slowly enough that
almost all the complexes have time to get activated, and cells have time to
enter mitosis, before the cyclin is destroyed. This slide shows a cartoon of the
amount of cyclin and the activities of Cdk1-cyclin complexes and the anaphase
promoting complex, showing the rapid activation of Cdk1 and the delayed
activation of the anaphase promoting complex.
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