The Impact of Obesity on Cancer Risk

February 27, 2020

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as time permits. Now I would like to
introduce your moderator for today’s Webinar,
Dr. Gabriela Riscuta, Program Director in the Nutritional
Science Research Group, Division of Cancer Prevention at
the National Cancer Institute. (Gabriela Riscuta):
Good afternoon. I would like to welcome you
all to the sixth presentation of the Frontier’s in Nutrition and Cancer Prevention
online series. I am very pleased to introduce
today’s Webinar The Impact of Obesity on Cancer Risk. Before we get started, I want
to thank to Dr. Barry Kramer, our division director
and to my colleagues on the steering committee
and planning committee who made these webinars
possible. We are very excited as we have so many people joining
the webinar today. We have researchers, physicians,
nurses registered dieticians and nutritionists, clinicians,
fellows and students with us from all 50 states of United
States and many countries all over the world like
Canada, Italy, Brazil, Sweden and Argentina
are just to name a few. I suspect that we’ll hear
a variety of interests and perspectives shared during
our question-and-answer portions of the webinar. According to the U.S.
Centers for Disease Control and Prevention more than one
third, like 24.9% or 78 million of adults in the
United States are obese. Growing obesity incidence
is associated with a (matter of) health
consequences including cancers. In our webinar today, experts
in the field on nutrition and cancer will evaluate
the strengths and weaknesses of epidemiological data and the
underlying molecular mechanisms and common pathways
of obesity and cancer. During the presentations, gap
in knowledge and new tactics to advance obesity cancer
research will be discussed. Now, I would like to
turn over the program to our first presenter,
Dr. Edward Giovannucci. Dr. Giovannucci is a Professor
of Epidemiology and Nutrition at Harvard T.H. Chan
School of Public Health. He is an associate
professor of medicine at Harvard Medical School and he is also an associate
epidemiologist in the Department of Medicine of the Brigham
and Women’s Hospital. The title of Dr. Giovannucci’s
presentation today is Obesity and Cancer: Epidemiological
Observations. When finished, Dr. Giovannucci
will take a few minutes to answer questions. Dr. Giovannucci, please? Edward Giovannucci:
Thank you, Dr. Riscuta. It’s a pleasure for
me to be talking about obesity and cancer. I’m going to focus on the
epidemiologic observations. As you all know, obesity
has been associated with an increased risk
of cancer incidents and especially mortality
for many cancers. The American Institute for Cancer Research
estimates greater than 100,000 cancers per year in the United States
are attributable to excess body weight. Now it’s amazing how many
cancers are related to obesity. There (are) not many risk
factors that have cross-cutting across so many cancers. This slide shows the 13 cancers
that have been associated with obesity and they range
from GI cancers, endocrine, genitourinary system,
quite a broad spectrum. I’m going to focus on
the epidemiologic data, and as you know in the
epidemiology we have to assess obesity or adiposity
in a large population. So we have to use
practical measures and the most common
is – oops, sorry. The most common is
body mass index which is kilograms per
meter squared which takes into account the person’s
weight and their height. And you probably
know this category, overweight’s considered
greater than 25, obesity greater than 30, (and) greater than 35
is even more severe obesity. Now using this measure
the study, a large study from the American
Cancer Society estimated that in non-smoking individuals
in the United States, about 14% of cancers
are attributable to having a body mass index
greater than 25 for men and about 20% for women. So at least in theory this
means that if we got everybody to a body mass index (of) below
25, we would prevent about 14% of cancers in men
and 20% in women. Now, so if we look at all the
individual types of cancer, you know, each cancer
has, is different but the proportion attributable to overweight is approximately
10% to 20% as we’ve seen. Now for two cancers, endometrial
cancer and esophageal cancer, obesity is much more
strongly associated and the proportion
attributable to BMI greater than 25 is greater than 50%. So for these two cancers, obesity is a very
strong risk factor. But I’d like to point
out that the percent of cancers attributable to access adiposity is
likely underestimated because most studies have
used a single measure in the BMI cut point of
greater than 25 but what happens if we use a stricter cut point of 22.5 kilograms
per meter squared? So (I) just show
one slide here from, this is from the Health
Profession Study and I just want to make the point
here that the relation between body mass index
and cancer is linear. We use a practical cut
points like 25 and 30 but the associations
as you can see is across the whole spectrum. In fact you can see that using
the bottom group, BMI 20 to 22.5 as a reference there’s a
statically significant 50% increase even in individuals
with BMIs from 22.6 to 25, but even in the moderate range or in the lean range not
considered overweight there is a relationship between adiposity
or BMI and risk of colon cancer. So if, in the cancer, American
Cancer Society Study they concluded that 10% of colon
cancers were attributable to BMI greater than 25. And in our study (a) Health
Professions Follow-up Study, we use a stricter
cut point of 22.5 and we used also multiple
measures so we try to get more consistent BMI
measures over time and we found that 30% of colon
cancers are attributable to having a BMI greater
than 22.5. Of course this may not be, getting people below 22.5 may
not necessarily be practical on a population basis but at
least it’s important to (know) that the relationship
is even stronger if you consider lower BMIs. Now BMI’s a useful measure in
large epidemiologic studies but it does have
some limitations and (that) the two most
important are it does not distinguish lean
mass from adiposity and it does not distinguish
visceral from subcutaneous adiposity. So circumference
measures are useful also. In this study, in the Health
Professional Study we looked at waist circumference
(in) colon cancer and we actually found a
strong association even after adjusting for
body mass index. So it seems that waist
circumference gives independent information than
just body mass index. In this study, in the
Nurse’s Health Study, they stratified body
mass index, you can see, into three categories and also
then stratified by a large and lower waist to hip ratio. So if you can see with
the reference group with individuals less than
25 BMI, BMI less than 25 and also having a low waist to
hip ratio, if you have BMI 25 to 29.9 which is the
overweight, you see that those with the lower waist – hip – waist to hip ratio had
a relative risk of 1.25. But it was actually
2.05, much stronger if they had a high
waist to hip ratio. So even in the overweight
range the waist to hip ratio adds a
lot of information. Now visceral adiposity
is important to consider. What is visceral adiposity? Well circumference
measures are useful in distinguishing adipose
mass from lean mass. However circumference measures, (it’s) even waist circumference
does not directly assess visceral adiposity
especially among those with a relatively small
waist circumference. I think this slide illustrates
the point very nicely. This is from CAT scans (on
the), from a published paper from (Thomas) and as you can see
(in) the CAT scan, this is taken at the level of the umbilicus. So these are eight separate men
all have the exact same waist circumference but
you can see the, from going from the top left
the, you see much less fat. The adipose comes out as white,
you know, on the CAT scan. So you see the top-left man
has a visceral fat estimated at 0.5 liters. If you go to the bottom right,
the visceral fat is 4.3 liters which is eight to nine times
higher visceral fat even with, among men that have exactly
the same waist circumference. So there’s a lot of information
in, that’s not captured by even circumference measures. And (their) studies, it’s hard
to use a CAT scans or MRIs to estimate visceral adipose
tissue in epidemiologic studies because they’re costly. There’s been studies done
for colorectal adenoma which is a precursor to cancer
because these are very common and you only need to, you know, measure about a thousand
to get good power. And we actually did
a pooled analysis of the published studies and we
found that independent of BMI, you see a nice linear
association between the visceral adipose
tissue or VAT and the odds ratio of colorectal adenoma with almost a three-fold
increased risk going to the high level
compared to the low. Now these measures
of BMI circumference, even visceral adiposity
tissue are static measures, they don’t take into
account changes. Now ideally we would like to
do a large, randomized trial to show that changes in weight,
(of) preventing weight gain or inducing weight loss
will reduce a risk of cancer but those studies are very hard
to do for practical reasons. There is a little bit of
epidemiologic studies, observational data
that inform on this. So if we assume that adiposity
is causally associated with cancer risk, two
important questions are, would preventing adult weight
gain lower one’s cancer risk? And the second is would
intentional weight loss lower one’s cancer risk? Well, let’s look at
the first question and there are some epidemiologic
studies that suggest this (and) that this is preventing
weight gain in adulthood would
potentially lower risk, and this is a pooled
analysis we did on studies of postmenopausal breast cancer which has been associated
with obesity. And we can see that adult
weight gain strongly correlates with risk of breast cancer
and this is among women, non-hormonal (replace)
therapy users. So this at least is
observational data that women who gain the most weight had the
highest risk of breast cancer. And there are a few other
studies, there’s a study for example in colon cancer
that also shows this pattern but it needs to be looked
at for other cancers. Now there’s another
question is (what), whether intentional weight loss
would lower one’s cancer risk and that’s actually a much
harder question to answer from an epidemiologic
perspective for three reasons
that I list here. First of all intentional adult
weight loss is rare so it’s hard to actually get enough numbers, and then (the) second
thing is much of the weight loss is
not maintained over time. And (the) third is that (and)
most of adult weight loss, if you look broadly at (a)
population is actually due to illness, underlying disease
and loss of lean body mass. So that may not be really
what you’re looking for, it’s not an intentional. There have been a few studies, and this is in a Nurse’s Health
Study in which they try to take into account some of
these issues by looking at longer-term weight loss and they actually
did find a reduction. So women who lost weight, 10
kilograms for example or more over the menopause period
actually had about half the risk of developing post-menopausal
breast cancer. The other sort of
evidence is from studies of bariatric surgery
where people have surgery and then have (a) weight loss and these are very
obese individuals. These aren’t perfect
randomized trials by any means, they usually need to have a
control group of women or men of similar weight that
did not have the surgery. And as you can see in the
slide here at least for women after the surgery there was a
pretty large reduction primarily in breast and endometrial
cancer compared to what their rates
would be expected. So this is a little
bit of evidence that weight loss actually would
impact your risk of cancer. Now other speakers,
particularly Dr. Dannenberg, is going to talk a lot more
on mechanisms so I just want to touch briefly based not so
much on (detailed) mechanism but more sum of what the
epidemiology suggests. And there are multiple
mechanisms where obesity may be
associated with cancer risk and what’s been most interesting
in the past ten years or so have been large studies that have linked pre-diagnostic
blood levels of hormones such as insulin, insulin-like
growth factor one or IGF-1 and estrogen, these are
all linked to obesity and with various cancers. So for example here we can see
that studies have clearly show, multiple studies that IGF-1
and estrogen (are) associated with increased risk
of breast cancer. But for the five cancers listed
there is a pretty compelling (and) data that suggest at
least there’s an association between these markers
and (the) risk of cancer, and these blood samples are
taken years sometimes decades before the risk of,
before the cancer occurs. And) just to show you
one, a little bit of this, this is body mass index
in (cross-sectionally) in the Nurse’s Health Study. You can see there’s a strong
association between BMI and bio-available estrogen
levels, almost a three-fold, three to five, four-fold
difference between the low and
the high group. And this corresponds almost
perfectly with their risk of endometrial cancer which
is strongly associated with estrogen. And if you look post-menopausal
breast cancer, you also see that adult weight
gain interestingly is, strongly predicts a cancer in non-hormonal replacement
therapy users, women not receiving
estrogen post-(menopausally). But you see no association in
estrogen users which indirectly, not definitively but indirectly
supports the role of estrogen in breast cancer because the
women taking hormones already have high estrogen levels
and are at high risk, but among the women not taking
estrogen therapy there’s a nice correlation between weight
gain which is associated with estrogen and their risk. I’ll also point out that there
are other mechanisms and, that maybe very specific
for cancers, and I think local inflammation
is an interesting concept here. For example obesity is
associated with acid reflux which causes chronic low-grade
inflammation in the esophagus, Barrett’s esophagus
a precursor and leads to adenocarcinoma
of the esophagus. Gall stones are strongly
associated with obesity and probably chronic
gall stones increase risk of gall bladder cancer
through chronic inflammation. And fatty liver is a, very
strongly associated with obesity and sometimes leads to inflammation and
to liver cancer. (So), now (I’m) finishing
up here but I just want to note an important
observation, obesity may influence
prognosis from cancer and cancer mortality beyond
effects on cancer incidents. (All) that I’ve talked about so
far has been on the incidents) but there are potential reasons
why obesity may impact cancer mortality independently. It may for example cause more
aggressive sub-types of cancer or it may influence things
such as diagnosis and treatment which may (make) cancers (have), obese people have
a poor survival. I just wanted to
show that these data. So for breast cancer, if you
look at these two age groups, you look at the relative risk
for a 10-unit increment in BMI and you see a much
stronger increment in risk of mortality than incidents. (But) for example (in) the
women 60 to 60 to 64 years in this study, this increase
in BMI was associated with 22% increase risk
of getting breast cancer but a 75% risk of getting
and dying of breast cancer. So the impact of obesity
goes beyond just incidents. And this study just
shows recurrence. As you can see the lowest risk
is a BMI of 22 and then it goes up with increasing BMI. This is (distance)
recurrence in women with localized breast cancer
diagnosis, strong association. And prostate cancer is one
cancer that’s interesting because obesity is not
associated with incidents but it does seem to
increase mortality and obesity has been associated with higher-grade
prostate cancer, more advanced stage
and poorer survival. So just in summing
up here quickly, we’ve seen that excess
body weight increases risk of at least 13 types of cancers,
broad spectrum of cancers. Cancer mortality maybe increased
independently of incidents, the effect of obesity on mortality may be
even independent. It may be independent mechanisms that increase mortality
beyond just increasing risk. Multiple mechanisms are involved
and Dr. Dannenberg will talk about some of those, and
the final note is the impact of obesity on cancer incidents and mortality may now
be comparable to that of tobacco in the United States. As tobacco has gone down,
still of course (in), a very important risk factor,
but as tobacco use has gone down and obesity has gone up, obesity
is now becoming comparable to tobacco use as a
risk factor for cancer. Thank you and I’ll be glad to
take questions at this point. Coordinator: Thank you. At this time we would like to
begin the question-and-answer session of the conference. If you would like to ask
a question at this time, please press star then one. You must record your first and
last name to ask your question. To withdraw your question,
you may press star then two. Once again, if you would like
to ask a question at this time, please press star then one and
record your first and last name. One moment for the
first question please. (Gabriela Riscuta):
Yes, it’s (Gabriela). (I just put out), we actually
received some questions through the chat box and
I will read some questions for Dr. Giovannucci. Dr. Giovannucci, thank you so
much for a great presentation, and the first question
that I would like to read for you is is any hypothesis or do you have any
thoughts why the risk of some cancer is
higher than others in relation to the BMI level? So I guess the question is why
not all cancers are (having), showing the same
relation to the obesity in regard to the BMI levels? Edward Giovannucci: Yes. I mean that’s a good question. Every cancer has its own set
of risk factors and, you know, for example smoking is a strong
risk factor for some cancers, not a risk factor for others, and actually even a little bit
protective for some cancers. So there is, you know, cancers
are very complex and it’s hard to think that there
would be a factor that would be strongly related
similarly to all cancers. Now some cancers like
for example endometrial and breast cancer, they’re
both, they’re tissues that are strongly
related to estrogen. Estrogen is a strong
proliferative component of these tissues. So it’s not surprising
to me for example that in post-menopausal women
most of the estrogens are from, made from adipose tissue. So for these cancers
you would almost predict that there would be
a strong association between obesity and cancer. For other cancers, you know,
they’re, they may not have as clear hormonal factors that
are associated with obesity. So I think it’s hard to say, you
know, (when) go down the list, we don’t have time for each
cancer site but I think for some cancers the
hormonal link is much stronger than for others and
that’s the main reason. (Gabriela Riscuta): Thank
you so much, Dr. Giovannucci, and I have one more
question for you. I mean there are more questions but I will read one more
due to the timeliness. So this question is
is your impression that the visceral adiposity is
as important, more important or same important as BMI level
in regards to the cancer? Is because I think you presented
– I am just adding (my thought) but you presented (the) visceral
adiposity I think an important factor related to cancer. (If so), how would you
relate the visceral adiposity and the BMI level? Which one, is one more
important than other? Do we have enough data to
make any – (thoughts about)? Edward Giovannucci: Well,
yes, I mean (it), that, it’s – the visceral adiposity, (but) some people believe it’s
the most important component of adiposity that’s related
to metabolic aberrations such as insulin resistance. So now I think (that), I think
the main point to take from some of the slides that I
showed is that when you get like for example individuals
with a very high BMI of let’s say 35 for example, those individuals very likely
have a lot visceral adiposity. It’s hard to get a BMI that
high without having a lot of visceral adiposity. But when you get to lower BMIs, as I showed in that slide (of
some) CAT scans you can see even men with seemingly normal
waists have a wide range of visceral adiposity. So when you get into the
normal range of BMI that’s where the visceral adiposity
I think becomes much more a predictor for risk but I
think they’re both two ways of getting at the same thing. But I think it’s –
maybe one way to think of it is the visceral adiposity
is more useful at the lower end of BMI where you don’t
really, you know, you might (say) a
BMI of 25 is normal. But that could be very different
from an athlete for example, a marathon runner
can have a BMI of 25 or a couch potato can have a
BMI of 25, (but) I think that’s where visceral adiposity
might be more informative. (Gabriela Riscuta): So
you making the difference between people having the
same actually weight but the, a different waist or
a visceral adiposity so they would be placed
at maybe higher risk of… Edward Giovannucci: Yes. (Gabriela Riscuta):
(Unintelligible). Edward Giovannucci: Yes. (But that’s right)
(unintelligible). (Gabriela Riscuta): (Unintelligible) normal even
being in the normal BMI level? Edward Giovannucci:
That’s right, yes. BMI I think is more
informative at the upper levels so people with, you know, BMIs of above 30 are almost
clearly (or are) always obese unless they’re, you know,
super athletes or something. But at the lower end of BMI (is)
individuals can still have a wide range of adiposity
especially visceral adiposity but that’s not really
captured by the BMI. So the (B) – it’s
sort of a limitation of the measure of BMI. You can (view) it that way. (Gabriela Riscuta): Okay, thank
you so much, Dr. Giovannucci, and for additional questions
we will provide your contact information and our contact
information to follow-up with the e-mails in case the
participants will have or would like to continue (these). (And) we need to move
to our next presenter, Dr. Andrew Dannenberg. And Dr. Dannenberg is
the Associate Director of Cancer Prevention
at the Sandra and Edward Meyer Cancer Center. And Head MD, Roberts
Family Professor of Medicine at Weill Cornell Medical
College of Cornell University where he is also Professor
of Medicine in Surgery, Weill Cornell Medical College. Dr. Dannenberg will discuss the
obesity inflammation connection, implications for breast cancer. When Dr. Dannenberg will
finish we’ll have time for a few questions. Dr. Dannenberg? Andrew Dannenberg:
Thank you very much for the opportunity to speak. As shown in this slide, the title of my presentation
is the Obesity/Inflammation Connection, Implications
for Breast Cancer. Obesity is a risk factor
for the development of a hormone receptor
positive breast cancer in post-menopausal women. It’s also as you’ve just
heard a poor prognostic factor for breast cancer patients
regardless of menopause or hormone-receptor status. There are a variety of pathways
which have been suggested to be important in
explaining the link between obesity and
breast cancer. For example insulin
resistance can increase the risk of breast cancer and
is commonly found in association with obesity. Both high levels of
insulin and elevated levels of free IGF-1 have been
suggested to be causally linked to the pathogenesis
of breast cancer. In the obese, one
sees as you’ve heard from Dr. Giovannucci
increased estrogen synthesis. This reflects both an
increase in adipose mass, adipose tissue being
an excellent source for estrogen synthesis. Additionally several years
ago we reported that levels of aromatase, the
rate-limiting enzyme for estrogen biosynthesis
were increased in association with
elevated BMI. Additionally one finds
a decrease in SHBG, steroid hormone binding
globulin in the obese and consequently there’s an
increase in free estradiol, and it’s the free estradiol
which we believe is important in the pathogenesis
of breast cancer. In the obese one also
finds alter adipokine and cytokine production. From the standpoint
of adipokines, one sees elevated
leptin and reduced levels of adiponectin commonly in the
obese (and) both elevated leptin and reduced levels of
adiponectin have been suggested to play a role in breast cancer. It is also common to have a
low-grade systemic inflammatory syndrome in the obese and macrophage-derived
pro-inflammatory meditators including TNF, IL1 beta and interleukin 6 have all
been suggested to play a role in obesity-related
breast cancer. During the remainder of the
presentation I am going to focus on inflammation which
is associated with many of these pathways that
I’ve just mentioned. In this slide one sees
a cartoon demonstrating that obesity causes
an inflammatory state. It’s been known since
approximately 2003 that obesity is associated
with adipose inflammation. In the obese, one sees
adipocyte hypertrophy. Ultimately, presumably
due to hypoxia or at least partially
due to hypoxia, a large cell will die depicted by this (browner) cell
that I’m pointing to. In the context of an adipocyte
becoming sick or dying, macrophages are recruited
– these are depicted by these star-like cells and
they form a halo or envelope around the dead or
dying adipocyte and ultimately phagocytose
that dead adipocyte and become (foam)
cells in that process. One commonly sees
increases in levels of pro-inflammatory
cytokines in association with crown-like structures. Crown-like structure
simply refers to this crown of macrophages decorating
the dead or dying adipocyte. I will use the term
crown-like structure or CLS during the remainder
of the presentation. Finally I should add
that in the context of obesity one sees increased
lipolysis and elevated levels of free fatty acids, specifically saturated fatty
acids have been reported to activate macrophages
contributing to the pro-inflammatory state. Our next objective
therefore was to determine if crown-like structures of the
breast or CLSB exist in women and correlate with
body mass index. Many of you will probably be
aware that there is a link between chronic inflammation as
Dr. Giovannucci just mentioned and increased risk of a variety
of cancers but at the time that we did this work there was
no known chronic inflammatory state in the human breast. So our initial study design
was to evaluate breast tissue from 30 women who underwent
mastectomy and to carry out routine H&E staining and CD68 immunohistochemistry
looking for crown-like structures. CD68 stains specifically for
macrophages and it’s much easier to see a macrophage
when it’s stained by CD68 then by simple H&E. And this is what we found
are crown-like structures of the breast are in fact common
in overweight and obese women. Here you can see a crown-like
structure based on H&E, dead or dying adipocytes
surrounded by a halo of leukocytes which
prove to be macrophages. And here by CD68 staining you
can see the macrophages (or) crown-like structure
of the breast or CLSB, and when we broke the code it
showed at the bottom you can see that these lesions were much
more common in the overweight and obese than in the normal. To date we’ve evaluated
several hundred samples and we find crown-like
structures in 85% to 90% of breast samples from obese
women, a little bit more than half of overweight
women, and fully a third of normal-size women
and I will say more about the normal-size
women later on during the presentation. In this slide we demonstrate that increasing body
mass index is associated with increased breast
inflammation on the X-axis, you can see body mass index. And on the Y-axis we scored
the severity of inflammation, and you can see overall as BMI
increases so does the severity of breast inflammation. However they’re (outliers). Here you can see three
women who are overweight and did not have
breast inflammation, and here’s a normal-size woman who did have breast
inflammation. So the take-home message is that
overall one sees a relationship between elevated BMI and, or
between BMI and the severity of breast inflammation
but for normal-size women and overweight women you can’t
make a prediction simply looking at body habitus. You can easily be fooled. A normal sized woman could have
occult breast inflammation, an overweight woman
might or might not. So armed with this information
our next question was to determine whether
or not the presence of crown-like structures
had clinical significance. So our goal was to determine
whether breast white adipose tissue inflammation
manifested as CLSBs associated with shortened recurrence
(free) survival in women who develop metastatic
breast cancer. Shown here are the clinical
pathological characteristics in patients with
recurrent breast cancer. So as you can see at the
top there were 127 women in this retrospective study, 52 of the 127 women had
crown-like structures of the breast, 75 of these
women were crown-like structure negative. And let’s focus for
a moment on those who were crown-like
structure positive. You’ll note on average compared to the crown-like structure
negative women, they were older, they were more likely
to have an elevated BMI, crown-like structures
of the breast or white adipose
tissue inflammation of the breast was associated
with the post-menopausal state. And interestingly, features of the metabolic syndrome
including hyperlipidemia, hypertension, type II diabetes
where more common in association with crown-like structures
of the breast. That’s relevant because
metabolic syndrome has been associated with an increased
risk of breast cancer in some studies and
also worse prognosis. So our data shown
here strongly suggest that breast adipose tissue
inflammation associated with features of the
metabolic syndrome. Next we went on to
evaluate a distant recurrence-free survival. Shown (at) the top is a graph
whereby (the) solid line represents CLSB-negative women. Again, crown-like
structures measured at the time of index mastectomy. And the dashed red
line represents those who had white adipose
tissue inflammation or crown-like structures
of the breast at the time of indexed mastectomy, and
you can see quite clearly that the time to recurrence
was earlier in the presence of crown-like structures
of the breast or white adipose
tissue inflammation. Shown below in numerical
form the median time to recurrence was
20 months in those who had white adipose
inflammation at the time of index mastectomy and
it was 26 months in those who had no evidence
of inflammation at the time of mastectomy. (By) univariate analysis this
difference was statically, was significant. When we adjusted
for other factors that could have predisposed to
recurrence, the presence of CLSB or crown-like structures of the breast are white
adipose tissue inflammation in the breast remained
associated with an earlier time
to recurrence. So based on these
observations we conclude that breast white adipose tissue
inflammation is associated with metabolic syndrome. In patients who develop
metastasis, white adipose tissue
inflammation is associated with shortened (distance)
to recurrence-free survival. And so the question becomes
does white adipose tissue inflammation promote
the progression of breast cancer via local
effects, systemic mechanisms such as (hyper-inflammnemia)
or both? So to address this question
we carried out the next study, the goal was to determine
whether white adipose tissue inflammation is associated
with local or systemic effects that can potentially
promote breast cancer. This study involved assessing
CLSB status in 100 women, all comers regardless of BMI. We then carried out RNA-Seq
on non-tumorous breast tissue to evaluate local effects and to evaluate the potential
systemic effects, fasting serum and plasma were used to
perform lipid profiling, to look at hs-CRP
and IL-6 markers of systemic inflammation,
and insulin and glucose under fasting conditions, and
we also did metabolic profiling, small molecule profiling. And here is a description
of these 100 women in this particular study,
roughly of the woman, of the women that were enrolled
had crown-like structures of the breast. Once again they tended
to be a little bit older. Again, the presence
of CLSB was associated with elevated body mass index. They were more likely
to post-menopausal if CLSB-positive
compared to CLSB-negative. And as you can see there
was a significant increase in the incidence of a clinical
diagnosis of dyslipidemia in those who were
CLSB-positive compared to those who were CLSB-negative. Here one sees a heat map
representing the RNA-Seq analysis and breast white
adipose tissue inflammation as defined by the presence
of CLSB is associated with numerous changes
in gene expression. (But) shown at the bottom you
can see the CLSB-positive cases versus the CLSB-negative cases, and this white line
(derides) the two groups. Each column represents a
different human subject, each row represents
a different gene, and these represent the 50
most (up) regulated genes, red being increased,
green being low, and the 50 most decreased green, genes in association
with CLSB positivity. But the take home message is
that this histologic finding, crown-like structures of the
breast, a histologic biomarker of inflammation is associated with significant changes (in)
gene expression in the breast which could contribute to the development and/or
progression of breast cancer. What about systemic effects? In fact breast white adipose
tissue inflammation is associated with biomarkers
of cardiovascular risk. Here we see nearly statistically
significant association between CLSB positivity and elevated levels
of LDL cholesterol. Statistically significant
reduction in HDL cholesterol, the CLSB-positive versus
CLSB-negative women, and elevated levels of
triglycerides in CLSB-positive versus CLSB-negative subjects. Breast white adipose tissue
inflammation is also associated with elevated hs-CRP, IL-6,
fasting insulin and glucose. Panel A, you can see
the hs-CRP levels. In B, the IL-6 levels being
increased in the CLSB-positive versus the CLSB-negative,
and one also sees as already mentioned
elevated levels of free – of fasting insulin,
fasting glucose in the CLSB-positive cases. Now what I’m not showing in the
interest of time is the fact that breast adipose
inflammation is a sentinel for what is a more diffuse
inflammatory process involving other adipose depots,
and once you know that, it makes good sense that there
might be a blood signature in association with a systemic
low-grade inflammatory disorder. Here are the results of our mass
spectrometry based (metabolic) profiling study. Again a heat map, we
were able to demonstrate that breast white adipose tissue
inflammation is associated with altered levels of more
than 50 plasma metabolites. Again, red represents
high levels and green represents low levels, each column again represents
a different human subject, and each row in this case
represents a different small molecule. And if you focus your
attention on the two groups on the right you can see the
overweight and obese, OW and OB, were either CLSB-negative
or CLSB-positive. And I think you can see
very clearly a large number of metabolites were
increased in association with white adipose
tissue inflammation and a smaller number shown at the top decreased
(an) association with breast white adipose
tissue inflammation. Now this is perhaps the
most important slide of the presentation. We broke the code
and here you see that breast white adipose tissue
inflammation occurs not just in the obese, and in this
particular study it was virtually all of the obese,
but also in roughly a third of the normal-sized women. So if that implies that a
third of women with normal BMI who are) visiting their
physicians have a occult breast inflammation, (and a)
significant medical dilemma to this day relates to
why do normal-sized women who are not BRCA1 or BRCA2
mutant carriers develop breast cancer? Now could occult breast
inflammation be causally linked? So we went on and
carried out RNA-Seq on these normal-sized women
and here one sees the results. The take-home message is that breast white adipose tissue
inflammation is associated with numerous changes
in the transcriptome in normal BMI women and at
the bottom you can see groups that say yes. Yes refers to being
CLS-positive, no, CLS-negative. So the take-home message
and the key point really is that occult breast inflammation
in normal BMI women, normal BMI, normal-sized women is associated
with changes in gene expression, local changes in the breast. Now one of the changes
that was most striking and perhaps most meaningful from my perspective was
a change in aromatase. Now aromatase is the
rate-limiting enzyme for estrogen biosynthesis. There are several FDA-approved
aromatase inhibitors. Aromatase inhibitors are not
only useful for the treatment of hormone-receptor
positive breast cancer but they been shown in very,
very large trials to lead to about a 50% reduction
in the risk of hormone-receptor
positive breast cancer in high-risk women. So what did we find in
our normal-size women? We found that breast white
adipose tissue inflammation is associated with level,
elevated levels of aromatase in normal
BMI women. We’ve shown here are the
CLSB-positive normal-size women versus the CLSB-negative
normal-size women. And we found about a
one-fold increase in the level of aromatase in those
normal-size women with occult breast inflammation. It is intuitively
reasonable to anticipate that if a women is
walking around long term with elevated levels
of aromatase that this will increase
the risk of breast cancer. Of course that remains
to be proven but certainly it is
intuitively reasonable. We went on and were
able to demonstrate that breast white adipose
tissue inflammation in normal BMI women
is associated with insulin resistance. But here you’ll see (the)
CLSB-positive normal-size women versus the CLSB-negative
normal-size women, and you can see a nearly
statistically significant increase in insulin, statistically significant
increase in fasting glucose. (HOMA2-IR) is way a
calculating insulin resistance. Though there was relative
insulin resistance in the normal-sized women who
had occult breast inflammation. Now why is this important? Well, as mentioned earlier on hyperinsulinemia has
been shown previously if one considers all
comers to be associated with increased risk of breast
cancer, but in 2015 in work from a different group, not
from our group, it was shown that elevated insulin
levels are associated with increased breast cancer
risk in normal-weight women. (So) in this case metabolic, unhealth versus metabolic health
is defined by insulin levels and one sees about a doubling
in the risk of breast cancer in those who are defined
as metabolically unhealthy because they were
(hyperinsulinemic). So I would submit to you
based on our recent discovery that occult breast
inflammation is associated with hyperinsulinemia that
adipose inflammation is likely to contribute to elevated levels
of insulin and increased risk of breast cancer even
among normal-size women. So based on these findings we
conclude white adipose tissue inflammation is associated
with numerous changes in gene expression
in the breast. White adipose tissue
inflammation is associated with systemic changes that
occur in the metabolic syndrome. White adipose tissue and its
associated pathophysiology (per in) a meaningful subset
of normal-sized women, white adipose tissue
inflammation is a potentially targetable process linking
obesity to breast cancer. So in the last few minutes I’d like to briefly discuss
our (nation) efforts to reverse this process. It is simply not good enough to
identify a new disease process, obviously we need to be able
to diagnose it and we need to be able to treat it. So from the standpoint
of potential strategies to reverse this process we are
considering lifestyle changes such as exercise,
changes in diet. Will saturated fat
matter for example, or might pharmacologic
interventions be developed to disrupt the obesity
inflammation access thereby reduce the risk of breast
cancer or improve prognosis? So these are data that we have
generated using mouse models and let me walk you
through these data. It represents one
pre-clinical strategy which may in fact translate
to humans, to women, but this remains to be proven. We studied caloric restriction
and we were able to demonstrate that caloric restriction
attenuates high-fat diet induced weight gain. So in this particular mouse
experiment the green line represents lean mice,
low-fat ovary intact mice. The other groups of
mice were ovariectomized to mimic the post-menopausal
state. Remember early on I said
obesity is a risk factor for breast cancer in the
post-menopausal state. So to mimic that we
ovariectomized mice and then put them
on a high-fat diet. We fed the high fat to induce
obesity (and) an inflammatory state and then we randomized
the mice to three groups. Represented by the
blue line those that could continue
eating ad lib and as you see they
gained weight. Or we subjected two
additional groups of mice to 30% caloric restriction
for either seven or 14 weeks. Same bad high-fat diet but
30% calorie restriction, seven or 14 weeks which you can
see did not induce weight loss but protected against
weight gain. And this is what we found. Here you see that caloric
restriction reverses obesity-induced mammary
gland inflammation. (The) Panel A represents an H&E
stain of a crown-like structure in the mouse mammary gland, and on Panel B we quantified the
number of crown-like structures in the mammary glands
in the different groups. And you can see that
in the lean, low-fat ovary-intact mice there
was no detectable inflammation but by ovariectomizing a mouse
and feeding it a high-fat diet to cause substantial weight
gain, we induced inflammation in the mouse mammary gland. If we subjected the mouse
to seven or 14 weeks of caloric restriction, 30%
caloric restriction that is, we dramatically reversed
occult inflammation in the mouse mammary gland. I can also tell you because it’s
encouraging, we’ve gone as low as 10% calorie restriction and also seen substantial
benefit in the mouse. Here we went on to carry
out molecular studies, we like to compliment histologic
analyzes with molecular studies. Here we looked NF-kB binding
activity in the mammary gland. NF-kB is a transcription factor which is implicated (it
in) both pathogenesis and of inflammation, cancer and
inflammation-related cancer. And here you can see
that in the obese mice, the high-fat ovariectomized
mice, one sees a marked increase in NF-kB binding activity
compared to the lean mice, and you can see that
either 7 or 14 weeks of calorie restriction
led to a marked reduction in NF-kB binding
activity consistent with the histologic findings
which I shared with you. And finally I think we need to
be open minded when we think about trying to translate
these findings to humans. These are the interventions
we are considering. Weight loss, yes. We’re very interested in
hormone-replacement therapy. Exercise needs (to) evaluated. We are beginning
pre-clinical studies to look at potential medications
that might reverse this, and of course combination
regimes maybe most prudent, and all of this needs
to be personalized and tailored to the individual. And so it could be that in
some individuals a little bit of weight loss and medication
may prove to be important where in somebody else weight
loss alone may be practical. On that note, I thank you for
your attention and I am here to address any questions. Thank you. (Gabriela Riscuta): Thank
you so much, Dr. Dannenberg, for a great presentation. Indeed we have a few
questions for you and I’m reading the
first question. (If was) any study transacted in
women which BMI equal or lower than 25 to evaluate their
visceral adiposity and to see if there is any correlation
between visceral adiposity and (the) inflammatory status? Andrew Dannenberg:
That’s a great question… (Gabriela Riscuta):
(Unintelligible). Andrew Dannenberg:
The answer is no. I can say that with confidence
because we were the first to start evaluating
breast inflammation but I can also tell you… Woman: (Unintelligible)
right now. Andrew Dannenberg: But
I can also tell you that breast inflammation
is likely to correlate with altered visceral adiposity. We have new data to show that
the adipocyte size is larger in those who have a
normal BMI who are inflamed versus those who
are not inflamed. And later this month we will in
fact initiate a study to look at body composition versus
breast inflammation including but not limited to
normal-size women. (Gabriela Riscuta): Okay… Woman: (Unintelligible). (Gabriela Riscuta): Thank you. That’s a – yes. So it appears that it
is a correlation maybe, and another question we have
is has there been any research on the association of
decreased physical activity in the normal BMI women
that would be related to the increased
inflammatory status due to the more sedentary behavior? Andrew Dannenberg:
Another great question. We’ve just conducted our
first retrospective study to evaluate physical activity and the data haven’t
been fully analyzed, the study is too small. But we (too a) fully agree
that it will be very important to evaluate the role of physical
activity, exercise as it relates to adipose inflammation not only
in the normal-size individual but also in the overweight
and obese. So (it) needs to be done, hasn’t
been done adequately to date. (Gabriela Riscuta): Okay. Thank you, Dr. Dannenberg. Only one more question
because of the time constraint. So what would you think
about measuring insulin level as a possible factor in evaluating the
breast cancer risk? (So in), basically in
women having BMI equal or lower than 25? Andrew Dannenberg: So that is… (Gabriela Riscuta):
(Unintelligible). Andrew Dannenberg: Also
an excellent question. One of the – I think (insulin)
will provide some insight but not adequate insight. In other words although
we find a relationship between hyperinsulinemia and inflammation is the
normal-sized woman there is plenty of overlap between the
inflamed and the uninflamed. Also single-point
measurements can have their own (Unintelligible). So we’re more interested in
the possibility that a series of blood biomarkers may
provide, may prove useful for risk assessment
than insulin alone. I think insulin alone to
shorten it, to summarize will be of interest but not
adequate as a risk profiler. (Gabriela Riscuta): (Okay). Thank you so much,
Dr. Dannenberg. Due to the time constrain we
have to move to our next speaker but of course we’re going to
provide as I said at the end of the webinar the e-mail
address for the speakers to send additional question. So now we – I’m going to introduce our third
speaker, Dr. Berger. Dr. Berger is the
Hanna-Payne Professor of Experimental Medicine,
Professor of Medicine, Biochemistry, Genetics
and Oncology, and Director of the Center for
Science, Health and Society at Case Western Reserve
University. He is also the Director of the Case Comprehensive Cancer
Center Program on (Aging) Cancer at (the) Case Western Reserve
University School of Medicine. Dr. Berger will present on
the topic obesity and cancer, gaps in knowledge and future
directions of research. When he will finish we will have
time for two more questions. Dr. Berger? Nathan Berger: Thank
you and good afternoon. When we think about (the)
approaches to control obesity and its impact on cancer we
think about in two categories. On the top is obesity control and down below is
what do we have to do to disrupt the obesity
cancer linkage. In terms of obesity
control, the primary goal is to prevent obesity
and that’s mainly through lifestyle activities, either physical activity
and diet. And then the secondary
approach is weight reduction and we have pharmacological
options, and three of the drugs that are recently proved
effective are listed here, Contrave and Belviq and Qsymia. When I say effective we need to
remember that they’re associated with about 5% to 10% weight
loss and it’s really difficult to maintain that weight loss. Another approach is
bariatric surgery and that’s already been shown to
prevent some primary incidence of tumors but it’s
interesting that it occurs, the cancer prevention
occurs primarily in women and not at all in men. Some of the obstacles to
obesity control are listed here. So one is the fact that we
all seem to be programed more or less, genetically
programmed for energy storage, and the programming, the differential programming
has been associated with polymorphisms in (fox o)
with mutations or polymorphisms in uncoupling proteins that reduce energy loss
and heat generation. We’re also exposed
to an abundance of high-energy dense foods
and most of them taste good. There’s poor adherence
to caloric restriction. Nobody wants to do it. We have inadequate sleep
nowadays with disruption of our diurnal rhythm and
there’s a clear relation of obesity and increased
cancer with shift workers. We have much more
sedentary lifestyles and there’s been a proliferation
of energy-saving devices and increase in screen-based
activities and simulated-recreation
activities. The (built) environment
impedes our physical activity. We don’t have to walk to
the store, it’s even hard to find sidewalks to
walk on in many suburbs. Exercise equipment and
exercise programs may be costly. I mentioned the fact that
there are some pharmacological interventions but they
are small and probably not of long duration and then
there’s the high cost and the consequences
of bariatric surgery with the best estimates now
of bariatric surgery costing about $25,000 to $30,000 pre-op and that doesn’t
include the follow-up. I think it’s important to
consider some of the gaps to think about (on) some of the other (possibly)
related mechanisms are by which you’ll be
obesity promotes cancer and that includes
(non)-increased levels of bioavailability of growth
factors like insulin and IGF-1, increased sex steroid
hormones like estrogen. And the recent observation in
elevated cholesterol levels in the right genotype
can be converted to 27-hydroxycholesterol which in itself stimulates
the estrogen receptor. We have (altered) adipokines
like increased leptin and decreased adiponectin
and a number of others which I’ll talk about, and
as Dr. Dannenberg pointed out the low-grade chronic
inflammation (and) oxidative stress which is associated
with the metabolic syndrome and has been given the
name of meta-inflammation. We also have altered
microbiomes in which changes in the intestinal
microflora associated with obesity especially
increased (vermicides) and decreased (bacteria
oddities) could potentially increase the availability
of toxins and the possibly that (alter) microbiome
and other aspects of obesity may affect
epigenetics. And I think epigenetics with
obesity causing methylation of some tumor-suppressor
genes with obesity, and I should have
said demethylation, and increased methylation
with exercise and (poll) weighted NIHs
recently shown (chromatid and) rearrangements in obesity and
simulate some of the changes that occur in colon cancer. We have a number of adipokines, these are peptides (in our)
hormones that are secreted by or from adipose sites. Some of these are secreted from many other tissues
(but) everything – well it started first with
the first adipokine identified in 1994 was leptin which
is the satiety hormone. It suppresses appetite, it
also stimulates tumor cells and especially stem cells. And not only does
it stimulate growth but it also stimulates
proliferation in cells that have the appropriate
leptin receptors. I’m not going to go through
each of the others but each one of these has been shown to have
effects both in weigh regulation and regulation of diabetes but
each of them has been shown to have an impact on one
or many types of cancer. When we initially
started thinking about this situation
the concept was that excess weight
caused adiposity which led to free fatty, increases
in free fatty acid, changes in some adipokine’s
insulin resistance which lead to the secretion
of (more insulin). The insulin had several effects
including changing IGF binding proteins which led to more
IGF-1 synthesis and the fact that both insulin could react
with an insulin receptor and IGF-1 could react
with a receptor and that would stimulate target
cells that decrease apoptosis, increased cell proliferation
and it caused tumor development. That was the simple version. What (was going on) more
recently, we understand that all these other
factors can be interactive, stimulate each other and cause
all the different components associated with cancer cell
promotion and progression. And I’ve shown you here that
obesity stimulates these effects in adipose tissues,
stimulates the aromatase as Dr. Dannenberg discussed,
stimulates estradiol which can cause all these
effects but you can see that other factors like PAI-1 and (digest) can also
interact with these pathways. And so there are a number of
routes that obesity can take to stimulate cancer
cell proliferation. I also want to point out it, not does obesity cause
all these effects but many of them are stimulated
by dietary fat. And (now) what I showed you
before was on the outside of the cell, now I’m
showing you here what happens at the cell membrane. So each of those factors have,
has a cell membrane receptor and it can stimulate all
these different pathways which interact and all of
which can lead to cell growth and tumor promotion
and progression. And it’s quite clear that if you
block one there’s a good chance that one of the other pathways, or that one of the other
receptors may activate another pathway that will stimulate
cell growth and tumor formation. And I mentioned just before that dietary fat can
cause obesity leading to inflammation (in) a
number of these other factors but in addition to the
dietary fat causing obesity, a direct effect of dietary fat
mostly (with) saturated fats will also lead to inflammation. Whereas a number of
other dietary fats, the so called healthy fats like
Oleic acid, (Unintelligible), the Omega-3 polyunsaturated
fatty acids will block the inflammation and this has
been amply demonstrated both at epidemiological studies and
in some animal models (do), either stimulate cancer
promotion or in fact to increase apoptosis and
decrease cancer promotion. (Unintelligible) can
you advance the slide? Okay. So some of
the other factors that affect the energy
balance in cancer are myokines, these are muscle-secreted
polypeptides, and a number of these either cause
inflammation in the muscles, reduce inflammation, may
cause, inhibit muscle growth. Irisin has been shown
in white adipocytes to induce the uncoupling and
increase thermogenesis (spark) which is a secreted protein
as (it is rich in) cysteine and otherwise known as
osteonectin has been shown to reduce growth of colon
cancer cells in tissue culture. And I show you here a
diagram which indicates some of the many myokines that are
secreted in response to exercise with particularly emphasis
on this (spark) protein and another calprotectin
which has been shown to inhibit colon carcinogenesis. But a number of these others which have anti-inflammatory
effects and others which may either lead to
or (prevent) muscle wasting in terms of (kinkectisia). In addition to the
adipokines and the myokines, we also have a host of
gastrointestinal peptides all of which have been shown
to be active in some degree of modulating energy balance,
appetite control, glucose, insulin, homeostasis,
obesity, and growth control. Again, I won’t go through
each of these but your, each of them has been shown
in one system or another to be associated with increased
or with some sort of malignancy. You’re probably most familiar
with gastrin which is, stimulates gastric
acid secretion and it’s commonly elevated
in multiple aspects of multiple endocrine
neoplasia and leads to duodenal and gastric ulcers
and malignancies. I’ve listed here some of
the basic gaps in knowledge by which obesity
impacts cancers. So one of the key questions is
whether obesity is actually a carcinogen or a promotor
of tumor progression. If it’s a carcinogen it
means we have to deal with it in an entirely different way than if we think it’s a
promotor, and I can tell you that at least in animal models, 99.9% of all animal models
obesity will not cause cancer unless there’s a
preliminary mutation present. And so that leads to the question (are)
cancer-driver genes the same or different lean and obese
patients and depending on the answer to that question
there’s some strong implications about how you would treat cancer
in an obese or a lean person. The question of does
obesity interact with microbiomes
(to) drive cancer? The question of what
is (the) nature of the adipocyte interaction with the microenvironment
and in tumor cells? And can the normal
tumor-promoting effects of some of the peptide hormones
be separated for therapeutic advantage? So for example the IR – the
B-insulin receptor is decreased in breast cancer
relative to normal tissue, the A-insulin receptor which is
also the fetal form is increased in tumors, and can we
design insulin molecules that would take advantage
of this difference? These are some of the gaps
at the translational level. I’ll simply say when does
obesity impact cancer and we have all these
possibilities. Again, are the mechanisms
the same or different? Should interventions be
the same or different at different time points? And I think we really
need to decide for any experimental
system what are the goals of our intervention? Are we trying to get
primary prevention? Do we want to improve compliance
(of) therapeutic efficiency? There are tremendous
number of studies out there on treating patients who
are already have cancer and the goal is to
improve the quality of life but are we interested
in reducing recurrence and enhancing survival? I mean I think the answer
is clearly we are interested in these approaches
but these are really, really long (experiments). (And) so here’s a summary
of some of the obstacles to disrupting the
obesity/cancer linkage. One is the multiplicity of obesity-driven extracellular
hormones that I showed you. The other is the multiplicity of obesity-driven
inflammatory factors. The third is the fact that the
receptors can hybridize (cross stalk) and stimulate
growth pathways. The fourth is the
multiplicity and (cross stalk) of the intracellular pathways. The fifth plane is
the multiplicity of cellular targets,
are we really – in any intervention we need
to know what we’re targeting, the cancer cells, the
cancer stem cells, the tumor microenvironment, and
also at this point (the real), the lack of clarity on
timing (in) targets? Are we looking at
mutagenesis promotion, progression or recurrence? So here’s my suggestion and
I’ll make the disclaimer that this is my suggestion, doesn’t reflect anybody
else’s (be able on how) you develop
an intervention to disrupt obesity
cancer linkage. First you need to select a
process and a time period. So you might want to
target epigenetics and if you do you might
want to look at epigenetics in the prenatal time period
or the adolescent period. You might want to look at
cancer promotion, you may want to target the metabolic
syndrome and meta-inflammation. Then you need to identify
an intervention as Dr. – you might want to
prevent maternal obesity. If you’re looking at
epigenetics, you might want to change the dietary component. You might want, need to increase
physical activity and we need to identify a biomarker. We do not have a good biomarker. We need the equivalent of a
hemoglobin A1c which is (used) – nobody would treat diabetes
without following hemoglobin A1c and we need a marker
like that for obesity. Also nobody would treat diabetes
without multiple approaches and so we probably need multiple
approaches to, (on) this. And then you need to
identify an end point which I have listed
several choices here, and this is just an example
(on) say if you wanted to disrupt the obesity/cancer
linkage in women treated for breast cancer, again, the first thing you do
is select a process. Let’s say we pick time
period, adults being treated for breast cancer and
cancer promotion, metabolism and meta-inflammation, and then
you identify the intervention. And again I think you need
to make it comprehensive. So it probably requires
diet change, pharmacologic intervention
with weight-loss agents, anti-inflammatory agents and
increasing physical activity. Again, as I said
before we really need to identify a biomarker and
the question is should it be, is there some way we can
get a local biomarker or is there still a
systemic biomarker out there? And then what’s the
(ideal pinpoint)? Do we prevent recurrence,
increase survival? And I think on the one
hand the ultimate goal is to prevent cancer but if
we’re treating obese patient with cancer, the most
important thing that we want to do is prevent recurrence
and increase (the) survival. (And) then the fifth challenge
is to figure out how do you, you know, it’s such a long
process how do you develop a randomized control study, and
I think with that I’ll stop and thank you for
staying with us and I’ll be happy
to answer questions. Hello? (Gabriela Riscuta):
Thank you so much, Dr. Berger, for a great presentation. We have received a number
of questions for you and I’ll read the
first question. Can you address dietary
fat as a cause of obesity? Are you referring to a
hyper-caloric diet or any diet with a high percentage
of dietary fat? Nathan Berger: So I think
it’s all of the above. I mean I think, you know, people
talk about the Western diet versus the Mediterranean
diet and depending on how rigidly you adhere to
the Mediterranean diet you, you’re presumably going
to have less weight. But nonetheless we know, you
know, we’re aware of plenty of pictures at least of people who are enjoying the
Mediterranean diet and are just as obese as people
on the Western diet. But nonetheless a diet, you
know, high in fish oils and nuts and some of the other components
of the Mediterranean diet seem to be less prone to some
of the problems associated with the high saturated
fat diets that we have in the
Western diet. (Gabriela Risuta):
(Oh) thank you. And the next question is what
anti-inflammatory would you recommend for including
in a comprehensive, randomized control trial
in (this) population? Nathan Berger: Yes. So that’s an outstanding
question and, you know, that’s an important
question that really needs it to be answered and
I mean I think that the best recommendation
now would have to be based on the fact that we know
that there’s a lot of, (from one) of the major problems with stimulating
cancer is involved with prostaglandin metabolism. And it interfering with some of
the prostaglandin’s synthesis. It has shown some effect. So at this moment I think (that)
maybe we could recommend is or that should be tried for starters is aspirin,
non-steroidal. But I think that we need
to do a lot of work. (That’s) one of the gaps in
knowledge so to speak and one of the areas where a lot
of work needs to be done. (Gabriela Riscuta): And
the last question is if a foundation will
fund a study of your choice what would
be the topic of that study that you would choose? Nathan Berger: If a
foundation would fund the topic of my choice? (Gabriela Riscuta): Yes. What the topic would be. Nathan Berger: Well,
so I think two things. I think we, you know, if (it
was), what we really (need) – what’s most important is to do
a clinical trial and (equate), and we are doing
several clinical trials and it’s interesting. We’re doing trials in uterine
cancer, we’re doing trials in breast cancer, we’re doing
(trial), clinical trials in prostate cancer, and
quite frankly the one where we get the
most cooperation is for women with breast cancer. And so based on that theory
it would be to do sort of a more definitive approach
to that and/or for lots of other reasons (say
to) colon cancer. (Gabriela Riscuta): Okay. Thank you so much, Dr. Berger,
and thank you, Dr. Giovannucci and Dr. Dannenberg, for your
insightful presentation. Thank you, our audience,
for participating today. I hope you found this
presentation both inspiring and practical and you will use
the information towards your future work. Indeed obesity is an important
risk factor for cancer and we learn more about
some common pathway, some gap in knowledge,
the mechanisms and we encourage researchers
to continue their work and help to answer (the) remaining
question. (From the Nutritional) Science
Research Group in the Division of Cancer Prevention is eager
to assist with your research and to learn more about (our)
Nutritional Science Research Group, please visit
us on the Website that you see on the slide. Also if you have future
questions please contact us at [email protected]
and also for information regarding
clinical trials please visit Upon completion of this Webinar,
you will receive an e-mail with information about obtaining
continuing education credit. Thank you, all, for
joining us today. Good bye. Coordinator: Thank you for joining today’s
conference call. The call has now concluded,
you may disconnect. Thank you for your

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