Age against the Machine: how aging drives tumor progression

November 09, 2021

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Yale Cancer Center Grand Rounds/Skin Cancer SPORE | November 9, 2021

Presented by: Dr. Ashani Weeraratna

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00:00Actually, we're Ratna.
00:02Who is an outstanding scientist
00:04and a dear friend, and I'll give
00:08a little background about ashis.
00:12Current many titles and are where where
00:15she developed from as a scientist.
00:18So Ashley is the EV McCollum chair of
00:20Biochemistry and molecular biology at
00:22John Hopkins School of Public Health.
00:24She's also a Bloomberg
00:26Distinguished Professor Co,
00:28leader of the program and cancer
00:30invasion and metastasis at the
00:33Sidney Kimmel Cancer Center.
00:35And I had interacted also a lot
00:37with Ashley before joining Hopkins,
00:39where she was a named professor
00:41and a program.
00:42Leader at the Wistar
00:44Institute in Philadelphia, AH.
00:46She has a very international background,
00:48having been born in Sri Lanka
00:50and grown up in South Africa.
00:51I think a brother who lives in Scotland.
00:53Now she's just a very cool person
00:55with a great great background on
00:57great science and you know one of the
00:59things that I would really emphasize
01:02about Ashley is that there's been
01:04a real emphasis and appropriate
01:07emphasis on supporting junior faculty.
01:11A female faculty and fat and and scientists
01:17of color over the last few years.
01:21But I can say that I can think of
01:23pretty much no one who is more of an
01:25advocate for all of those areas over
01:27a decade ago already and has been
01:29tireless in her efforts and promoting that.
01:32And it's really great to see the
01:34rest of the world that slowly
01:35catching up on those fronts.
01:37And you know,
01:39it's a real great pleasure to hear.
01:41And I I know a fair amount about the science.
01:43She's going to talk about,
01:44but it's a really appropriate area,
01:46especially at Yale,
01:47where we're thinking about having
01:49a new aging center based in
01:52the pathology department,
01:53and I think she's going to be talking
01:56about age against the machine,
01:58how the aging microenvironment covers
02:00tumor progression and response to therapy.
02:03I was thinking of playing some
02:04Rage Against the machine in the
02:06background during the introduction,
02:08but I thought that's probably
02:09go horribly wrong,
02:10so you'll just have to imagine that and.
02:14Actually,
02:14it's a real pleasure having you
02:16be a yellow sport and skin cancer,
02:18Cancer Center ground round speaker.
02:20Thank
02:21you so much Marcus for that
02:23lovely and warm introduction.
02:24And yeah, the title appeals to a very
02:28specific demographic of people think so.
02:30Thank you so much.
02:32I'm delighted to be giving this talk,
02:35although I really do wish it was in
02:37person and I will be talking to you all.
02:40As Marcus said about our work in the aging
02:42microenvironment and how that governs.
02:44Response to therapy.
02:45So we've been so interested in aging
02:48as a driver of tumor progression
02:50because we know that it's one of the
02:53most significant prognostic factors
02:54for the development of cancers.
02:57So of all hundred people diagnosed with
03:00cancer, 89 of them will be age 50 or over.
03:03And of those that are diagnosed with
03:05cancer and die from this disease again,
03:07the largest percentage of them
03:09is over the age of 50,
03:11and so we've been trying
03:12to understand why that is.
03:14And why that happens?
03:15Obviously there are a lot of
03:17systemic factors that Dr.
03:19Tumor progression,
03:20but we've been super interested
03:22in what is happening in the local
03:25microenvironment specifically of Melanoma.
03:26But as I'll tell you later,
03:28we are expanding into other cancers,
03:31such as pancreatic cancer as well.
03:33So what we have seen in our studies
03:36is that there are significant changes
03:38that occur largely due to fibroblasts,
03:41and I'll tell you a bit more about
03:43that in a second and these changes.
03:44Can affect not only the way tumor cells grow,
03:48but the way endothelial cells grow
03:50into the tumor as well as a biophysical
03:52matrices around these tumors,
03:54allowing them to metastasize and
03:57invade more effectively with age.
04:00So a few years ago what we did,
04:02and this was a lot,
04:05this was a very collaborative piece of work,
04:08and Marcus was on this paper as well.
04:11The cell lines and resources that he's
04:13developed up and absolutely critical.
04:15Press and continue to be to this day,
04:17so we're very grateful for those and
04:20the reason that we looked at the
04:22skin was that we were very interested
04:24in the fibroblast themselves.
04:25Because fiberglass in the skin also in
04:28work out of Yale from Valentina Greco
04:31slab tend to age with the individual
04:34rather than undergo a lot of turnover,
04:37and we were very curious to know as
04:39the age what were the differences they
04:41were sick reading and how would they
04:43change in their physical environment.
04:45Because the Melanoma cell spends
04:47much of his life right here at the
04:49intersection of the epidermis and dermis,
04:51becoming invasive.
04:52So in order to recapitulate that work,
04:55what we did was to take skin
04:57fibroblasts from the upper inner arm.
04:59So intermittent sun exposure of individuals,
05:03healthy non Melanoma bearing
05:06individuals in their mid 20s to mid
05:0930s and then in there in the in the
05:13age where sort of Melanoma starts
05:15the incidence of Melanoma starts
05:17to skyrocket which is 55 to 65.
05:19We use those fibroblasts
05:21to create artificial skin.
05:23Which is a technique taught to
05:25us by our friend
05:26Meinhardt Harlan and in doing that we were
05:30able to see that when we mate reconstructs
05:34with fibroblasts from young individuals
05:36versus fiberglass from aged individuals,
05:39those Melanoma cells would invade
05:40far more rapidly in the fibroblasts
05:43in the skin reconstructs made with
05:45fiberglass from aged individuals now.
05:49You know the only difference between
05:51these these sets of skin reconstructs
05:53is the age of the fibroblasts.
05:55Everything else is the same,
05:57so we wanted to know if we
05:59could recapitulate that in vivo.
06:01And as I mentioned,
06:03Marcus along with Martin McMahon has made
06:06the beer FP10 mouse model of Melanoma Marcus,
06:09then backcrossed ease to see 57 black,
06:11six mice,
06:12and as I'm sure you all know,
06:13created a series of cell lines.
06:16The most of the experiments I'm
06:17going to show you are from the young.
06:191.7 so line which we have taken
06:22and then injected into either young
06:24mice of 6 to 8 weeks of age or age.
06:27Mice of 12 to 18 months of age,
06:29depending on the experiments we're doing.
06:32And what we saw was that actually
06:34in the young mice to tumors grow
06:35much faster and they grow much
06:37more slowly in the age mice.
06:39However,
06:39they metastasized to the lung far
06:42more effectively in the age mice
06:44than they do in the young mice,
06:46and so we wanted to better understand that,
06:49and Mitchell Fain,
06:50who is a postdoctoral fellow in my lab
06:52of very talented postdoc Buffalo in my lab,
06:55decided to do an experiment where
06:57he ceded the young 1.7 cells
07:00intradermally in the skin of the mice.
07:02And then he allowed them to metastasize
07:05overtime to the lungs of the mice
07:07and at three weeks he took the lungs
07:09of both the young and the age mice,
07:11and he looked for his M cherry labeled
07:14Melanoma cells and what he found was
07:16that in both the young and aged mice,
07:18there were these sort of single or maybe
07:21double cell colonies all over the lung.
07:23If he waited just a couple more
07:25weeks and he did this at five weeks,
07:28what he saw is that in the Yung Lung,
07:30the colonies remained as he single cells.
07:33They're much smaller qualities,
07:34whereas in the age long they had
07:36started to grow up quite dramatically,
07:38and we could quantitate this over a
07:40series of mice which wanted to know
07:43what kind of role the fiberglass
07:44played and all of this,
07:46and so he took fibroblasts from the
07:48Yung lung and from the age long,
07:51and then he ceded GFP tagged Melanoma
07:54cells in a 3D sandwich.
07:56With these fibroblasts and what he saw
07:59is that when he incubated Melanoma
08:01cells with age long fiberglass.
08:04They would proliferate far more
08:05rapidly than when he ceded them
08:08with Yung lung fibroblasts.
08:10He then looked compared the growth
08:12rates of the Melanoma cells with
08:15lung fibroblast to that of the skin.
08:17Sorry,
08:18and he found that the age skin
08:20fiberglass actually suppressed the
08:22growth of these Melanoma cells,
08:24which we had seen before and which I
08:26just showed you in the mouse model.
08:27Whereas the young skin fibroblast
08:29promoted it and so we saw a distinct
08:32difference between the way the fiberglass.
08:34And these two different tissues behaved,
08:36which was sort of a very striking
08:40and eye opening thing for us.
08:43So Mitch then did proteomics on both the
08:46skin fibroblasts and the lung fibroblasts,
08:48comparing the age to the young
08:50in both cases and what he found
08:52was something quite interesting.
08:54He found that in aging skin there was
08:57a signature of fiberglass promoting a
08:59non canonical went signaling phenotype
09:02which included jeans like SFRP 2 serpin
09:07E2DK1158RR2 in the age long.
09:09However, he saw a signature that
09:11showed there was a promotion
09:12of Canonical went signaling.
09:14And what he would see is sometimes the
09:17same family members SFRP one and SFRP
09:192 which we know to play very different
09:22roles and one signaling were the ones
09:25that were differentially expressed.
09:26And so I'll tell you a little
09:27bit more about these two guys.
09:29So we had shown a few years ago
09:32that age fiberglass decreed SFRP 2.
09:34And when they do that,
09:36they shut off beta catenin signaling.
09:38So SFRP 2 inhibits Canonical went signaling.
09:41And and in doing so decreases the
09:45ability of a Melanoma cell to react
09:48to the reactive oxygen species
09:50in the micro environment because
09:52it disables this basic vision and
09:55a nucleus repair gene AP one.
09:57Sorry for the inappropriate
09:59domination animation over here,
10:01we'll get to in a second, however, So what?
10:04That did was to decrease the
10:06proliferation of the Melanoma cells,
10:08but make them more invasive.
10:10However,
10:10when Mitch looks at SFRP one and he treats
10:13Melanoma cells with recombinant SFRP one,
10:16they increase their proliferation
10:18and they actually shut off.
10:20Noncanonical went signaling in what
10:24Mitch then did was to do an experiment
10:27in Vivo where he took age mice.
10:30He allowed three weeks for the
10:31initial dissemination of the tumor.
10:33As I showed you previously.
10:35And then once the tumor cells
10:37had seated in the lungs,
10:38he treated the mice with
10:42antibodies against SFRP one.
10:44So in the IgG control you see
10:46this outburst of metastases,
10:48as I showed you earlier.
10:50But in the mice that were treated
10:52with anti SFRP one you see that
10:54the cells that have seated in the
10:56lungs remain there as single cells
10:58which were super interesting to us.
11:01So the reason this was so interesting is
11:03we've been working for a while on this idea.
11:06Of what we call phenotype switching
11:08where we have canonical wind
11:10signaling that's driven by beta,
11:12catenin and Noncanonical went signaling,
11:15driven by went such as 158 and we
11:18had always associated the wind 5A
11:21phenotype with metastasis and and the
11:24beta catenin phenotype with proliferation.
11:27But what I'm going to tell you shows
11:29that we were not as sophisticated in
11:31our thinking as we should have been,
11:33and instead the roles are much more
11:36interchangeable. And much more complex.
11:38So important to note that when
11:405/8 promotes an invasive but slow
11:42cycling phenotype and that led us
11:45to wonder whether these changes we
11:47were seeing in the young versus
11:49aged lung colonies have any.
11:51I'm sorry I don't know what's
11:53happening to my animation.
11:54Had any relation to dormancy and so we
11:56turned to our good friend Julio Gerike.
11:59So who's now?
12:00I just started an Institute of
12:03dormancy at the Albert Einstein
12:05College of Medicine in New York.
12:07And he is a world leader in
12:10understanding tumor dormancy,
12:11and he has these signatures of door machines.
12:14So what Mitch did was to look
12:17at the expression
12:18of these genes and win 5A high
12:21versus 15 LO cells and what he sees
12:23is that when 5A high cells carry
12:26very strong markers of dormancy.
12:28Whereas went five a low cells carry
12:31very high markers of proliferative
12:33cells and so much is question was does
12:36the aging microenvironment drive a
12:38switch from a win 5A high to win 58 low
12:42phenotype and in doing so Dr increased
12:46proliferation in Melanoma cells?
12:48So to answer this, UM,
12:50the first thing which did was to
12:52take Melanoma cells and expose them
12:54to the condition media of young.
12:55An age long fiberglass and what
12:57he sees is that indeed,
12:59in the same Melanoma cells
13:01exposed to age condition media.
13:03These are just three separate.
13:05These are the same Melanoma cells,
13:07three separate donor, fiberglass media.
13:11What Michelle was that the the markers
13:14of dormancy were decreased when he
13:16exposed Melanoma cells to these?
13:19Each condition media from the lung,
13:21whereas the markers of proliferation
13:23were increased in the Melanoma cells,
13:26the next thing he did was to look
13:28at 15-A specifically and to look at
13:31it in vivo and what he saw is that
13:35if he stained young and aged tumors
13:38for 15-A and Ki 67 in the lungs,
13:42so these are cells that he has
13:44implanted in the skin of the mice that
13:46have now metastasized to the lung.
13:47They're labeled with them cherry.
13:49In the absence,
13:50and this is just standing for and
13:52cherry showing you that there are
13:53far fewer cells in the yung lung
13:55than there are in the age long.
13:57And if he stains the the lungs for
13:59win 5/8 these large tumors that
14:01are growing out in the age long
14:04have much less went 5A staining
14:06than the tumors in the yung lung,
14:08and they're highly positive for Ki 67
14:10telling us that the wind 5A may be
14:12driving this dormant phenotype in the lung,
14:15which was super interesting to us.
14:17What Mitch did then was to manipulate.
14:2015A in these conditions,
14:21so he took young mice,
14:23UM,
14:24and he injected cells with an
14:27induced adops inducible went 5SH158,
14:30so he knocked 158 out of the Melanoma
14:33cells in the young mouse lungs
14:35and what he saw is if he did that
14:37very early on he could reduce the
14:40number of metastases altogether.
14:42But if he did that later,
14:44he could cause the metastases to grow out.
14:47If he did the opposite experiment
14:49where he took age mounts.
14:50Once and then he gave them went
14:535/8 he could come.
14:55He could actually prevent these
14:58these tumors from growing out at day
15:0121 and and he could also if he if
15:05he induced the win 5A at day three.
15:08They had already started to get
15:10to the lungs but they again were
15:12prevented from growing out,
15:13so this was absolutely fascinating
15:15to us because it kind of changed
15:18our thinking of how when 5A was
15:20driving metastasis.
15:21And what we saw was that you
15:24know these Melanoma
15:25cells in the young.
15:26First of all, the tumors are much bigger
15:29in the young skin than the age skin,
15:32and so even though we might see
15:34similar rates of seating in the lung,
15:36we know that the rates of tumor cells
15:38leaving the age skin are higher than
15:41the rate sleeping the young skin.
15:43But once they get to the yung lung,
15:45the yung lung fibroblasts are are secreting
15:49factors that maintain the win 5A phenotype.
15:52And and retain those cells in this
15:55invasive but slow cycling state.
15:57However, in the age long,
15:58we're seeing that there is an
16:01increase of secretion of SFRP one,
16:03and that is maintaining that is allowing
16:06these cells to now lose that slow
16:08cycling state become more proliferative.
16:11These are also positive for
16:13beta catenin MITF and Mark one,
16:15and they're they're rapidly proliferating,
16:18and so really for us,
16:21where we had always thought of 15-A
16:22is simply a driver of metastasis.
16:25It's actually playing a much more
16:27complicated role and driving an
16:29invasive but then dormant tumor
16:32phenotype that requires a change for
16:34these cells to come out of dormancy.
16:37I will add that we've also seen changes
16:39in the immune microenvironment in
16:41both the young and each lung that
16:43are contributing to this outgrowth
16:45and lack of immune editing of
16:47these cells as they grow out so.
16:51Sorry,
16:52hold on a second so I've started to
16:55give you now a snapshot of the fact that
16:58Asian can drive metastasis of tumors,
17:01but we've been very interested in
17:02also all of the other things that
17:05the aging microenvironment can do
17:07from driving not only metastasis,
17:09and we'll talk a little bit more about this,
17:12but things like therapy resistance,
17:14angiogenesis, metabolism,
17:15and changes in the immune
17:17microenvironment as well,
17:19so I'll start with the angiogenesis story,
17:21which is a story.
17:22That was recently published out of our lab.
17:24I should mention that all the work
17:26I just showed you is of matches is
17:29completely unpublished at this time,
17:31and most of the slides I'll show
17:33you today are unpublished work,
17:35but I thought I'd give you some snapshots
17:37of some recently published work as well,
17:40so the tumors that we grow in age mice
17:43have far more angiogenesis if we stay
17:46in with either CD31 or even CD105,
17:50and when we take.
17:52Dermal massive dermal microvascular
17:55endothelial cells and we treat them
17:58with medium from young age fibroblasts.
18:01We see that those dermal microvascular
18:03endothelial cells will form networks when
18:05they're treated with age conditioned media,
18:08but not so much when they're
18:09treated with young,
18:10and we can quantitate this as well.
18:13And,
18:13and this was really mysterious
18:15to us because we needed that veg.
18:17F and its receptors were decreased
18:20during aging,
18:21and so it didn't make sense to us that.
18:22We were seeing a decrease in veg
18:24F But an increase in angiogenesis.
18:27However,
18:27we knew from our work with SFRP
18:302 that SFRP 2 has been shown
18:33to stimulate angiogenesis
18:34via a went related signaling pathway.
18:37So when it keeps rearing its head again
18:40and we knew that if we if we treated
18:42mice with recombinant SFRP 2 we could
18:45increase their metastases of these cells.
18:47So Mitch, along with Brett Decker and
18:50among car decided to explore this further.
18:53And what they did was to
18:55take these endothelial cells,
18:56treat them with either recombinant
18:58SFRP 2 and young media,
19:00or I don't know why that keeps happening
19:03or an antibody against SFRP 2 in age
19:07media when they manipulated SFRP 2 they
19:09could show that when they increase it,
19:12these microvascular endothelial
19:14networks increase.
19:16If they decrease SFRP 2,
19:18they can disrupt the formation of networks.
19:20They also did this in vivo and
19:22showed exactly the same thing.
19:24If they give young mice recombinant SFRP
19:262 they have a ton more angiogenesis,
19:29old myself, more angiogenesis.
19:30But if you treat with an antibody
19:33against so far P2,
19:34it decreases the number of blood vessels.
19:37And so when UM mentioned,
19:39his colleagues looked at Veg F and
19:42SFRP 2 what they found was that these
19:45young mice had very high levels of veg.
19:47F But the age tumors in aged mice did not.
19:51The opposite was true for SFRB 2 and so
19:56you know that led us to ask the question,
19:58what does that mean for
20:00antiangiogenic therapy?
20:01Because antiangiogenic therapy,
20:02of course, is designed against veg F.
20:06And so this this hinted to us that.
20:08Younger patients might benefit
20:09from this therapy,
20:10but certainly older patients who had
20:13highly angiogenic tumors that were not
20:15dependent on veg F may not benefit.
20:17So to answer that question,
20:19what we did was to turn to our colleagues
20:21Pecori and Mark Middleton in the UK,
20:23who had just conducted this large
20:26trial for Avastin and Melanoma where
20:29they had treated over 1300 patients,
20:31or their observation at the end of
20:34this trial was that overall there
20:36was no change or no response.
20:38To adbaston, however,
20:39we asked them to go back and re
20:41analyze their data and this time,
20:43stratified by age and when they do that.
20:46Sorry for the traffic outside my window,
20:49and when they do that.
20:52We see that patients under the age
20:54of 45 who receive Avastin actually
20:56do do better on Avastin,
20:59whereas those over the age of 6565
21:02and older really have no difference
21:04in their response to Boston.
21:06To sort of close,
21:07this loop would match them did
21:09was to take young animals.
21:10He treated them with an antibody
21:12against Veg F and then attempted to do
21:15that in the presence of high levels
21:17of SFRP 2 and so when he does that
21:20there is no change and no response.
21:22To the mouse equivalent of Avastin in
21:26tumors in which which have highest Fr P2,
21:29which may be the reason why we're
21:31not seeing older patients responding
21:33to this therapy as well.
21:35So one of the things that we learned
21:37from this study was that you know
21:39not only could SFRB to
21:41take over from Veg F as a driver
21:44of angiogenesis during aging,
21:45meaning that older patients you know we're
21:48unlikely to respond to Avastin the reviewers
21:51had actually asked us some questions.
21:54About the matrix and what was happening to
21:56the permeability of these blood vessels.
21:58And so, although we felt that it was out
22:01of the scope of that particular paper,
22:04it was a question that really intrigued us,
22:06and so are my graduate student Gloria
22:09Mareno decided to take this on.
22:12The reason we found this so interesting
22:14is because of a previous study
22:16from an car in my lab who had shown
22:19that collagen density is decreased
22:21during aging and that can happen.
22:24Whether it's in the presence of a tumor,
22:26or even altogether in the absence of a tumor,
22:29so this is just normal mouse skin from an 8
22:32week old compared to a 12 week old mouse,
22:34and I think you can see that the collagen
22:36looks dramatically different between the
22:38two and a man wanted to know what was
22:41driving these differences in collagen,
22:44she identified this protein,
22:45called happen one,
22:46which was actually the protein that
22:48was the most significantly increased
22:50in the young skin,
22:52fibroblast secret tone and happen
22:53one turns out to be a super.
22:56Interesting protein because it's
22:57the protein that knits together,
22:59the collagen and the elastin in the skin.
23:03And maintain sort of the integrity
23:05of the skin,
23:06so you know when you're young you
23:08have this lovely smooth skin.
23:09And as you age,
23:11those collagen and elastin
23:12pressings breakdown,
23:13and that's a little bit how wrinkles occur.
23:16And so I happen,
23:18one is responsible for stitching together
23:22hyaluronic acid to proteoglycan monomers.
23:25So I'm undecided to explore this
23:27and the first thing she did was to
23:29just simply injected into mouse skin
23:31and see what it did and she found
23:32that if she put it in H mouse skin
23:35she could she could re densify the
23:39collagen again in the age mouse skin.
23:42She wanted to know what that meant
23:44for the type of fibers that these
23:47fibroblasts were laying down,
23:48and the ECM networks there.
23:50It's just selling matrix and so we
23:52collaborated with my dear friend.
23:54It secure men at Fox Chase and a
23:57man seated fiberglass.
23:59And then what she did was to basically
24:01look at the matrix they left behind and
24:03look at the orientation of those fibers.
24:06And when she does that,
24:07she sees that with young fiberglass,
24:09fibers are oriented in multiple different.
24:12Directions and each direction
24:14is assigned a color,
24:16so you see this very colorful matrix.
24:18If she knocks down happen one
24:20in these fiberglass,
24:21she now sees that the the direction
24:23of the fibers is more aligned.
24:25Fewer colors means fewer directions
24:27of the fibers and issue reconstitutes
24:30us by adding back happened once
24:32you can start to increase the multi
24:35directionality of these fibers again
24:38we can do the opposite experiment
24:39in the age so you can see that the
24:42age fiberglass start out.
24:43Looking very linear and if we
24:46add in recombinant happen one,
24:48we can now increase the multi
24:50directionality of the fibers.
24:52If we first boiled it happened
24:53one before adding it in.
24:55It doesn't do that,
24:56so it tells us that it really
24:58requires to happen one activity.
25:00A man wanted to know what that
25:02meant for the invasion of
25:03the Melanoma cells in vitro,
25:05and so she looked at.
25:07She added in recombinant happen
25:09one into reconstructs made with
25:11aged fibroblasts and showed
25:12that when she does that,
25:14there no longer is able to invade
25:17as effectively into the membrane.
25:19If she does the opposite where she depletes,
25:21happen one in the fibroblast before
25:23making reconstructs with them,
25:25they increase their ability
25:27to invade into the membrane.
25:30If we do this experiment in vivo,
25:33where we treat the primary tumor
25:35with japlan one in the age mice,
25:38we no longer see their these cells
25:41able to metastasize to the lungs
25:43in the age mouse versus C versus
25:46those mice treated with Kaplan
25:48one and and so we were super
25:51excited by those data and even
25:53more so when in a parallel study.
25:56Brett Becker,
25:57who is a visiting clinician to the lab,
25:59showed that happen one.
26:00Played a role not only in the metastasis
26:03of these cells from the primary tumor,
26:06but also the japlan one played a
26:08critical role in maintaining the
26:10integrity of the extracellular matrix
26:13around the lymphatic vasculature
26:15in the lymph node as well.
26:17And when it happened,
26:181 broke down during aging
26:21to primary tumor cells,
26:23leaving the primary tumor.
26:24Site could escape both through the
26:27lymphatic vasculature and not spend
26:29too much time in the lymph node.
26:31But go on to.
26:32Very quickly formed visceral
26:34metastases so that was one of the
26:36studies that first showed us that
26:38this loss of integrity of the ECM
26:40during aging might actually help
26:42to direct the route of metastatic
26:44dissemination from the primary tumor.
26:46So taking all of those data,
26:49the angiogenesis data and the
26:51matrix data together.
26:52Gloria Moreno,
26:52who's a grad student in the lab,
26:54currently decided to explore this further,
26:57and which she saw was that if she
26:59stained for blood vessels, the.
27:01They were sitting in very different
27:04matrices in aged versus young skin,
27:06and again to remind you this is what
27:09the age versus young skin looks like.
27:11So she wanted to know whether
27:14that difference in these matrices
27:16could impact angiogenesis and
27:18so she embedded her endothelial
27:21cells in a matrix that had aged or
27:24young fiberglass or H fiberglass
27:26treated with recombinant happen
27:28one or young fiberglass in which
27:30happened one had been knocked down.
27:32What Gloria saw was that the
27:35endothelial cells in the H matrices
27:37had all of these sprouting.
27:39You know these?
27:40These are basically what we think of
27:43as little artificial blood vessels
27:44that are sprouting off the endothelial
27:47cells as compared to the young and,
27:49and if she treats the aged.
27:52And to tell your cells with
27:54the endothelial cells in
27:55the age matrix with happen one,
27:57they decrease their ability to sprout.
28:01And if she knocks down happen one in
28:03the young fibroblasts and then embeds
28:05endothelial cells, are they increased?
28:07Her ability to spot so happen one was
28:10having a direct impact on angiogenesis,
28:12and so when she looked at mouse tumor,
28:14she saw the same thing again.
28:16There's more angiogenesis
28:17and the age versus a young,
28:19but if she treats the age
28:21tumors with happen one, she can.
28:23Directly, she can reduce quite dramatically
28:26the amount of angiogenesis ongoing,
28:28but was interesting,
28:29though is that when we stayed for vCard
28:31hearing we saw something quite different.
28:33Again, there are far more blood
28:35vessels in the tumors in the age mikes,
28:37however they don't stain very
28:39well for V could hear,
28:41and they stay beautifully for CD31,
28:43CD 105, etc.
28:44But the V card here in standing
28:46is super weak compared to the
28:48young or the age plus happen one.
28:51So Gloria wanted to understand
28:53that better and our hypothesis was
28:55that young fibroblasts lay down
28:57and matrix that endothelial cells
28:59can anchor to really beautifully,
29:00and that sustains the interactions
29:02between their cells as well.
29:04However, age fibroblasts,
29:05that matrix is disrupted,
29:07disrupting the integrin connections between
29:09the age matrix and the endothelial cells.
29:12And we hypothesize that
29:14the cell cell interactions,
29:15specifically V could hear it
29:17would also be disrupted.
29:18And so that's exactly what.
29:22Gloria C So she laid down in dathyl
29:24cells on matrices that she had
29:26made from young or each fiberglass.
29:28You can see that the endothelial
29:29cells on the young matrices have
29:31beautiful V card here in,
29:32but on the age they lose these
29:35connections and now she wanted
29:36to manipulate happen one to sort
29:38of not up these matrices and see
29:40what happened if she knocks happen
29:42one out of the young fibroblast,
29:44they now lose their ability to
29:46make these nice feet.
29:47Could hearing connections and if she
29:49adds happen one into the age fiberglass,
29:51now the endothelial cells?
29:53Have beautiful vegan hearing connections
29:55so that was super exciting but she
29:58also wanted to know did that mean
30:00that if they have these nice tight
30:02end vCard hearing connections,
30:05was there barrier integrity of these
30:07endothelial cells and to measure that?
30:10But Gloria did was to use an electrode
30:13assay where she ceded the CDM so the
30:17fibroblast derived extracellular
30:18matrix and then she played at the
30:21endothelial cells on top of that matrix.
30:23And then she measured the current.
30:25So the more resistance there is,
30:28that better the barriers are and
30:30the tighter these interactions are.
30:31So in in in in endothelial cells,
30:34seated on an HTC M,
30:36there's very little barrier integrity
30:38on those seated on a young CDM,
30:41there's a lot of better integrity,
30:43and if we take our cells that are
30:45on an aged man,
30:46we give them half and one to not
30:48up there matrix.
30:49We can now see that there is
30:51an increase in
30:51barrier integrity.
30:52So basically all of these data.
30:54From Gloria so far are telling us
30:57that the more happen one there is,
30:59the tighter these matrices are,
31:02the more intact these
31:04blood vessels are as well,
31:07which can have significant
31:08impact for tumor cells.
31:10Being able to invade in and out of that,
31:12and so now what or is doing is some
31:14very beautiful in vivo imaging of
31:16these vessels and of the flux of
31:19tumor cells in and out of these
31:20vessels in these different conditions.
31:24So I'll move on to the next
31:27story that we recently published.
31:30So this was work conducted by Gretchen Ellis,
31:32CEO, who's a grad student in
31:34my lab at the time,
31:35and what she did was to notice that each
31:38fiberglass made a ton of lipids and
31:41they've created a lot of these leopards,
31:43and when they see created
31:45a lot of those lipids,
31:46Melanoma cells would take those lipids up.
31:49And so these are Melanoma cells grown
31:51in young or each condition media,
31:53and then simply staying.
31:55Or for Debbie,
31:56and if Gretchen looks at the lipidomics
32:00of the the what is being secreted
32:02by the young or each fiberglass,
32:04she can see that it,
32:06whatever age fibroblasts are secreting
32:08Melanoma cells are taking up.
32:10So that was super interesting and the
32:12question there were two questions.
32:13One what are how are they taking it up?
32:16And two what are they doing with it?
32:18So Gretchen looked at a bunch of
32:20different fatty acid transporters and
32:23identified this particular one called fat P2.
32:26In fact,
32:26P2 is increased in Melanoma cells
32:29exposed to age condition media.
32:31It's increased in Melanoma cells prone
32:34and skin reconstructs with age fiberglass.
32:36It's increased in Melanoma cells
32:38that we put an age tumors in mice.
32:41If we look at patient tumors,
32:44this is just TSJ data.
32:46We can see that patients over
32:48the age of 50 are the ones who
32:51have the most fat P2 expression.
32:53So the other thing that we
32:55noticed is when we.
32:56We're standing patient tumors for Fabry 2.
32:59We noticed that the patients who survived
33:01UM the the shortest time after being
33:04treated with B RAF MEK inhibitors were
33:07patients who had very high fat P2,
33:10so that may Gretchen asked the question,
33:12could fat be two and lipid metabolism be
33:15playing a role in therapy resistance?
33:18So something we've seen before
33:20is that patients over the age of
33:2265 have a lower response this.
33:26These data on this slide are single agent.
33:28I'll show you double agent in just a second.
33:31So this is just very rough and ebb
33:33and these are data from the very early
33:35trials and we found that patients
33:36over the age of 65 in those trials
33:39were less likely to mount a complete
33:41response to be rough inhibitors in
33:43patients under the age of 65 and
33:45in our mouse studies we showed that
33:48the exact same tumors implanted
33:49into young mice would respond to
33:52the venue rafanan tool compound,
33:54whereas those planted into age monks.
33:56Would not so Gretchen wanted to
33:58know how fat P2 could affect this
34:01and she wanted to do this using
34:03the B RAF and MEK inhibitors.
34:06So she created a cell line in which
34:09she had knocked down fat P2 and a docs
34:12inducible manner and what she found is
34:15that when she knocks down so she has
34:18an empty vector control and then she
34:20has the empty vector plus to be RAF
34:22MEK inhibitor and in tumors in young mice.
34:25Of course they respond to
34:26the beer afmic inhibitor.
34:28And after some time they grow back.
34:30So we've all seen this a million times.
34:32UM, if she now knocks down fat P2 using docs
34:36and treats with the B RAF MEK inhibitor,
34:39it's exactly the same.
34:41And the young Lisa tumors respond.
34:42They eventually grow back.
34:44However, in the age mice,
34:46it's a completely different story.
34:48What we see is that the tumors,
34:50first of all treated with B RAF MEK
34:52inhibitor in the age wise kind of
34:53just stopped growing for a little
34:55bit but then continue to grow so
34:56they they rarely respond at all.
34:59Uhm,
35:00but now she first treats them
35:02by knocking down the fat P2.
35:04You can see that those tumors basically
35:07go into remission and stay grimmest
35:09if you will for a very long time.
35:11So this was super exciting data to
35:13us 'cause it was one of the first
35:15incidences we really had of targeting
35:17this very age specific change in a
35:20Melanoma cell and showing that it we
35:22could overcome therapy resistance
35:24quite dramatically in this case.
35:26So you know, a lot of times I think that.
35:30We,
35:30UM,
35:31the questions are my favorite part of
35:33a talk because they make me think and
35:35they make me think about what we want
35:37to do in the future and out of the
35:40questions have come some questions about,
35:42well,
35:42you see a lot of changes in with age
35:45does gender or I guess tag to be
35:48technically correct biological sex,
35:50player role and so this is something
35:52we've just started exploring in the lab.
35:55We see that there are.
35:57We see that in Melanoma,
35:59there's a big difference.
36:00In mortality estimates in males
36:03versus females,
36:04as well as incidences in as well
36:07as differences in incidence,
36:09and so yes, chabra,
36:10who is a junior faculty in my lab,
36:13started to explore this and what
36:15he found was that while there
36:17are certainly differences between
36:19male and female,
36:21they tend to be less qualitative
36:24and more quantitative.
36:25So, for example,
36:26if we look at something like senescence,
36:29senescence increases.
36:30With age and both female and
36:32male dermal fibroblasts,
36:34but they it increases to a higher
36:36extent from the start point in the male
36:40fiberglass versus a female fiberglass.
36:42If we look at changes in lipid
36:44oxidation we see the same thing
36:46and if we look at changes in
36:48things like exosomal content
36:49so this is work done by
36:51Laura who's are who's
36:52also a postdoc in the lab,
36:54we see that again between males and
36:57females there are distinct differences.
37:01In the changes that we see in CD9,
37:04so CD9 is decreased in both
37:06males and females during aging as
37:09compared to the young exosomes.
37:11This is an EXO view chip,
37:13but we see that in the males it's
37:15far more dramatically decreased
37:16than it is in the females.
37:19If we look at the impact of these
37:22fiberglass on Melanoma cells,
37:24we see the same thing.
37:25So we see that if we treat Melanoma
37:27cells with the B RAF MEK inhibitor,
37:29this is a spheroid assay.
37:31We're just looking at survival.
37:33We see that, UM,
37:34Melanoma cells treated with B RAF MEK
37:37inhibitor and the presence of age
37:40male condition media do not die as
37:43effectively as they do when they're
37:45treated with young male condition media.
37:48So the more red you see,
37:49the more dead cells there are and the
37:51same is true for Melanoma cells treated
37:54with age female condition media.
37:55But again, the impact is not as great, so.
38:00You can see that quantified here age,
38:03Melanoma cells treated with age,
38:04male conditioned media have far less
38:07relative cell death than those treated
38:09with age female condition media.
38:11The same is also true for invasion,
38:14so in vitro,
38:14at least we see that there is an
38:16increase in invasion and Melanoma
38:18cells created with age.
38:20Males conditioned media versus
38:23age female condition media.
38:25What's been fascinating is that
38:27recently we've been able to get
38:29fiber blasts from the same people.
38:31So they're genetically identical,
38:32and they've been collected
38:3420 plus years apart,
38:36and where what we're seeing is that even
38:38within the same individual that's now
38:40reflecting some of the changes we see,
38:42so that's been super exciting.
38:44So here within the males you can
38:46see that there is a distinct impact
38:48in the increase in invasion.
38:50This is two different men.
38:53Their fibroblast taken over 20
38:55years apart in each case in the
38:58females again the trend is there,
39:00but it's not as dramatic as it
39:01is in the mail,
39:02and that's sort of a constant
39:04theme that we see here.
39:06Uhm,
39:07Yash also did the in vivo
39:10experiment where he took a young.
39:12He took both the Yum cells which
39:15are male and these PST 9AJ2 cells
39:17which are female and he sort of did
39:20the crisscross experiment where he
39:21put them both in male and female
39:23or both in and these both male and
39:26female and what he sees again over
39:29and over again is that when he puts
39:31the Yum cells in young versus age male again,
39:35they grow far more slowly.
39:37But if he does this in females in the yums,
39:41there's a little bit of a difference.
39:42But in the female to female
39:45there's very little difference,
39:46although again there is a big difference
39:49between the way the age males bro.
39:51If he looks at Ki 67,
39:54he sees that the tumors are
39:56proliferating far less in
39:57the age male mice than they
39:58are in the age female mice,
40:00so telling us again that there are
40:02distinct differences in the micro
40:04environments between the male and female,
40:06and we're still trying to figure out.
40:08Actually, what those differences are, we
40:10see that there are changes in angiogenesis.
40:12Again, the same story.
40:14There's more angiogenesis with aging,
40:16but again, it's more dramatic in the
40:18males than it is in the females.
40:20If we look at metastasis,
40:22we see the same thing where we
40:25have more metastasis in the males.
40:28Actually, I take that back.
40:30The one thing that's not as different,
40:32and so these were earlier data,
40:35we have more data now from about 20 miles.
40:38And we're now seeing that there is
40:40actually not much of a difference in
40:42invasion between age males and age females.
40:45So that's going to be really interesting
40:46to sort of tease out because we're seeing
40:49so many differences in the growth rates.
40:51So just to summarize,
40:52some of the key changes we've seen
40:55female dermal fiberglass undergo
40:57early replicative senescent,
40:59so there's elevated Ross in the
41:01age male dermal fibroblasts,
41:03but female dermal fiberglass are better
41:06equipped with repairing the Ross and.
41:09Age male fibroblast.
41:10Promote invasion and therapy
41:12resistance in Melanoma cells in vitro.
41:15However, both age male and aged.
41:17Female drive invasion and
41:20therapy resistance in vivo.
41:22And finally, we're moving beyond Melanoma.
41:25I know this is a Melanoma sport talk,
41:27so I'll be very quick here,
41:28but we're super excited to be
41:30working with my dear friend list.
41:32Jaffe, Huerco, mentoring guns.
41:33Bronski is a very talented he monk fellow UM,
41:37and what we've done is to obtain human,
41:40young age pancreatic fibroblasts and
41:42do a lot of the same assets we're doing
41:45and have done with the Melanoma cells.
41:47And we're also using mouse models of cancer,
41:51both having taken.
41:52Young age pancreatic fibroblasts from
41:54these knives and using the transgenic
41:57APC models and what Dan has seen
41:59is he's already started to see some
42:02really super interesting stuff,
42:03so if he takes pancreatic cancer cells,
42:06human pancreatic cancer cells
42:07and treats them with young age,
42:09fiberglass conditioned media,
42:10he sees that actually they increased
42:13their proliferation quite rapidly.
42:15They have an increased and invasion.
42:18It's not very dramatic in vitro,
42:20but when we look in vivo,
42:21what we see is in the KPC.
42:23Model that we put into 18 month old
42:26mice compared to 8 week old mice.
42:28The tumors grow very grow up very
42:30rapidly in the age mice as compared
42:33to the young mice.
42:34If he looks at angiogenesis as far more
42:37angiogenesis and the tumors of the
42:38age mice compared to the young mice.
42:40And now if he looks at the metastases,
42:43he sees that there's far more
42:45metastases in general to the different
42:47sites and the age mice than there
42:49are in the young life.
42:50So that has been super exciting to see these.
42:53Kind of data holding up in
42:55a whole different cancer
42:56as well, and I'm excited to explore
42:58this and tell you more about it later,
43:01so I hope at this point I haven't run
43:03overtime and I hope I've convinced
43:05you that the aging micro environment
43:07is critical to consider when you're
43:10designing your preclinical studies.
43:12And when you're treating patients,
43:14I've told you a little bit about
43:15how things like the matrix change.
43:17Andrew Genesis changes in metabolism
43:19as well as metastasis and all
43:22of these are impacted by.
43:25Fiberglass, specifically aging fiberglass.
43:29These did the wonderful people
43:30who do all the work.
43:31I've tried to call them out as I go,
43:33but really the lab is a team and
43:35works very closely together.
43:37I've been so happy or at Hopkins the
43:40last couple of years that I've been
43:42here and I have a whole cadre of
43:45amazing collaborators from engineers to
43:47immunologists to buy informatics experts.
43:49It's really been a lot of fun.
43:52Uhm, I'm also very lucky 'cause
43:54Melanoma is such a global effort.
43:56We have collaborators all around,
43:59like I say across the street,
44:00across the country and across the world.
44:03I usually end with the picture
44:04of my favorite agent study,
44:06which is my daughter who is now 16 and a
44:09half almost 17 and looking at colleges,
44:12which is just about breaking my heart
44:14to think of her leaving and I will
44:17end as I always do as Marcus said,
44:21promoting diversity. And women in science.
44:24You know women, especially women of color,
44:27really earn a tiny percentage
44:29of even bachelors degree.
44:31And when you think about PHD's,
44:32this is an even smaller percentage.
44:35If any of you are interested in my
44:37dear friend Danita Brady and I have
44:39written a commentary in cancer discovery
44:42with some actually actionable items
44:44and interesting websites and reading
44:47material if you're interested in
44:49promoting diversity in your local
44:51community as well. So I'll stop there.
44:53Really take any questions.
44:55Thank you so much.
44:59Thanks Ashley, that was really great
45:02and what I'd like to do is invite folks
45:06to come to post questions in the chat.
45:10I don't think we have a Q&A area,
45:12so I see one already from Harriet Cougar and
45:16I will read that and so it is welcome here.
45:21Thank you for a terrific talk.
45:22Do you think we should be looking at
45:25old versus young in a binarized fashion
45:28and young versus old humans and mice?
45:30Do you think there is a difference
45:32between old and very old?
45:34And that's real question, harrietta.
45:37You know, from my point of view,
45:38that changes as I get older.
45:40But what does that mean?
45:42But anyway, I think I was going to
45:45ask a similar question about you
45:47had shown that bevacizumab study
45:50re looking at clinical data.
45:51Should we be looking at all clinical
45:54data and trials in a similar manner?
45:57So my bias to that last
45:59question of course is yes.
46:01I do think we should be looking
46:03at all clinical data according
46:05you know according to age.
46:07To answer Harriet's question specifically,
46:11you know what we, although I often
46:13present the results as binarized.
46:15What we really do is to look at
46:17it in bins so we have our under 50
46:20age group are 50 to 65 or over 65.
46:23To answer your question about old and
46:26very old we call them aged and super aged.
46:29In the lab.
46:30There are definitely differences
46:31and the reason we even started
46:33looking at that is 'cause if you
46:36look at the incidence of Melanoma.
46:38Right, there's this bell curve where
46:40it kind of goes up and up and up,
46:41and then suddenly,
46:43after like 8085 the incidence drops off,
46:45the mortality rates drop off
46:47and the question is,
46:48you know if you if you get that
46:50old or you just a super survivor.
46:52There's a lot more going on.
46:54Or is there something actually physical?
46:57So for example,
46:58one of the physical changes we've
47:00seen are that you know if you
47:02look at the biophysical matrix,
47:04for example, there is a bell curve.
47:08Of how a cell can make its way through that.
47:11So if you have a super stiff matrix,
47:13the cell can only go so far 'cause
47:15then nucleus gets stuck and as you
47:17decrease the density of that matrix the
47:19cell starts to be able to move through it.
47:22But if you decrease it too far then
47:24it's got nothing to hold onto and it
47:26kind of flounders as if it's in a soup.
47:28So that's sort of one of the
47:31things that we're looking at in
47:33context of age versus super aged.
47:36And there are definitely.
47:38Differences,
47:39so yes,
47:39we do think there is a difference
47:41and we are looking at some of those.
47:45And and I'll, I'll follow up on that now
47:48she you know with regard to you know,
47:52there should be a lot of data
47:53in this particular area.
47:54So AJC staging for Melanoma
47:56has been in existence for,
47:58you know for decades.
48:00And there are some very well characterized
48:03parameters that predict prognosis that
48:06are very closely correlated to metastasis.
48:08So one of the predictions with some
48:11of the discoveries that you've made
48:13is that with depending on like.
48:15Breslow thickness or thickness
48:17of the Melanoma.
48:18You might have different prognosis
48:20and old versus young because they're
48:22more likely to metastasize and old.
48:24I don't know if you've tried to
48:26do something like that already,
48:28or what your thoughts are about about that.
48:31Yeah, that's a great point, Marcus,
48:32so we have not yet tried to do that,
48:34only because I think we haven't really had.
48:39You know, one of the things we
48:41haven't done since we moved here
48:43is really fully established.
48:44All of the clinical.
48:46A collaboration, so we need a man and.
48:50Yeah, I mean I I,
48:52I would imagine that I mean I think
48:55even with the AJC staging age is
48:58really the overriding factor, right?
49:00So Breslow thickness is a close second,
49:05but it would be really interesting to
49:07go back and look at thin lesions and
49:09old versus young patients and see if
49:11there is an increase in metastasis.
49:13Things like certainly things like lymph
49:16node metastases are dramatically different.
49:18Were actually younger patients have more
49:20lymph node metastases than older patients,
49:23but the older patients have more
49:24visceral Mets and we you know,
49:26we think some of these disruptive changes
49:28to the matrix etc are part of that.
49:32It would be interesting to ask, you know.
49:34So like Jefferson or someone else,
49:35you know who does The Who has access to that
49:37data and have had them do it, you know?
49:41Great point, I'll reach out to him. That's
49:43OK and I guess another question
49:45I would have to is that and you
49:48probably guess this might be question
49:51I might ask is that it's been kind
49:54of surprising that responses for
49:56older versus younger patients and
49:59Melanoma with immune checkpoint
50:02inhibitors have been better in older
50:05patients and and sort of that.
50:08That also introduces a complication
50:10in terms of survival.
50:11Because there could be immune editing
50:13in some older Melanoma patients
50:15because their immune system might
50:17be more primed to fight it,
50:18but any thoughts about you know how the
50:22micro environment might be affecting
50:25those enhanced rates of response,
50:27right? It's a great question,
50:29so we think it's several full,
50:33so we published, I think back in
50:352018 that observation right that
50:37older patients getting anti PD one
50:40do much better than younger patients.
50:42And you know, part of it is that
50:44the immune microenvironment is very
50:45different between young and age.
50:47Actually young younger patients have more T.
50:49Rex, so that CD8T rec ratio is
50:53off in the younger patients as
50:55compared to the older patients.
50:57However, our recent data and data I
50:59didn't really talk about today is how much
51:02angiogenesis is playing a role in this.
51:04And so, as you know,
51:07angiogenesis can have a quote
51:09unquote beneficial effect by
51:11being a good venue for delivery.
51:13Of immunotherapeutic agents,
51:15and so although Veg F can be a
51:19negative prognostic factor for
51:22immunotherapeutic delivery,
51:24having angiogenesis in the absence of veg.
51:26F, which is what we're seeing in the aged,
51:29seems to be sort of the sweet spot
51:32for the delivery of immunotherapy,
51:34which might just might be a part
51:36of it as well.
51:38Super and it's funny, 'cause I think
51:40a lot of people had assumed that this
51:42concept of immune senescence, you know,
51:44in older individuals might be happening,
51:46but it might be in specific
51:48subsets like T regs as you're
51:50mentioning the observation there.
51:53So I am I could go on all day,
51:57but here we got.
51:58We got a question just when
51:59I was getting desperate here.
52:01So Brenda IMO has a question in
52:03terms of fatty acid transporters.
52:06Was fat P2.
52:07Uniquely upregulated in tumors
52:09from older than individuals,
52:11or is this true for other fatty
52:14acid transporters as well,
52:15including like CD36,
52:16which there has been interest
52:18at Yale and as well,
52:19and in particular,
52:21are there particular lipid species
52:23that agent fibroblasts secrete?
52:26That's a great question, so we did look at.
52:28We looked at CD 36.
52:30We looked at fat P1 through six and
52:33the only one that was up regulated
52:36according to age was fat P2.
52:39Now that's not to say these others
52:41aren't upregulated simply by virtue
52:42of these cells being Melanoma cells.
52:44They are, however, fat.
52:46P2 is uniquely upregulated with age in
52:49terms of the particular lipid species,
52:52yes, so our lipidomics analysis showed
52:54us that probably the lipid species that.
52:57We were most interested in were Sarah mind,
53:00so Sir, mine seemed to be the
53:02most differentially expressed or
53:04secreted by the age fiberglass,
53:06the most efficiently taken up by the
53:08Melanoma cells in that environment,
53:11and the ones that have the most impact on.
53:14You know,
53:15that wasn't in the cancer Discovery paper,
53:17but we've shown that Ceramides
53:19can drive invasion and metastasis
53:22in Melanoma cells as well.
53:25Interesting question, interesting,
53:27it's really interesting results from
53:29last chance for folks to ask questions,
53:31as is really been a wonderful summary,
53:34especially for you.
53:35Know us at Yeles were interested
53:37in getting in aging center set up.
53:41I was I had emailed a mutual friend
53:43of ashes in mind so deep I don't
53:45know if he was able to make it.
53:50Don't kick them in the shins too hard,
53:52but anyway, I'm obviously a really
53:55great interest for us here. Jeff.
53:57Jeff Townsend also has a question I
54:01think I saw three fibroblast lines
54:03used for at least one comparison,
54:05and in that comparison results
54:08were very consistent.
54:09Are there any inconsistencies
54:10among different samples or lines?
54:13Sure, so Jeff, of course.
54:15So we, you know, for most of the
54:17experiments we've done at this point,
54:19we've used up to. Get 12 or even 15
54:22in one case different cell lines.
54:25There are definitely some inconsistencies.
54:28The most consistent inconsistency that
54:30we see is that we have some young lines
54:34that behave as if they're an old line,
54:36and when we go back and sort of dig
54:38through the history of those lines,
54:40they tend to be from young
54:42women with a tanning history.
54:44So that's another ongoing project in the lab.
54:46I didn't talk about is you?
54:47Keep looking at the effect
54:49of UV as a premature aging.
54:51Agent, so wear your sunblock,
54:53everybody, but you already know that.
54:57One question related to that is that
55:00there's including some work from Yale
55:03interest in looking at DNA methylation.
55:07Epigenetic changes as an aging clock,
55:10and have you done any looking into
55:12as to in those cases where there's a
55:15disconnect between biological between a
55:18chronological age and biological age?
55:20You know if if there's a component
55:22related to DNA methylation that
55:24might be UV induced, right,
55:26right so? So in terms of Melanoma,
55:30where just beginning to delve into that,
55:33however, we are collaborating
55:34very closely with Harris.
55:36Warren, who is a associate professor here
55:38at Hopkins who works on colon cancer,
55:41and we've got a lot of interesting
55:42data coming out of those studies,
55:44so I'm super excited about that.
55:46And of course, people like John,
55:47Pierre Issa and Shelly Berger have
55:49done a ton of work in, you know,
55:51understanding this epigenetic
55:52drift that we see during aging.
55:56Well, super well, I and less we
55:59have another last minute question.
56:01I would really like to thank you Ashley
56:03for giving us such a stimulating talk.
56:05Obviously generated a lot of interest.
56:07We're looking forward to actually having
56:08you here in person sometime in the future,
56:10but thanks so much for sharing all of
56:13your work and I would encourage folks
56:15to also read that cancer discovery.
56:18Yeah, article about increasing
56:22opportunities for.
56:24Scientists of color and of
56:26other backgrounds that are less
56:28advantageous to move forward.
56:30So thanks so much. Ashley
56:31Marcus. Thank you so much for having
56:33me absolutely take care. Take care.