Age against the Machine: how aging drives tumor progression

Transcript

• 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.