Epigenetic regulation of immune evasion and drug resistance in melanoma and beyond

Transcript

• 00:00Got it. So it's my distinct pleasure
• 00:03to introduce Chen Yan to us today.
• 00:06He's one of the invited speakers for
• 00:08this year for the Melanoma program.
• 00:10So for those that don't know,
• 00:11Melanoma program is a fairly well
• 00:14established 1 going back to the 1980s
• 00:16when we started the first what wasn't me,
• 00:18other folks started the first
• 00:21interdisciplinary disease team,
• 00:22John Kirkwood and Steve Arians specifically.
• 00:26And then as the years went by,
• 00:27Ruth Taliban, who's sitting here,
• 00:29wrote the first version of the Yale.
• 00:30Or in skin cancer first funded in I
• 00:33think 2006 or 7 or something like that?
• 00:36We just submitted the 4th iteration.
• 00:40So one of the best things about working
• 00:42here is actually our colleagues and I
• 00:44think Chin actually exemplifies that.
• 00:46So you came to us from from Harvard where
• 00:50he worked in the lab of Bill Kalen,
• 00:52actually on epigenetics and renal
• 00:53cell carcinoma.
• 00:54But at some point it became clear
• 00:56that some of the things that he was
• 00:58studying were very applicable to
• 01:00Melanoma as well and he submitted a
• 01:03developmental research project to
• 01:04the sport in its previous iteration.
• 01:06And that subsequently blossomed
• 01:08to a full project.
• 01:09We are thrilled to have Chen working with us.
• 01:11We couldn't,
• 01:12we couldn't ask for a better collaborator,
• 01:15both in terms of his scientific depth
• 01:16and in terms of his personality.
• 01:18He's definitely one of us.
• 01:19And I actually don't care that he's the
• 01:21scientific Co director of the breast unit.
• 01:23As far as we're concerned, he's ours.
• 01:25So without further ado,
• 01:26chin, the floor is yours.
• 01:27Thank you.
• 01:31Well, thank you Harry for your kind
• 01:33introduction and and and I was also
• 01:35like to thank my normal program for
• 01:37nominating me here to present here.
• 01:39I would say Cancer Center ground is
• 01:42one of the event that actually led
• 01:44me to work on Melanoma and on my way
• 01:48back from Grandma's talks and I was
• 01:50working together with Marcus Bosenberg.
• 01:52I bought a decade ago and we were
• 01:55talking about Jerry 1B who might be
• 01:57which might be important in Melanoma.
• 01:59I was working on Jerry one.
• 02:01Because I generally knockout my and well,
• 02:04we just started the collaboration and
• 02:06it's a very fun collaboration and this is
• 02:08something I'm going to tell you today.
• 02:13So let me get this started.
• 02:17Fixed the pointer.
• 02:22So this is my disclosure.
• 02:25So what I'm going to do is first
• 02:27you give you a very quick overview
• 02:29of cancer epigenetics and then you
• 02:31tell you two stories related to
• 02:33this histone demethylase KDM 5B,
• 02:35how it recognizes drug resistance
• 02:38and immune evasion.
• 02:40So as many of you know,
• 02:43the epigenetics is study of
• 02:45health heroical traits that does
• 02:47not depend on the underlying DNA
• 02:49sequences and the major epigenetic
• 02:51mechanism include DNA methylation.
• 02:54Put his own structure,
• 02:56histone modifications and non coding on it.
• 02:58There's a number of regulators of
• 03:01IPG netting mechanism including the
• 03:03coronary modernness which are involved
• 03:06in moving the nuclear zones around
• 03:08and rider eraser and the readers
• 03:11of histone or DNA modifications.
• 03:15So what I'm going to tell you
• 03:17today mainly focus on KDM 5B which
• 03:19is an eraser which is involved in
• 03:22removing a certain modification
• 03:23and sandbag one which I'm touched
• 03:25upon which is the right approach.
• 03:30So many of you are quite familiar
• 03:32with this hallmarks of cancer
• 03:34and what I'm going to tell you a
• 03:37little bit about is the immune,
• 03:39the immune invasion that
• 03:41cancer cells have to achieve.
• 03:43And if you look at it on the right side,
• 03:46this is a new,
• 03:47those are new hallmarks that have
• 03:50been added to the hallmarks of
• 03:52cancer and two of which actually
• 03:54quite related to epigenetics,
• 03:56including unlocking phenotypic.
• 03:59Plasticity and epigenetic reprogramming.
• 04:03So that's what I'm going to tell you today.
• 04:07So as many of you know epigenetic can
• 04:11epigenetics can regulate many of the
• 04:14cell fate and also a lot of mechanisms
• 04:17are involved in anti tumor immunity
• 04:20and just on the tumor cells for example,
• 04:23it has been shown DNA machination,
• 04:26histone modifications have been
• 04:28involved in regulating tumor antigen
• 04:31expression and cytokine secretion,
• 04:33PDL one expression and
• 04:35also chromatin structure.
• 04:37Have been shown to be important
• 04:39to response to cytotoxic attack,
• 04:41and those modifications are also
• 04:43important on other immune cells,
• 04:46including cytotoxic T cells,
• 04:48dendritic cells and macrophages,
• 04:50which is not duplicated here.
• 04:53So just a brief introduction on my
• 04:55laboratory and we are interested
• 04:56in cancer epigenetics of course.
• 04:59And one of the area we are interested
• 05:01in is a cancer metastasis shown here.
• 05:04Just one of the example where we showed
• 05:07one of the target called CCR two is a
• 05:10driver of breast cancer metastasis.
• 05:13And you can look at here,
• 05:15if you knock down CCR two,
• 05:16you can suppress the ability of those
• 05:18breast cancer cells to metastasis to the
• 05:20lung and if you overexpress CCR two,
• 05:22you.
• 05:22And rescue this phenotype.
• 05:24And of course we are very interested
• 05:26in the immune invasion part of the
• 05:28talk I'm going to talk about then and
• 05:31this is something that I will mention later.
• 05:33And so I'm not going to go over this figure.
• 05:36And we are also interested in drug
• 05:38resistance and I will tell you about our
• 05:41work on the drug resistance in Melanoma,
• 05:43but this is a diagram actually found a.
• 05:47Had breast cancer walk where we
• 05:49showed that trastuzumab resistant
• 05:51cells have increased oxidative
• 05:54phosphorylation and if you block
• 05:57oxidative phosphorylation with only a,
• 06:00if you combine that with transfusion level,
• 06:02you can actually regress the tumor
• 06:05formation by the drug resistant cells.
• 06:09As a matter of because we
• 06:10are interested in the area,
• 06:12we are also interested in
• 06:14developing epigenetic drugs.
• 06:15And I will tell you some of the work
• 06:18on KDM 5 inhibitor development.
• 06:20And this is a some work that we have
• 06:23done a couple years ago where we
• 06:26characterized I potent bromodomain
• 06:28inhibitor where we show that this
• 06:31bromodomain inhibitor and HW 870 can
• 06:33not only inhibit the ability of the
• 06:36cell tumor cells to grow but you can.
• 06:38Also hit on the macrophages by
• 06:41suppressing the expression of CSF 1A,
• 06:44critical regulator of macrophage
• 06:46polarization and the macrophage
• 06:49proliferation and this drug actually
• 06:51have entered the phase one clinical
• 06:52trial in in China and moving
• 06:54into phase two very
• 06:55soon.
• 06:57So my laboratory had been focusing
• 07:00on a group of England called KDM 5
• 07:03histone demethylase and and as you can
• 07:06see here this group of vendors have
• 07:09four of them and they they are called
• 07:12KDM 5 ABC D or Jared 1A1B1C and 1D
• 07:15and all of those have this team JC
• 07:18domain which is the Jumanji C domain,
• 07:21it's hydroxylase domain and the by
• 07:24hydroxylation of the methanation.
• 07:26Group and the removal of formaldehyde.
• 07:28They actually can demate the histones.
• 07:32So this group of landline can demonstrate,
• 07:35try and demonstrate nice thing
• 07:37four on histone H3.
• 07:39And because those machination
• 07:41marks are critical marks for
• 07:43actually transcribed genes,
• 07:45so by doing so this group of
• 07:48online can silence transcription.
• 07:51But that's not the whole story.
• 07:52And all those protein actually have
• 07:55other domains including 80 rich
• 07:57interactive domain which is involved
• 08:00in DNA binding and some of the PhD
• 08:03fingers which are involved in binding
• 08:05specific histone modifications.
• 08:07In addition,
• 08:08they can interact with many other
• 08:11proteins involved in chromatin remodeling
• 08:13and transcription recognition.
• 08:15So they have.
• 08:16It has been documented that
• 08:18this group ENDLINE cannot only.
• 08:20The transcription repressor they
• 08:21can be transcription activated
• 08:23in some other settings.
• 08:26So today's talk we'll we'll be,
• 08:28I'll be focusing on on this protein
• 08:31called Kadian 5B or Jerry 1B.
• 08:33Also another known name
• 08:35is called the PLU One.
• 08:38Because there's a number of.
• 08:41Evidence showing that uh
• 08:43Kadian 5B has oncogenic role.
• 08:46It was shown to be overexpressed
• 08:47in many cancer types,
• 08:48including skin cancer.
• 08:50Initially was identified as a
• 08:53downstream gene downstream of her
• 08:562IN breast cancer because it was
• 08:59shown to be downregulated by anti to
• 09:02anybody in her two overexpression cells.
• 09:05And these have been shown by 90 points
• 09:07group that is amplified in luminal
• 09:10breast cancer and it's a potential
• 09:12luminal linearity driving oncogene
• 09:13and we have shown in any in mouse.
• 09:18Me, I'd be single cells that are
• 09:22Jerry 1B can recruit Gallant St to
• 09:25regulate Fox A1 expression and that
• 09:27contribute to estrogen receptor
• 09:29target gene expression and in
• 09:31fact if you look at the estrogen.
• 09:35Except the positive tumors
• 09:37in for breast cancer,
• 09:38higher activity of Jerry won't
• 09:41be OK and 5B is correlated with
• 09:46poor prognosis of those patients.
• 09:50And and then you point out group
• 09:52has also shown that Kadian 5B can
• 09:55promote transcriptomic heterogeneity
• 09:57and this actually contribute to the
• 09:59therapeutic resistance and this is
• 10:02just one of the mechanism that this
• 10:05could contribute to resistance.
• 10:07I will tell you more about our
• 10:10work on a different angle.
• 10:12In addition,
• 10:13when we deplete KDM 5B first
• 10:16initially in breast cancer cells
• 10:18in syngeneic mouse model,
• 10:20you can see down regulation of
• 10:22KADIAN 5B can decrease the ability
• 10:25of those tumor cells to grow.
• 10:27And it was shown by Mihan honing
• 10:31scope that if you suppress.
• 10:35Expression in normal cells initially,
• 10:37those tumor cells actually grow faster.
• 10:39However, after you serial transplantation,
• 10:42those cells still crash,
• 10:43so suggesting that it's required
• 10:46for Melanoma maintenance instead of
• 10:49putting refreshing initial proliferation.
• 10:51And they was shown in multiple groups
• 10:54including ours that KADIAN file be
• 10:56is involved in drug resistance and
• 10:58shown here just one of the example by
• 11:01actually by a company constellation
• 11:03where they showed in multiple cancer
• 11:05cell lines including Melanoma.
• 11:06Here if you compare the effect of
• 11:10Canadian five inhibitor on parental
• 11:13cells or drug tolerant persister
• 11:17cells if you actually in this
• 11:19case they did a pre treatment of.
• 11:21Both S and and they should have shown
• 11:25that the KADIAN 5 inhibitor cannot
• 11:28inhibit the growth of the parental cells,
• 11:31but they can prevent the emergence
• 11:35of the drug resistant tolerant.
• 11:38Would DP cells or drug tolerant
• 11:41persister cells or drug resistant cells?
• 11:44In prostate cancer if we cost the
• 11:49KADIAN file be knockout model to
• 11:52the P-10 knockout model in process
• 11:55specific deletion and where you
• 11:57can see P-10 knockout model can
• 12:00form a prostate cancer.
• 12:02But if you get relocation 5B you can
• 12:05normalize the those those prostate
• 12:08tumors basically you can see the
• 12:12the the size is much smaller.
• 12:15Now I want to move back to Melanoma
• 12:18because this is a focus on our talk today.
• 12:221st when we looked at the TCA data set,
• 12:25this was done by Goran, a tenant in
• 12:28the graduate student at that time.
• 12:30In exposing like who is final right now?
• 12:34Where he showed that high
• 12:37expression is associated with poor
• 12:40survival of Melanoma patients.
• 12:43So now we decided to look at the
• 12:47Melanoma when we when we followed some
• 12:50of the work from Marcus Bosenberg.
• 12:53I have about my normal propagating cells.
• 12:57Was published more than a decade ago that
• 13:00if you look at the mouse Melanoma cells,
• 13:03you can sort them to three
• 13:06different populations,
• 13:07the P75P-75 positive cells,
• 13:11CD 34 positive cells or the
• 13:14double negative cells.
• 13:15If you look at the ability
• 13:17of the cells to form tumors,
• 13:19the CD 34 positive cells can form
• 13:23tumors very efficiently and the
• 13:25double negative cells can do so.
• 13:28With less efficacy but still works
• 13:31and the PDP 75 positive cells
• 13:34do not actually form tumors if
• 13:36they put them into modern mice.
• 13:39So we decided to look at this more
• 13:43systematically and when this is
• 13:45just a diagram show a table showing
• 13:47and many of the Yale University
• 13:50mouseman normal cell lines generated
• 13:52by Marcus Bosenberg Snapstory and
• 13:54those cell lines are generated was
• 13:57fun back six animals and you can do
• 14:00use those and use those cells for
• 14:05syngeneic transplantation experiments.
• 14:07And two of the cell lines we.
• 14:09Used here uh Young 11.7 which will
• 14:13actually I will use it also later
• 14:16on on for e-mail invasion studies
• 14:19and also young ones 3.3 cells.
• 14:21The reason why we chose those cells
• 14:24because they only have two populations
• 14:26so these 34 positive and city 34
• 14:28negative both of them can form too much.
• 14:30So this provide a nice system to look at
• 14:34the the population changes and when we put.
• 14:38Drugs on onto them.
• 14:41So we used the because those
• 14:44are mutant tumors and we treat
• 14:48those cells with rough inhibitor.
• 14:50In this case we use actually
• 14:52use the PX4 or three, two over.
• 14:57Stephanie.
• 14:57Umm,
• 14:57as you can see here,
• 15:00if you compare the parental cells and
• 15:02you have more CD 34 positive cells.
• 15:04If you look at the resistance the
• 15:07drug resistant cells you have
• 15:10which we delicate as the Yom Young
• 15:131.73 R or resistance,
• 15:15they have more city 34 negative cells.
• 15:18When you look at the the effect
• 15:22of the Bureau of inhibitor on
• 15:24those soap sub populations,
• 15:26you can see 3034 negative.
• 15:28Those are more resistant to be
• 15:32off inhibitor treatment because
• 15:34there's less growth inhibition.
• 15:37And this phenomenon is also reversible.
• 15:41If we treat those,
• 15:42you can see that they shifted
• 15:45to the left side,
• 15:46meaning CD 34 negative cells.
• 15:49However,
• 15:49if you remove the drug after a couple
• 15:52passages and they will shift it back
• 15:54to the parental cell population.
• 15:56So one of the things that was
• 15:58actually who it was a graduate student
• 16:01once Marcus and I basically should
• 16:04notice that there's an increased
• 16:06expression of KDM 5B if we treat
• 16:09those cells with BRAF inhibitor.
• 16:11And this is shown in young
• 16:141.7 cells, 3.377 cells.
• 16:15But also when you compare the parental
• 16:18with the resistance cells you see the
• 16:21similar increase of KADIAN fab expression.
• 16:25And this is reversible if you take
• 16:28out out and be rough inhibitor and
• 16:31the expression drops down and it's
• 16:34showing 1.7 cells as well as 3.3 cells.
• 16:39So when we did the genetic experiment
• 16:43when we knocked down kidding 5
• 16:46expression by a as shown here.
• 16:49We can see in the one point 11.7 cells,
• 16:54there's a decrease of CD34 negative
• 16:57cells after we deplete eighteen 5B.
• 17:00When we look at the phenotype and
• 17:02it's consistent to what other people
• 17:05have seen in other Melanoma setting,
• 17:07if you knock down killing five,
• 17:10you actually increase the ability
• 17:12of them to grow in vitro.
• 17:17And then those cells are actually
• 17:21more sensitive to inhibitor treatment?
• 17:25So this is not only.
• 17:28Two in most cells but also in human cells,
• 17:32this is you Max cells.
• 17:35If you knock down Killian 5B
• 17:37and you can see induction HPK
• 17:394 trimethylation which is the
• 17:42substrate of the enzyme and you
• 17:45can see those cells grow faster.
• 17:47However, they are less sensitive,
• 17:51they're they're more sensitive
• 17:53to BF inhibitor treatment.
• 17:57And if you look at this in animal models,
• 18:00uh, similar things happens when we treat
• 18:03cells with borough inhibitor and you can
• 18:06see KADIAN file being level increase
• 18:09and if you take away the inhibitor,
• 18:12you can see the level drops down.
• 18:18So Umm, and then we look at the if you
• 18:20look at the population of the cells,
• 18:23you can see increased.
• 18:26City City for negative cells.
• 18:30When we treat the cells
• 18:33with Burrough inhibitor,
• 18:34when you take out the inhibit that way
• 18:37and then those would not normalize.
• 18:40So Umm, and this is all consistent
• 18:43with our data and others have shown,
• 18:46which you're not showing
• 18:47here on that KADIAN filing.
• 18:48Hebetor can suppress the emergence
• 18:51of drug resistance cells.
• 18:53So to summarize this part,
• 18:55we see we have showed that 634
• 18:57negative cells are more resistant
• 18:59to BRF inhibitor treatment and BF
• 19:02inhibitor can increase C30 four
• 19:04negative cells and you can induce
• 19:07KADIAN file be up recognition and
• 19:10this is reversible and kadian Fabian
• 19:13N can reduce this population cells and
• 19:17induce drug resistance sensitivity.
• 19:20So now I want to switch switch gear
• 19:23to talk about uh immune evasion
• 19:25and firstly I want to start with
• 19:27this cancer immunity cycle on which
• 19:29many of you know have seen before.
• 19:32Basically this is a diagram showing
• 19:35that the cancer cells interact with
• 19:38the immune system and and there are
• 19:41many ways that cancer cells have
• 19:44adopted to evade immune evasion
• 19:47to evade the immune response.
• 19:49So as a matter of fact,
• 19:50because of this mechanism and some drugs
• 19:54have been developed including the anti PD1,
• 19:57PDL one anti 4 antibodies as well as the
• 20:02ways to push the effect of on the T cells.
• 20:06However,
• 20:06there's not much he's really actually
• 20:09known about the trafficking of T
• 20:11cells to tumors and the infiltration
• 20:12of the T cells into the tumor
• 20:15at that time when we started.
• 20:18And what's known about epigenetics,
• 20:20uh, in this setting,
• 20:22many of you are quite familiar with
• 20:25this concept about code tumor and
• 20:28hot tumor code tumor are not really
• 20:31responsive to another treatment,
• 20:33but the hot tumor will enable them to
• 20:37be responsive to even checkpoint block.
• 20:41And a sub couple for epigenetic.
• 20:43Uh regulators have been shown
• 20:46to be critical for this.
• 20:50Code to how the transition and
• 20:54if we treat this the tumors with
• 20:57a couple of inhibitors against
• 21:00those targets like DMT inhibitors.
• 21:03Two inhibitors. You can ship them to
• 21:06be more hard to become more hot hot.
• 21:10Um, in some of the settings,
• 21:12not in all the settings.
• 21:15And this is kind of related to what
• 21:18we are trying to do and at that time
• 21:22actually a couple of years ago before
• 21:25that and we have looked at the cadian 5B.
• 21:29And how it's related to other genes when
• 21:33we look at the TCA Melanoma data set?
• 21:36And to our surprise,
• 21:38actually KADIAN 5 expression was
• 21:40shown to be negatively correlated with
• 21:43many of the immune related genes.
• 21:46And if you look at those top
• 21:48signaling pathway,
• 21:48those are all immune system related
• 21:50genes and those are negative
• 21:52coordinate with expression.
• 21:53If you look at the the identity
• 21:56of those genes,
• 21:57those shown here are the gene
• 21:59names and on the right side of
• 22:01the Spielman score and you can see
• 22:03many of the silo kinds,
• 22:05for example interferon gamma and
• 22:10TNF A6796 O 10 which are involved in
• 22:12T cell recruitment are all negative
• 22:14coordinate with cadian fair expression.
• 22:17And some of the targets for immune
• 22:19checkpoint blockade PDL one CPT
• 22:21for also negative coordinate
• 22:23with KADIAN fabric expression.
• 22:24This will be important when we
• 22:26are trying to look at the e-mail
• 22:28checkpoint blockade resistant tumors.
• 22:32So when we looked at the KDM 5 be
• 22:35expression protein expression in
• 22:37melanomas and if you compare nonresponse
• 22:41boundaries with and responders,
• 22:43we can see increased expression location
• 22:455B which is shown in red in those non
• 22:49responders compared to the responders
• 22:51and and the quantification is shown here.
• 22:55So this motivates us to look at the role
• 22:57of Canadian file be using animal models.
• 23:00So as I mentioned earlier.
• 23:02Um, Marcus Bosenberg snapped,
• 23:04had generated a series of
• 23:07why UM or young models.
• 23:09Uh, one of the models that we started
• 23:11to use is this Yamaha 1.7 models.
• 23:14Yeah, this stand for ER stands
• 23:17for exposed to radiation,
• 23:19meaning those cells will radiate
• 23:22so that they have more mutations,
• 23:25they can generate more antigens that
• 23:28can be recognized by the immune system.
• 23:31So when we knocked out Kadian 5B in
• 23:33those cells, as you can see here,
• 23:35those cells can initially can grow,
• 23:38then they got fully rejected after a while.
• 23:41And the more importantly when we challenge
• 23:45those animals with the cells control
• 23:48cells which normally can grow very well,
• 23:51they never grow up.
• 23:53So this is very important imagine that if
• 23:56we have to treat patient with a drug and
• 23:59case for example in this case KADIAN 5
• 24:02targeting drug and those patient will not,
• 24:06will not have recurrence because
• 24:08they they will should never grow up
• 24:12because the immune memory response.
• 24:14So this is actually translated
• 24:15to 100% survival,
• 24:17which is uh, this is great.
• 24:20And then we look at the UM uh T
• 24:23cell infiltration when we compare
• 24:25the control cells and KADIAN file B
• 24:29knockout tumors at the very early stage,
• 24:32you can see the T cell infiltration
• 24:34either by e-mail,
• 24:35histochemistry as well as fax analysis.
• 24:39And there's another way to say that
• 24:41this is immune system dependent on we
• 24:44compared the ability of cells to grow
• 24:47in wild type cell wild type mice or rats.
• 24:50Deficient mice and as you can see here
• 24:54the the the the B6 is the wild type.
• 24:58Those two curves are what I have
• 25:00showed you before and if you look at
• 25:02the the ability of cells you grow in
• 25:05rectification mice the control goes
• 25:07here and then can be deficient once grow
• 25:11kind of similarly although slightly slower.
• 25:14So this basically set up the
• 25:17stage that Kadian 5B which is
• 25:20critical for immune evasion.
• 25:23So the next question is what's the mechanism,
• 25:26right?
• 25:27So how to?
• 25:29To understand this,
• 25:30we are look dead on a sequencing
• 25:33comparing Yammer 1.7 cells,
• 25:35probably knockout versus wild type.
• 25:38And we can see there's an induction
• 25:40of a lot of signaling pathway
• 25:43involved in DNA on a sensing pathway
• 25:46and showing here that generation analysis,
• 25:49the instrument parts where you
• 25:52can see there's an enrichment
• 25:54regarding like research pathways
• 25:56at Sonic DNA sensing pathway,
• 25:58those are all induced after
• 26:00you get rid of Canning Vale B.
• 26:02So now how does this actually work?
• 26:05And are those sensing pathway
• 26:07critical for the function of KDM 5B?
• 26:10As as many of you know that the
• 26:12double strand DNA double strand on
• 26:15the Ascension sensed through those
• 26:17pathways and double strand DNA is
• 26:19sensed through cgas sting pathway
• 26:21to big TV K1F3F7 and the interferon
• 26:25response and this need to induction
• 26:28interferon stimulated genes.
• 26:30And the double stranded on a could
• 26:32be sensed through regard MDA 5
• 26:34maps Altos three and basically
• 26:36also signals through and activate
• 26:38interference and steam engines.
• 26:40So what we did is we knock cloud
• 26:43each single component through
• 26:45this pathway and see what happens
• 26:48when we knock out the Canadian 5B.
• 26:49As you see it does not grow in the
• 26:52wild type cells do grow if we combine
• 26:55that with knockout of the mouse or
• 26:58steam and the important mediator of.
• 27:00Christian Arnie or double Strand
• 27:02DNA sensing pathway,
• 27:03you can see partial rescue right here.
• 27:06If you get rid of both of them
• 27:09you see much better rescue.
• 27:11So we went on and when the upstream
• 27:14when we get rid of the sea gas or
• 27:17MDA 5 and you can also see partial
• 27:20rescue if you get rid of both of them.
• 27:24You can see pretty good rescue response
• 27:27in this case when in two independent.
• 27:31So how many established that?
• 27:34Now we want to understand why
• 27:36those pathways are activated.
• 27:38So why would the sense that we notice
• 27:41is that when we compare the control
• 27:44cells with the knockout cells,
• 27:46we can see the induction of double
• 27:50stranded on a in Kadian 5B knockout
• 27:53cells and then we have seen this
• 27:55also in two months as well.
• 27:57And this motivated us to go back and
• 28:01to realize our only sequencing data.
• 28:04For expressing those retro elements
• 28:08and those retirement are part of junk
• 28:11genome and then people are totally
• 28:13normally ignore and it turned out
• 28:16to be very important in this case.
• 28:18And what we have seen is that
• 28:20we knock out Kadian 5B,
• 28:21we can see induction of those
• 28:24retro elements and especially
• 28:26some of the endogenous retrovirus.
• 28:29Animals.
• 28:29And the one with which is called MOV 30 and
• 28:34you can see multiple of those showing up.
• 28:37And then we study is actually
• 28:40critical for the interferon response
• 28:42because if we knock down M30 with
• 28:45SRAM as you can see here,
• 28:47you can see the down recognition or
• 28:51interference imagines suggesting that
• 28:53this is at least partially contribute
• 28:56to the interferon induction and maybe
• 28:59the response to e-mail evasion.
• 29:02And the one thing that we were
• 29:04puzzled about is that since I
• 29:06showed you that both DNA and only
• 29:08sensing password are required,
• 29:10where are those DNA coming from?
• 29:12And we postulated that those
• 29:14DNA will be coming from
• 29:16reverse transcription of those only
• 29:19species that that would generate
• 29:23through after we get rid of Kadian 5B.
• 29:27And one experiment we did is use
• 29:31reverse transcriptase inhibitor.
• 29:32This is a cocktail of reverse transcriptase
• 29:35inhibitors used for HIV treatment and
• 29:37where we see if you treat the cells with
• 29:40those reverse transcriptase inhibitor.
• 29:42You can see suppression of the interference
• 29:46imaging expression suggesting that this
• 29:49DNA might be created through this pathway.
• 29:52So now with all those mechanisms,
• 29:54now the question is can we
• 29:57translate it to targeting this?
• 29:58The quick question is that can
• 30:01we induce under tumor immune
• 30:03response with KDM 5 inhibitors?
• 30:05So as I mentioned because there's a lot
• 30:09of evidence showing that KDM five are
• 30:13critical for cancer initiation progression.
• 30:17So we have started working on
• 30:19this on to by multiple methods to
• 30:23develop locating file inhibitors.
• 30:26So initially with that panel ground from
• 30:29Yale Small Molecule Screening Center
• 30:32now called Yale Center for Monica.
• 30:35Discovery,
• 30:35we have done some screening,
• 30:37biochemical screening for KADIAN
• 30:405D methods inhibitor.
• 30:41And initially we did 100,000 compounds
• 30:44with those as a preliminary data we
• 30:46were able to obtain support for NCI
• 30:49experimental security program where we
• 30:51were able to assemble a team about 30
• 30:55scientists to to develop those inhibitors.
• 30:58So we have done a high school screening
• 31:01about 200,000 compounds those are high
• 31:03quality compounds and have done extensive
• 31:06medicinal chemistry optimization of some
• 31:08of the compounds and we have solved.
• 31:1225 uh crystal structures,
• 31:14can you find a way with different inhibitors
• 31:16and shown here just the two of them,
• 31:19basically showing that they combined
• 31:22very tightly to the active site.
• 31:25One thing that I want to mention that those
• 31:27inhibitors are all pancaking from inhibitors.
• 31:29They hit both all Canadian five
• 31:32family members because the
• 31:34Catholic side is very similar,
• 31:37very similar for all those
• 31:40Canadian 5A family members.
• 31:44So even with with those and we decided to
• 31:48ask what the Canadian five inhibitor can do.
• 31:52And the one thing that we decided to do is
• 31:56we selected four KDM 5 and inhibitor here.
• 32:00Those are high quality specific
• 32:02calling from inhibitor.
• 32:03As you can see here they all induce
• 32:05HK for translation which is the
• 32:07substrate of the reaction and then
• 32:10did not do anything to the other
• 32:12of the histone modifications.
• 32:14And we did those actually in I'm 6-7
• 32:17and multiple human breast cancer cells
• 32:20and and when we looked at the gene
• 32:23expression changes to our surprise we
• 32:25see the top pathway that's upregulate
• 32:28are those interference signaling
• 32:30pathway at that time I was like
• 32:32interfering pathway is not something
• 32:34I want to work on not so much now.
• 32:38So, so anyway,
• 32:39so when we see there's an induction
• 32:41interfering pathway and we have
• 32:43seen this in multiple cell lines,
• 32:46multiple drugs.
• 32:47And we were able to.
• 32:50Understand how this actually worked.
• 32:52And at the end we were able to
• 32:55show that KADIAN 5 inhibitor can
• 32:58induce H3K4 termination at the
• 33:00steam promoter and by doing
• 33:02so, it actually induce Stein expression.
• 33:06And this need to the interferon
• 33:09stimulated gene expression and
• 33:11listening to the T cell infiltration.
• 33:15So this is a little bit different from
• 33:18what other people have been trying to.
• 33:22Uh, to activate this pathway
• 33:24through either using Steam agonist,
• 33:26which the limitation of those drugs and is.
• 33:31Many of the cancer cells you
• 33:33actually have Stein silence.
• 33:35So by inducing Stein and this
• 33:37provide another mechanism how we
• 33:39can activate this signaling pathway.
• 33:42So now and we actually tested KADIAN 5
• 33:45inhibitor in multiple human Melanoma
• 33:48cells and we can see induction of
• 33:51sting and in this case in Western
• 33:54border here and the induction
• 33:56of interference steam engines.
• 33:59And so we thought this is the shoe
• 34:01bat and the Canadian five inhibitor
• 34:03is going to work.
• 34:04And to our surprise, nothing happened.
• 34:07And when we took put this in
• 34:09the mouseman normal cells,
• 34:10the Yammer 1.7 cells,
• 34:12the model system that we have tested.
• 34:142 into 2 Canadian farm inhibitor and
• 34:19the retro element was were not induced,
• 34:23the interference images were not induced,
• 34:26nothing happened.
• 34:27So we did not want to give up
• 34:30because we thought maybe there's
• 34:32some limitation of the drugs and so
• 34:35we did those rescue experiment to
• 34:37understand whether the critical the
• 34:39community activity is required or not.
• 34:41So what we did is that for.
• 34:44I'll call it Yama cells.
• 34:45We reintroduced either wild type or
• 34:48mutant KADIAN 5B into those cells.
• 34:51Those mutant are dead Canadian 5B.
• 34:55And as you can see here,
• 34:57in both cases you can see wild type
• 34:59or mutant Canadian 5B can suppress
• 35:02the expression of retro elements and
• 35:04those interference stimulate genes.
• 35:06Moreover,
• 35:07both of those can induce the
• 35:10growth of those tumors.
• 35:12So now what?
• 35:13Now we are back to the starting point
• 35:16and kind of depressed right at time.
• 35:19So we went on and decided to look
• 35:22at all the repressive mechanisms
• 35:24and to see which one might work.
• 35:27And one of the things that
• 35:28we decided to look at is,
• 35:29is actually inhibitor for
• 35:30example and those are two higher
• 35:32quantities that true inhibitor,
• 35:34it did not do much either.
• 35:36Umm, and then uh,
• 35:39it.
• 35:39There's some clue that HK9
• 35:41message transfers would work,
• 35:43and we use a pretty dirty
• 35:45actually actually canine method.
• 35:46Transfers inhibit the code channel thing
• 35:48and it can inhibit actually K9 translation.
• 35:52You can see induction of MOV 30 and some
• 35:55of the interferon stimulated genes.
• 35:58So now there are multiple HK9
• 36:01methyltransferase and so we knocked out
• 36:03each single one of them to see which one.
• 36:06Is critical when we knock out the G9A or
• 36:10SO39H1 and it did not really do anything.
• 36:12But when we knockout set
• 36:14B1 which is shown here,
• 36:16you can see robust induction on mobile 30.
• 36:20So this is what was a great news.
• 36:22So at that time we're quite excited.
• 36:25And then when we did call e-mail
• 36:28precipitation experiment,
• 36:29we actually can see that KADIAN
• 36:31file B can interact with set DB1.
• 36:34When we did set DB1 IP,
• 36:36that's the pull down of Kadian 5B by Sade 1.
• 36:42And then uh, this is quite exciting.
• 36:46Then we decided to map the binding of
• 36:50KDM 5B and set DB1 and shown here just
• 36:54the the the heat map where we ranked
• 36:58those KADIAN file B target genes where
• 37:00you can see KADIAN file B combined
• 37:02them very well in wild type cells,
• 37:05not so much in knockout cells.
• 37:07When we look at set DB1 binding,
• 37:10you can see amazingly overlapping
• 37:12binding of the set DB1 and the HTK 9
• 37:17formation which is the product of set
• 37:22DB1H3K9 formation is a repressible mark
• 37:25that can suppress gene expression.
• 37:28And to our surprise, when we look at
• 37:31the HK4 translation and imagination,
• 37:33which are the substrate of the Kadian 5B,
• 37:37you can actually do not see much effect.
• 37:40Suppress a suggestion that KDM 5B
• 37:43function add message function is
• 37:45probably silenced in this setting.
• 37:47So now those are all.
• 37:53Important and now we want to look at this in.
• 37:58Drug resistance setting and
• 38:00in this case e-mail checkpoint
• 38:02blockade resistance setting.
• 38:04When you look at the KTM 5 be expression,
• 38:06it's actually lower in the patient
• 38:09with computer response to anti
• 38:11PD1 blockade compared to the ones
• 38:14with the progressive disease.
• 38:16So this is suggesting that if
• 38:18we can lower expression you can
• 38:20make the reason tumor sensitive.
• 38:23Indeed that's actually true and
• 38:25we use this young 1.7 model.
• 38:28Which is the parental model for the
• 38:32Yammer 1.7 I have showed you before.
• 38:34This model is resistant to all immune
• 38:39checkpoint blockade, PD1 blockade.
• 38:41If you look at this, nothing happens.
• 38:43If you throw CTO four anybody
• 38:46on then nothing happens.
• 38:47If you combine them still nothing happens.
• 38:50In this very refractory model,
• 38:53you can see if you get relocating 5
• 38:55you can already see some response.
• 38:57If you combine with PD1 blockade
• 39:00you see synergistic response.
• 39:02It can extend the survival of those animals.
• 39:06You can basically double the
• 39:08survival of those animals.
• 39:09And this is just one of the PD1
• 39:11resistant model and when we look at
• 39:13the another model which is the Yammer
• 39:15interfering gamma resistant model,
• 39:17you can see similar phenotype.
• 39:21So lastly, is this also true in humans?
• 39:26When we compare the the KADIAN 5
• 39:29expression with the indulgence
• 39:31retro elements part of the category
• 39:34of the retro elements,
• 39:35you can see the the ones with high
• 39:37Acadian 5 be expression was shown.
• 39:40On this you have no expression
• 39:41of some of the.
• 39:44You always showing here just one example
• 39:48RV 2637 and it's anti correlated
• 39:51with Kaden 5 expression and the
• 39:53expression is correlated with the
• 39:55better response to PD1 blockade is
• 39:58opposite to what we see with PKD and 5B.
• 40:00So to basically to summarize this part
• 40:04of my talk which I showed you that Kadian
• 40:075B can interact with set DB1 and and
• 40:10you can recruit set DB1 to the targets.
• 40:13To deposit actually K9 traumatization
• 40:16to silence retroelements,
• 40:17if you gather with locating 5B you
• 40:19can activate endogenous retroelements.
• 40:21You can activate double stranded
• 40:23on Ascension pathway and double
• 40:25strand DNA sensing pathways through
• 40:27the reverse transcription process.
• 40:29It I need to the better representation
• 40:31of the MHC one and the cytokine secretion
• 40:35lead to higher immunogenicity and better
• 40:38response to e-mail checkpoint blockade.
• 40:41So although with the first group
• 40:43that show that Kadian 5B is critical
• 40:47for immune evasion,
• 40:48we are not the first group to so
• 40:50shows that B1 has this function and
• 40:52multiple groups about the similar
• 40:54time show that said B1 is involved in.
• 40:59Suppressing tumor immunogenicity and
• 41:03and and this is just multiple papers
• 41:06basically by multiple groups and this
• 41:08add to basically add to the what.
• 41:12Uh, what?
• 41:13What do we know about epigenetic
• 41:15regulation of the viral mimicry pathway?
• 41:20Basically I've showed before that double
• 41:23DMT and SD one can do this and here we
• 41:26just showed up and said one can do this
• 41:29and all those inhibitors will be able
• 41:32to induce those biometric response and
• 41:35the firm response and better response
• 41:38to e-mail checkable and blockade.
• 41:40So now I would like to thank all
• 41:42the people involved in this and
• 41:45especially Marcus Bosenberg group and
• 41:47where we had the fun collaboration.
• 41:49A decade on collaboration and and the
• 41:53drug resistant work is led by Shawnee
• 41:56anew and Sami Zang and the immune
• 41:59evasion they walked the net by Samin
• 42:03Jan and Samin has actually started.
• 42:07Isn't Professor Ship at
• 42:09Shanghai Tech University?
• 42:11And on the some of the bad formatting works
• 42:13are done by Western East High and the glory,
• 42:16and also like to thank all the
• 42:19youthful members for the kind of help
• 42:23through the course of this project.
• 42:27And when I try to start on Melanoma,
• 42:30the SPORE members welcomed me
• 42:33with open arms and that's how
• 42:36I can get where we are here.
• 42:39And I'd also like to thank all the other.
• 42:41Funding agencies for their support
• 42:43as you can see in a couple of
• 42:46Melanoma Research Foundation,
• 42:47Melanoma research alliance have
• 42:48been very helpful in supporting our
• 42:51research in Melanoma and I would
• 42:53like to thank you all for your
• 42:55attention and I welcome any questions.
• 43:09Or maybe 1 back.
• 43:35Yeah. That's a great.
• 43:36So the question is whether we
• 43:39have tried to combine KDM 5
• 43:41inhibitor with sting agonist,
• 43:43that's great suggestion.
• 43:44And we have thought about this,
• 43:46but we have not had the
• 43:48time to do this experiment.
• 43:50Yeah, which we should have done, yeah.
• 43:54OK.
• 43:56That was a great job. Thank you so much.
• 43:58And went back and forth a little bit
• 44:01between 10:20 and five inhibition
• 44:03and 25 B specific inhibition.
• 44:06And I know that you think the KDM 5B
• 44:09is the most important one. What about?
• 44:13And so we have, we actually have
• 44:18been working on breast cancer and
• 44:20also some other cancer types where
• 44:23we have seen is that in actually
• 44:27maybe I'll show you one slide here.
• 44:29This was just published basically
• 44:32this is MC38 with the colorectal
• 44:35cancer where when we treated those.
• 44:39So those animals, uh tumor bearing
• 44:41animals with KDM 5 inhibitor,
• 44:43you can suppress the ability to grow.
• 44:44So it works incorrect cancer.
• 44:47Also when we look at the breast cancer
• 44:49you can see they have some new efficacy.
• 44:52You can also combine that with
• 44:54PD1 blockade and we can have
• 44:56I would say additive effect.
• 44:57So it works in multiple cancer types.
• 45:02It's just where we need to find
• 45:05the correct cancer types and
• 45:07subtypes even to so that we were
• 45:09able to use those inhibitors.
• 45:13Yeah, yeah. So, yeah,
• 45:15those are all planning.
• 45:17Can you invite me here with us?
• 45:18So, so one of the things that we
• 45:21are trying to do is to develop
• 45:24KADIAN file family members,
• 45:27specific degraders.
• 45:28And with the.
• 45:32Because with the protect or some
• 45:34other similar kind of mechanism or
• 45:36molecular glue type of mechanism
• 45:38you can develop a specific
• 45:40degraders against KDM 5 and we
• 45:42are actually working on that.
• 45:44We have some potential degraders that
• 45:49work specifically on Canadian 5B and
• 45:52some of them work on multiple all
• 45:54kidding 5A in different settings.
• 45:58Online question from City Chin.
• 46:03Yeah, I can. I can read. I can read it.
• 46:05So the question is, do I anticipate?
• 46:09Other epigenetic reader and writer
• 46:13to have similar effect, yes,
• 46:15because actually I have showed
• 46:18you one in one of the diagram.
• 46:21There are multiple other ones on this.
• 46:26OK. Yeah. Once which have been shown
• 46:30have similar effect and although I
• 46:34have to say in different cancer types
• 46:36and they have different effect and
• 46:38we just need to find the right one
• 46:41and that work in the in our setting.
• 46:47OK, that's.
• 46:51Question for you.
• 46:55So you showed that Kenny M5
• 46:57views anticorrelated with all sorts of
• 47:00new vectors, both positive and negative.
• 47:06What about the cell types?
• 47:11DC.
• 47:14Well, that's a great question.
• 47:15We have not looked. Yeah.
• 47:18So you just need to do something
• 47:21also analysis too or just analyze
• 47:23single cell data to see to see that.
• 47:25Yeah, it's great, great suggestion.
• 47:26Yeah, should do that.
• 47:30I don't know.
• 47:33Wonderful mechanistic. Right.
• 47:40My question is regarding Katie M5B.
• 47:43And it's a deck that seemed to be asymmetric.
• 47:49You showed us. I was wondering whether
• 47:51they would be animators that could
• 47:53maybe the scaffolding effect of paying
• 47:565D its interaction with 71 and whether
• 47:59those could be more appropriate for
• 48:01who gets PDL 1 increased response.
• 48:07Yeah, that so answer the question is
• 48:10whether we should inhibit the scaffold
• 48:14function location 5B, which is great.
• 48:17So that's something that we are thinking
• 48:19along the way because we have to first
• 48:22of all we need to identify the domains
• 48:24that are critical for those interaction.
• 48:26And then one of the things that we're trying
• 48:29to do is you to look for those domains
• 48:31that are involved in interacting with
• 48:34said said B1 and then those inhibitors.
• 48:37To have more specificity as you as
• 48:41you suggested to target this pathway
• 48:44and it's probably better than getting
• 48:475 inhibitor or 71 inhibitor which
• 48:49might have some other off target
• 48:51effect that we don't want to see.
• 48:55That's what interesting,
• 48:56because when you think of,
• 48:57for example, LC-1, there are requests
• 48:58that seem to be targeting the.
• 49:04But we know that they actually
• 49:06impact step folding effects,
• 49:08other proteins that play a role in one.
• 49:15I wonder if those types of
• 49:17indicators are out there.
• 49:19Yeah, you could be made, but uh,
• 49:21we we don't have those yet.
• 49:23Work in progress.
• 49:30OK. If no more questions. Thank you.