# "Type I Interferon Transcriptional Network Regulates Expression of Co-inhibitory Receptors on Human T cells" and "co-Stimulating Innate and Adaptive Immunity to Treat Melanoma"

December 11, 2020## Information

Yale Cancer Center Grand Rounds | December 8, 2020

David Hafler, MD, FANA and Harriet Kluger, MD

ID5992

To CiteDCA Citation Guide

- 00:00Sure, there's enough time for both of you,
- 00:03so I see folks here.
- 00:05The numbers are going up and appreciate
- 00:08folks logging on welcome everyone once
- 00:10again to Cancer Center, grand rounds,
- 00:12and we're really very privileged
- 00:14today to have two of our exceptional
- 00:17physician scientists presenting.
- 00:19You know, really and frankly,
- 00:21what's exciting is it it
- 00:23once again highlights the
- 00:25extraordinary work in immunology.
- 00:26Immuno biology at Yale and at
- 00:29the impact on this ultimately.
- 00:32In our cancer therapy and in our
- 00:34understanding of cancer biology,
- 00:36so let me turn to our first
- 00:38speaker to ensure we have time.
- 00:41Our first speaker is Doctor David Hafler,
- 00:43who is, you know,
- 00:44is the ugly professor and chair of
- 00:47the Department of the Rolla G and
- 00:49Professor of Immunology, Immunobiology,
- 00:51and David's accomplishments
- 00:52are are really quite Legion.
- 00:54Renee actually prepared a synopsis,
- 00:56and I just said that I want to make
- 00:59sure David has time to present.
- 01:01I won't.
- 01:02Go through all of it,
- 01:04but his accomplishments in
- 01:06terms of understanding.
- 01:08Advancing neuroscience and understanding
- 01:10that human autoimmunity in an understanding
- 01:14how to leverage our understanding
- 01:16of immunology to impacting human
- 01:18disease is really quite impressive.
- 01:21And among his awards include the
- 01:23distal Prize for Ms Research,
- 01:26the University of Miami
- 01:28Distinguished Alumni Award,
- 01:30the American Urology Association,
- 01:32Adams Lectureship.
- 01:34And most recently,
- 01:35and I think a year or so ago,
- 01:38election to the National Academy of
- 01:40Medicine and and David has really
- 01:42been an incredibly engaged member
- 01:44of our Cancer Center faculty.
- 01:46I think David's leadership,
- 01:47I think, has advanced the cause
- 01:50of our brain tumor program,
- 01:51among other things,
- 01:53an David thank you for making the time
- 01:56to share your work with us today.
- 02:00Thank you Charlie.
- 02:01It's really a pleasure to be here.
- 02:04And let me turn this on and.
- 02:08My cell phone, so I'd like to do today
- 02:12is to present some new unpublished
- 02:15work which really epitomizes to me of
- 02:19physician scientists of learning from
- 02:21the patient and just in a nutshell,
- 02:24what I'm going to show you is
- 02:28very fundamental question,
- 02:29which is what induces the checkpoint
- 02:32inhibitors particular PD one Tim three lag,
- 02:363 digit on human T cells.
- 02:39And that's gonna be the nature
- 02:41of the talk that the work has
- 02:43been submitted for publication.
- 02:45It was put online,
- 02:46a bio RX being one's interest in
- 02:48seeing the paper itself and upfront.
- 02:50I want to really, now Stamos Amita,
- 02:53who really really performed
- 02:54this work in our laboratory tone
- 02:56was now an assistant professor
- 02:58and then pursuing this work.
- 03:00It wanted knowledge.
- 03:01My long term collaborator, Vijay Kutru.
- 03:03Yes, you see a Yale,
- 03:04a sticker that he was here
- 03:06helping us recruit students.
- 03:08Don't tell the people in Boston.
- 03:10Enjoy dulberg in the Softmod
- 03:12who did the computational work.
- 03:14So the question is,
- 03:16what are the regulatory mechanism
- 03:18for induction of a Co inhibitory
- 03:20receptors on human T cells?
- 03:22But I'll show you is surprisingly type one,
- 03:25interferons induce Cohen Cohen
- 03:26territory receptors on human T cells,
- 03:29so that's the bottom line of what I'm
- 03:31going to show you over 30 minutes.
- 03:34We worked through the in vitro
- 03:37transcriptional regulatory network
- 03:38for this interferon beta response and
- 03:40then we identified an in vivo model
- 03:42where abara load strongly correlate's.
- 03:44With type one interferon signature,
- 03:46which allowed us to perform an in
- 03:48vivo validation of the in vitro
- 03:51interferon transcriptional regulatory
- 03:52network Co inhibitory receptors.
- 03:54So that's what my talk will be.
- 03:58Now it's been known for a number
- 04:00of years to work.
- 04:02Button from Vijay Kutru and be ready
- 04:04given we've had a program Project
- 04:06Grant 2 program project grants looking
- 04:09Cohen inventory molecules valene
- 04:10sharp for well over 25 years that PD one Tim,
- 04:14three lag three and TIGIT ARCO,
- 04:16regulated and expressed as a module.
- 04:18So here we have.
- 04:20Hopefully you will see the pointer.
- 04:22I won't advance the slide
- 04:24while I'm doing this,
- 04:25but you can see that there.
- 04:28Expression of PD one Tim,
- 04:30three lag three and TIGIT on C4 and CD8
- 04:34cells that their modulated together.
- 04:37And that this is a new spot.
- 04:40I'll 27 here.
- 04:41We have the induction of Tim 3
- 04:44not so much PD one but lag three
- 04:47and TIGIT by I'll 27 you knock
- 04:50down aisle 27 the mouse you lose
- 04:52the induction by aisle 27.
- 04:54That's the upregulation and
- 04:56downregulation by the knock down.
- 04:58Now it's been known for a long time.
- 05:01That type one interferon signatures,
- 05:03or enriching chronic viral infection,
- 05:05and both mouse and humans,
- 05:07and that chronic viral infection
- 05:10induces T cell exhaustion.
- 05:12Really first identified by Rafi
- 05:14Ahmed in the HIV system and
- 05:16in El CMV infection and that's
- 05:19associated with expression and Co
- 05:21inhibitory receptors such as PD,
- 05:23One Tim, three lag.
- 05:25Three antigen is interferon signature
- 05:27with the LC MP model suggesting that
- 05:29there may be an Association with type
- 05:32one interferons and these cone hitori
- 05:35molecules so wish to ask do they
- 05:38induce these receptors again here's
- 05:40why I showed you in terms of mouse.
- 05:44An you know first experiments and when
- 05:47I googled in photograph of human,
- 05:50I swear this is what showed up and I know
- 05:54way mean to denigrate mouse immunologist.
- 05:58By showing this picture,
- 05:59but one can see is that in CD4 cells,
- 06:04either with with no cytokine
- 06:06I'll 27 or interferon beta.
- 06:09This market induction of Tim three lag
- 06:12three and PD one. By interference.
- 06:15So now we go into more depth to show this.
- 06:20Here's how the experiments were done.
- 06:22We took CD4 CD 8 cells.
- 06:24That was CD.
- 06:26That were CD 45 negative positive.
- 06:29That is a naive T cells and
- 06:31stimulate them for non use.
- 06:33Different different time points
- 06:35with CD3 plus minus.
- 06:37I'll 27 and interferon beta and one can see.
- 06:41The induction of here's a control.
- 06:43The market induction of lag three
- 06:45and Tim three with interfere on.
- 06:48Here's the control and he is
- 06:50looking at Tim three PD.
- 06:52One here is a summary of data
- 06:54with Tim three lag through in PD,
- 06:57one individually and the summary
- 06:58of Tim three lag 3P1 positive
- 07:01cells within this market.
- 07:02Induction by type one interferons interferon
- 07:04beta of these Co inhibitory molecules.
- 07:07But surprisingly unlike in the mouse with
- 07:09digit is Co regulated part of the module?
- 07:12These other Co inhibitory molecules in human.
- 07:17We saw that TIGIT use digit expression
- 07:20in the presence of interferon is
- 07:22markedly decreased from 25% down to four,
- 07:2612% from 28% when look the
- 07:28RNA expression we saw there.
- 07:30In fact two modules,
- 07:32one with interferon with Lag,
- 07:353 Tim, three PD,
- 07:37one increase with interferon beta
- 07:40and the other module with digit.
- 07:43The Jennifer subtest.
- 07:44Nine other modules,
- 07:46a CD 160 being decreased by
- 07:48type One interferon.
- 07:49So these data show that in humans
- 07:51there are two modules regulated
- 07:53by interferon that in fact
- 07:55go in opposite directions.
- 07:57Here's a kinetex.
- 07:59Overtime the induction of Tim three lag,
- 08:01three PD,
- 08:02one with the decrease in digit.
- 08:07So just take a step back.
- 08:09Why do we have an interest in Tidjane?
- 08:12I mention this because under the
- 08:14leadership of Antonio Mora we're
- 08:16about to embark upon a phase one
- 08:18clinical trial in patients with
- 08:20glioblastoma with anti TIGIT or anti PD.
- 08:23One or a combination of of the two,
- 08:26working with Jemal eternal
- 08:27and lead in my lab.
- 08:29By Liliana Luca.
- 08:30So why an interest in tinge of this
- 08:33work goes back to 2012 work done by
- 08:35S Duluth Lozano in the laboratory.
- 08:38We've always been impressed with
- 08:41the biologic effects of blocking
- 08:43with anti TIGIT looking at Tibet.
- 08:45The gamut of fear on Gata,
- 08:483RF-9 and and RRC expression.
- 08:51And one can see that with anti TIGIT
- 08:54antibody there's a market loss of
- 08:57these cytokines in culture and if you
- 09:00knock down ticket here within SHR Now
- 09:03you have market increases engagement
- 09:06affair on and decreases dial 10.
- 09:09So comparing PD one antigen,
- 09:11our hands in human systems been very
- 09:13impressed with the effects of ticket and
- 09:16also just comparing Ms two glioblastoma,
- 09:18there really isn't a big difference between
- 09:21PDL one or PD1 between Ms and brain tumors,
- 09:25but there is a virtual absolute
- 09:27difference between TIGIT expression,
- 09:28typically on the CD 8 cells in patients
- 09:31with GBM virtually absent in Ms,
- 09:34he was looking at teacher by
- 09:36flow and tills versus blood,
- 09:38suggesting the potential importance of digit.
- 09:41In the central nervous
- 09:42system for glioblastoma.
- 09:44So first one to work through.
- 09:46After that identification of the
- 09:48effect of type One interferons
- 09:51wanted to work through the in vitro
- 09:54transcriptional regulatory network.
- 09:56So we use the same model
- 09:58that would be regift.
- 10:00Near Youssef used in terms of setting up
- 10:03identifying the TH17A regulatory network,
- 10:05and this is work done by a soft in BJ's lab,
- 10:09so we needed to have higher
- 10:11resolution transcriptomic data to
- 10:13construct the regulatory network.
- 10:15For those of you who aren't engaging
- 10:17in terms of looking at RNA now,
- 10:20what we used to do is to
- 10:22take a T cell stimulate,
- 10:25measure the RNA 4 hours later
- 10:27and say this is what it is.
- 10:30We've learned that their complex regulatory
- 10:33networks and one needs to really do this.
- 10:36The kinetics overtime to construct
- 10:39a dynamic regulatory network.
- 10:41Such a performance.
- 10:42This network we took dive CD4 CD 8 cells,
- 10:45stimulate them,
- 10:46measure them in different time
- 10:47points with control versus type.
- 10:49One interferon did bulk RNA sequencing.
- 10:51We did 34 samples time three
- 10:53replicates with the same healthy
- 10:55donor and we decided that rather
- 10:57than looking at human variation,
- 10:59which is significant mediated by the
- 11:01by the genetics of the individuals,
- 11:04we do what mouse immunologists do,
- 11:06which is pick one strain of
- 11:08mice and study it in detail.
- 11:11And we measured are we did RNA seek RT
- 11:13PCR protein for flow so that this is a
- 11:17transcriptomic analysis of interferon
- 11:19beta high temporal resolution.
- 11:21We so differential expression of
- 11:23gene levels for eight different time
- 11:25points with interferon stimulation.
- 11:27Here's a log 2 expression so we have
- 11:30differential expression patterns.
- 11:31We have an early expression
- 11:33pattern here and here.
- 11:35We have an intermediate expression pattern.
- 11:38A late expression pattern over here and
- 11:40finally a bimodal expression pattern goes up,
- 11:43down and back up.
- 11:46So in performing it just
- 11:49transcriptomic analysis,
- 11:50we looked divided into transcription factors.
- 11:52Here CD four cells with
- 11:54different kinetics and these are
- 11:56different transcription factors.
- 11:58Again, we can see early
- 12:00transcription factors immediately,
- 12:01transcription factors induced
- 12:03and we identified different Co
- 12:06inhibitory receptors and different
- 12:08T cell related genes for both the
- 12:10CD four and for the CDA population.
- 12:13Again, in looking at the effect
- 12:16of interferon.
- 12:17And what it does in terms of
- 12:19the transcriptional networks is
- 12:21critical to look over time 'cause
- 12:23there's a dynamic change in these
- 12:26transcription factors and Co
- 12:28inhibitory receptors overtime.
- 12:29So we identified the most differentially
- 12:32expressed transcription factors and
- 12:34about 20 of them here and these
- 12:37are transcription factors that
- 12:38were differentially regulated and
- 12:40decreased in both CD4 and CD8T cells,
- 12:43and we as a reality check we
- 12:46asked of these word known.
- 12:48Interferon responsive gene.
- 12:50So here's the IFN responsive responsive
- 12:53gene score overtime and then the
- 12:56green represents regulators for Co
- 12:58inhibitory receptors until the yellow
- 13:01HIV signatures in progressive patients.
- 13:04And then I'll 27 regulators.
- 13:07So we we want to examine these
- 13:10transcriptional for these
- 13:12transcriptional factors in detail.
- 13:15So in order to do this and presented dilemma,
- 13:19we had to develop new technology
- 13:20because I called the Heisenberg
- 13:22uncertainty principle of immunology.
- 13:24The process of examining the cell
- 13:26with activation perturb the system.
- 13:28Some of looking for an electron
- 13:30after hitting it with HV.
- 13:32So we had to develop a gene
- 13:35knockdown the early time points and
- 13:37primary T cell without activating
- 13:39T cells and again this is all work
- 13:42developed by Tomo by Thomas Anita.
- 13:44We used an efficient lentiviral vectors
- 13:47that developed by wearing a green.
- 13:49And basically one takes a
- 13:51viral like particles V LP's
- 13:53which is incorporated with TPX,
- 13:55which degrades Sam Sam HD one,
- 13:58removes restrictions,
- 13:59you can transfect primary human
- 14:01T cells with this Sam S1,
- 14:04which now allows transfection with SH RNA,
- 14:07HIV, HIV, lentivirus and all.
- 14:09This can be done in an activated T cells.
- 14:13Could knock down the gene and
- 14:15then do the the incubation.
- 14:17So here we have night CD.
- 14:20Or cells incubated without
- 14:22CD3 CD 28 with this procedure,
- 14:24knocking down the different genes
- 14:26and then there is stimulated with
- 14:29and without interferon beta and then
- 14:31measured five days later and then
- 14:34we perform fax GFP of we sort of
- 14:36the GFP positive cells were knocked
- 14:38down and did bulk RNA sequencing
- 14:41and you can see very efficient
- 14:43knockdown in the GFP positive cells.
- 14:46With these different transcription factors.
- 14:47This is a monumental amount to work.
- 14:51Performed by tomo.
- 14:52So we perform principal component
- 14:54analysis to changes in the total
- 14:56RNA expression after the interferon
- 14:58signature associated with each knockdown.
- 15:01So let me just say that again,
- 15:03so these are PCA plots.
- 15:05We knock down each transcription
- 15:07factor and then looked at all
- 15:10the RNA expression and then put
- 15:12that into a principle component.
- 15:14One in principle component,
- 15:16to what that revealed is that the interferon
- 15:19one stimulated genes are positive.
- 15:21Regulated by we call interferon
- 15:25regulated module one, this modulator
- 15:29increased the downstream interferon.
- 15:32Stimulated genes with module 2 represented
- 15:36transcription factors that negatively
- 15:40regulated the interferon interferon genes.
- 15:44So to go into more detail,
- 15:46we first have the interferon
- 15:49regulated module one,
- 15:50so a something that a transcription
- 15:53factor that knocks down the gene
- 15:55will lead to decreased expression,
- 15:58which means as positive regulating.
- 16:00So the interferon regular module one
- 16:03regulates the conical interferon
- 16:05stimulated genes over here.
- 16:07Where is interferon regulated module two over
- 16:10here regulates these non Canonical jeans?
- 16:13Interferon stimulated genes perhaps
- 16:15a greater interest was looking at the
- 16:19Co inhibitory receptors so we have.
- 16:22Interferon regulated module one
- 16:24over here which is bath map.
- 16:28ETS2 SP 140 which differentially
- 16:32regulate lag 3.
- 16:34PD1 PD L1 slam F6 and other
- 16:40transcription factors.
- 16:41And then we have stat one and stat
- 16:44three which positively regulate
- 16:46Tim three but not lag 3.
- 16:48So we see that these different
- 16:50transcription factors differentially
- 16:51regulate different Co inhibitory receptors.
- 16:54And here's a summary.
- 16:55The data just showed you,
- 16:57which is the effect of these
- 17:00transcription factors.
- 17:01Interferon stimulated stimulation,
- 17:02so again there are two modules of
- 17:05transcription factors based on
- 17:07the global effects on interferon
- 17:10stimulated genes,
- 17:11thereby directly regulated by
- 17:12different modules,
- 17:13transcription factors and then
- 17:15Co inhibitory receptors are also
- 17:17regulated by interferon associate
- 17:19transcription factors and which up
- 17:21regulate and down regulate these receptors.
- 17:24So we have for example,
- 17:27a MoD in module one, the which is a bath.
- 17:31ETS2 math one which positively
- 17:34regulate lag 3 Tim three and PD one
- 17:38but negatively regulate a TIGIT.
- 17:40BTL BTL A and CD 160 again.
- 17:43Going along with the flow cytometry data.
- 17:46And again this I showed you step
- 17:49one and three here.
- 17:51Positively regulate Tim three
- 17:53but negatively regulate PD one.
- 17:56So then we performed a hierarchical
- 17:58backbone network analysis transcription
- 18:00factors.
- 18:00I'll just go over this very briefly,
- 18:03but basically looked at gene expression,
- 18:05overtime, differential expression,
- 18:06protein, DNA bonding,
- 18:08a transcription factor database
- 18:09is integrated.
- 18:10Those data looked at a rank list
- 18:13of transcription factors which we
- 18:14perturbed and knocked down as I
- 18:17showed you integrated those data
- 18:19into refine network model and what
- 18:21we found was at the early and
- 18:24intermediate network contain more
- 18:25up regulated transcription factors.
- 18:27And downregulated in contrast late
- 18:30network had more downregulated in up,
- 18:33regulated transcription factors and
- 18:35interferon induced differentiation.
- 18:36Involves dominance of the up
- 18:39regulated transcription factors.
- 18:40The first 16 hours over here which
- 18:43then the dominance of down regulated
- 18:47transcription factors over here.
- 18:49And just a summary.
- 18:51So there were dominant transcription
- 18:53factors that bridge each wave to the next.
- 18:56So the green circles represent
- 18:58a transcription factors that
- 19:00are differentially expressed in
- 19:02one transcriptional wave.
- 19:04Where is the purple circles represent
- 19:07transcription factors that differential
- 19:09expressed in all transcriptional waves.
- 19:12So Cal offense tattoo are early
- 19:15intermediate transcription factors.
- 19:16Math blimp one?
- 19:17An MIP are intermediate transcription
- 19:20factors and stat one hit 1A and T bet or
- 19:24bimodal transcription factors apart show
- 19:26this it just to get the bigger picture
- 19:29of the what nature does in terms of the
- 19:33biologic complexity of these systems.
- 19:36So a dear friend of mine,
- 19:38somebody may know of one of the great.
- 19:42Textbook authors of immunology.
- 19:44Abul Abbas would say to me,
- 19:47in Vivo Baratas and then in vitro maybe.
- 19:51So the challenge for us was to find
- 19:54an envy both system which replicate
- 19:57all this lovely in vitro data.
- 20:00So.
- 20:00Like to show you it in Beeville.
- 20:02Model that we did not develop a nature
- 20:05developed for us with the viral load.
- 20:07Strongly correlate with interferon
- 20:09T cell signature which is COVID-19.
- 20:12So this is work that is presently
- 20:14under revision.
- 20:15That nature communication,
- 20:16led by a team of individual or for two
- 20:20at the end where we perform single cell.
- 20:23Now sis of patients with healthy
- 20:25controls and various COVID-19
- 20:27samples of individuals with mild,
- 20:29severe or moderate severe disease and
- 20:31basically for the purpose of this talk.
- 20:34But we found this out as a very
- 20:36strong correlation between the
- 20:38interferon score and the viral load,
- 20:41as measured by PCR.
- 20:42Nasal swabs,
- 20:43in fact,
- 20:44if you look at the correlation time
- 20:47difference between here and the
- 20:49respective change interferon score,
- 20:51we had a remarkable R ^2 .9 seven.
- 20:54So nature had accidentally given
- 20:56us a in vivo model of type one
- 21:00interferons in their effect on T cells.
- 21:03So if you look at the interferon signature,
- 21:06it's higher in progressive Covid patients,
- 21:09his controlled,
- 21:10stable progressive CD4 CD 8 cells.
- 21:12One can see that the type one interferon
- 21:15score went up with more progressive disease,
- 21:18so then we wish to ask.
- 21:21Looking at these,
- 21:22the interferon stimulated T cells
- 21:24in ex vivo with a similar to what
- 21:27we saw in vitro with our interferon
- 21:30transcriptional signature and
- 21:31the answer is yes.
- 21:33So here is CD4 cells CD 8
- 21:36cells this this column.
- 21:38Here are the controls,
- 21:39stable and progressive patients.
- 21:41So we see this module too.
- 21:43Upregulated these are highly upregulated.
- 21:46PD one Tim, three CTO for lag three.
- 21:50Precisely what we saw in vitro in
- 21:53CD4 and CD8 cells, whereas module 1.
- 21:58Which led to downregulation again
- 22:01of TIGIT BTL ACD 160 and such.
- 22:06So we had a extremely.
- 22:11Could the recapitulation what
- 22:13we saw on in vitro.
- 22:15Here's expression of Co inhibitory receptors
- 22:17for the controls and COVID-19 patients.
- 22:20Just to summarize,
- 22:21here's like 3 going up to three going up,
- 22:25whereas TIGIT Slam 6 and
- 22:27layer one all went down.
- 22:29Similar to what we saw in vitro.
- 22:34So we looked at the T cells induced in vitro,
- 22:38which led to with an interferon
- 22:40score and asked that really
- 22:41mirrored the transcriptional wave
- 22:43score aren't dividing covid CD4
- 22:46and CD8T cells and basically one can see
- 22:48then dividing CD four and eight cells
- 22:51that the in vitro interference core very
- 22:54much recapitulate if we saw in vitro.
- 22:56And finally we looked at the relation
- 22:59between regulators that we saw in vivo and
- 23:02in vitro in this intermediate wave network.
- 23:05The positive regulated
- 23:06transcription factors in red,
- 23:08negative and blue, and we saw that SP.
- 23:11140 is a bidirectional regulator,
- 23:13so this is the regulator which
- 23:16induces lag three and other Co
- 23:19inhibitory molecules while inhibiting.
- 23:22Going the opposite direction for ticket.
- 23:26And then we looked at the relationship
- 23:28between late faith covid for lag free,
- 23:30Tim three and PD one and found
- 23:32that BSL three instaff 3A positive
- 23:34regulated flag 3 and 10 three.
- 23:37And finally,
- 23:38looking directly in patients to the
- 23:40SP140B cell three and stat three
- 23:43while elevated in COVID-19 cells,
- 23:45so we're able to recapitulate what
- 23:48we saw in terms of induction wisco
- 23:51inhibitory molecules in vivo in
- 23:53terms of what we thought on Pedro.
- 23:56So in summary,
- 23:57interferon is a major driver of cone
- 24:00hitori receptor regulation and human T cells.
- 24:04The computational and biologic
- 24:06approaches identifies.
- 24:07Regulatory networks under interferon one.
- 24:09Responses in human T cells.
- 24:11There are modules of transcription factors
- 24:14that control interferon stimulated genes.
- 24:16Colon,
- 24:17hip to receptors and interferon
- 24:19which really highlights the novel
- 24:21noncanonical transcription factors
- 24:23beyond the conventional Jack stat
- 24:26pathways that we previously knew about.
- 24:28We then demonstrate the relevance of
- 24:31our in vitro T cell type one interferon
- 24:34responses by integrating single cell RNA.
- 24:37See data from COVID-19.
- 24:39Patients were strong T cell into fair.
- 24:42One response was observed and
- 24:45finally we identify SP 140 as a key
- 24:49regulator that differentiates Lag 3
- 24:51digit expression during acute viral
- 24:54infection as well as Aaron Vivo systems.
- 24:57So let me just acknowledge the individuals.
- 25:00Again, this truly represents the
- 25:02work of Thomas Amita.
- 25:04Here, members of the laboratory
- 25:06contributed various parts of this.
- 25:08My long,
- 25:09long term collaborator,
- 25:10collaborator PJ Kutru Shadow Bergen is
- 25:12off Marty and also wondering knowledge.
- 25:15The covered work led by audio
- 25:17Untermann with Tomo Jonas Scoop
- 25:20and enough Tally Kaminski.
- 25:21So I'll stop there and take any questions.
- 25:25Thank you.
- 25:26David, thank you.
- 25:27What an incredible body of work and
- 25:30congratulations on sorting through
- 25:32what is clearly a very complex.
- 25:35Regulatory system, let me ask,
- 25:37and this is sort of my concrete question,
- 25:41which is you know.
- 25:43Obviously you're sorting through
- 25:44what's driving expression of Tim.
- 25:46Three lag, three TIGIT an realizing
- 25:49that almost the Holy Grail
- 25:51today is what's the next PD one?
- 25:54So does this work?
- 25:56Help us understand the relative
- 25:58merits of these targets and in
- 26:00the future of immuno oncology
- 26:03or give us some insight there.
- 26:06Great question. I think the short
- 26:08answer is probably not at one level.
- 26:10It gives us insight,
- 26:12so I guess one could ask what
- 26:14what induces type one interferons
- 26:17in different tissues and.
- 26:19And how are tumors so presumably in
- 26:22tumors are secreting type one interferons.
- 26:24We know they are and that that may be
- 26:28influencing the local team environment.
- 26:30But the reason why I say no is my
- 26:33suspicion is that each organ has
- 26:36his own set of regulatory module
- 26:38for controlling LG cells work.
- 26:41We just completed an extensive
- 26:43analysis paper published in Science
- 26:46Immunology doing a single cell RNA seek.
- 26:49In T cells from normal spinal fluid
- 26:51is normal yell graduate students and
- 26:54see that over 50% of the T cells.
- 26:57In this DSL or PD,
- 26:59one positive high expression
- 27:01digit in three with spontaneous
- 27:03production of gamma interferon.
- 27:04So I think each organ and that's
- 27:07why I showed the Ms GBM data.
- 27:10I think looking at what is expressed in
- 27:13tumors compared to autoimmune disease,
- 27:15which goes the opposite direction may
- 27:17give us insight as to what is the next
- 27:21Holy Grail coding inventory molecule.
- 27:23I think that would be perhaps
- 27:25the best way of addressing it.
- 27:28And this is more mechanistic,
- 27:30and it was surprising because it's
- 27:32a Vijay kept saying well Style 27.
- 27:34Can't you find it kept saying?
- 27:35Well we keep looking and kept saying
- 27:38what you're doing the experiment
- 27:39wrong and I didn't show them
- 27:41picture of Donald but you know,
- 27:43we just couldn't get it to work
- 27:44and then we explore different
- 27:46like going hit or molecules.
- 27:48And then it's very simple observation
- 27:50and actually predicted based on
- 27:51all the viral immunology work.
- 27:53Yeah, thank you, Ann Habermann has a
- 27:56question which is how long does the
- 27:58T cell response to interferon persist
- 28:01and why would this be a desirable
- 28:03response during a viral infection?
- 28:06Well, I I think in terms of
- 28:09covid there cleared two phases.
- 28:11The initial phase of the
- 28:13high interferon response.
- 28:15We thought the intermediate phase
- 28:17and then with time disappears.
- 28:19If one can generate so there really are
- 28:22these biphasic interferon response?
- 28:24Is this what nature does to try to
- 28:27clear clear viruses and we suspect that
- 28:30one reason why patients do badly and
- 28:33we're positive that the loss of TIGIT.
- 28:36Which is induced by interference.
- 28:38We have persistent high interference
- 28:40signature leads to a loss
- 28:42of the mean regulation.
- 28:44We actually wrote a grant
- 28:47that supplemental grant.
- 28:49Hypothesising that Tim three
- 28:50PD one go up and teacher will
- 28:53go down in covid patients.
- 28:55I don't like hypothesis driven science.
- 28:57It seemed like a long shot and were
- 29:00shocked to see that was going on.
- 29:03So so in terms of why be desire response
- 29:05because indifference help clear viruses.
- 29:08But then I think it becomes a
- 29:10less desirable response with time.
- 29:12And we suspect that will raise the
- 29:14issue that loss of digit which is
- 29:17really quite remarkable in these individuals.
- 29:20May late relate to the hyper mean
- 29:22response that we see in patients.
- 29:26Well, David, thank you for a really a
- 29:29terrific talk and and thank you for
- 29:31sharing that the work in progress.
- 29:34It's really impressive.
- 29:35Let me now turn to our next speaker,
- 29:38Doctor Hairy Cougar,
- 29:39who as you all know is is a professor
- 29:42of medicine and along with Marcus
- 29:44Bosenberg leads or yell Sporen
- 29:46skin cancer which were so pleased,
- 29:48got renewed about a year ago and
- 29:50continues to be extremely productive.
- 29:52Harriet's work in the Cancer
- 29:55Center has been really.
- 29:56Sort of the triple threat.
- 29:58Obviously she is a highly.
- 30:01Respected and highly sought after physician,
- 30:03but at the same time leader in
- 30:05research and immunology in Melanoma
- 30:07and also a leader of our education
- 30:10program and not many people can
- 30:12can do all that and do it so well.
- 30:15Harriet's work I think has really
- 30:16been instrumental in understanding
- 30:18the biology of Melanoma.
- 30:20How do we leverage Immunobiology
- 30:22towards novel therapies?
- 30:23And Anne frankly I suspect
- 30:24willingness to hear about it today,
- 30:27but her work on metastases
- 30:28as well has really, I think.
- 30:31Very insightful,
- 30:31but Harriet thank you for taking the
- 30:34time and sharing your work with us.
- 30:38Thank you Charlie and thanks
- 30:39for that wonderful introduction.
- 30:41I'm just going to share my screen here.
- 30:45So it's always humbling to
- 30:47talk after David Heffler,
- 30:48but that was the assignment I received,
- 30:51so I will do my best here.
- 30:54So I'm going to be talking to you about
- 30:57one of the sport projects which focuses
- 31:00on Co stimulating the the innate immune
- 31:03adaptive immunity to treat Melanoma.
- 31:06So just a few fast facts about Melanoma,
- 31:08so it's a disease of the relatively young
- 31:11most patients present between age 45 and 55.
- 31:13The incidence has been going up
- 31:15actually for decades already,
- 31:17so just by way of example,
- 31:19in 2003 there were around 54,000
- 31:20new cases in the United States,
- 31:22and just a decade and a half
- 31:24later it was already up to 87,000.
- 31:27It's now the fifth most common malignancy
- 31:29among men and the seventh among women,
- 31:31but Fortunately most of our patients
- 31:33present with stage one disease,
- 31:35so stage one refers to diseases
- 31:37confined to the skin and is.
- 31:39Then stage two is confined to the skin
- 31:41and thicker stage three is disease.
- 31:44It's spread to the lymph nodes and
- 31:46stage four is distant dissemination.
- 31:48And that's essentially what kills patients.
- 31:50So we're really going to be talking
- 31:53about stage four disease today.
- 31:55So for mortality, Interestingly,
- 31:57it was going up as well.
- 32:00So for 2000 three 7600 deaths,
- 32:022017 ninety 700 deaths.
- 32:04But if you start tracking later on 2019,
- 32:08the death rate started to go down
- 32:10for the very first time 7230 deaths,
- 32:14and the projected number for
- 32:16this year is 6850.
- 32:18And this is because of
- 32:21our improved meta static.
- 32:23Approved therapies for metastatic disease,
- 32:25particularly immunotherapy.
- 32:26And that's what I'm going
- 32:28to be talking about today.
- 32:30So we've known for years that some Melanoma
- 32:33patients are cured by old-fashioned therapy.
- 32:35If you do a medister tech,
- 32:37to me,
- 32:38this is an old series published in 2011.
- 32:40You can see that eight or ten
- 32:43years at approximately 5 or 7%
- 32:45of patients are still alive.
- 32:47Chemotherapy you actually see
- 32:48a similar kind of a figure,
- 32:50and we don't think chemotherapy
- 32:51really prolongs survival.
- 32:52Maybe it's just Natural History
- 32:54of disease that some people live
- 32:56for a long time.
- 32:57Now over here on the right you see
- 32:59the the five year survival data from
- 33:02our flagship phase three study of
- 33:04epilim abalon versus nivolumab alone
- 33:06versus the combination thereof at
- 33:09where at five years you see 26% of
- 33:12patients are alive with EPI alone
- 33:1444% with anti PD one alone and 52%
- 33:17or maybe even higher than that.
- 33:20With the combination of the two drugs.
- 33:23So what we're really trying to
- 33:25do in the Melanoma field,
- 33:26especially the drug development field,
- 33:28is to raise the tennis tail
- 33:29at the end of the curve.
- 33:31So this is a figure that I borrowed
- 33:33from one in Microsoft students, Irina,
- 33:35who I'll mention as we go along,
- 33:37just showing that targeted
- 33:38therapy and chemotherapy.
- 33:39You're very low down here with
- 33:41people in Malibu starting
- 33:42to push up. We're pushing up
- 33:44further with Anti PD one even
- 33:46further with the combination.
- 33:47But really, what we need to do is to
- 33:49get new drugs and drug combinations,
- 33:51so hopefully in the next five years
- 33:53will have a five year survival of 80%.
- 33:56And eventually we'll reach 100%,
- 33:58and until then we still have employment.
- 34:02So what are the limitations
- 34:04of immunotherapy's,
- 34:05the Society of Immunotherapy or City?
- 34:07Which is the big society that Mario
- 34:11presides over recently formed a
- 34:13task force to define to provide
- 34:16some clinical definitions of.
- 34:18Limitations so firstly,
- 34:19not all patients respond upfront.
- 34:20We call that primary resistance.
- 34:22Then there's some patients that will
- 34:24respond and subsequently progress.
- 34:25So we call that secondary
- 34:27resistance or required resistance.
- 34:28The third problem that we have is
- 34:30that we sometimes give combinations.
- 34:32So for example,
- 34:33when we give a pill and an urban Nevada map,
- 34:36we give the two together for
- 34:38four cycles and then we continue
- 34:40with Nevada map monotherapy.
- 34:42So if somebody has a nice response in
- 34:44the beginning and then 18 months later
- 34:47when they're on monotherapy maintenance,
- 34:49they then progress.
- 34:50Is that resistance to the combination or
- 34:53is that resistance to the monotherapy and
- 34:56all of these things need to be defined?
- 34:59And then how do we define regrowth
- 35:01after patient stops therapy?
- 35:02So we normally treat for a
- 35:04limited period of time being at
- 35:06one years one year or two years.
- 35:08However long we treat for specific disease,
- 35:11if a patient is in off therapy
- 35:13and then has regrowth,
- 35:14does that mean they're actually
- 35:16resistant to the original code?
- 35:17Because in theory the tumor
- 35:19should have been gone.
- 35:20Or are they just dependent on it
- 35:22and we need to continue so the task
- 35:25force is starting to define all of
- 35:28these categories and to come up with?
- 35:30Specific definitions that can be
- 35:32used for clinical track for drug
- 35:34development so that all trials
- 35:36are designed the same way.
- 35:37We've started on that,
- 35:38but we're chipping away at
- 35:40all of these questions,
- 35:41and I think many valuable faculty
- 35:43are actually participating in
- 35:44this endeavour with concurrent
- 35:46with the clinical definitions,
- 35:47we really need to work on the science.
- 35:50So really,
- 35:51what I'm going to talk about mostly today
- 35:53is is translation going back and forth.
- 35:56So what?
- 35:56Why do patients develop resistance?
- 35:58Or many many potential mechanisms
- 36:00of resistance have been described,
- 36:01and I think.
- 36:02You know half of the cancer immunology world
- 36:04is now working on one or other of these.
- 36:07So some of the some of these
- 36:09tumors are just desert rumors,
- 36:11lack of till of tumor infiltrating
- 36:13lymphocytes within the tumors you can have,
- 36:15in effect of priming of your T cells.
- 36:18We know that defective antigen presentation,
- 36:19such as bile acid,
- 36:21beta,
- 36:21two microglobulin in the tumor
- 36:23cells will cause resistance.
- 36:24Sometimes T cells get exhausted
- 36:26as David just mentioned.
- 36:27Of course lack of PDL one in the tumor
- 36:29or in the tumor microenvironment
- 36:31suggests that we don't live PD
- 36:34one. Inhibition isn't going
- 36:35to do very much over there.
- 36:37And then the other costimulatory
- 36:39or Co inhibitory molecules
- 36:40that David just mentioned,
- 36:42particularly teachers and
- 36:43Lag 3 might also be present,
- 36:45and maybe it's just not sufficient in
- 36:48all cases to inhibit PD one or PDL 1.
- 36:51And finally there there are many other
- 36:54immune inhibitory cells that we need to
- 36:56focus on in the tumor microenvironment,
- 36:58and sometimes those might just be
- 37:01overpowering the role of the T cells.
- 37:03So examples are MD's season T regs
- 37:06which might need inhibition as well.
- 37:09So when we started putting
- 37:11together the renewal of the spore,
- 37:13one of the projects that we
- 37:15worked on is specifically looking
- 37:16at the innate immune system.
- 37:18So Sucic, when she was here,
- 37:20provided all of the preliminary
- 37:22data which I'll be reviewing very
- 37:24quickly and some sewers left,
- 37:25Marcus has become a key collaborator,
- 37:27and actually it's now become a whole
- 37:29village in the whole party because
- 37:31all of the investigators and trainees
- 37:34listed over here on the right are
- 37:36quite involved in this project,
- 37:37and I'll mention some of their.
- 37:39Contribuciones as we go along.
- 37:42So Sue started off looking at
- 37:44Marcus is young 1.7 models,
- 37:46so I'm sure everybody knows that
- 37:48this is a cell line that was
- 37:51generated from the from a gym model.
- 37:54It's byref mutant and P tenancy.
- 37:56DK into a null and when you take
- 37:59this young 1.7 and you treated with
- 38:01anti PD one you see over here there's
- 38:04absolutely no tumor regression.
- 38:06If you irradiate the cells
- 38:08and generated the second.
- 38:10This tortoise airline called Yammer 1.7.
- 38:12ER stands for exposed to radiation.
- 38:14You get some sensitivity to anti PD one,
- 38:17but ultimately with time these
- 38:19tumors to grow out as well.
- 38:22So the first question next to asked was
- 38:24what was actually in these in these tumors.
- 38:27So all of this work was done by Kurt Perry,
- 38:30who's over here on the right.
- 38:32We can see his picture and he's actually
- 38:34one of the new fellows that match to.
- 38:36Our program will be very thrilled
- 38:38to have him as part of our
- 38:41medical oncology fellowship.
- 38:43So first question that they asked
- 38:45was what was the infiltrating
- 38:46tumor content in these mass?
- 38:49In these mass melanomas?
- 38:50And it turns out that the predominant
- 38:53cell type was actually terms or
- 38:55tumor associated macrophages.
- 38:57The next question that they asked was
- 38:59what kind of macrophages are these?
- 39:02Are there more inflammatory or inhibitory?
- 39:05Classic definition of M1 and M2
- 39:07and over here on the right you
- 39:09see a contour plot where on the
- 39:11X axis you've got F 480 and the
- 39:13Y axis you've got like 6 E.
- 39:16It turns out that there at
- 39:18least three populations,
- 39:19and they're probably more than that,
- 39:21and just in a nutshell,
- 39:22the terms that have highlights 6,
- 39:24three like 6 E and low EF 480,
- 39:26or those that are more inflammatory
- 39:28in the ones on the right over here
- 39:30are those that are presumed to
- 39:32be more inhibitory.
- 39:36So at that point they said, OK, we've got.
- 39:39We've got these terms.
- 39:40We need to try to modulate them,
- 39:42and there are many, many mechanisms
- 39:43out there for modulating terms.
- 39:45But the ones that they chose to
- 39:47work on with CD, 40, agonism,
- 39:48and CSF, one R inhibition,
- 39:50and in the beginning they used
- 39:52a small molecule inhibitor.
- 39:53So if you take these memory
- 39:55cells and implant them in mice,
- 39:57and you treat either with control vehicle or.
- 40:00The CD 40 agonist.
- 40:02You'll see some some decrease in
- 40:03the size of the tumors with the
- 40:05CD 40 agonist if you give the CSF
- 40:08one receptor inhibitor you get a
- 40:09similar amount of tumor reduction.
- 40:11If you give the two together,
- 40:12you get synergism.
- 40:13As you can see by the red line over here.
- 40:17So to look back into the similar
- 40:19contour plots,
- 40:20what is the content of these different
- 40:22tumors within the mice treated in the
- 40:24graph over here on the left you can
- 40:27see that when you give doublet therapy,
- 40:29the CD 40 agonist in the CSF
- 40:31one receptor inhibitory,
- 40:32the main difference is that you get
- 40:34an increase in this little group over
- 40:36here on the right in the upper corner,
- 40:39which are like 60 high and in 480 low and are
- 40:42presumed to be more inflammatory macrophages,
- 40:44and that's essentially
- 40:45verified on the bar graph.
- 40:47Over here on the left.
- 40:49On the right,
- 40:49at the bottom over here you can
- 40:52see this to the changes in the in
- 40:54the immune infiltrating content,
- 40:56and I think what's most interesting
- 40:58over here is that when you give
- 41:00the CD 40 agonist along with
- 41:02the CSF one receptor inhibitor,
- 41:04you do get an increase of
- 41:06infiltration of T cells.
- 41:07So possibly we might be able to make
- 41:09desert those desert tumors more
- 41:11inflamed by using a regimen such as this.
- 41:14And in addition you get more
- 41:16PD one high T cells.
- 41:20So Catherine Miller Jensen on the main
- 41:22campus is developed a technology for
- 41:24single cell site eccentric creation,
- 41:26and she looked at what the difference of
- 41:29was between these different treatment
- 41:31arms and what you can see here on
- 41:34the principle component analysis.
- 41:36On the left is that if you only treat with
- 41:38assistive one receptor inhibitor versus
- 41:40the city for The Agonist inhibitor alone,
- 41:44versus the combination,
- 41:45you get quite a different pattern
- 41:47of cytokine secretion on the right.
- 41:49Oh, I'm sorry in the middle over here,
- 41:52you've got a heat map which we
- 41:54essentially depicts the differences,
- 41:55and some of them are highlighted over here
- 41:58on the right for cytokines and chemo kinds.
- 42:00Pretty much as as one would expect
- 42:02when you give the combination therapy,
- 42:05you get an increase in TNF Alpha.
- 42:07I'll 12 BIL 6 etc and the same
- 42:09for the panel of the side of kinds
- 42:12of the chemo kinds at the bottom.
- 42:14So essentially the doublet therapy
- 42:16over here is inducing quite quite
- 42:18vast changes in the animals.
- 42:19What does it do to the T cells?
- 42:22What else is important over here?
- 42:24What you see on this figure here is
- 42:26that when you give the doublet therapy,
- 42:29you can actually abrogate the
- 42:30effect if you give anti TNF Alpha
- 42:32or anti interferon gamma,
- 42:34again highlighting the the importance
- 42:35of the T cells in this process as well.
- 42:38So with that at the time we concluded
- 42:40that CSF one receptor inhibitors in city
- 42:43for The Agonist treatment can induce
- 42:45an inflammatory term population in
- 42:46the two in the tumor microenvironment.
- 42:48It also induces a functional T cell response.
- 42:52And this is dependent on TNF Alpha
- 42:54and interferon gamma,
- 42:55and these were the preliminary data
- 42:56that we had to start our project.
- 42:59So when we received funding,
- 43:00we by then Curtis Perry had gone
- 43:03off for residency.
- 43:04So Bill Dembski came in to help
- 43:06us and you'll see a whole cast of
- 43:08trainees along the way over here.
- 43:10So Bill Bill did a heroic job over here
- 43:13with bringing us closer to the clinic.
- 43:15So we decided at that point not to
- 43:17use a series of 1 receptor inhibitor,
- 43:20the small molecule inhibitor,
- 43:21but rather to move towards and.
- 43:23Antibody because of precision
- 43:25of drugging our target.
- 43:26Also in the clinical arena,
- 43:28it would be very difficult to take
- 43:30a patient who progressed on a PD one
- 43:32inhibitor and not to continue the PD
- 43:34one inhibitor with the next regiment.
- 43:37That's essentially how most regimens
- 43:38are now being developed for Melanoma
- 43:40and renal cell as well.
- 43:42So the question is what can we add onto a PD?
- 43:45One inhibitor to get us there so
- 43:47he these are large groups of mice
- 43:49treated either with control vehicle,
- 43:51either one of the three drugs alone
- 43:54so anti PD one.
- 43:55CD40 agonist or CSF one receptor.
- 43:57Any doublet of the from among
- 43:59those three and the triplet,
- 44:00and you can see by the Brown line
- 44:03over here that by far the triplet
- 44:05therapy was superior on the
- 44:07right you see the spider plots
- 44:09for the size of these tumors,
- 44:11which in the beginning
- 44:13they'll grow and then shrink.
- 44:15Irina clickbait ever.
- 44:16Who's MD PhD student who is in Marcus's
- 44:19lab at the time or selection Marcus is
- 44:21lab did similar experiments on aranka
- 44:23model because we wanted to go into
- 44:26the clinic in kidney cancer as well.
- 44:28Again, showing their triple therapy
- 44:30was superior to double therapy.
- 44:31Not quite as pretty as
- 44:33in the Melanoma models,
- 44:34but that's then that's consistent
- 44:36with what we see in the clinic,
- 44:38whereby renal cell patients respond less well
- 44:41to these therapies then Melanoma patients.
- 44:43So because it's a sport project,
- 44:45you have to have a clinical Pi and
- 44:46a basic science Pi and everything
- 44:48has to have a clinical trial so
- 44:50to go back to the bedside.
- 44:51What are we going to do with these data?
- 44:54So we formed collaborations with Bristol
- 44:55Myers Squibb and a company called a passage
- 44:57and that makes a CD 40 agonist and we
- 44:59were able to get them to work together.
- 45:03The problem was that there was no
- 45:05phase one data for the triplet.
- 45:06Now could be oralism AB which is the
- 45:08CSF one receptor antibody and the
- 45:10volume Abbott being given to hundreds
- 45:13of patients in BM S LED studies in
- 45:15the activity in Melanoma was modest,
- 45:16but there was a little bit of
- 45:18activity at that point.
- 45:20We knew that a CD 40 agonist can have
- 45:22significant activity in Melanoma
- 45:24based on studies by done by the
- 45:26group at Penn already years ago.
- 45:28But we didn't know very much
- 45:30about the other combinations,
- 45:31so at the time sterilize,
- 45:33brought in a Phase 1 two study of APX.
- 45:36005 AM.
- 45:37In other words,
- 45:37the CD 40 agonist plus nivo in
- 45:39Melanoma and lung cancer started at
- 45:41around that time and we rolled a
- 45:43good number of patients there and
- 45:46actually saw phenomenal responses.
- 45:47So this is an example of a patient
- 45:49treated by doctors know who had
- 45:52a mucosal Melanoma,
- 45:53which tends to be very resistant
- 45:54to implement map in the volume.
- 45:56Evan the patient indeed had
- 45:59progressed on there.
- 46:00So we put the patient on the CD
- 46:0240 agonist plus nevala mehrban.
- 46:04The patients had a complete response
- 46:06and remains of therapy couple of years
- 46:08later we have four of these patients
- 46:09and others and implement Melbourne Nivolumab.
- 46:12We don't actually see this,
- 46:13so maybe this is the answer to Charlie's
- 46:16question is what's the next anti PD?
- 46:18Why?
- 46:20So we're very excited about this
- 46:22molecule and with that Sarah Weiss.
- 46:24This picture over his over here and I
- 46:27wrote a Phase one slash 1B or phase
- 46:30two for the combination of the triplet.
- 46:32We partnered with the yellow Spore
- 46:34in lung cancer and we were able to
- 46:37get support both from the Cancer
- 46:39Center Bristol Myers and Apixaban.
- 46:42So the phase one trial design is
- 46:44depicted on this picture over here.
- 46:45In the beginning we were very
- 46:47anxious because nobody had
- 46:48ever given two macrophage modulating
- 46:50agents together and we were worried
- 46:52that we were going to get like
- 46:53diffuse macro activate macrophage
- 46:54activating syndrome and kill patients.
- 46:56So we had to go very very gingerly.
- 46:58We will also working with
- 46:59two pharmaceutical companies,
- 47:00each with its own opinion so it
- 47:02could be oralism AB which was being
- 47:04developed by Bristol Myers Squibb
- 47:05dead already did it already defined
- 47:07the recommended phase two dose and
- 47:09we had to stick with the dose that
- 47:11they gave us which was for me.
- 47:13Ramza, kilogram.
- 47:14We escalated the CD 40 agonist very gently,
- 47:17so cohort one only had the doublet therapy
- 47:20at a tenth of the recommended phase.
- 47:23Two dose for the CD 40 agonist within
- 47:26escalated by a half a log into cohort
- 47:29three in Cohort 5 and concurrently
- 47:31added the nevala map on with the goal
- 47:34of ultimately reaching cohort six,
- 47:36which would be 4 doses at the
- 47:38record for of Cabrera.
- 47:40Lismer,
- 47:41the pic surgeon drug and nivolumab at the.
- 47:44Same recommended phase.
- 47:45Two dose of each one of these individually.
- 47:49Once we get to the Cohort 6 or to
- 47:51the recommended phase two regimen,
- 47:53the plan is to go into.
- 47:57The Phase 1B component,
- 47:58which is which is essentially
- 48:00three phase two studies,
- 48:01each one with its Simon phase.
- 48:03Two design, one per disease.
- 48:06At this,
- 48:07this trial has lots of embedded correlates,
- 48:10both blood based and tumor,
- 48:12based with pretreatment biopsies
- 48:13mandatory on treatment,
- 48:14biopsies etc.
- 48:15So to update you on what's going on
- 48:18with the Phase one trial which is an
- 48:21integral part of the sport project.
- 48:24We have completed the Phase 126
- 48:26patients in total have been
- 48:28enrolled sarahs busy preparing the
- 48:30publication for this and that should
- 48:32be going out over the coming weeks.
- 48:35Overall it was reasonably well tolerated.
- 48:38It certainly wasn't candy,
- 48:39though we saw a lot of periorbital
- 48:41edema as well as diffuse edema
- 48:43elevations in CPK AST and a Lt,
- 48:45but those didn't appear to be
- 48:47particularly clinically significant.
- 48:48Fevers Insider Kind release,
- 48:49but a lot of fatigue.
- 48:51I think that was the biggest problem.
- 48:53The other big problem that
- 48:55we saw was skipped.
- 48:56While there was some activity
- 48:58in some of the patients,
- 48:59it was mostly stable disease in
- 49:01progression of disease and not
- 49:03quiet what we've seen in the mice.
- 49:05The trial has preceded to the Phase 1B
- 49:07component in Melanoma and lung cancer.
- 49:09Both are in the first stage,
- 49:11but we've we've completed the phase one.
- 49:14I'm going to show you some examples
- 49:16of correlative studies that we've
- 49:18done and this is still a bit
- 49:20of a work in progress,
- 49:21so we looked at cytokine panels before
- 49:24and on treatments at 24 hours later,
- 49:26and you can see nice increasing interferon
- 49:28gamma as well as in in TNF Alpha.
- 49:31The different cohorts are listed over here,
- 49:33but Code 5 and six are when we hit
- 49:35them at the recommended phase,
- 49:37two dose of deep excision drugs,
- 49:39so that's where you see most of the activity.
- 49:44There are other changes in circulating
- 49:45cytokines and I could spend an
- 49:47hour just talking about this,
- 49:48but I selected a few just just
- 49:50to show you what we're seeing,
- 49:52so we've got the CL 2,
- 49:54which is a side kind that's primarily
- 49:56secreted by dendritic cells and macrophages.
- 49:57Very high levels of the higher dose levels,
- 50:00same with. P.
- 50:0110 and then the macrophage
- 50:03colony stimulating factor,
- 50:04also highest levels in Cohort
- 50:076 but clear increases.
- 50:09Across the board,
- 50:10we do have the pretreatment and on
- 50:12treatment specimens show me jessel
- 50:13who supposed dark in my lab is
- 50:16busy analyzing these what you see
- 50:17over here is the basic analysis,
- 50:19so these are just this is just a
- 50:21munificent staining a CD4 and CD8
- 50:24before treatment and on treatments
- 50:25on the left is pre and on the right
- 50:27is post and you can see an increase
- 50:30in the infiltration of the CD 8
- 50:32cells which are colored in green.
- 50:34There's also an increase of
- 50:35the CD Force which are in red.
- 50:37CD 68 also actually.
- 50:39Increase in the amount of CD
- 50:4168 on this particular patient,
- 50:42but in some patients we actually
- 50:44see the opposite,
- 50:45so over here you can see that the
- 50:47C8 cells pretreatment were much
- 50:49more dense than post treatment.
- 50:51Although you do see some post treatment,
- 50:53I don't know how well this projects.
- 50:56There's an increase in the CD 68 though.
- 51:00Just to highlight one of the challenges
- 51:02that we have with doing this.
- 51:04Pre Anon treatments studies in
- 51:05that it may not come from this
- 51:07come from the same site,
- 51:09so the pretreatment was a a containers
- 51:11tissue metastasis on the back and
- 51:13the post treatment in this particular
- 51:14patient came from the Gallbladder,
- 51:16so it's possible that the tumor
- 51:18micro environment in the different
- 51:19organs is playing a part over here.
- 51:21But because we didn't see much
- 51:23activity in the Phase one trial,
- 51:25we're going back to the bench
- 51:27to try to determine what can we
- 51:29do to improve our trial.
- 51:31So Irina clickbait ever,
- 51:32who was the postdoc working?
- 51:34I'm sorry there's the doctoral
- 51:35student in Marcus's lab,
- 51:37partnered with Deanna,
- 51:37who's working in my lab to ask the
- 51:40question of whether we're actually just
- 51:42giving too much CSF one receptor antibody.
- 51:45So more isn't always better,
- 51:46particularly when we're trying
- 51:48to polarize macrophages and not
- 51:50necessarily knock them off completely.
- 51:52So when we do these experiments in the mice,
- 51:55we were seeing much better
- 51:56activity than the humans,
- 51:57and the question is why?
- 51:59So the dose is selected for the Marin
- 52:01experiments with somewhat random we go
- 52:03based on what is done by other researchers,
- 52:05what's done by format and the amount that
- 52:07we were giving them was 200MG kilogram.
- 52:09So we asked the question.
- 52:11Well,
- 52:11what happens if we give them more CSF?
- 52:13One receptor antibody and keep
- 52:15the other two drug steady?
- 52:16And as you can see in this figure over here,
- 52:19if you give more CSF,
- 52:21one receptor antibody basically
- 52:22doubling the dose.
- 52:23The mice actually do less well
- 52:25die sooner or sacrificed sooner,
- 52:27and as you can see here on the left,
- 52:30the tumor volume is actually bigger
- 52:32when you give the higher dose of
- 52:34the CSF one receptor antibody.
- 52:36So we're still debating what to do
- 52:38about that as we go into the clinic.
- 52:41But then the Meanwhile,
- 52:42because it's a small project,
- 52:44we still need to have an ongoing
- 52:46clinical trial, and the question was,
- 52:48well, is the CSF one receptor
- 52:50the optimal second target,
- 52:52in addition to CD 40 agonist
- 52:54and PD one inhibitors?
- 52:56So it's possible,
- 52:57at least theoretically,
- 52:58that CTA for is a better target because
- 53:00CTA for new mission is is really
- 53:03key for dendritic cell activation.
- 53:05So Kelly Alina,
- 53:06who's one of our wonderful
- 53:08surgeons in the Melanoma group
- 53:10and also surgeon scientists,
- 53:11is doing work in the lab.
- 53:14It, primarily Marcus is lab where she
- 53:16is taking a very aggressive model
- 53:18marine model whereby she injects
- 53:20these cells into the left ventricle.
- 53:22So they developed vast mistake
- 53:24metastases all over,
- 53:25including in the brain.
- 53:27And this model is particularly resistant
- 53:29to anti PD one in Antici TLA 4.
- 53:31So the question is whether the addition
- 53:33of the CD 40 agonist adds something.
- 53:35And as you can see over
- 53:37here with the red bar,
- 53:39the addition of the CD 40 agonist
- 53:41does appear to improve the survival
- 53:43of these nice that typically
- 53:44will be dead within 20 days.
- 53:46This is some subq injection
- 53:48data over here on the left,
- 53:50which we don't have time to go through,
- 53:52but with those data we again
- 53:54approached the passage and we said,
- 53:56well, maybe we should do a
- 53:58different trial now in parallel,
- 53:59and this is our second trial which Kelly
- 54:02and Sarah worked with me to to write.
- 54:04So it's a phase one study of the CD 40
- 54:07agonist in combination with epilim urban,
- 54:09the volume app in Melanoma.
- 54:11So just to highlight some of the
- 54:13challenges of a study like this,
- 54:15we know that a polymer mabona volume
- 54:17app toxicity rate of at least 6570%.
- 54:20We're talking about these immune
- 54:22related adverse events all the time.
- 54:25And we also know that sometimes
- 54:26these events occur late,
- 54:27so you can have a patient who
- 54:29is treated comes off therapy,
- 54:31and six months later develops
- 54:33a horrendous toxicity.
- 54:34So how long?
- 54:35How do we design a study like that?
- 54:37How long can we follow the patients?
- 54:39For how long do we go from one
- 54:41cohort to the other?
- 54:42So it took a lot of negotiation
- 54:44back and forth with the FDA,
- 54:46but we put a lot of thought into this
- 54:48really slow trial design where we
- 54:50actually have only two dose levels,
- 54:51so dose level one is a.
- 54:54Third of the recommended phase.
- 54:56Two dose of the seat of the CD 40
- 54:58agonist which is the drug that we're adding,
- 55:01and we give people a map in the volume AB.
- 55:04We only treat three patients.
- 55:06Monitor them for 28 days and
- 55:07then and then enroll
- 55:09another 46 and at that and
- 55:10all of these six patients.
- 55:12They need to be monitored for six
- 55:14weeks so this is going to take
- 55:16us a long time to get through.
- 55:18But what we're hoping is that we'll have
- 55:21a regimen that may not be more toxic,
- 55:23but that will be significantly
- 55:25more effective.
- 55:25Then the PD one and see TLA for that.
- 55:28We have right now to finally bring
- 55:30that tail of the curve up to 80%.
- 55:33We have started.
- 55:34We've enrolled three Melanoma patients
- 55:36or have completed their 28 day DLT
- 55:38period and they did OK with there,
- 55:40but they have not all completed
- 55:42their nine week observation.
- 55:43Before Christmas, we going to enroll.
- 55:45Two more patients have consented and
- 55:47we're looking for the six patient,
- 55:49but they all have to be monitored
- 55:51for 9 weeks before we can proceed.
- 55:54So I'm going to conclude there that
- 55:56Co targeting the innate and adaptive
- 55:59immune system with the CSF one
- 56:01receptor inhibitor or antibody plus
- 56:02CD 40 agonist results in better anti
- 56:05tumor activity than either alone.
- 56:07It also increases the CD 8 tumor
- 56:09content in animals if we treat
- 56:11mice bearing PD one resistant
- 56:13tumors with all with these drugs
- 56:15in combination with anti PD one,
- 56:17it does look better than the doublet.
- 56:19The findings were confirmed in a renal
- 56:22cell carcinoma model where we are
- 56:24in the clinic already testing this.
- 56:26We're having some difficulty with.
- 56:29With insufficient activities,
- 56:30so we're back in the lab right
- 56:32now trying to modify the doses
- 56:33in the regimen before we go back
- 56:35again into the clinic,
- 56:36and this kind of back and forth between
- 56:38the lab in the clinic is something that
- 56:41can only be done at a place like this.
- 56:43We are also at the same time evaluating
- 56:46the combination with the CTL A4 inhibitor
- 56:48and hopefully this will be as exciting,
- 56:50more exciting and just to
- 56:51say the final conclusion,
- 56:53that is that it really takes a
- 56:55village to do a project like this.
- 56:57So all of the the folks have been
- 57:01involved acknowledged on this slide.
- 57:02The scientific collaborators at Yale,
- 57:04colleagues in other labs have
- 57:06helped a lot through this process.
- 57:09Members of my lab members
- 57:10of the Collaborating lab,
- 57:12clinical collaborators,
- 57:13pharmaceutical collaborators,
- 57:14patients and their family,
- 57:15and then finally the funding.
- 57:17So I did mention the sporting skin cancer
- 57:20which which is funded the core project.
- 57:24But the K12 is funded a couple
- 57:26of the investigators here,
- 57:27Kelly Alina and Sarah Weiss,
- 57:29and Cancer Center has supported it,
- 57:31and some of our folks of which
- 57:34have received career development
- 57:35awards as well related to this.
- 57:38So with that I'll stop.
- 57:39I'm happy to take any questions.
- 57:41Thank you for listening.
- 57:43Hurry, thank you.
- 57:44What a great example of translating
- 57:46science into the clinic and folks can
- 57:49certainly submit questions online.
- 57:51So let me I have a question watching
- 57:53'cause I you sort of anticipated my
- 57:56question by adding the CTA four antagonist.
- 57:59But to what extent do you think that
- 58:02triplet might have had greater benefit if
- 58:05they weren't previously exposed to a PD?
- 58:08One antibody?
- 58:08And that's really good
- 58:10question. So the masks were
- 58:12not exposed to PD one antibody,
- 58:14whereas the humans would.
- 58:16And it's possible that you know,
- 58:18we've we've just used that
- 58:19app and developed it yet,
- 58:21and you're of mechanism of resistance,
- 58:23so we haven't done that
- 58:24experiment in the mouse.
- 58:25But that's actually a
- 58:26really good next step to do.
- 58:28It's a great thought.
- 58:29We should expose the mice to
- 58:31PD one inhibitors and then
- 58:32add on the other ones instead
- 58:34of giving all three up front.
- 58:36And this may be impossible,
- 58:38but is there any consideration of
- 58:40combining all four agents in previously?
- 58:43I mean that is a CSF one R CD40 anti CD L4,
- 58:47GTA 4 and PD one and I realized
- 58:50that's a smorgasbord of agents,
- 58:52but is that a conceivable approach?
- 58:54We could, we just got it.
- 58:57We can get through the 1st 3 first,
- 58:59so the CTA for CD for D and P1.
- 59:03So far we're doing OK with toxicity.
- 59:07But we are only on the 1st dose level.
- 59:09It's it's very intimidating
- 59:10to do all of this sure,
- 59:12and then the other question
- 59:13is in what line do you do it?
- 59:15So what we're trying to do now is to
- 59:17actually move it forward to the first line,
- 59:19that that very last trial that I
- 59:21showed with the CTA for antibody.
- 59:23We decided to go in first line.
- 59:26Mostly because of of memory.
- 59:28So if you if you take patients
- 59:30with her previous settling for,
- 59:32you can get additive toxicity over there.
- 59:37But that's a really good idea to do that in
- 59:40the mouse. Thank you.
- 59:41Yeah, well, I know where I
- 59:43know we're just we're out of.
- 59:45We're a little past the hour and I want
- 59:47to be sensitive to everyone's time.
- 59:50So Harriet and David.
- 59:51Thank you both for really exceptional talks.
- 59:53Congratulations on all your
- 59:54work and everyone in attendance.
- 59:56Thank you for joining us and enjoy your day.
- 60:00Thanks. Bye bye.