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Advances in Treatment of Hemophilia and Targeting dsRNA in Tumors to Overcome Immunotherapy Resistance

November 20, 2020

Advances in Treatment of Hemophilia and Targeting dsRNA in Tumors to Overcome Immunotherapy Resistance

 .
  • 00:00The hearts go out to his wife.
  • 00:03Doctor Kellie Martin is two
  • 00:05children tests and Jacob and just
  • 00:08take a moment just to silence
  • 00:10just to recognize Tony's legacy.
  • 00:21Well, thank you, so let's now turn
  • 00:24to our first of two great speakers.
  • 00:28We were very fortunate this year
  • 00:31to recruit Doctor Jeffrey Ishizuka.
  • 00:34Jeff is an assistant professor of medicine.
  • 00:38And Jeff's work.
  • 00:39Previously at Harvard was was
  • 00:42focused on the biology of T cells.
  • 00:44Discovering knew better understanding
  • 00:46of that biology and and and
  • 00:49ultimately leveraging that science
  • 00:50to what is likely to be the next
  • 00:54generation of amino therapies.
  • 00:55And we're really very fortunate to have
  • 00:58Jeff as one of our physician scientists in
  • 01:01the center of molecular Italian Colosseum,
  • 01:04member of the Melanoma program,
  • 01:07and physician scientists in general at.
  • 01:09At Yale and Smile also,
  • 01:11Jeff really excited to hear about your work.
  • 01:14Turn it over to you.
  • 01:17Thank
  • 01:17you so much Charlie, really appreciate
  • 01:20it and let me just project my slides.
  • 01:23How there we go?
  • 01:25Yes, thank you so much and thank you
  • 01:28for the opportunity to speak today.
  • 01:30Today I'm going to be talking to you
  • 01:32about some of the work we've done.
  • 01:34Targeting double stranded RNA in
  • 01:37order to overcome immunotherapy
  • 01:38resistance and also update on
  • 01:40other ongoing projects in the lab.
  • 01:42This is my disclosure slide.
  • 01:45I wanted to begin with the overall survival
  • 01:48curves from the Checkmate 067 trial,
  • 01:51which is likely familiar to this audience.
  • 01:54These curves represent survival in
  • 01:56advanced Melanoma by patients treated
  • 01:58with immune checkpoint blockade.
  • 01:59In this case,
  • 02:00with antibodies targeting PD 1C,
  • 02:02TL A4 or the combination.
  • 02:05I wanted to start here because
  • 02:06Melanoma has been something of
  • 02:08a touchstone for the use of
  • 02:10checkpoint blockade in solid tumors.
  • 02:11First indication approved and remains
  • 02:13one of the indications in which immune
  • 02:15checkpoint blockade is most effective
  • 02:16in these data are outstanding,
  • 02:18particularly when compared with the pre
  • 02:20immunotherapy standard of Care Dakar Busine,
  • 02:22which had an overall survival
  • 02:23of five to 10% at five years.
  • 02:26However,
  • 02:26even in this disease,
  • 02:28large proportion of patients
  • 02:29don't experience durable benefit.
  • 02:31The situation which is which is
  • 02:33actually more challenging in other
  • 02:35diseases where responses are less good.
  • 02:38And this is really the focus of
  • 02:39our work to improve responses
  • 02:41in this disease and in others.
  • 02:46Certainly, however, if you check,
  • 02:48my blockade is rapidly reshaping the
  • 02:49landscape of cancer care across indications.
  • 02:51I was preparing for this talk and I
  • 02:53had to go through and update this slide
  • 02:56because indications have nearly doubled
  • 02:58since its original publication by
  • 02:59Tony Ribas and Jed will Chuck in 2018.
  • 03:01Although many of us have followed
  • 03:03this emerging data very closely,
  • 03:05I have to admit that it gave me pause to
  • 03:08consider the pace of change in this field.
  • 03:11The advancement of PD one access approvals
  • 03:14continues through lymphomas and solid
  • 03:17tumors of desperate tissue origins.
  • 03:19Combination approaches have also
  • 03:20proliferated, including approaches,
  • 03:22approvals in music, leoma,
  • 03:24breast cancer, and others.
  • 03:26Successful combinations include
  • 03:27combinations of checkpoint inhibitors
  • 03:29with other checkpoint inhibitors,
  • 03:31chemotherapies and touristing
  • 03:32kinese inhibitors,
  • 03:33and notably many here at Yale,
  • 03:36have played critical roles in this dance.
  • 03:42Still, for all the advances,
  • 03:43there have been a lot of failures and
  • 03:46there remain a lot of ongoing challenges.
  • 03:48For most, many patients don't respond,
  • 03:50indeed, considered across all indications,
  • 03:52most patients don't respond in a few
  • 03:54of the response rates listed are
  • 03:56really based on earlier trials that
  • 03:58likely overestimated response rates.
  • 04:00Many of them also include
  • 04:02biomarker cutpoints,
  • 04:03PDL 1 positive ITI and this sort of thing.
  • 04:07And in my mind there are really a couple
  • 04:09of big areas in which we can improve.
  • 04:111st for all of the new indications,
  • 04:14few combinations involving novel
  • 04:17targets have been approved.
  • 04:192nd, we have a limited mechanistic
  • 04:22understanding of how these agents work.
  • 04:25Accordingly,
  • 04:25the biomarkers that we used to deploy
  • 04:27them lack sensitivity and specificity,
  • 04:29and there's not a great way to rationally
  • 04:32prioritize combinations with anti PD one.
  • 04:36So it's worth considering for a moment what
  • 04:37we've learned about response and resistance,
  • 04:39not so much in the interest of
  • 04:41an extensive overview for which
  • 04:42we wouldn't have time today,
  • 04:43but in terms of the pathways that have
  • 04:46given the strongest clinical signals to date.
  • 04:48The data shown here are from the study
  • 04:51by Merck of over 300 different patients
  • 04:53across 22 different tumor tissue types.
  • 04:56These figures show responses.
  • 04:59Non response defined as CR
  • 05:01or PR versus no CR PR.
  • 05:04When graphed with tumor mutational burden
  • 05:06on the Y axis and a gene expression profile
  • 05:09representing tumor microenvironment,
  • 05:11inflammation kind of T cell
  • 05:12inflammation on the X axis.
  • 05:14The genes in this profile are listed in the
  • 05:17upper right here and notably include PDL,
  • 05:20one among them as well as several MHC related
  • 05:23genes and kind of T cell related genes.
  • 05:28Tumor mutational burden, as you know,
  • 05:30is often used as a surrogate for
  • 05:32too many antigens and the gene
  • 05:34expression profile really points
  • 05:35to information of the tumor,
  • 05:37micro environment and the authors make
  • 05:39two points that are important here.
  • 05:41First, that these are two of the
  • 05:43strongest predictors they could find.
  • 05:45Reviewing one of the largest
  • 05:46and most comprehensive datasets
  • 05:48that existed at the time.
  • 05:49Really, it's telling us in second
  • 05:51that they appear to predict response
  • 05:52independently of one another.
  • 05:54That is to say that although the
  • 05:56best responses are in that kind of.
  • 05:58Upper right quadrant that you actually get
  • 06:01a good number of responses in a T cell.
  • 06:05Inflamed only micro environment,
  • 06:06or in TMB only TB high only tumors.
  • 06:12For the sake of time today,
  • 06:13I won't spend a lot of time
  • 06:15on TMB or antigen load,
  • 06:17so it's obviously an important consideration.
  • 06:18Instead, I'm just going to talk about
  • 06:20tumor microenvironment information,
  • 06:21which is really the focus of our lab.
  • 06:23Aside from the work by the Merck
  • 06:25Group A number of lines of evidence
  • 06:27have established inadequate tumor
  • 06:28microenvironment information.
  • 06:29As one of the most prominent mechanisms
  • 06:31of resistance to me, no therapy.
  • 06:33Most dramatically,
  • 06:34this occurs in immune desert type tumors,
  • 06:37which entirely lack T cell infiltrate,
  • 06:39as depicted here. However,
  • 06:41it can also occur in a different phenotype.
  • 06:44The so-called immune excluded
  • 06:45tumors which have anti tumor immune
  • 06:47cells at the site of the tumor,
  • 06:49although they are excluded
  • 06:50from the tumor core,
  • 06:51either by physical barriers
  • 06:53or by immune signaling.
  • 06:55Finally,
  • 06:55we believe that there is the T cell
  • 06:57inflamed type of tumor that have
  • 06:59diffuse infiltration of T cells
  • 07:01that tend to be PD L1 positive,
  • 07:03and these are the ones that we
  • 07:06believe respond best to immunotherapy.
  • 07:09To date,
  • 07:09there's been progress in identifying
  • 07:11therapeutic strategies to enhance this
  • 07:13tumor microenvironment information,
  • 07:14many of which involve either real
  • 07:16or simulated infection of the tumor
  • 07:18to trigger anti tumor immunity,
  • 07:20and I think about them in kind
  • 07:22of two big buckets.
  • 07:24The first is the provision of
  • 07:26exogenous sources that mimic
  • 07:28nucleic acid ligands to tumors.
  • 07:30This includes sting agonist,
  • 07:31MDA 5 or rig I agonist,
  • 07:33double stranded RNA sensing
  • 07:35pathways and uncle lytic viruses.
  • 07:37The other is the induction of endogenous
  • 07:40sources of nucleic acid ligands,
  • 07:43primarily endogenous retroviruses,
  • 07:44although others have been published recently,
  • 07:47alualu repeats in humans.
  • 07:51And examples of this include a
  • 07:53deciding in CDK 46 inhibitors.
  • 07:57So my interest in turning these cold
  • 08:00microenvironments hot and kind of
  • 08:02providing these logins to tuners really
  • 08:04developed out of work in the Canings
  • 08:07lab was finishing my postdoctoral work
  • 08:09there and through the type of experiment
  • 08:11that I'm showing here on the left,
  • 08:14you have kind of a transplantable tumor
  • 08:16cell line, something like a B16 Melanoma,
  • 08:19and the way the experiment works is to,
  • 08:22in fact, that cell line with a
  • 08:24library of CRISPR CAS 9 guides
  • 08:26that knockout thousands of.
  • 08:28Immunologically relevant genes.
  • 08:29In the genome and then to kind of
  • 08:33select those guides until you have
  • 08:35a pool of knockout tumor cell lines
  • 08:38that is then implanted into mice
  • 08:40under increasing immune selective
  • 08:42pressure from extremely immunodeficient
  • 08:44mice that lack T cells to mice with
  • 08:46an intact immune cell system.
  • 08:482 mice treated with immunotherapy.
  • 08:50In this case,
  • 08:51the irradiated GM CSF secreting
  • 08:53whole tumor cell vaccine GBX,
  • 08:55plus anti PD one kind of strong
  • 08:58immunotherapy treatment regiment.
  • 08:59Would grow these tumors for about
  • 09:012 weeks and then remove them.
  • 09:04Harvested tumors and sequence the sequence.
  • 09:06The barcodes sequence the guides using
  • 09:09them as barcodes and quantitating.
  • 09:11Enrichment and depletion of each
  • 09:13guy and the way we interpreted
  • 09:15this experiment was to compare high
  • 09:17to lower mean selective pressure.
  • 09:20So immunotherapy treated to
  • 09:22immunodeficient mice, for example,
  • 09:23and to interpret it that guides
  • 09:25that were depleted.
  • 09:27Comparing height alone,
  • 09:28selective pressure represented Jews that,
  • 09:30when deleted, convert sensitivity.
  • 09:32To the mean system,
  • 09:34and therefore potential targets
  • 09:36for combination therapy.
  • 09:38In contrast,
  • 09:39guides that were enriched under
  • 09:41strongly selective pressure suggested
  • 09:42to US jeans that were lost made
  • 09:44tumors resistant to new therapy.
  • 09:48And a lot of the targets that we
  • 09:50found this way actually ended up in
  • 09:52the kind of realm of double stranded
  • 09:54RNA sensing or antiviral triggering,
  • 09:56and this is really the area that
  • 09:58I focused on throughout my time.
  • 10:01And this guy is thinking because a lot of
  • 10:03what we know about viral infection comes
  • 10:06from the study of exonerees viruses.
  • 10:08But of course the genome is comprised
  • 10:11largely of repetitive elements that have
  • 10:14the potential to form double stranded RNA.
  • 10:17These could be small interspersed
  • 10:19nuclear elements and obvious retrovirus.
  • 10:21Endogenous retroviruses are long
  • 10:23interspersed nuclear elements or or others.
  • 10:26And so we considered that that we've
  • 10:29Co evolved with these elements.
  • 10:31With these kind of viral remnants
  • 10:33in many cases and ourselves have
  • 10:35developed systems to regulate double
  • 10:37stranded RNA sensing to distinguish
  • 10:39between double stranded RNA.
  • 10:41That's a result of normal cellular
  • 10:43activity and exogenous viral threats.
  • 10:45And so we thought that by targeting some
  • 10:48of the genes that control this regulation,
  • 10:51we might sensitize tumor cells
  • 10:52to tumor therapy.
  • 10:53Trigger this kind of anti virus state.
  • 10:58And the top hits that we discovered
  • 11:01through this process in the antiviral
  • 11:03sensing arena was this paid.
  • 11:05R18 R is an adenosine deaminase
  • 11:07that acts on double stranded RNA.
  • 11:10It has a long cytoplasmic P-150 isoform.
  • 11:12That's interferon inducible and a short.
  • 11:15Constitu Tively Express P110I support him.
  • 11:19The main known function of edar is to
  • 11:21catalyze the conversion of adenosine
  • 11:22to in a scene and double stranded RNA.
  • 11:25And it's thought that in so doing it
  • 11:27prevents double stranded RNA sensing in
  • 11:30the triggering of antiviral immunity.
  • 11:32Kind of autoimmunity.
  • 11:33Accordingly,
  • 11:33there is an autoimmune syndrome called
  • 11:36Acardi Goutieres syndrome that is
  • 11:38associated with biallelic mutations
  • 11:40of a Darwin on the catalytic domain.
  • 11:43It can be quite severe effects
  • 11:45children and mimics viral infection.
  • 11:47However, Interestingly,
  • 11:47the parents of affected patients
  • 11:49who have monolith mutations in the
  • 11:52catalytic domain have evidence of
  • 11:54increased signatures of interferon
  • 11:55gene expression in the blood,
  • 11:57but have no detectable disease phenotype,
  • 11:59suggesting that there's a gene dose effect.
  • 12:04So to begin to validate our
  • 12:06one as a potential drug target
  • 12:08for combination immunotherapy.
  • 12:09We created dedicated knockout tumor cell
  • 12:12lines again using the B16 Melanoma model.
  • 12:15This transplantable tumor model and
  • 12:16we implanted these into mice under
  • 12:19increasing selective pressure.
  • 12:20It means selective pressure starting
  • 12:23with the extremely immunodeficient
  • 12:24nods give gamma mice that entirely
  • 12:27lack adaptive immunity and have
  • 12:29only impaired innate immunity.
  • 12:31In these mice,
  • 12:32looking at the 8 Arnold tumors,
  • 12:34either P-150 knockouts in Orange,
  • 12:36P-150 P, 110 knockouts in red
  • 12:38compared to controls and Gray,
  • 12:39and looking at tumor volume on the top,
  • 12:42or survival in the bottom,
  • 12:44you can see a sort of minimal
  • 12:46decrease in the growth of the
  • 12:49Darnell tumors compared to controls.
  • 12:51And a minimal increase in survival.
  • 12:55In contrast,
  • 12:55when planted these tumors into wild
  • 12:57type mice with an intact immune system,
  • 12:59you see a significant decrease in
  • 13:01the growth of tumors in a significant
  • 13:03survival advantage for the mice.
  • 13:05Finally,
  • 13:05when we implemented these tumors into
  • 13:08mice and treated with anti PD one,
  • 13:10we saw a near 100% cure rate for
  • 13:12mice treated that were a Darnall and
  • 13:15almost no cures in the control chambers.
  • 13:18So to start to understand
  • 13:20the mechanism of this,
  • 13:21we looked at the tumor micro environment
  • 13:23of untreated a Darnall and control
  • 13:25tumors 14 days after implantation,
  • 13:27and we did this using immuno histo
  • 13:29chemistry and as you can see on the
  • 13:32left in control tumors you have
  • 13:34the immune desert type phenotype.
  • 13:36Almost no CD8T cells infiltrating.
  • 13:38In contrast,
  • 13:39in a Darnall tumors we saw this
  • 13:41T cell inflamed phenotype with
  • 13:42diffuse infiltration of CD8T cells.
  • 13:44Quantitative here on the right.
  • 13:49To understand this more deeply,
  • 13:50we next perform flow cytometry.
  • 13:52Again with tumors 14 days after
  • 13:54implantation in the untreated setting,
  • 13:56and as you might predict,
  • 13:58we saw an increase in CD 45
  • 14:01positive immune cells and a Darnell
  • 14:04tumors compared with controls.
  • 14:06And then looking within the CD 45 compartment
  • 14:08we saw increases in CD 3 positive T cells,
  • 14:12CD 4 positive T cells,
  • 14:13CD 8 positive T cells,
  • 14:15gamma Delta T cells and NK cells.
  • 14:19In contrast, when we looked at
  • 14:22immunosuppressive populations,
  • 14:23including mdse and tumor
  • 14:25associated neutrophils,
  • 14:26we saw significant increases in control
  • 14:30tumors relative to a Darnall tumors.
  • 14:34Finally, to probe the micro
  • 14:35environment yet more deeply,
  • 14:37we perform single cell RNA sequencing.
  • 14:39These are the populations we
  • 14:41recovered with myeloid populations
  • 14:43in the upper right and T cell
  • 14:46populations in the bottom left.
  • 14:48As you can see,
  • 14:50using these density plots that
  • 14:51we adapted for this purpose,
  • 14:53you get a strong signal from suppressive
  • 14:56myeloid populations and to like
  • 14:58macrophages and mdse in control tumors.
  • 15:00But a weaker signal from inflammatory
  • 15:02monocytes and CD8T cells.
  • 15:03In contrast,
  • 15:04in the 8 Arnold tumors you
  • 15:06have hardly any signal from the
  • 15:08suppressive minded populations
  • 15:09and and enrichment of single from
  • 15:11inflammatory monocytes and CD8T cells.
  • 15:16To understand what's driving this
  • 15:18change in the micro environment,
  • 15:20we wanted to study the double
  • 15:22stranded RNA sensing pathways that
  • 15:24we thought could be associated
  • 15:25with the phenotypes we'd observed.
  • 15:28Specifically, we wanted to understand the
  • 15:30role of protein kinase are an MD5 rig,
  • 15:33I and nouns which are both associated
  • 15:35with his internal sensors of nucleic
  • 15:38acids in double stranded RNA,
  • 15:40specifically protein kinase power
  • 15:41is associated with translation
  • 15:43arrest in a pop ptosis.
  • 15:44Upon binding double stranded RNA.
  • 15:47Where is MD5 regarding mass induced type
  • 15:50one interferon in the antiviral state?
  • 15:53To test the role of each of these sensors,
  • 15:56we generated a series of double
  • 15:58and triple knockout tumor cell
  • 16:00lines and probe some of the in
  • 16:02vitro phenotypes that we previously
  • 16:04previously studied in a Darnell tumors.
  • 16:06Specifically,
  • 16:07we looked 1st at growth inhibition.
  • 16:09So when you stimulate control
  • 16:11tumors with interferon in vitro,
  • 16:13there's a slight defect in growth that's
  • 16:17magnified when you knockout eight R1.
  • 16:20Looking at our double knockouts,
  • 16:22we saw no effect of knocking out rig.
  • 16:25I MDA 5 or Mens but saw that knocking
  • 16:28out peak PQR reduced the phenotype to
  • 16:31the levels observed in control tumors,
  • 16:34suggesting a PQR was alone.
  • 16:37Responsible for the in vitro
  • 16:39growth defect that we'd observed.
  • 16:41We next looked at interferon beta production.
  • 16:44And this was again an in vitro Aliza and
  • 16:47tumor cells stimulated with interferon.
  • 16:50As you can see,
  • 16:52control tumors produce no
  • 16:54detectable interferon,
  • 16:54whereas a Darnall tumors
  • 16:57produces significant quantity.
  • 16:58This is maintained from the loss
  • 17:00of Rig I suggesting that guy is
  • 17:02not involved in the phenotype.
  • 17:04However,
  • 17:04following the loss of MDA,
  • 17:06Five Man's or PK are you see a
  • 17:08significant reduction suggesting
  • 17:09that all three of these sensors,
  • 17:11or these two sensors in this adapter
  • 17:13have a role to play in phenotype.
  • 17:17We next wanted to understand which of
  • 17:20these double stranded RNA sensing pathways
  • 17:21was required for the in vivo phenotype of
  • 17:24sensitization to whom checkpoint blockade.
  • 17:26So we took our double and triple knockout
  • 17:28tumor cell lines and implanted them into
  • 17:30mice, treating the mice with PD one.
  • 17:33Antibodies targeting PD one,
  • 17:34and as you can see in our control experiment,
  • 17:37control tumors continue to grow out
  • 17:39as they did previously for us in the
  • 17:41eternal summers respond well to,
  • 17:43you know, therapy.
  • 17:45This phenotype persisted following
  • 17:47loss of PQR, suggesting that PQR is
  • 17:50alone not required for the phenotype.
  • 17:53Similarly.
  • 17:53It persisted following loss of MD5,
  • 17:57suggesting MDA 5 alone does not
  • 18:00explain the phenotype.
  • 18:01However.
  • 18:02Following the deletion of both PK
  • 18:04are in MDA 5 together with eight
  • 18:06or one we no longer observe any
  • 18:08difference between the growth of
  • 18:10eight R1 knowledge control tumors
  • 18:12treated with immunotherapy.
  • 18:14Together,
  • 18:14these results suggested to us that
  • 18:16growth inhibition by PQR or antiviral
  • 18:19sensing by MDA 5 amounts sufficient
  • 18:21mediate sensitivity to no therapy
  • 18:23but that at least one is required.
  • 18:28We next wanted to understand which
  • 18:30double stranded RNA sensing pathway
  • 18:32was required for the enhanced community
  • 18:34filtration for the inflammation in the
  • 18:36tumor microenvironment that we'd observed.
  • 18:39And so we again used our double and
  • 18:41triple knockout tumor cell lines.
  • 18:43In this time return to our habit of
  • 18:45looking at the tumor microenvironment,
  • 18:47dissecting the tumors out,
  • 18:49separating out the cells,
  • 18:50and quantitating them.
  • 18:52To look which sensor was was required.
  • 18:57In our control tumors,
  • 18:58you see a relatively low infiltration
  • 19:01of immune cells that significantly
  • 19:03increased following loss of eight R1.
  • 19:05And Interestingly,
  • 19:06this phenotype is,
  • 19:07if anything exaggerated following
  • 19:09loss of protein kinase are however
  • 19:12it's attenuated following loss of
  • 19:13MBA 5 and oblated following the
  • 19:16loss of the two senses together.
  • 19:18A similar pattern followed when
  • 19:19we looked at the proportion of
  • 19:22the 45 positive immune cells that
  • 19:24was comprised of CD8T cells,
  • 19:25again,
  • 19:26increases in eight are null that
  • 19:28persisted following loss of PQR
  • 19:30was attenuated following loss
  • 19:32of MD5 with loss following the
  • 19:34loss of both sensors together.
  • 19:36When we look at a immunosuppressive mdse,
  • 19:39we saw the opposite pattern
  • 19:41increases in control that persisted
  • 19:43or work were even increased.
  • 19:45Further following loss of PQR and no
  • 19:48loss of the phenotype following loss
  • 19:50of MDA 5 for the two sensors together.
  • 19:57This suggested to us that MBA five
  • 19:58may be playing the predominant role.
  • 20:00And inducing tumor microenvironment
  • 20:02inflammation may darnel tumors.
  • 20:04To confirm this,
  • 20:06we looked at the production of interferon
  • 20:08beta interferon gamma in the tumor
  • 20:11microenvironment of the eternal jiggers.
  • 20:13And we saw a similar pattern again
  • 20:15increases in a terminal tumors that
  • 20:18persisted following loss of PQR but was
  • 20:20lost after law after loss of MD5 or the
  • 20:23two sensors together in the same pattern.
  • 20:25Again looking at tumor
  • 20:28lysate interferon gamma.
  • 20:29So haven't seen having seen
  • 20:31this powerful dual mechanism for
  • 20:33sensitizing tumors to immunotherapy.
  • 20:35We asked whether loss of eight R1 was
  • 20:38sufficient to overcome commonly acquired
  • 20:40mechanisms of resistance to amino therapy,
  • 20:43including genetic aberrations
  • 20:45that have been identified as
  • 20:47enriched when comparing discordant,
  • 20:48responsive,
  • 20:49pretreatment,
  • 20:49and resistant posttreatment lesions.
  • 20:51Matched with the same patient.
  • 20:54Known mechanisms that fit this
  • 20:57description include the loss of MHC one
  • 21:00through mutations of HLA or beta 2M,
  • 21:02loss of targeting,
  • 21:03children expressing through Mino,
  • 21:05editing mutations and interferon sensing
  • 21:07pathways including interferon gamma receptor,
  • 21:09the Jackson,
  • 21:10the stats.
  • 21:13And we focused first on the loss of MHC one,
  • 21:16as mediated by loss of data to microblogging
  • 21:19which has been repeatedly identified as
  • 21:21important in challenging form of resistance.
  • 21:24To create this model we
  • 21:26again use CRISPR CAS 9.
  • 21:28This time deleting beta 2 micro
  • 21:30globulin and eight are together.
  • 21:32Along with creating match
  • 21:34control tumor cell lines.
  • 21:37To validate our model of resistance,
  • 21:39we compared control in beta two of null
  • 21:41tumors in the untreated that is dashed
  • 21:44line state versus the treated state.
  • 21:47That's the solid lines using again,
  • 21:49this strong immunotherapy treatment
  • 21:51regimen of GBX and PD one.
  • 21:54And we did this because the normal
  • 21:56control chambers responded very poorly
  • 21:58to PD one and we wanted to make sure
  • 22:00that we could see a response in control
  • 22:03tumors and then validate that it was
  • 22:05lost in the beta two unknown tumors.
  • 22:08And sure enough,
  • 22:09that's what we did see you can see the
  • 22:11control tumors respond albiate transiently.
  • 22:13Alternately,
  • 22:13do grow out to this strong unit
  • 22:15therapy treatment regiment,
  • 22:16but made it to heaven.
  • 22:18All tumors hardly respond at all.
  • 22:22We next looked at a Darnall tumors.
  • 22:25This is our positive control
  • 22:26experiment using strong again
  • 22:27with therapy treatment regimen.
  • 22:29We got a great response to treatment.
  • 22:31The untreated tumors grow out,
  • 22:33albeit more slowly than controls.
  • 22:36Strikingly, however,
  • 22:37this sensitivity persisted following
  • 22:39loss of beta two microglobulin,
  • 22:41suggesting that loss of a Darwin
  • 22:43in tumors is sufficient to overcome
  • 22:46this mechanism of resistance.
  • 22:48This result was a bit surprising actually.
  • 22:50At first, as it suggests that CD8T
  • 22:52cell recognition with MHC one in
  • 22:54tumors is not in all cases required
  • 22:56for the response to amino therapy.
  • 22:58It also raises the question as to
  • 23:01whether it could be possible to
  • 23:03target tumors that entirely lack
  • 23:04high quality CDH cell antigens.
  • 23:06A lot of ongoing work in the
  • 23:08lab is focused on dissecting the
  • 23:09mechanism of this finding,
  • 23:11and one of the first
  • 23:12things we wanted to know.
  • 23:14Is whether antigenic vaccine GBX,
  • 23:16which was unsuccessful in
  • 23:17translating to human use,
  • 23:19was required for this response.
  • 23:23This is actually pretty new data
  • 23:24or afraid with PD one alone,
  • 23:26and found that indeed you still get
  • 23:28great responses in a Darwin all tumors.
  • 23:32Even without the gmax.
  • 23:34To start to understand this
  • 23:36mechanism further, we again looked
  • 23:38in the tumor microenvironment,
  • 23:39this time focusing on our beta 2M
  • 23:41null compared to control tumors.
  • 23:43And so, as you would expect,
  • 23:46increased immune infiltration
  • 23:47CD 45 positive cells.
  • 23:50But now focused on some of these
  • 23:52MHC one non MHC one restricted
  • 23:55cytotoxic populations and these
  • 23:57include granzyme B positive CD
  • 24:004 positive T cells and NK cells.
  • 24:02With the hypothesis that perhaps
  • 24:04these cells which don't require MHC
  • 24:07one for recognition of tumor cells.
  • 24:09May be involved in the phenotype
  • 24:13we've observed.
  • 24:14We've also begun to dissect the
  • 24:16cytokinin kyma kind drivers,
  • 24:17by which these populations may
  • 24:19be recruited and activated.
  • 24:21These graphs are from side to kinda be
  • 24:24Teresa Beta to null and a Darnall tumors.
  • 24:28The two prominent chemo kinds
  • 24:29were identified so far.
  • 24:31CX CL 10 in CCL 5.
  • 24:34Which are both significantly
  • 24:35increased in our beta to emulate
  • 24:37our one all tumors compared with
  • 24:39beta to a control control tumors.
  • 24:44Notably Ehrenring here at Yale has
  • 24:46described a similar phenotype of
  • 24:47being able to overcome the loss
  • 24:49of MHC one using a modified I'll
  • 24:5118 side kind that he designed.
  • 24:52So this remains another possibility
  • 24:54that we haven't yet explored.
  • 24:56However, we think this type of study
  • 24:59is important 'cause articulating the
  • 25:00general principles by which loss of MHC
  • 25:02one can be overcome could lead to new
  • 25:05treatment approaches to target tumor
  • 25:06specific immune evasion mechanisms.
  • 25:11In summary, I hope I've convinced
  • 25:13you have several points.
  • 25:14First aid are one loss over improves the
  • 25:18response to me to therapy. Specifically,
  • 25:21it can overcome the lack of evidence.
  • 25:23Plain tumor, micro environment and the
  • 25:26loss of antigen presentation by image C1.
  • 25:29Additionally, this phenotype is
  • 25:31driven both by tumor microenvironment,
  • 25:33inflammation mediated by MDA
  • 25:355 and sensitization.
  • 25:36Interferon driven by PK are.
  • 25:40Finally, and I think this may be important.
  • 25:43Tumor cells contain sufficient innate
  • 25:45lightning into drive therapeutic information.
  • 25:47If they are in need.
  • 25:49Nucleic acid sensing
  • 25:50checkpoints are disabled.
  • 25:52And what we think this implies is that
  • 25:54there may be other similar innate
  • 25:56immune checkpoints that limit the
  • 25:57sensing of double stranded RNA or other
  • 26:00nucleic acid ligands that we could
  • 26:01think about as therapeutic targets.
  • 26:05And really, those questions inform the
  • 26:07rest of the work that the lab is doing.
  • 26:10I've mentioned already a focus on
  • 26:12double stranded RNA and eight R1.
  • 26:14We're also applying functional genomics
  • 26:15to try to identify other novel targets.
  • 26:18Really, with the insight that we
  • 26:19have to focus on turning on some of
  • 26:22these pathways of double stranded RNA
  • 26:24sensing or micro violent information.
  • 26:27And then we're involved in human translation,
  • 26:29doing kind of in depth tumor
  • 26:31microenvironment investigation across
  • 26:32several different tumor indications.
  • 26:34We're always looking for new
  • 26:37collaborators there.
  • 26:38And all of this comes under the rubric
  • 26:41of therapeutically targeting the
  • 26:43information in the tumor microenvironment.
  • 26:45In just the last couple of minutes here,
  • 26:47I want to quickly mention some of
  • 26:49the ongoing projects in the lab that
  • 26:51I haven't talked about this far.
  • 26:52First, I mentioned just the project.
  • 26:57Describing how to Riker environment
  • 26:59inflammation can overcome the
  • 27:01loss of MHC one.
  • 27:02This is being led by Jessica Way,
  • 27:05but she's Additionally leading a project.
  • 27:09Looking at human tumors and trying
  • 27:10to turn these pathways on in ex
  • 27:13vivo samples as well as doing deep
  • 27:14dissection of the micro environment.
  • 27:16Where we go is working on novel
  • 27:19strategies to detect double stranded
  • 27:20RNA and to mimic the sensors of double
  • 27:23stranded RNA that we believe will be
  • 27:26compatible with functional genomic
  • 27:28screening in the identification of
  • 27:30novel cancer immunotherapy targets.
  • 27:32And finally,
  • 27:32even Kim who is in the lab focused on the
  • 27:36comparison of discordant response lesions.
  • 27:39So responsive and resistant lesions.
  • 27:42From the same patient trying to
  • 27:44understand novel mechanisms of
  • 27:46resistance to new therapies so
  • 27:47that we can focus on overcoming.
  • 27:50With that I want to thank everybody in
  • 27:52our lab as well as our collaborators
  • 27:55and mentors here at, you know,
  • 27:57have been fantastic.
  • 27:58I also wanted knowledge at Nikki
  • 28:00Ning my form. Enter drumming.
  • 28:01So much of the work that I presented early
  • 28:04derives from from studies with them,
  • 28:06and of course our funding here
  • 28:08at the Cancer Center and the
  • 28:10International Research Alliance.
  • 28:11With that, I will wrap up.
  • 28:13Thank you so much for the chance to present,
  • 28:16and I'm happy to take questions.
  • 28:19Jeff, thank you. That's just
  • 28:21terrific work and really exciting.
  • 28:23And we we have folks can submit questions.
  • 28:27We have one question.
  • 28:28Mike Hurwitz asked.
  • 28:30So given the response in eight R1
  • 28:33knockouts in the absence of MHC class one,
  • 28:36do you think that's function of
  • 28:38CD4T cells or NK cells, or both?
  • 28:42Or some other mechanism? Yeah,
  • 28:44I think that's a great question and we
  • 28:46definitely would love to know that answer.
  • 28:50Best hypothesis Now is that partially
  • 28:52based on some of the work that Ehrenring
  • 28:56is presented in Marcus Bosenberg.
  • 28:58NK cells could be an important player there.
  • 29:01Certainly there increased and we
  • 29:02started to see some cytokines in Kemah
  • 29:04kinds that may activate them further,
  • 29:06but you know, we don't even know for
  • 29:08sure that CD8T cells aren't important.
  • 29:10That's an experiment we're doing now.
  • 29:12We just know they're not recognizing the
  • 29:14tumor, but could they be activated through
  • 29:16cross presentation or another means is
  • 29:18another question that we're investigating.
  • 29:21And then you know, in related work.
  • 29:24Obviously Akiko, Saki,
  • 29:25and Anna Pile of working independently on
  • 29:28Rig Rig I are iguana, which which it is.
  • 29:31But which obviously is not necessarily
  • 29:34related to the function vadar one,
  • 29:36and you know how?
  • 29:38How do you see those two with those
  • 29:41two sort of bodies of work relating?
  • 29:44Yeah, so this is
  • 29:46a great question Charlie and actually
  • 29:48Akiko is one of my mentors here and.
  • 29:52Collaborators and we've talked about this.
  • 29:55We're actually in the process of testing.
  • 29:58Are a guy at. Egotist with the innate
  • 30:03arnolin control tumor cell lines and
  • 30:05you know the colloquial way we we
  • 30:07thought about this is kind of as a
  • 30:09maximum inflammation bomb because what
  • 30:11we've shown is that any interferon
  • 30:13producing stimulus can trigger this
  • 30:158 Arnold amplification of sensing,
  • 30:16and so our hypothesis would be that if
  • 30:18you initiate signaling through a guy,
  • 30:20even if there a guy is not involved
  • 30:23in the pathways we've described here,
  • 30:25you basically create a massive
  • 30:26amplification of interferon,
  • 30:27buy by further knocking out eight
  • 30:29R1 so that remains to be seen,
  • 30:32but that's what I would hypothesize.
  • 30:34Yeah, that's interesting.
  • 30:35It sounds like a great
  • 30:37opportunity to look at that.
  • 30:38Well, I I want to keep us on time,
  • 30:41so Jeff, thank you.
  • 30:42I know there are other questions
  • 30:44coming in and people should certainly
  • 30:46reach out to you directly, Jeff.
  • 30:48But thank you for a superb presentation
  • 30:51and let me now turn to our second speaker,
  • 30:54doctor Robert Bone and Bob Bone is a
  • 30:56professor of medicine in hematology,
  • 30:58and recently the past year joins us as the
  • 31:01director of the Benign Hematology program,
  • 31:03as well as the medical director of
  • 31:06the Hemophilia Treatment Center.
  • 31:08Prior to joining Yale,
  • 31:09Bob was founding faculty member
  • 31:11and leader at the Frank Netter
  • 31:14School of Medicine at Quinnipiac,
  • 31:16as well as a professor of medicine at
  • 31:19the University of Connecticut School of
  • 31:21Medicine and Bob throughout his career,
  • 31:24really has been a leader in in in the
  • 31:27clinical care and sort of advancing
  • 31:30work in hemostasis thrombosis as well
  • 31:32as benign hematologic conditions.
  • 31:35And we're really,
  • 31:36very fortunate Bob to.
  • 31:38That Bob,
  • 31:38now leading this section and sharing
  • 31:40with his work with us.
  • 31:42So Bob thank you.
  • 31:44Thank you, Charlie for that introduction
  • 31:47and for the opportunity to speak today.
  • 31:50Let me just share my screen here.
  • 31:53So good afternoon everybody.
  • 31:56And what I would like to do in the
  • 31:58next 25 minutes or so is discuss with
  • 32:01you some of the advances that have a
  • 32:04curd in the treatment of hemophilia
  • 32:07and what I hope to show you is that
  • 32:09over the past five years there have
  • 32:11really been significant and substantial
  • 32:13advances which came in the background
  • 32:16of really several decades of really
  • 32:18only modest advances in therapy.
  • 32:21So just as a brief review here,
  • 32:24these are excellent disorders,
  • 32:26mostly affecting men,
  • 32:27but can also affect women who might
  • 32:30have low factor levels due to
  • 32:33unequal X chromosome inactivation,
  • 32:35hemophilia A&B or deficiencies
  • 32:37in factor 8 or 9 respectively.
  • 32:39They are clinically identical disorders
  • 32:42and the severity of the disease
  • 32:45is really relies primarily on the
  • 32:48residual factor that is remaining
  • 32:50in the blood with those with severe.
  • 32:53And moderate disease having less
  • 32:55than 5% of factor 8 or factor 9
  • 32:57and those with mild disease having
  • 33:00a higher value and morbidity and
  • 33:02mortality is due to spontaneous
  • 33:04and trauma induced bleeding,
  • 33:06including bleeding into joints which
  • 33:09can cause a hemophilic arthropathy
  • 33:12which we can be quite quite disabling.
  • 33:15And just the history of hemophilia
  • 33:17treatment in the last century
  • 33:19is seen briefly on this slide,
  • 33:21and at the end of World War Two
  • 33:24blood or plasma transfusions were
  • 33:26used to treat patients.
  • 33:28This these were largely ineffective,
  • 33:30is only small amounts of factor 8 or
  • 33:33factor 9 could be transfused in the 1960s.
  • 33:36Cryoprecipitate was discovered
  • 33:37as a source of Factor 8,
  • 33:40and that quickly gave way to the
  • 33:42use of factor concentrates either
  • 33:44factor 8 or factor 9.
  • 33:46Purified from the plasma of
  • 33:4910s of thousands of donors.
  • 33:51And of course,
  • 33:52while this advanced care,
  • 33:54it also exposed individuals to a
  • 33:56number of viral viral particles and
  • 33:59hepatitis C and HIV became a very
  • 34:02significant problem in this population.
  • 34:04And then in the early 90s
  • 34:07recombinant factors 8:00 and 9:00,
  • 34:09or produced and for the developed world,
  • 34:12where economically this was allowable
  • 34:14of the treatment of hemophilia
  • 34:17with recombinant factors 8 and 9.
  • 34:19Became really the standard of
  • 34:23care up until very recently.
  • 34:26There are now about 145 federally
  • 34:29funded hemophilia treatment centers
  • 34:31in this country and of course jeliz is
  • 34:34one of those is one of those centers.
  • 34:37And the therapeutic.
  • 34:38The approach in clinical issues
  • 34:40are outlined here.
  • 34:42Patients with hemophilia can either be
  • 34:44treated in what's known as on-demand
  • 34:46or episodic factor replacement,
  • 34:48which is the treatment with Ivy
  • 34:51Factor 8 or factor 9 to treat a
  • 34:54bleed or prophylactic therapy.
  • 34:56An inhibitor development,
  • 34:57that is an Allo antibody directed
  • 35:00against Factor 8 or less commonly,
  • 35:02factor 9 is a significant problem
  • 35:05for patients and may occur in 30 or
  • 35:0840% of individuals with hemophilia A
  • 35:10and makes treatment very difficult
  • 35:13and the goals of therapy are really
  • 35:15here to prevent
  • 35:16any bleeding. If possible,
  • 35:18prevent joint disease and optimize a
  • 35:21quality of life for these individuals.
  • 35:24And the infusion of factor 8 or
  • 35:25factor 9 by patients is traditionally
  • 35:27given at home intravenously.
  • 35:29Patients from a very young age learn to start
  • 35:32an Ivy and infuse factor 8 or factor 9,
  • 35:35but because of the short
  • 35:37half-life of these drugs,
  • 35:38about 12 hours for factor 8 and
  • 35:4018 to 24 hours for factor 9,
  • 35:42they need to be administered two to
  • 35:45three to sometimes four times per
  • 35:47week to keep the factor levels in a
  • 35:49range that will prevent bleeding.
  • 35:51So this is an onerous thing
  • 35:53for patients to do.
  • 35:54And any advances here would be
  • 35:58greatly appreciated by them.
  • 36:00So here's the obligatory coagulations
  • 36:02slide that I would like to show
  • 36:06to to reinforce and emphasize
  • 36:08the role that Factor 8 and factor
  • 36:119 having blood coagulation.
  • 36:14So what we're seeing here is the
  • 36:17tissue factor initiated pathway and
  • 36:20activation of factor 10 by tissue
  • 36:23factor 7A or activation by factor
  • 36:269 to 9 A by tissue factor 7A.
  • 36:29And 9A is also able to activate 9:50
  • 36:33A O2 pathways to get down to this
  • 36:36all important enzyme factor 10A,
  • 36:39and in this latter reaction factor
  • 36:418 serves as a cofactor for the
  • 36:44enzyme factor 9A.
  • 36:45To act on its substrate factor 10
  • 36:48and increases the rate of reaction
  • 36:51hundreds of 1000 fold when factor 8
  • 36:54is able to align the substrate and
  • 36:56enzyme on a phospholipid surface in
  • 36:59the correct in. In the correct fashion.
  • 37:03One other thing to mention about
  • 37:05Factor 8 before we get into some of
  • 37:08the details of the advances is that
  • 37:11factor 8 travels if you will in the
  • 37:13blood bound to von Willebrand factor.
  • 37:15Von Willebrand factor is seen here in
  • 37:18this linear structure at the bottom,
  • 37:20factor 8 is the yellow diagram above,
  • 37:23and the binding of factor 8 von
  • 37:25Willibrand factor enhances the
  • 37:27half life of factor 8 from about
  • 37:292 hours to about 12 hours.
  • 37:31So this is a very important interaction.
  • 37:34And just to point out here,
  • 37:36'cause this will become important
  • 37:38later is that the binding site
  • 37:40on von Willebrand factor is these
  • 37:42two protein domains,
  • 37:43designated D prime and D3,
  • 37:45and another important point is there
  • 37:47appears to be a large portion of the
  • 37:50factor 8 molecules termed the B domain,
  • 37:52which is not required for factor 8 function,
  • 37:55so you could remove that domain
  • 37:58and in fact factor 8 has a similar
  • 38:01activity than it does with that domain.
  • 38:04So the advances in care of hemophilia
  • 38:07really over the past five to six
  • 38:10years come into three different areas.
  • 38:12One is extended,
  • 38:13half-life factor concentrates,
  • 38:14allowing for patients to infuse
  • 38:16less frequently.
  • 38:17The development of non factor 8
  • 38:19or 9 therapeutics,
  • 38:20and then gene therapy and we'll
  • 38:24go through these individually
  • 38:26in the next 15 minutes or so.
  • 38:28So the extended Half-life products
  • 38:30have been produced by manipulating
  • 38:32the recombinant factor eight
  • 38:34or nine in a number of
  • 38:35different ways, many of which are familiar
  • 38:38to you by either adding polyethylene
  • 38:40glycol or conjugating the factor to the
  • 38:43FC portion of immunoglobulin or albumen,
  • 38:45to improve half-life, or,
  • 38:47in the case of factor 8,
  • 38:49to remove that B domain, which causes
  • 38:52a slight increase in the half life.
  • 38:55And there are now a number of products
  • 38:58that have been approved for use at
  • 39:00our extended Half-life products,
  • 39:02and I'll draw your attention
  • 39:04to the last three on this list.
  • 39:07These are factor 9 products which have
  • 39:09been manipulated by these methods,
  • 39:11seen here and the half life of these
  • 39:14products has been extended from 18 to
  • 39:1724 hours to upwards of 90 or 100 hours.
  • 39:20So this is allowed patients with factor 9
  • 39:23deficiency or hemophilia B to be treated.
  • 39:26Once a week,
  • 39:27once every 10 days and in some circumstances,
  • 39:31even once every two weeks.
  • 39:32So a significant advance for
  • 39:34people needing to give intravenous
  • 39:36therapy themselves at home.
  • 39:38The advances in hemophilia A with factor 8.
  • 39:41However,
  • 39:41a much more modest with this
  • 39:43type of manipulation,
  • 39:45and it turns out that the the
  • 39:47degradation in the catabolism and
  • 39:49clearance from the circulation of
  • 39:51factor 8 is much more linked to the
  • 39:54clearance of von Willebrand factor,
  • 39:56the protein that it's bound to.
  • 39:59So making modifications in the FAQ.
  • 40:00After 8 molecule has really had
  • 40:03minimal effect up until recently
  • 40:06on Factor 8 Half-life.
  • 40:08So an interesting construct has been devised,
  • 40:11and it's shown on the top panel here
  • 40:13and in this construct the D prime and
  • 40:16D3 regions of von Willebrand factor,
  • 40:19the binding region to factor 8,
  • 40:22is linked to an FC portion of an
  • 40:25immunoglobulin and linked to the
  • 40:27B domain less factor 8 molecule,
  • 40:29which also has linked on at
  • 40:32this hydrophilic polypeptide,
  • 40:33which also can extend the half life.
  • 40:36So this product has been called bib 001.
  • 40:39And was treated with.
  • 40:41Was used to treat a handful of
  • 40:43patients in a safety study,
  • 40:45and those results were were
  • 40:47reported in the New England Journal
  • 40:49of Medicine earlier this year,
  • 40:51and patients were either treated
  • 40:53at two different doses of this new
  • 40:56product and the factor a clearance
  • 40:58from the circulation was compared
  • 41:00to the typical factor 8 clearance
  • 41:02seen in the lighter blue bars here
  • 41:05and what you can see I think,
  • 41:07is that the half life of this newer product.
  • 41:11Is now about two days increased,
  • 41:13about five or six fold the half life
  • 41:15of the standard factor 8 product.
  • 41:18So this this product is now in
  • 41:20large scale clinical trials and I
  • 41:22think in the next year or two we
  • 41:24should have some more information,
  • 41:26and this may be an advanced
  • 41:29for for some of our patients.
  • 41:32So let me shift for a minute for
  • 41:34the to the non factor product for
  • 41:36the treatment of hemophilia and I
  • 41:38think their significant advance
  • 41:39has been made here and there are
  • 41:41three drugs that will talk about
  • 41:43will really focus primarily on this
  • 41:45first drug which is called EMAS
  • 41:48ISM AB. A nemesis Omab is a
  • 41:51bispecific monoclonal antibody.
  • 41:53That binds the factor 9 and factor 10,
  • 41:56so it simulates the activity of Factor 8.
  • 42:00Remember that factor 8 is able
  • 42:02to colocalize factor 9 and factor
  • 42:0510 on a phospholipid surface.
  • 42:07This antibody is able to bind factor
  • 42:109A and factor 10 in the circulation an
  • 42:14again simulate the activity of Factor 8.
  • 42:18So this drug is not exactly like Factor 8.
  • 42:21There are.
  • 42:22There are certain differences here.
  • 42:24It binds to factor 8 and nine
  • 42:27in the circulation,
  • 42:28not just on the phospholipid membrane.
  • 42:30It has different infinities
  • 42:32for the substrate and enzyme,
  • 42:34and whether or not that becomes an
  • 42:37issue for this drug will only know
  • 42:40as more experience is is accumulated.
  • 42:43But nonetheless,
  • 42:43this drug is really shown dramatic activity,
  • 42:46so this this is a study that was
  • 42:49published a few years ago in the
  • 42:52New England Journal of Medicine.
  • 42:54Here we had patients who have hemophilia
  • 42:57A with inhibitors to factor 8,
  • 42:59so a challenging group of patients to
  • 43:01treat were treated either with their
  • 43:04typical regimen of recombinant factor
  • 43:067A or factor 8, bypassing activity,
  • 43:08or with Emma system AB given by
  • 43:11subcutaneous injection once a week
  • 43:13and the annual bleeding rate.
  • 43:15Is been been described on this slide
  • 43:17here and you could see if we just look
  • 43:21at these blue histograms for a minute here.
  • 43:23The annualized bleeding rate in the
  • 43:26EMA system app Prophylaxis Group
  • 43:29was about five or six and it was
  • 43:32almost 30 in the standard of care.
  • 43:35Treatment of patients with
  • 43:37hemophilia A and inhibitors.
  • 43:39So a really significant
  • 43:41advantage for these individuals.
  • 43:43And then a second study was published
  • 43:45with looked at patients with hemophilia
  • 43:48A without inhibitors and these.
  • 43:50This was a randomized trial.
  • 43:52Patients were treated with one
  • 43:54of two doses of Emma's is a map
  • 43:56either given weekly or every other
  • 43:58week by subcutaneous injection,
  • 44:01compared with no prophylaxis.
  • 44:02About 100 patients in the trial,
  • 44:04and again the annual annualized
  • 44:06bleeding rate went from about
  • 44:0940 to about one or two.