Endocrine Adverse Events with Cancer Therapies

January 17, 2024

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Yale Cancer Center Grand Rounds | January 5, 2024

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00:00US online. It's my great pleasure today
00:02to introduce our Grand Round speaker,
00:04Doctor Kevin Harold.
00:05I've known Doctor Harold,
00:07it turns out, for 10 years now.
00:08We just figured it out.
00:10We met at the bedside.
00:12And I think for the fellows in the audience,
00:14this is a this hopefully will be a teaching
00:16moment because you get a sick patient,
00:18you're not sure what's wrong with him.
00:19You call the expert.
00:21And from that, we developed an
00:23entire universe of research projects,
00:25grants and so on that Doctor Harold
00:27will be talking about today.
00:29To me that exemplifies the beauty
00:31of Yale University and what we're
00:34about unusual clinical circumstances
00:35taken back to the bench,
00:37going back to the clinic,
00:38etcetera, etcetera.
00:39But the best part of it
00:41all is the collegiality.
00:43So I'm just remembering my
00:45first after we got our funding,
00:46the very first research meeting that
00:48I had with Doctor Harold and Doctor
00:50Eric Murphy, who's since left Yale.
00:52Yeah, I'm not an immunologist, but they are.
00:55They.
00:55They both are card carrying
00:57immunologists and Doctor Mephre in
00:59particular doesn't tolerate fools.
01:01So I was really intimidated by this
01:03meeting and I had established ground rules.
01:05I don't know if Doctor Harold remembers this.
01:07We decided that this is an idiot free zone.
01:10We're all smart,
01:10we can say whatever we like and
01:12we never have to be embarrassed.
01:13And I think that that principle
01:15has LED us in the last 10 years
01:18because it turns out that even I had
01:20something to bring to the table here.
01:22So collegiality, respect,
01:24creativity has led to a whole
01:26field that I think we've opened
01:29up here in translational research
01:31on immune related adverse events
01:34for endocrine toxicities.
01:35So other than this whole world Doctor
01:38Harold is actually really famous for
01:41delaying type one diabetes in kids,
01:44a major breakthrough in delivering
01:46CD3 antibodies to children who
01:49had started to develop type one
01:51diabetes giving them the anti CD3
01:54antibody delaying the onset of
01:56full blown islet cell destruction.
01:59I don't think he's going to be
02:00talking about that today,
02:01but today we look forward to
02:03listening to all the cancer related
02:04studies that he's done.
02:05So without further ado,
02:07thank you Doctor Harold for taking the time.
02:15OK, thank you very much Harriet
02:17for that very kind introduction.
02:19I, I, I I have to admit I I was also
02:21quite pleased that we were going
02:23to set up our research meeting.
02:25So there'll be no it would
02:26be an idiot free zone.
02:28I I I appreciated that.
02:32So here's my disclosures.
02:37So hopefully this is review to everyone
02:41that that basically we we live in
02:44a constant immunologic equilibrium
02:47balancing lymphocyte activation
02:49and control and the activation is
02:53controlled by a number of Co simulatory
02:56molecules and recognition by antigen
02:59by T cells and other immune cells.
03:04And we the the the major developments in
03:06the cancer field of course are that by
03:09disrupting this balance we can develop
03:12effective ways of treating cancers.
03:14And and indeed this has revolutionized
03:18the field over the past decade and
03:20it became very clear initially when
03:23these agents became available for
03:26clinical use that there were adverse
03:29events that would occur as well
03:31since the balance that prevents
03:33us from developing autoimmunity is
03:36controlled by the same mechanisms.
03:38And we and it's been established
03:40for many years that even normal
03:42patients have immune cells that are
03:45capable of recognizing self antigens.
03:47So by tipping this balance it's fairly
03:50clear that one would be able to develop
03:53autoimmune diseases and that's that's
03:56what I'm going to be talking about today.
03:59Now the endocrine organs seem to be
04:01particularly vulnerable to immune related
04:04adverse events with with biologic
04:07therapy particularly with checkpoint
04:10inhibitors and you can this is from a
04:13review that came out a number of years ago,
04:16but there are many,
04:17many organs that are affected.
04:19I've on the right side we see just the
04:22endocrine organs that are affected.
04:25Fibroid disease is the most common and
04:29frankly can be over 15% in some series
04:36and the second most common is pituitary
04:39disease that can be difficult to diagnose,
04:42certainly important to diagnose.
04:45And then the other endocrine organs seem
04:49to be affected as well including the
04:51the insulin producing beta cells that
04:54leads to the development of diabetes.
04:56Now I would point out from this graph
05:00that that the development of these
05:04adverse events are most common with
05:07combination therapies and this is going
05:09to come up again in some of the data.
05:11I'm going to present to you that the
05:14combination of anti C2A4 plus anti PD
05:19one or PDL one seems to be seems to
05:23impart a higher risk of developing these
05:25adverse events than either agent alone.
05:29So the timing of them varies a bit.
05:32And sometimes we, as a practical matter,
05:36have a hard time determining whether
05:38or not an adverse event that we may see
05:42is directly related to the checkpoint
05:44inhibitor that's been given or whether
05:47it was just happening by chance.
05:49Because some of these adverse events
05:51such as thyroid disease or diabetes are
05:54relatively common in the population,
05:56particularly in the older population.
05:58But this graph shows you the timing of
06:01some of the more common adverse events.
06:04You can see that hypothesitis can happen
06:08several weeks after the development after
06:11a checkpoint inhibitors are administered.
06:14Some of the others that are that
06:17are also quite common tend to occur
06:20in a more acute manner.
06:22Now as Harriet mentioned we started
06:27I'm going to spend most of my the rest
06:30of the talk talking about checkpoint
06:32induced autoimmune diabetes because
06:34that's where we've done the most,
06:36the most work.
06:37And let me just make it mention
06:39one thing about some of the others.
06:40You know I I I do want to say sort
06:44of upfront that that the mechanisms
06:46of some of these other checkpoint
06:49induced endocrine adverse events are
06:52not very well worked out at all.
06:54There is really one sort of lead paper
06:57that described the development of
07:00autoimmune hypothesitis that talked
07:02about expression of C of CTLA 4 on
07:05pituitary cells and suggested that
07:07what happened with anti CTLA 4 is
07:10that the antibodies bound to CTLA
07:124 on the pituitary fixed complement
07:14and destroyed the cells.
07:16But if you go through the paper carefully,
07:18you'll see that, well,
07:19it really wasn't sort of.
07:21It wasn't the ACTH producing cells,
07:23which is a common manifestation
07:26of hypothesitis,
07:26it was prolactin producing cells
07:29and and also TSH producing cells.
07:32So the precise mechanisms there
07:34really aren't quite so clear.
07:36Likewise for thyroid disease.
07:37I think it's still somewhat of
07:40an unknown or a wide open area
07:42for investigation I should say to
07:45understand the mechanisms.
07:46But we focused our attention on
07:48autoimmune diabetes and hopefully
07:50have made some inroads into
07:52understanding the mechanisms here.
07:54And our work began as,
07:55as I I pointed out to Harriet,
07:57if you take a look at the date on this,
08:00this paper almost a decade ago
08:05when the patient #1 here was
08:08referred to me by Doctor Kluger.
08:11And the IT was a woman with Melanoma
08:16who have been treated with IPI and also
08:21had gotten nivolumab at that point and
08:24presented with diabetic ketoacidosis.
08:26And you know this was quite striking.
08:29This is someone who's 55.
08:30And then subsequently there were a
08:32number of other cases that came from
08:35Yale of people over the age of 50 who
08:40were presenting with ketoacidosis
08:42often and new onset hyperglycemia.
08:45And this was kind of striking and
08:49to me it was striking because you
08:52know we hadn't seen it before the
08:54the the anti PD one drugs were new
08:58at that time but we had had anti
09:01CTLA 4 Ipilimab for a number of years.
09:04And so that was kind of kind of striking.
09:07So we ended up putting these series together
09:09and this I I know I mentioned this the
09:11last time I spoke but I I want to kind of
09:14bring this point up again particularly
09:16for the trainees who are here and and
09:21the the data that we've subsequently
09:23had even makes the point even further.
09:26So we we put this series
09:27together and we send it in,
09:28we send it into the endocrine
09:30journals for publication.
09:31And you know a lot of people,
09:34a lot of the journals or some
09:36of the journals didn't weren't
09:37weren't interested in it.
09:39And then finally it goes to one of
09:41the leading endocrine journals and
09:42it's sent out for review and we get
09:45comments back from the review and
09:47and we did a very extensive job
09:49answering all the all the comments.
09:51There were 12 pages of of responses
09:54and so we sent it back and and the
09:58reviewer comes back and says well
10:01if you know if this was really
10:05occurring the development of of
10:08diabetes after anti PD one we would
10:10have known about it already.
10:12So that that was the end of that journal.
10:14So we ended up publishing this as a
10:17letter actually in diabetes care and
10:19it is one of the most highly cited,
10:22certainly one of the most highly cited
10:25papers in diabetes care that that is
10:27the first description of anti PD1 antibodies.
10:30So the reason I wanted to mention
10:31this story to you is as I'm going to,
10:33as I'm going to show you later on that
10:36not only was the reviewer wrong in
10:38saying that we would have known about it,
10:42but mechanistically now we know
10:43why the reviewer was wrong.
10:45So that's kind of nice to know
10:47why your reviewer is so wrong.
10:49So what?
10:50What what is,
10:51what are some of the features
10:53of this form of of of diabetes.
10:55So first of all,
10:57it happens relatively very acutely.
10:59Here's here's some data.
11:01This is coming from our colleagues
11:03at UCSF where we've put together
11:04patients at the two institutions
11:06and you can see this here are a few
11:08patients who developed checkpoint
11:10induced diabetes and their blood
11:12sugars are completely normal And then
11:15dramatically there is a big spike
11:17in their in their glucose levels.
11:19And the other thing that's that's
11:21quite interesting about that is if
11:23you look at their endogenous beta
11:25cell function by measuring C peptide,
11:27remember C peptide is cleaved from
11:29pro insulin when the beta cells
11:31make insulin and it's a good measure
11:34of endogenous insulin production
11:35cause the insulin you inject doesn't
11:38have C peptide.
11:39So if you take a look at the kinetics of
11:42loss of C peptide here that it happens very,
11:46very quickly.
11:47In fact in one case it it happened
11:50while patients were following the
11:52the individual while investigators
11:53were following the individual in the
11:56hospital. And the other point about
11:58this is patients generally go to
12:010 or near 0 in other words levels
12:04that are clinically insufficient.
12:06We'll come back to that later on.
12:09Here's a few other bits of information
12:12about the demographics of patients,
12:15so you can see the age.
12:17These are people who are older than you
12:22might expect with presenting with diabetes.
12:25It generally occurs with anti
12:28PD ONE or anti PDL 1.
12:30The hemoglobin A1 CS are elevated at probably
12:34because of the degree of hyperglycemia.
12:37About half of the patients are OR and
12:40depending on the review some even even
12:43higher percentage present with ketoacidosis.
12:46See peptide frequently Becomes undetectable.
12:49The median time is about 11 weeks and
12:52only about 40% of individuals are
12:54positive for auto antibodies and this
12:56brings up a a classification issue.
12:58Some people call this type one diabetes.
13:01As I'm going to explain to you,
13:02I don't think this is type one diabetes,
13:04it's autoimmune diabetes induced
13:06by checkpoint inhibitors,
13:07but it's very different from classic
13:11spontaneous type one diabetes.
13:15Now there is a very large proportion
13:18of individuals who we don't talk
13:20about a lot who I think probably
13:23fall into this bucket,
13:24who are individuals who may have mild
13:27type 2 diabetes who then present
13:30with much worsening of their glucose
13:32control and may become may previously
13:35have been managed with oral anti
13:37diabetic agents and now all of a
13:40sudden may present ketoacidosis
13:42or may require insulin therapy.
13:44Now type 2 diabetes is a very common disease.
13:47So it may actually be that the
13:50frequency of this disease is much
13:53higher than is even represented by the
13:560.2 to 1.9% from the past reviews.
13:59Now I mentioned not everybody
14:01has autoantibodies.
14:03Here's some examples of that.
14:06Some patients, if you take a look
14:08at three patients on the bottom,
14:09some start out negative.
14:11Each of those antibodies are one of
14:13the auto antibodies that we measure
14:15in classic type one diabetes.
14:17You can see some patients start out negative,
14:19become positive,
14:20some patients start out positive,
14:22stay positive.
14:23So it varies about 40% overall are positive.
14:27But the frequency of those who are positive,
14:30sorry let me go back for two or
14:32more which is what we,
14:33which is kind of the hallmark of spontaneous
14:36type one diabetes is relatively low.
14:40Now curiously the the alpha
14:42producing cells in the islet,
14:45remember the islet is a collection of cells,
14:47alpha cells,
14:48beta cells,
14:48delta cells and so on that make
14:50a variety of hormones.
14:52The loss of of of endocrine cells,
14:55this seems to be limited to the beta cells.
14:58The alpha cells sitting right next
15:00to the beta cells are unaffected and
15:02the reason for that is not clear.
15:04But as you can see from this data
15:06from patients that we we where we
15:09measure Glucagon here didn't seem
15:11to make a difference in terms of
15:15their Glucagon levels.
15:17Now one of the early striking
15:19findings from our series
15:20of patients was that a high proportion
15:23of individuals were HLAD, R4. Now Dr.
15:26three and four are associated with with
15:29classic spontaneous type one diabetes.
15:31But this proportion of of DR4 is
15:34strikingly high and it's higher
15:36than the background population.
15:38And DR3, the other allele associated
15:41with spontaneous diabetes was
15:42not increased in frequency.
15:44So DR4 somehow or another seems
15:46to be important in predisposing
15:48to the development of type of
15:52of checkpoint induced diabetes.
15:54And I want to point out this recent
15:59observation that was originally made
16:01by Jasmine Caulfield and and Lilac
16:05Eisenbud from our patients here.
16:09And what was done is we were doing
16:12a a genome sequencing of tumors and
16:16identified a number of mutations in
16:18a variety of genes that seem to be
16:21associated what seemed what seemed to
16:22be at a higher frequency in people
16:25with checkpoint induced diabetes.
16:27And then we ended up going back and
16:30doing sequencing of of peripheral
16:32blood cells and finding that indeed
16:35there were germline mutations that
16:36seem to be associated with development
16:39of checkpoint induced diabetes.
16:41And interestingly the one of the the,
16:44the highest frequency was in this
16:46molecule called NLRC 5 and you
16:49can take a look on the right,
16:51the frequency of individuals with
16:54NLRC 5 variants was in our series 65%.
16:59Now it's not a huge series because
17:01we don't we don't have tons of
17:03patients we had we had 13 here.
17:06But you can see that at least
17:08the statistically it it,
17:09it turns out to be in a much higher
17:13frequency compared to those individuals
17:15without checkpoint induced diabetes
17:17who get the same checkpoint inhibitors.
17:20Now what's the importance of NLRC 5?
17:23So NLRC 5 actually tends to is is is
17:28evolved in a class one MHC antigen
17:31presentation.
17:32I'll tell you about that in just a moment.
17:34But you can see that it seems to be
17:37an important molecule involved in
17:42responses in in cancer patients that
17:46that methylation of NLRC 5 reduced
17:49NLRC 5 seems to be associated with
17:54impaired CTL activity and clearing
17:57of of tumors.
17:59The its expression seems to be
18:01correlated with survival and in
18:03diabetes it's also been a associated
18:05with beta cell antigen presentation
18:10and and the interferon response.
18:12So for example,
18:14the NLRC knocked down beta cells
18:17seem to have a decreased interferon
18:20induced class one MHC expression
18:22and seems to be associated with
18:26protection from autoimmune diabetes.
18:29So NLRC 5 is is a regulator of Class
18:331 dependent antigen presentation,
18:35much the same as the classic Class 2
18:43transactivator. It's responsible for
18:46bringing peptides into the endosome
18:50for processing and placing them on
18:55developing class one MHC molecules.
18:58It's expression seems to
18:59be induced by interferons,
19:01particularly interferon gamma
19:04through Stat 1 signalling.
19:07So this review actually
19:09describes the mechanism.
19:11I'm not going to go into detail about it,
19:13but what we ended up doing and this
19:15is work that Anna Pertigato did,
19:17we ended up looking at expression of TAP ONE,
19:20which is an important transactivator
19:25that's associated with class one MHC
19:28expression as well as HLAA on peripheral
19:31blood cells in patients with the mutation
19:35or with wild type type of the NLRC 5.
19:40And as you can see and in patients with
19:43the mutant there seems to be higher
19:47expression of TAP one and actually of HLAA
19:50although we haven't reached statistical
19:52significance for the HLA molecule.
19:55So it it suggests at least that there is
19:58some change in expression of MHC molecules
20:02or potentially presentation of peptides
20:05by individuals who have this mutant.
20:09So to summarize these two points,
20:10the there seems to be evidence
20:14for mutations or differences.
20:16In class one and Class 2 MHC molecules
20:19that that are associated with development
20:22of checkpoint induced diabetes.
20:24First of all HLAD R4 is common and
20:27perhaps that leads to the development
20:29of an auto autoreactive repertoire.
20:32This NLRC 5 mutation also seems
20:35to have some role in potentially
20:39in expression of molecules.
20:41A presentation of molecules by beta
20:45cells or even potentially in affecting
20:48a subgroup of CDA positive T cells have
20:52been associated with immune regulation.
20:56Now the let me just raise some
20:59questions about these these two points
21:01by make by by pointing this out.
21:04When we've looked at auto antigen
21:07reactive T cells in patients
21:10with checkpoint induced diabetes,
21:12we've looked for auto antigen
21:15reactive T cells that are reactive
21:17to conventional type one diabetes.
21:19Auto antigens,
21:20we don't really find an increase.
21:23So if you take a look at that,
21:25we've looked at T cells that are
21:27identified by binding to class one MHC
21:30tetramers that are loaded with the
21:32peptides that are shown on the left side.
21:35If you look at the frequency of
21:38these cells on the right side
21:40and the individuals treated
21:42with checkpoint inhibitors,
21:43those who don't have diabetes or do,
21:45there's really no difference.
21:46So it at least would suggest that the,
21:49the known auto antigens or recognition
21:53of the known auto antigens is not
21:56really increased or at least the
21:58frequency of cells is not increased
22:01in those individuals who are
22:03developing checkpoint inhibitors.
22:04Let me just you know sort of say
22:06as a preface to this data the the,
22:08the low hanging fruit on this was well,
22:11these individuals had an autoreactive
22:13repertoire. They had Dr.
22:15Four, we removed the checkpoint blockade.
22:17These cells just did their thing,
22:19don't think so.
22:20It could be that there are cells that
22:22are reactive to unknown auto antigens
22:24and as I'll show you in just a moment,
22:27there is some evidence that that
22:29might be true, but that's not all.
22:33There are also there's also evidence
22:35of inflammatory lesions that or
22:37inflammation that's occurring
22:38in the pancreas that may be very
22:41important for development of
22:43checkpoint induced diabetes.
22:44And this actually came from from
22:48actually a clinical observation from
22:50patients here in which we found that
22:53there was an increase in amylase and
22:56lipase in individuals who ultimately
22:58went on to develop diabetes.
22:59They don't develop clinical pancreatitis.
23:02But here we're looking at the amylase
23:05and lipase level on one individual
23:08who is who develops checkpoint
23:10induced diabetes and you can see the
23:12lipase on the left bumps and then
23:14red is when they developed diabetes
23:16and the amylase bumps and then red
23:19is when they developed diabetes.
23:21If you look at our entire series
23:26and look at the relative levels
23:28of lipacer amylase on the bottom,
23:31you can see that the that that
23:33both are elevated prior to the
23:35development of of of diabetes.
23:37Now interestingly it prompted us
23:39to look at what well like what's
23:42actually happening in the pancreas.
23:44They were not symptomatic and so we
23:48ended up looking at CT scans that
23:51fortunately we had from before and
23:55after individuals presented with diabetes.
23:57And what we found if you take a look
24:00at the CTS and on the on the top here
24:03is the the red arrow identifies the pancreas.
24:06The there actually seem to be shrinkage
24:09of the pancreas in individuals who went
24:12on to develop checkpoint induced diabetes.
24:15So it's suggested that there is more
24:18than just a direct attack on beta
24:20cells that there may actually be
24:23a broader attack in a a broader
24:25inflammatory response in the pancreas.
24:28And unfortunately one of our patients
24:31died as soon after they had developed
24:34checkpoint induced diabetes.
24:35But we had the opportunity to take a
24:37look at their pancreas by immunohistic
24:39chemistry and this is what we found.
24:41You can see that there are plenty
24:43of CD 45 positive immune cells that
24:46are infiltrating the islets and
24:48that are infiltrating the pancreas.
24:50They are not just in the islets and in
24:52fact many of them are outside of the islets,
24:54as you can see by standing
24:56for insulin on the right.
24:58And there are both CD4 and
25:00CD8 positive cells.
25:01Chromagranin identifies the endocrine cells.
25:05They're infiltrating the islets
25:07and they're outside of the islets.
25:09And if you look at cytokines that
25:12are present in the pancreas,
25:15we find both interferon gamma and TNF.
25:19And interestingly,
25:20one of the other findings from this
25:24immunohistochemical analysis is PDL
25:27one was actually induced on beta
25:31cells in and on the other endocrine
25:34cells in this patient who died
25:37with a checkpoint induced diabetes.
25:39Now that's a little weird.
25:41We thought that PDL one was actually
25:44protective against diabetes.
25:46So what what's going on here?
25:49So let me just make the point and again
25:52this is work that Anna Pertigato has
25:55done that indeed inflammatory mediators,
25:57particularly gamma interferon
25:59will induce PDL One on beta cells.
26:02There is a interferon response
26:04element in the promoter of PDL
26:07one and as you can see by looking
26:09but by flow interferon gamma.
26:11This is human beta cells.
26:13Interferon gamma and interferon
26:17gamma with TNF induce expression of
26:19PDL one on beta cells and it seems
26:23to be dependent through signaling
26:25by gamma interferon because if you
26:27give rexolitinib to block Jack
26:32signaling through Stat One,
26:34you can inhibit the expression of PDL one.
26:39Now there was good evidence for the
26:42importance of PDL 1 in development of
26:45autoimmune diabetes and most of this
26:48work came originally from Arlene Sharp.
26:51And the the work that I'm I'm showing
26:55on the left is from a paper of hers
26:59a number of actually 20 years ago
27:01now that showed if you knock PDL one
27:03out of this susceptible mouse strain
27:06NOD that the mice spontaneously
27:09developed diabetes at a very young age.
27:12And the the Histology is shown in
27:15the middle here.
27:16Furthermore,
27:16if you gave anti CD3 antibody to
27:19mice that spontaneously developed
27:22diabetes and induced remission
27:24with the anti CD3 antibody,
27:27if you gave anti PD one or anti PDL one,
27:30this is work by Jeff Bluestone
27:32and Brian Fife On the right side,
27:34the mice immediately redeveloped diabetes.
27:37So this work suggested that PDL one
27:41had a critical role in maintaining
27:44non development of diabetes in
27:46a susceptible host.
27:47And here are some additional studies
27:50from Arlene's lab that showed
27:53if you took wild type cells,
27:55transferred them into APDL 1
27:57knockout or a wild type
27:59host if you put them into the
28:02knockout recipient, which is on
28:04the left side in the open circles,
28:05mice rapidly developed diabetes whereas
28:07they didn't at the same rate if you
28:10put them into the wild type recipient.
28:12And it also was shown in her
28:14work that the importance of PDL
28:16One was indeed on the islets.
28:19Because if she transplanted PDL 1
28:22deficient beta cells into either
28:24wild type or knockout mice,
28:27which is shown on the on the right,
28:29the PDL 1 knockout islets were more
28:33rapidly killed compared to wild type eyelids.
28:38So PDL one seems to have some unique
28:43features that's important in in
28:46protecting against autoimmune diabetes.
28:48Now we did some additional studies
28:51look comparing anti PDL one and
28:54anti CTE 4 because let me go back
28:57to that paper in that that letter
29:00in 2015 and and the comments from
29:03the reviewer that pointed out,
29:05well if this was really important
29:07we would have known about it.
29:08Well that reviewer was completely wrong
29:11because indeed the only checkpoint
29:13inhibitor that was available prior
29:15to that time was anti CTLA 4.
29:18And if you take a look at the
29:20mouse data here and this has been
29:22reproduced in other labs,
29:24anti CTLA 4 doesn't do this seems
29:27to be unique for anti PDL 1.
29:30And so we did some studies to to
29:33try to identify what's different
29:36about anti PDL one and anti CTLA 4IN
29:41induction of diabetes and I'm going to
29:44go through the the data fairly quickly.
29:46We did this by performing single cell
29:50RNA seq on infiltrating cells and
29:56islet cells from mice that had received
30:00either of these checkpoint inhibitors.
30:02And let me first point out that in the
30:05presence that when when these susceptible
30:08mice and OD mice are given anti C24,
30:11there are cells that infiltrate the islets.
30:13It's not that they don't develop insulitis,
30:16it's just that they don't develop diabetes.
30:18They don't go on and kill,
30:20kill the beta cells.
30:21So first of all,
30:23when we look at and when we look at immune
30:26cells that are infiltrating the islets,
30:28you can see there is a difference.
30:30If you take a look at panel
30:32D in the MELD analysis,
30:34there's a difference in CDAT cells
30:36that are infiltrating the islets when
30:38the when the mice are treated with
30:41anti PDL 1 compared to anti cetal A4.
30:43And there are a number of genes that
30:46are differentially expressed including
30:47some of the the ones that you might
30:50expect such as as Tea Bed Interferon,
30:54Gamma Granzyme B and even PDL one
30:57as as we would have predicted,
31:00as well as Perfran and the volcano
31:03plot showing you the differences
31:05in expression in the CDA T cells
31:08as shown in the bottom.
31:10Now what about the cells that
31:11are infiltrating the eyelids?
31:13Are they the same? Maybe they're different.
31:16And this is the data that we have to date.
31:18And fortunately I can't go into
31:21this and more with more granularity
31:23except to point out that yes,
31:26they are different.
31:26They are not the same cells that are
31:29being driven to the eyelids in when
31:31with the two different checkpoint inhibitors.
31:34If you just take a look at the
31:36frequency of various clonotypes
31:37you can see with anti PDL one in
31:40mice that that do develop diabetes,
31:43there seems to be a relative selection
31:47of particular clonotypes compared
31:49to the anti C2E4 treated mice.
31:53Now macrophages also seem to be
31:56different for reasons that we
31:59we don't completely understand.
32:00But you can see that they they express
32:06PDL one, they themselves express PDL one.
32:09They produce CXCL 10, which is important
32:12in recruiting cells to the islets,
32:15as well as Stat 1 indicating they've
32:18they've been looking at interferon gamma.
32:21And this is interesting because
32:23work from Emil Yunanoway's lab had
32:26actually pointed out that these cells
32:28seem to be the critically important
32:31cells for initiating checkpoint
32:33induced diabetes in in this model.
32:38Now in addition there are there
32:42there are changes in beta cells.
32:44I showed you already in humans that
32:46that we found that there was induction
32:49of PDL one in human beta cells that
32:52were treated with interferon gamma.
32:54And indeed if we looked at
32:57genes that are differentially
32:58expressed with interferon gamma,
33:00you can see that there are a
33:02whole lot of genes that have
33:05some immune response properties.
33:07Now the reason that we think
33:09this is important is because
33:11seeing inflammatory when beta
33:13cells see inflammatory cytokines,
33:15they make a number of important
33:18immune ligands such as CXCL 9,
33:21CXCL 10 important for recruiting
33:24cells to the islets and as well as
33:29increase expression of of of class one.
33:31MHC when we looked at this again
33:35is with human cells.
33:36When we looked at other features of
33:39human islets exposed to gamma interferon,
33:42we found that actually there
33:43was induction of FAS suggesting
33:45that indeed that cytokine might
33:48induce a killing of beta cells.
33:51And if you take a look at impanel
33:55E you you can see that in the PDL
33:581 expressing cells we we we find
34:01this morphology suggesting the cells
34:03are are are are actually dying.
34:05And indeed if if we look at at
34:08the percentage of dead beta cells
34:11in panel D it is much higher with
34:14cells that are cultured with
34:16interferon gamma back to the mice.
34:19Now when we look at beta cells
34:21in the mice in site two,
34:23there are a number of differences in
34:26in in them including the development
34:29of a unique subgroup of of beta cells.
34:33If you take a look at panel C,
34:36the fate,
34:37the fate diagram here shows you
34:402 populations of beta cells.
34:43The the the standard beta cells
34:44that you can see in mice treated
34:47with anti cetal E4 or anti PDL one
34:49and then this unique a cluster
34:51of beta cells that seems to be
34:54uniquely found in anti PDL one.
34:56The main beta cells express the same
34:58log in so they just showed you with
35:02human beta cells CXCL 10 PDL one.
35:04Class one MHC goes up stat
35:06one is signaling and trail is
35:08actually increased as well.
35:10But in the unique beta
35:12cells there's also changes,
35:14including reduced expression
35:16of a number of the beta cell
35:20identity genes such as NTX 6.1,
35:23Maffe of course,
35:25insulin and and and chromogram.
35:28So it's what this,
35:29what this finding suggests is work
35:32that we've done in other models
35:34of diabetes that there is some
35:39pathway leading to beta cell survival in
35:41the presence of checkpoint inhibitors
35:44that that seems to be turned on when
35:48these drugs are given. All right.
35:51So that's that's kind of where things are
35:54in terms of what's going on in the islet,
35:57what how human beta cells respond
36:00similarly to inflammatory mediators.
36:02So what what is, what is,
36:04what's the point of that and
36:07what can we do about it.
36:08So let me point out that in follow
36:14up work that that we did to try to
36:17figure out could we based on this
36:19knowledge stop the development
36:21of checkpoint induced diabetes.
36:23We first tested whether anti cytokine
36:26antibodies might be able to do that.
36:28And I've shown you already the
36:31critical role of interferon gamma and
36:33potentially TNF in development of
36:36checkpoint induced diabetes at least
36:38in mice and evidence in humans that
36:40both of these cytokines were present
36:43in the pancreas of an individual who
36:45died with checkpoint induced diabetes.
36:47What happens if you neutralize
36:50those cytokines?
36:51And you can see in the on the top here
36:54that if you gave the combination of
36:57anti PDL interferon gamma and anti TNF
37:00to mice treated with anti PDL one,
37:03you could indeed prevent the development
37:06of checkpoint induced diabetes in the mice.
37:09Furthermore,
37:09if you blocked a little further downstream
37:12with a Jack inhibitor and this is,
37:15I'm sorry, this says Jack inhibitor 1,
37:17Jack inhibitor 2 and I should
37:19just mention this is an ongoing
37:21collaboration with folks at Pfizer
37:24and with two new Jack inhibitors,
37:26The identities of which we don't know
37:28except we know they're different.
37:29But as you can see Jack inhibitor 1
37:32looks pretty good in terms of developing,
37:35preventing the development of
37:38checkpoint induced diabetes.
37:40So to summarize what I've just told
37:42you then what we think is there's
37:45actually an inflammatory cycle that's
37:47going on between immune cells and beta
37:49cells that leads to the development
37:52of of a checkpoint induced diabetes
37:54in response to interferon gamma.
37:57Beta cells in turn make a number
38:00of immune regulatory molecules
38:02that recruit other immune cells,
38:05activate immune cells leads to increased
38:09production of inflammatory cytokines
38:12particularly interferon gamma.
38:14It leads to expression of PDL one.
38:16When you block PDL 1 you seem to
38:20block the stop signal in immune cells
38:24that otherwise would would cause
38:27them to leave the eyelid and and
38:29the immune cells then are there in
38:31the eyelid and capable of going on
38:34and killing the insulin producing
38:36cells so and and killing beta cells.
38:40So what is,
38:41is there anything we can take home from
38:43this in terms of treating patients?
38:45And let me just start by mentioning
38:49this patient that was again another
38:53another letter in diabetes care
38:57that was treated in Switzerland.
39:00This is a patient who had presented
39:02with type 2 diabetes and let me go
39:05back to a point I made earlier.
39:07Type 2 diabetes is a common disease
39:09and so it follows that there are
39:11patients who are going to develop
39:14checkpoint induced diabetes who already
39:16may have pre-existing type 2 diabetes.
39:19And that's the explanation I'm going
39:21to give you for for this this case
39:24report that appeared in the literature.
39:26So this is an individual with pre
39:29pre-existing type 2 diabetes had
39:32much worsening glucose control.
39:35You can see with a hemoglobin A1C of 11.6%
39:39but did have detectable beta cell function.
39:42The C peptide was 993 which is
39:45you know plenty respectable and
39:48was also auto anybody positive.
39:50So they believe that this patient
39:52had immune mediated diabetes.
39:54They gave the patient infliximab,
39:56the anti TNF antibody and as you can
40:00see the the glucose is improved.
40:03The hemoglobin A1C came down
40:05and so that was
40:09that seemed to be very impressive
40:11to those investigators.
40:12The patient had been treated with insulin.
40:13They stopped the insulin.
40:15Now since we saw that,
40:17we've also treated a few patients
40:19here and I want to mention this
40:23work that's been ongoing by Noam
40:25and Anna for treating patients
40:28here who've developed checkpoint
40:30induced diabetes with infliximab.
40:33Let me show you 2 cases.
40:36This patient had a history of type
40:392 diabetes like the previous one
40:42that I showed you and presented with
40:45very very high glucoses and the the
40:49hemoglobin A1C in the past had been
40:52a fairly reasonable and the patient
40:54had not been treated with insulin.
40:57There was a bump in the amylase
40:59and light paves just as I showed
41:01you in in one of the first slides.
41:04And then the glucose became markedly
41:06elevated and as you can see the
41:08patient received 3 doses of infliximab.
41:11And if you take a look at the response
41:14curves and in terms of the C peptide,
41:16it actually did seem to these
41:18are random C peptides.
41:19I should point out the C peptide
41:21did seem to improve after the
41:23patient was treated with infliximab
41:25and the glucose was also better.
41:27Now these are, these are anecdotal,
41:31these are not performed in a rigorous
41:34endocrine setting where we're actually
41:36stimulating beta cell function.
41:38But nonetheless and I think from
41:39the patient's point of view,
41:41the fact that he was able to get
41:43off of insulin and his hemoglobin
41:45A1 CS were subsequently improved
41:47is is clinically meaningful.
41:50Here's another case.
41:52This individual with metastatic
41:55Melanoma was treated with EPI
41:57and Nevo and had adverse events
42:00including uveitis and diarrhea that
42:03have been treated with steroids and
42:06hyperglycemia was noted at cycle 21.
42:10There was no prior history of
42:12diabetes in this patient and previous
42:14hemoglobin A1 CS have been normal.
42:17This patient again presented with
42:19a very elevated hemoglobin A1C and
42:22the glucose was also quite elevated.
42:25This patient did not have evidence
42:27of ketoacidosis whereas the previous
42:29patient that I showed you did.
42:31And remember that ketoacidosis is a
42:34sign of of substantial insulin deficiency.
42:37This patient was auto antibody negative.
42:41So here we're looking at the
42:43random C peptide levels,
42:45one of them is stimulated,
42:47the last one that was just done a
42:49few days ago and the glucose levels
42:51and you can see that the glucose did
42:54improve probably with the medical care
42:56of the patient received but the C
42:59peptide also seemed to be pretty substantial.
43:01This is markedly different than what
43:03I showed you in in in one of the
43:06first slides where the C peptides
43:08pretty much go to undetectable in
43:10in the majority of patients who
43:14present with checkpoint induced
43:16diabetes and do so fairly rapidly.
43:19So to conclude adverse events are not
43:21infrequent with checkpoint inhibitors.
43:23In fact I would change that to
43:25say adverse events are common
43:27with checkpoint inhibitors.
43:28Most common is thyroid disease
43:31and hypothesitis but diabetes
43:32also occurs in about 1%
43:34of checkpoint induce a checkpoint
43:37inhibitor treated patients.
43:39Now one thing I should mention is for
43:42patients and you know we see them.
43:45Thanks to all of you in our clinic.
43:47But for the patients this
43:48is a difficult disease.
43:50I mean you know it's it, it,
43:52it's a lot different when a
43:5512 year old presents with.
43:56It's not that the disease
43:58is easy for a 12 year old,
43:59but it's even more cumbersome
44:01for a 65 or 75 year old who now
44:04has become insulin deficient,
44:06completely dependent on exogenous insulin
44:09for maintaining metabolic control.
44:12So it is quite a burden for patients.
44:15So preventing the disease would obviously
44:18be would result in very significant
44:21improvements in quality of life.
44:23It's most common in patients treated
44:25with anti PD one or anti PDL 1
44:28antibodies and in patients or HLAD R4.
44:30Still a lot of work needs to go on to
44:33understand what is the significance of
44:36DL DDR4 or the significance of NLRC 5.
44:40But it nonetheless suggests that there
44:43is some some change or some difference
44:46in these patients in presentation of
44:48either class one or Class 2 or both.
44:51MHC presented antigens,
44:53pancreatic inflammation is is
44:57frequent prior to the development
44:59of checkpoint induced diabetes.
45:01Curiously, PDL one's expressed on beta cells.
45:04And I think we have to conclude
45:06that in spite of expressing PDL
45:08One on beta cells and in spite of
45:11showing its extraordinary protective
45:13effect in animal models of disease
45:16that when you give a checkpoint,
45:19when the checkpoint inhibitor
45:21is given that protective,
45:23that protective blockade is gone.
45:26And even afterwards PDL one
45:30expression is no longer able to
45:33stop the development of diabetes.
45:35And I think the identification of
45:38mechanism suggest have suggested a
45:40therapeutic strategy inhibition of
45:42inflammatory mediators may potentially
45:44halt progression of diabetes and
45:46beta cell loss with checkpoint
45:48induced diabetes and a short acting
45:51inhibitor potentially Jack inhibitors
45:53would warrant some further testing.
45:56One last one last comment,
45:58let me mention that you know I
46:00think one of the interesting things
46:02about all of the adverse checkpoint
46:04induced adverse events is,
46:06is it a feature of the checkpoint inhibitor,
46:08a feature of the tissue or a feature
46:11of the patients or all three of these.
46:13And let me just point out this work
46:16from Jackie Mann in our group who
46:19looked at checkpoint inhibitor induced
46:21colitis and she did this by single cell RNAC.
46:25This work was published fairly recently,
46:28but let me point out that a number of
46:30the molecules that I just told you
46:33about being found in the pancreas of
46:36checkpoint induced diabetes can also
46:38be found in patients who develop colitis,
46:41suggesting that we might even think about
46:44a broader use of of various inhibitors,
46:48not inhibitors.
46:49Obviously that would prevent the anti
46:51tumor effect of the checkpoint inhibitors,
46:54but might be given sequentially
46:56after the anti tumor effects of the
47:00checkpoint inhibitors and that might
47:03be rapidly tapered in the event that
47:07further cancer therapy is needed.
47:09So I'm going to close with that.
47:10I want to thank a number of individuals,
47:13particularly Harriet, who's been,
47:16you know, a colleague for a decade now,
47:19and a number of individuals in
47:22her group who've I've had the
47:24good fortune of working with.
47:25As well, I want to mention
47:30Lalak's work on identifying
47:33the LLRC 5 mutations.
47:35I showed you some of Jackie's work.
47:37Nolan is continuing this work with
47:41particularly with giving with the
47:44NLRC 5 mutations and therapies
47:46of checkpoint induced diabetes.
47:48Anna Perdigata did a lot of,
47:50did actually all of the work,
47:52the single cell work with the mouse models
47:54and it's continuing to go on to do that.
47:56And we have colleagues at UCSF and funding
48:00you can see on the right side here.
48:03So I'll stop there and I'm
48:05happy to answer any questions.
48:14Thank you, Kevin for a
48:16wonderful presentation. Kurt,
48:23thank you for an excellent
48:23talk. I wanted to ask,
48:25so LRC 5 is a little bit
48:27kind of superficially counter intuitive
48:29in terms of germline mutation.
48:30I was wondering if there was a
48:31role in central tolerance and
48:32if you saw increased checkpoint
48:34inhibitor autoimmunity in
48:36hypothesitis or hypothyroidism.
48:41I'm sorry I I missed the second part.
48:43I, I, I, I, I understood your
48:45question about central tolerance
48:47but so and so whether you saw
48:49rather than an LRC 5 mutations,
48:52germline ingest type one diabetes
48:55or well check one inhibitor diabetes
48:57or whether also intra,
49:00I think that's still somewhat
49:03of a ongoing question.
49:07I think it's unlikely Harriet may have a
49:11thought as to whether it's more likely.
49:13Yeah, I can Norm can answer it as well.
49:15So we have looked in at NLRC 5
49:18SNPs in other other toxicity,
49:21it seems to be higher as well in
49:24hypothesitis but not colitis.
49:25That's as far as we know so far.
49:28But the statistics are they're
49:30not this numbers are small.
49:31Still, that's exactly what
49:32Norm is working on right now.
49:46Yeah. I mean it could be
49:48the only. So I I I think
49:51that's an interesting question.
49:54But you're taking us back
49:55to the original model.
49:56These patients had a repertoire ready to go.
50:00And look, it could be right.
50:02I mean just because we don't
50:04see the usual suspects doesn't
50:05mean that there aren't suspects.
50:07Kevin, that was an amazing lecture.
50:09It it reminds me of 2015 or earlier when
50:11we first started using these agents
50:13and we're seeing wonderful responses.
50:15And you know patients with lung
50:16cancers and others would have these
50:17problems and you know they'd be
50:19on the throughout the hospital and
50:20they wouldn't get the care they
50:22needed because no one recognized
50:23that these toxicities were were
50:24part of this even though they were
50:26benefiting from the the therapy.
50:27I have a two-part question for you and
50:29you you now know who's at most risk,
50:31you have the NLR, other other risk factors.
50:33So my first question would be 1,
50:36would you treat prophylactically or
50:38or would you wait until they develop
50:40the toxicity to to start treating
50:43And then the second would be you see
50:44that the activity against the cancer
50:46is is increased in the patients
50:48that have these abnormalities.
50:50Yeah that's a let.
50:51Let me address the second question
50:53first because there is some literature
50:55suggesting that those who develop
50:57these adverse events do better in
50:59terms of their anti cancer activity and
51:02indeed our patients did well in general,
51:04but there is a publication for sure
51:07suggesting that those who develop
51:09hypothesitis had better outcomes
51:11in patients with Melanoma.
51:13So,
51:14so I'm not certain but I think it's
51:17certainly not a negative thing
51:20in terms of the cancer response
51:22and it may look it may,
51:23I mean just because you don't develop
51:26toxicities doesn't mean you can't
51:28do well with checkpoint inhibitors.
51:29So in terms of when I would treat
51:32if I if if if we knew how to
51:34treat type autoimmune diabetes,
51:37if we knew what the antigens
51:38were for example,
51:39we could we could dream about coming
51:42up with some sort of antigen specific
51:45prophylactic therapy and give that
51:47before we give the checkpoint inhibitor.
51:49At this point,
51:50I don't think we have that.
51:52And so my suggestion would be
51:54to carefully follow patients,
51:56look for the signs that identify
51:58those who are at risk of developing
52:00it and then when is appropriate in
52:03terms of the cancer therapy strategy,
52:05if if it's possible come in with
52:08some short term inhibitor. Thanks.
52:13Thanks, Kevin. Dr. Wagner.
52:15And then just just great talk,
52:19just a couple of simple questions.
52:21Are there gender differences in toxicity?
52:27We
52:30not that we had seen in diabetes.
52:32Not significantly different.
52:35Harry looks puzzled.
52:36Why I would ask that only because
52:38autoimmune disease is so much
52:39more common in is more common
52:41in women than men. Yeah. We
52:45didn't find that we we'd
52:47love. Yeah. The only the only
52:48thing I could say is type one
52:50diabetes is not really general.
52:51No, I I realized that, but
52:53this isn't type 1 to obvious and
52:57and this is for either of you.
53:00I mean do you think that that clinicians
53:02really have a sense of how abrupt the
53:07onset is of of of diabetes in this
53:10situation and are looking for it.
53:13I mean because you know it's
53:15happening not at week two,
53:16it's happening at week six or eight.
53:19The presentation is very acute.
53:22I mean you know there are some
53:24number of people out there as
53:25these therapies are used more and
53:27more we're going to die from this.
53:28So there have been deaths,
53:31there will be deaths where
53:33there isn't sufficient there,
53:36there isn't sufficient insight.
53:38The cup, the two patients that we
53:40haven't showed that we were able to
53:42give the TNF that was just chance.
53:43The first one was in hospital because
53:45of colitis or something else and that's
53:47when they noticed the ship going up.
53:49The second one is an EMT and
53:50he he noted his only party,
53:52that's it called a million
53:53started checking his glucose.
53:55But there there's not sufficient awareness.
53:57Yeah. The but the other sort
53:59of take home point from that is
54:01you need to be aware of this
54:02acutely because I showed you the C
54:04peptide levels when it goes to 0,
54:06there's no turning back.
54:08So I think close surveillance was important.
54:13Yeah.
54:15Well, I can tell you that I don't
54:19educate patients, you know so, so look
54:23for these kinds of things.
54:24Can I just a quick, very,
54:25very interesting data,
54:26Two quick questions.
54:27One for the germline NLCR 5 mutations,
54:31you may have said this,
54:32but are those associated with
54:35standard classic autoimmune
54:37diet type one diabetes as well?
54:39Yeah, there there's,
54:40there's that one paper from Dejo Isrich
54:44suggesting that the answer is no not really,
54:48not one of the important players.
54:50None the less though seems to be
54:52important and it it can affect
54:55antigenicity and development of diabetes.
54:57And and did you go back so you made
54:58a comment early that you know the,
55:00the, the, the, the,
55:04the 40% of the patients who have autoimmune,
55:07who have auto antibodies to to,
55:09to, to the islet cells.
55:13There's only relatively it was
55:15only 40% as opposed to all of them.
55:17And that was one of the reasons
55:18why this looked like this,
55:19one of your conclusions why this was
55:22different than standard, you know,
55:23type one diabetes did when you went back
55:25and you started looking at all these
55:27mechanisms in your patient population,
55:29did you, did you look at the difference
55:31in those patients who had auto
55:33antibodies and those who did not,
55:35You know, yeah it's interesting point.
55:39No, to my knowledge,
55:42I don't think we've done that.
55:45That's an interesting point way to kind of.
55:47Yeah, yeah.
55:48Yeah, confirm this here,
55:49this hypothesis.
55:50Yeah.
55:50So we
55:52have a couple of online questions.
55:54Oh, oh comments that would be
55:55easy for you to look at it there.
55:57OK. Anna has a comment.
56:01It'd be helpful to monitor blood
56:03glucose more carefully in patients
56:05who have lipase elevation and in some
56:08patients there's mild elevation in
56:10glucose before severe presentation.
56:13So monitoring them more more
56:15carefully may be valuable that that's,
56:17yeah, a very good point.
56:19And then there's a question about
56:21racial differences in in toxicity,
56:23not that I know of
56:29most. Yeah, I think we, I think that's right.
56:31Most of our patients are Caucasian.
56:36Yeah. Time for two.
56:39Oh, what are we going to do here?
56:40You see you should have sent your
56:42paper to the New England Journal to the
56:45clinical oncology inside the diabetes.
56:47That's right. That's right.
56:53That was an amazing talk. Thank you.
56:55I had a question about the the,
56:57the lipase elevation occurring before
57:00the onset of diabetes as well.
57:03You showed that it's it's
57:04common that that occurs,
57:05but did you look at patients
57:07that have lipase elevations and
57:09how often they develop diabetes.
57:11We don't routinely follow
57:13amylocin lipase in patients but
57:14occasionally on clinical trials we
57:15do we are required to look at it.
57:17And so that may be it would be
57:19interesting to see is it common
57:21that it it it is pre occurring or or
57:24that's a very good point.
57:26I I don't believe we've done the
57:28analysis that way unless area
57:29to know them you or Anna you
57:31know of of doing it differently.
57:33It's an interesting approach
57:34because we use the a lipase
57:36elevated or not often but when we
57:38see elevated amylase or lipase and
57:39patients are asymptomatic we we just
57:41we don't really do anything about it.
57:43We just watch them.
57:43But if you knew that that had a higher
57:45incidence of going to diabetes,
57:47maybe that's a population you could treat.
57:52Yes.
57:59Hello, I'm relatively new to immunobiology,
58:03but I had a question about
58:05the slide where you showed the
58:08immunohistochemistry results and
58:09you said that you saw signal or you
58:12saw standing outside of the eyelids.
58:14And I was wondering if you could
58:16further explain the significance
58:18on why you were excited about
58:20them being outside of the islets.
58:22Oh yeah, look, I would have been more
58:24excited if they were inside the islets.
58:27But the I think I think the point from
58:32that is that this is not just there's
58:36a broader inflammatory response and
58:40our assumption is that the islets
58:43cells can see the soluble mediators.
58:47So I I think you know we at least in
58:50the type one diabetes field we tend
58:53to think of you know single T cell
58:56clone going into the islet hitting a
58:58single target and I think this is this
59:01is a bigger inflammatory response.
59:04Thank you.
59:04And I think that's why the lipase
59:06and amylase are elevated.
59:10I have, I have many questions
59:12but I'll I'll just ask you.
59:13Had you mentioned or you
59:16had referred to the potential
59:18implication of regulatory
59:20CDAT cells and was wondering in
59:22your comparison between anti PD1,
59:25anti CTLA 4 differences, did you see any,
59:28no differences, haven't seen it.
59:30And then have you also,
59:31but we're going to look
59:32for it, you know if there
59:33are any differences in HLAC allotypes
59:36or HLAU or non canonical MHC.
59:42That's a good question
59:44and not that I know of,
59:47but that certainly is something
59:51worth doing EG and yeah,
59:55yeah, for the yeah,
59:57for the Kurds probably the
59:58C and EI think.
01:00:02Yeah. Kevin, thank you so
01:00:04much for a wonderful talk.