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Harnessing Hypoxia Biology for Cancer Therapy

September 04, 2024

Yale Cancer Center Grand Rounds | September 3, 2024

Presented by: Dr. Peter Glazer

ID
12043

Transcript

  • 00:00Peter is the chair of
  • 00:03therapeutic radiology
  • 00:05and the Robert Hunter professor
  • 00:07of therapeutic radiology and professor
  • 00:09of genetics.
  • 00:11Peter did his MD and
  • 00:13PhD at Yale.
  • 00:16I'm
  • 00:17sobered to admit that, in
  • 00:19fact, we were here at
  • 00:21the same time,
  • 00:23in medical school.
  • 00:26And, Peter has spent his
  • 00:29career at Yale,
  • 00:31where
  • 00:32he has,
  • 00:34focused, of course, on radiation
  • 00:36oncology and has led the
  • 00:38group,
  • 00:39for quite a number of
  • 00:40years.
  • 00:42And himself is,
  • 00:44predominantly
  • 00:45a laboratory scientist,
  • 00:47who has,
  • 00:49worked in a number of
  • 00:50areas, but,
  • 00:52predominantly in the area of
  • 00:53DNA damage repair
  • 00:55and is the recipient of
  • 00:57an outstanding investigator award that
  • 00:59that focuses on that very
  • 01:00topic.
  • 01:01So without further ado, Peter,
  • 01:03it's really a pleasure to
  • 01:05have you as our first
  • 01:06noon speaker
  • 01:08in the current, Eric.
  • 01:15Thanks, Eric. I appreciate it.
  • 01:16And,
  • 01:18nice to be here, everyone.
  • 01:20Thank you for coming. And
  • 01:21it doesn't hurt that there's
  • 01:22a free lunch, so
  • 01:24that's great. So I'm I'm
  • 01:25gonna tell you about some
  • 01:26of the work that we've
  • 01:27been doing for a number
  • 01:28of years.
  • 01:29And so there's gonna be
  • 01:30something old and something new,
  • 01:33related to hypoxia biology and
  • 01:35how you might exploit that
  • 01:36for,
  • 01:37cancer therapy. So these are,
  • 01:39my disclosures.
  • 01:42And so,
  • 01:43many of you will be
  • 01:44familiar with the hallmarks of
  • 01:46cancer. It's a series of
  • 01:48publications from Hanahan and Weinberg
  • 01:50and others that have talked
  • 01:52about some of the properties
  • 01:53of cancer cells. And what
  • 01:55I just wanna call out
  • 01:56here is that, tumor hypoxia
  • 01:59plays a important role in
  • 02:01a number of these. And
  • 02:03some of these listed here
  • 02:04altered metabolism,
  • 02:06inducing invasion, metastasis.
  • 02:08There's a literature on that.
  • 02:10Of course, hypoxia causes,
  • 02:12angiogenesis.
  • 02:14But what I'm going to
  • 02:15talk about today is our
  • 02:16work in which we identified
  • 02:17that,
  • 02:19one of the impacts of
  • 02:20hypoxia is,
  • 02:21genetic instability
  • 02:23in, cancer.
  • 02:24Now this work started,
  • 02:26a number of years ago
  • 02:28when I was at a
  • 02:29Gordon conference
  • 02:30on DNA repair mutagenesis,
  • 02:33and, one of the speakers
  • 02:34was Larry Loeb, who's a
  • 02:35very prominent pathologist
  • 02:37at University of Washington
  • 02:39in the DNA repair field.
  • 02:40And he proposed,
  • 02:42you know, in the nineties
  • 02:43that,
  • 02:45there would be a mutator
  • 02:46phenotype in cancer cells. And
  • 02:48this was based on the
  • 02:49idea that
  • 02:51the the,
  • 02:52frequency of mutations in cancer
  • 02:54cells was above and beyond
  • 02:56what you would predict from
  • 02:57the frequency of mutagenesis
  • 02:59and normal cells.
  • 03:00So
  • 03:01he inferred that there had
  • 03:02to be a mutator phenotype.
  • 03:04Now at the time, people
  • 03:06were focused on, well, there's
  • 03:08gonna be mutations in mute
  • 03:10in DNA repair mutator genes
  • 03:12that's that is going to
  • 03:13lead to
  • 03:14the increase in mutation frequency.
  • 03:17But, as I was sitting
  • 03:19in the audience, it occurred
  • 03:20to me, well, one of
  • 03:21the issues is people do
  • 03:22all these studies of,
  • 03:24DNA repair mutagenesis
  • 03:26in cells and culture,
  • 03:27but they're growing in a
  • 03:29in a standard,
  • 03:30tissue culture dish,
  • 03:33in really nice media at
  • 03:35twenty percent oxygen.
  • 03:37And in fact, most cancer
  • 03:39cells do not exist in
  • 03:40twenty percent oxygen. They they
  • 03:41exist in somewhere between
  • 03:43point one to five percent
  • 03:45oxygen.
  • 03:46And in fact,
  • 03:47there is
  • 03:49a lot of variety in
  • 03:50the level of oxygen tension
  • 03:51in tumors that has to
  • 03:52do with abnormal and fluctuating
  • 03:55perfusion,
  • 03:57and then as well distance
  • 03:58from the vasculature, which creates
  • 04:01a gradient of hypoxia.
  • 04:03So
  • 04:04my my proposal was,
  • 04:06could this,
  • 04:07hypoxia that you see in
  • 04:09the tumor microenvironment
  • 04:10impact genetic instability?
  • 04:12Now one of the first
  • 04:13grants that I submitted on
  • 04:15this was turned down, and
  • 04:17one of the reviewers
  • 04:18said, well, that can't be
  • 04:20possible
  • 04:21because the absence of oxygen
  • 04:24will actually reduce the amount
  • 04:25of oxidation. And, of course,
  • 04:26oxygen causes rust
  • 04:28and and damage to other,
  • 04:31molecules. And, of course, that
  • 04:33individual was thinking only chemically,
  • 04:35not thinking biologically.
  • 04:37So we went on to
  • 04:38test this hypothesis,
  • 04:40and and this is some
  • 04:41older data. And the first
  • 04:42dataset here is a a
  • 04:44table in which we grew,
  • 04:46tumor cells
  • 04:48that had a specialized mutation
  • 04:50reporter,
  • 04:51and we grew them either
  • 04:52cells in culture or we
  • 04:54use them to form tumors
  • 04:55in mice. And And what
  • 04:56we consistently saw was the
  • 04:58frequency of
  • 05:00mutations was higher when the
  • 05:01cells were grown as tumors.
  • 05:04Then we went on to
  • 05:05to study, well, what's the
  • 05:06underlying mechanism? First of all,
  • 05:08we showed that if you
  • 05:09put those cells in hypoxia,
  • 05:11you could recapitulate the mutagenesis.
  • 05:13So that linked that effect
  • 05:15to hypoxia.
  • 05:16And we subsequently showed that
  • 05:17if you had a damaged
  • 05:18plasmid
  • 05:20and introduced it into cells
  • 05:21that were either normoxic or
  • 05:22hypoxic,
  • 05:23there was better repair
  • 05:25or lesser repair of the
  • 05:27damaged plasmid and the hypoxic
  • 05:29cells.
  • 05:30And this work was, carried
  • 05:32out predominantly by Jenling Wan,
  • 05:33who's now a faculty member
  • 05:35at University
  • 05:36of Minnesota in radiation oncology.
  • 05:41So then,
  • 05:42we went on, to
  • 05:45oh, I'm sorry. I skipped
  • 05:47one. So thinking about,
  • 05:49what we saw in those
  • 05:50experiments, we noticed that the
  • 05:51pattern of mutations
  • 05:53had a fair proportion of
  • 05:56changes within repeated sequences, which
  • 05:59would be,
  • 06:01indicative of a mismatch repair
  • 06:02deficiency. So we took a
  • 06:04candidate approach and looked at
  • 06:05DNA mismatch repair gene expression.
  • 06:08And,
  • 06:10what you can see here
  • 06:11is that in the in
  • 06:12the mismatch repair pathway, which
  • 06:14involves,
  • 06:16proteins, MSH two and MSH
  • 06:18six recognizing a mismatch, and
  • 06:20then MLH one and PMS
  • 06:21two coming on to mediate
  • 06:24of downstream effects and steps
  • 06:26and repair.
  • 06:27The MLH one and PMS
  • 06:28two proteins were, decreased in
  • 06:31expression levels and hypoxia,
  • 06:33and that correlated when we,
  • 06:35put in a specific sequence
  • 06:37repeated sequence that we could
  • 06:38probe for mutation.
  • 06:40The frequency mutations was increased
  • 06:42in that sequence. So that
  • 06:44was the first
  • 06:45demonstration on a biological level
  • 06:47that there was a repair
  • 06:48pathway that was diminished
  • 06:50in hypoxic cells.
  • 06:52Then we took
  • 06:54a a nonbiased approach and
  • 06:56did a gene array analysis
  • 06:57of,
  • 06:59DNA repair expression and hypoxia,
  • 07:01and you may see two
  • 07:02familiar faces here, Ran, Ranjit,
  • 07:05Bindru, who everyone knows, and
  • 07:06Susan
  • 07:07Gable, who was then Susan
  • 07:08Scanlon, both MD PhD students
  • 07:10in the lab and now
  • 07:11on our faculty here in
  • 07:12radiation oncology. And they did
  • 07:15some,
  • 07:16seminal work in which they
  • 07:17looked at the expression
  • 07:19of genes that we identified
  • 07:20in that screen,
  • 07:22including Rad fifty one, BRCA
  • 07:24one, and FANC t two
  • 07:25in the Fanconi anemia pathway.
  • 07:27So Rad fifty one and
  • 07:28BRCA one are in the
  • 07:29homology dependent repair pathway.
  • 07:31And you can see here
  • 07:33on, a western blot that
  • 07:35Rad fifty one is diminished
  • 07:36in the hypoxic component,
  • 07:38whereas HIF one as a
  • 07:40control is increased.
  • 07:42And then here on a
  • 07:42northern blot,
  • 07:44which people hardly do anymore,
  • 07:45BRCA one is decreased in
  • 07:47hypoxia, whereas VEGF RNA is
  • 07:50increased.
  • 07:51And, interestingly, on a western
  • 07:53blot, you can see the
  • 07:54BRCA one is down. But
  • 07:55if you look here closely,
  • 07:57you'll see the the protein
  • 07:58has actually shifted a little
  • 08:00bit up on the, gel
  • 08:02mobility, and that has to
  • 08:03do with post translational modification
  • 08:06in in response to hypoxia.
  • 08:08And the same is true
  • 08:09with Fanconi anemia.
  • 08:10And you see here that,
  • 08:11the FANC t two expression
  • 08:13is down, and, actually, there's
  • 08:15an increase in the second
  • 08:16band, which
  • 08:17represents ubiquitination.
  • 08:21So what is the mechanism?
  • 08:22So it turns out that
  • 08:23many of these repair genes
  • 08:26have common elements in their
  • 08:27promoters that respond to the
  • 08:29e two f family of
  • 08:30transcription factors.
  • 08:32And, these factors interact with
  • 08:35the pocket proteins that are
  • 08:36related to retinoblastoma
  • 08:38protein, p one thirty, p
  • 08:39one zero seven, and p
  • 08:41r b. They form heterodimers
  • 08:43that regulate these promoter sites.
  • 08:45And what we found is
  • 08:46that in response to hypoxia,
  • 08:48those pocket proteins become hypophosphorylated
  • 08:51due to the activity
  • 08:53of a phosphatase called PP
  • 08:54two a. And this is
  • 08:56a common theme throughout this
  • 08:57talk that I'll return to,
  • 08:59several times. And, basically, the
  • 09:01mechanism is that hypoxia causes
  • 09:04p one thirty or the
  • 09:05p one zero seven or
  • 09:06RB hypophosphorylation
  • 09:08formation of e two f
  • 09:10heterodimers, and these are repressive
  • 09:12and cause the downregulation
  • 09:14of DNA repair.
  • 09:16We also found that hypoxia
  • 09:18causes, changes in expression of
  • 09:20microRNAs, and these lead to
  • 09:22a cascade of events that
  • 09:23regulate,
  • 09:24DNA repair as well as
  • 09:26adaptation to hypoxia
  • 09:28on several levels.
  • 09:29But I'm not going to,
  • 09:31go into this further in
  • 09:32in the talk. Just mention
  • 09:34it for completeness.
  • 09:36In addition
  • 09:38to acute and chronic changes
  • 09:40acute and short term changes
  • 09:42in gene expression,
  • 09:43Yuhang Liu in the lab
  • 09:44has shown,
  • 09:46that both BRCA one and
  • 09:47MLH one become silenced with
  • 09:50persistent hypoxia,
  • 09:52due to a specific set
  • 09:54of epigenetic,
  • 09:55changes related to particular,
  • 09:58histone,
  • 09:59demethylases.
  • 10:01And you can see here
  • 10:02as an example, persistent downregulation
  • 10:05of BRCA1 and prolonged hypoxia.
  • 10:08So
  • 10:09just
  • 10:10an overview,
  • 10:12you know, we found,
  • 10:13that there are a number
  • 10:14of changes in DNA repair
  • 10:17pathways related to the hypoxia,
  • 10:18but predominantly
  • 10:20in the homology dependent repair
  • 10:21or homologous recombination
  • 10:23pathway
  • 10:24and the mismatch repair pathway
  • 10:25at the transcriptional,
  • 10:27translational, and epigenetic
  • 10:29level.
  • 10:32And,
  • 10:32in addition, I alluded to
  • 10:34the fact that there is
  • 10:35acute activation of DNA repair
  • 10:37and hypoxia,
  • 10:39and, this is transient.
  • 10:41And you can see that,
  • 10:43in response to acute hypoxia,
  • 10:45you get activation of check
  • 10:47two,
  • 10:48which then leads to a
  • 10:49phosphorylation
  • 10:50of BRCA one. And, actually,
  • 10:52as,
  • 10:53we accumulated data, there's actually
  • 10:54a network of signaling events
  • 10:56that happens early in hypoxia
  • 10:59followed by, down regulation of
  • 11:01the DNA repair expression. So,
  • 11:03initially, DNA damage response pathways
  • 11:05are activated
  • 11:07and then transcriptionally
  • 11:09suppressed and then eventually silenced
  • 11:11if the hypoxia continues.
  • 11:13So, this is basically a
  • 11:15summary of a lot of
  • 11:16work
  • 11:17that shows a scale of
  • 11:18time. And in minutes, you
  • 11:20get these post translational modifications.
  • 11:23But over time, you get
  • 11:24suppression of DNA repair expression
  • 11:26in specific pathways
  • 11:28at the level of
  • 11:30translation, transcription, and eventually epigenetic
  • 11:33silencing.
  • 11:34Now
  • 11:35people sometimes
  • 11:37ask me when I give
  • 11:38these talks, why does this
  • 11:40happen?
  • 11:41Why would the cell do
  • 11:42this? And, you wouldn't think
  • 11:44that a a cancer cell
  • 11:46that's,
  • 11:47you know, looking to survive
  • 11:49and and,
  • 11:50overcome cancer therapy is interested
  • 11:52in down regulating
  • 11:54subsets of DNA repair pathways.
  • 11:56Well, it turns out that
  • 11:58one answer could be related
  • 12:00to what people have been
  • 12:01doing in the evolutionary biology
  • 12:03and microbiology
  • 12:04area
  • 12:05for a number of years,
  • 12:06and this has been, pioneered
  • 12:08by Susan Rosenberg at Baylor.
  • 12:10And what you see here
  • 12:12is, a study where people
  • 12:14isolated,
  • 12:16e coli in the wild,
  • 12:18a lot of different isolates,
  • 12:20and then put them under
  • 12:21stress. And the stresses could
  • 12:23be starvation,
  • 12:25in terms of what's in
  • 12:26the agar plate as far
  • 12:27as, nutrients.
  • 12:29Could also be certain antibiotics
  • 12:31that are not directly genotoxic.
  • 12:34And what they found was
  • 12:35an upregulation
  • 12:36of a hypermutable
  • 12:37state in the E. Coli
  • 12:39that increased their ability to
  • 12:41evolve and adapt to the
  • 12:43stressful environment.
  • 12:45And, interestingly,
  • 12:46as they started to do
  • 12:47the molecular,
  • 12:49studies,
  • 12:50one of the pathways downregulated
  • 12:51in e coli is mismatch
  • 12:53repair, and another one is,
  • 12:55what they called upregulation of
  • 12:57a mutagenic double strand break
  • 12:59repair. But what actually happened
  • 13:01is they suppressed the normal
  • 13:02homologous recombination pathway, and you
  • 13:05get an increase in,
  • 13:07something similar to nonhomologous end
  • 13:09joining. So very similar to
  • 13:10what we saw in cancer
  • 13:12cells.
  • 13:14So
  • 13:15if if we wanna look
  • 13:16at a parallel, the hypoxia
  • 13:18induced genetic instability
  • 13:19mirrors what's been seen in
  • 13:22e coli and other microorganisms.
  • 13:24And and in a way,
  • 13:25you could consider cancer
  • 13:27as a population of unicellular
  • 13:29organisms under stress.
  • 13:32Okay. So
  • 13:34that's the biology, but now
  • 13:35can we exploit it for
  • 13:37cancer therapy?
  • 13:38So this is work that
  • 13:39Denise Heakin in the lab
  • 13:40did where she was the
  • 13:41first, one to show that
  • 13:43hypoxic cells are sensitive
  • 13:45to an inhibitor of the,
  • 13:47DNA repair enzyme poly ADP
  • 13:49ribose polymerase or PARP. Many
  • 13:51of you know will know
  • 13:52that PARP inhibitors are used
  • 13:54in the clinic now for
  • 13:55cancers deficient in BRCA one
  • 13:56and BRCA
  • 13:58two because they are synthetically
  • 14:00lethal to,
  • 14:01cells deficient hematology dependent repair.
  • 14:04And, of course, I I
  • 14:06showed you when I show
  • 14:07show again here that, hypoxia
  • 14:09causes a downregulation
  • 14:10of the BRCA pathway,
  • 14:12and so those cells are
  • 14:13sensitive to PARP inhibitors.
  • 14:16So so then,
  • 14:18an MD PhD student in
  • 14:19the lab, Alana Kaplan, came
  • 14:21and we said,
  • 14:22can we exploit that biology
  • 14:24for cancer therapy in a
  • 14:25pharmacologic
  • 14:26way?
  • 14:27And our thinking was we
  • 14:28would use an angiogenesis
  • 14:30inhibitor called cediranib,
  • 14:33and it's shown here on
  • 14:34the upper right, for those
  • 14:36of you who are chemically
  • 14:37inclined. And it's a small
  • 14:39molecule receptor tyrosine kinase inhibitor
  • 14:42that was designed to inhibit
  • 14:43the VEGF receptor, but, actually,
  • 14:45it it inhibits multiple
  • 14:47receptor tyrosine kinase,
  • 14:50receptor tyrosine kinases,
  • 14:54not just the the VEGF
  • 14:55receptor.
  • 14:56So we we asked, could
  • 14:57we use
  • 14:58cediranib
  • 14:59to cause hypoxia in cancer
  • 15:02in tumors and then exploit
  • 15:04it? So what Alana did
  • 15:06was, treat, we set up
  • 15:08tumors in mice, and we
  • 15:10treated the mice with cediranib.
  • 15:12Then we isolated cells
  • 15:14from the tumors, and this
  • 15:15says mouse depletion because it's
  • 15:17a human tumor. We deplete
  • 15:18the mouse cells, and then
  • 15:19we isolate the tumor cells.
  • 15:22And,
  • 15:23you can actually stain them
  • 15:24with carbonic anhydra for carbonic
  • 15:26anhydrase nine because it's a
  • 15:28marker of hypoxia.
  • 15:29And in fact, we saw
  • 15:30that there was an increase
  • 15:32in the hypoxic fraction in
  • 15:33this experimental system from twenty
  • 15:35to about thirty percent.
  • 15:38So we took these cells
  • 15:39and we looked at, expression
  • 15:41of, rec the DNA repair
  • 15:43genes in the HDR pathway,
  • 15:45and we actually saw pretty
  • 15:46good downregulation.
  • 15:47In fact, we saw downregulation
  • 15:49that was too good in
  • 15:51the sense that it was
  • 15:52more than you would expect
  • 15:53from that
  • 15:55smaller change in the hypoxic
  • 15:57fraction.
  • 15:58So it was clear that
  • 15:59maybe something else was going
  • 16:00on.
  • 16:02So,
  • 16:03what Alana did was we
  • 16:04repeated that experiment
  • 16:06using that CA nine marker.
  • 16:07But instead of just
  • 16:09counting those, we actually sorted
  • 16:11them, and we collected the
  • 16:13normoxic fraction and the hypoxic
  • 16:15fraction. And what I'm showing
  • 16:16you here is the normoxic
  • 16:18fraction. And even in the
  • 16:19normoxic fraction,
  • 16:22homology dependent repair genes were
  • 16:24downregulated, and that was the
  • 16:25unexpected result.
  • 16:27So what was going on?
  • 16:29Well, actually
  • 16:31so we then looked at
  • 16:32some of the nonmalignant tissues
  • 16:34in the mice, and we
  • 16:35did not see downregulation. So
  • 16:37it was only happening in
  • 16:38the tumor.
  • 16:39So we looked at bone
  • 16:40marrow, liver, lung, and mammary
  • 16:42fat pad.
  • 16:43And just
  • 16:45a little more of a
  • 16:46survey, we looked at, some
  • 16:48other DNA repair factors, and
  • 16:49these are in the nonhomologous
  • 16:51end joining pathway,
  • 16:52which we already knew from
  • 16:53our hypoxia work
  • 16:55is that pathway is not
  • 16:57affected, and it was also
  • 16:59not affected by sedarinib.
  • 17:01In,
  • 17:02but, also,
  • 17:03in this, slide, I'm showing
  • 17:05you results of,
  • 17:07treatment of cells and culture
  • 17:09with sedarinib
  • 17:10where you cannot generate hypoxia
  • 17:12because there's no vasculature or
  • 17:14angiogenesis.
  • 17:15This is a direct effect
  • 17:16of sedarinib,
  • 17:17and you can see that
  • 17:18those pathways are downregulated,
  • 17:21directly by cediranib. But interestingly,
  • 17:24in,
  • 17:25bone marrow, CD thirty four
  • 17:27positive stem cells, we do
  • 17:28not see the same, downregulation.
  • 17:32So that is consistent with
  • 17:33what we had seen in
  • 17:34vivo.
  • 17:36Now, functionally, if we look
  • 17:38at cells treated with cediranib
  • 17:39and then treat them with
  • 17:40radiation
  • 17:41and and compare them to
  • 17:43controls, we see a functional
  • 17:44decrease in,
  • 17:46DNA repair capacity.
  • 17:48And you can see here
  • 17:49that,
  • 17:50in normal cells, you will
  • 17:51see foci of a Rad
  • 17:53fifty one coalescing
  • 17:55to repair double strand breaks.
  • 17:57But in cells treated with
  • 17:58cediranib,
  • 18:00there is substantially fewer
  • 18:02foci indicating that,
  • 18:04that pathway has been suppressed.
  • 18:07Similarly, if we do an
  • 18:09assay looking for,
  • 18:11homologous recombination
  • 18:12between two fragments of the
  • 18:13GFP gene,
  • 18:15one of which is cut
  • 18:16by an enzyme that can
  • 18:17be induced in the cells,
  • 18:19we can see that in
  • 18:20the presence of cediranib, that
  • 18:22recombination
  • 18:23event is substantially suppressed and
  • 18:25to a similar extent as
  • 18:26what you would see if
  • 18:27you knock down Radka one
  • 18:29or Rad fifty one. But
  • 18:31as controls, there's no effect
  • 18:33in knocking down the nonhomologous
  • 18:35end joining pathway
  • 18:36proteins, Kuwaiti and XLF.
  • 18:39Now we then return to
  • 18:41what Denise had observed in
  • 18:43hypoxic cells, and we said,
  • 18:44okay.
  • 18:45Does siderinib sensitize to a
  • 18:47PARP inhibitor? And here's
  • 18:49the example that shows,
  • 18:51in the in the presence
  • 18:52of, cediranib,
  • 18:54there is increased sensitivity to
  • 18:56elaparib, a commonly used
  • 18:58PARP inhibitor in the clinic.
  • 19:00So this is a survival
  • 19:01current curve on the left,
  • 19:03and this is example of
  • 19:05molecular markers of, cell death
  • 19:07and apoptosis on the right.
  • 19:10So what this,
  • 19:12data
  • 19:13these data show is that
  • 19:14cediranib treatment phenocopies the BRCA
  • 19:16deficiency
  • 19:18and creates a synthetic lethality
  • 19:20to PARP inhibitors.
  • 19:22Now what's what's the mechanism
  • 19:24here? So,
  • 19:26I'm not showing you all
  • 19:27the data, but one that's
  • 19:28particularly striking is we used
  • 19:31the papillomavirus
  • 19:32e seven protein that doctor
  • 19:34DeMeo will be very familiar
  • 19:35with. And the e seven
  • 19:36protein
  • 19:38was known for a long
  • 19:39time to interact with the
  • 19:40RB family of proteins
  • 19:42and cause their degradation and
  • 19:44prevent their interaction with the
  • 19:46e two f factors.
  • 19:47So when we express
  • 19:49e seven,
  • 19:52we see that there is,
  • 19:56abrogation of the sensitivity
  • 19:58of sedarinib treated cells to
  • 20:01olaparib.
  • 20:02So this is one piece
  • 20:03of evidence that supports that
  • 20:06the downregulation is happening by
  • 20:08the same method as happens
  • 20:09in hypoxia
  • 20:10that is through the,
  • 20:12r b e two f
  • 20:14family of pro of proteins.
  • 20:16And so
  • 20:17our conclusion of them, mechanistically,
  • 20:19is suderninib has two effects
  • 20:21on DNA repair. One is
  • 20:23through hypoxia, which was our
  • 20:24original
  • 20:25hypothesis,
  • 20:26and the other one is
  • 20:27a direct one through its
  • 20:29receptor tyrosine kinase inhibition
  • 20:33effects. And and in these
  • 20:35particular ovarian cancer cells, we
  • 20:37linked it to the platelet
  • 20:39derived growth factor receptor.
  • 20:42That leads to an upregulation
  • 20:44of phosphatase two a
  • 20:46and, changes in the
  • 20:49phosphorylation of the pocket proteins
  • 20:51and that cascade that leads
  • 20:53to suppression of repair capacity.
  • 20:57So then we took this
  • 20:58into an in vivo model
  • 21:00in, mice
  • 21:02in which we form tumors
  • 21:03from those of one of
  • 21:04those ovarian cancer cell lines.
  • 21:06And,
  • 21:07this is the tumor growth
  • 21:08suppression curve,
  • 21:10and the control or olaparib
  • 21:12alone are similar.
  • 21:13Sediranib has some effect, but
  • 21:15now the combined
  • 21:17olaparib and siderinib has the
  • 21:19most growth suppression,
  • 21:20and that's correlated with an
  • 21:22increase in survival.
  • 21:24Now when I,
  • 21:26first presented this,
  • 21:27at a meeting,
  • 21:29I I subsequently was contacted
  • 21:31by two fairly large pharmaceutical
  • 21:34companies.
  • 21:35One said, oh, gee. We
  • 21:38reproduce that, and we're actually
  • 21:39working on,
  • 21:41an even better version of
  • 21:43cediranib, and we'd like to
  • 21:44come talk to you about
  • 21:45that.
  • 21:47The other one
  • 21:48said, oh, well, we can't
  • 21:49reproduce what you did, and,
  • 21:51actually,
  • 21:52we don't like, that in
  • 21:54vivo model.
  • 21:56We prefer a different one
  • 21:57that we don't think that
  • 21:58one is,
  • 22:00a good one.
  • 22:01So, thankfully,
  • 22:04Joseph Kim, who I see
  • 22:05in the audience here,
  • 22:08decided to try a different
  • 22:10in vivo model,
  • 22:12and that one is called
  • 22:13patients in the clinic.
  • 22:15And and in his work,
  • 22:17reported,
  • 22:18in, JCO,
  • 22:21he did a trial in,
  • 22:22patients with metastatic prostate cancer
  • 22:25combining,
  • 22:26cidernib and olaparib and saw
  • 22:28positive results.
  • 22:32So
  • 22:33what about other repair pathways?
  • 22:35Well, it turns out that,
  • 22:37like I said, nonamog is
  • 22:39end joining, which you can
  • 22:40see here on the left
  • 22:41on the right. This is
  • 22:42a,
  • 22:44heat map of gene expression
  • 22:45where blue is down
  • 22:47and nonbluer red is up.
  • 22:49You can see nonhomologous end
  • 22:50joining is not suppressed,
  • 22:54but we do see the
  • 22:55suppression of,
  • 22:56HDR in a different,
  • 22:59cancer type, in this case,
  • 23:00lung cancer.
  • 23:01And we also see some
  • 23:03synthetic lethality induced
  • 23:05to alaparib in this lung
  • 23:07cancer line HCC
  • 23:08eight two seven.
  • 23:11And then Denise,
  • 23:13also looked at,
  • 23:15DNA mismatch repair in a
  • 23:17series of cancer cell lines
  • 23:18as shown here in the
  • 23:19middle panel, lung cancer, ovarian,
  • 23:22and a glioblastoma.
  • 23:23And in this case, DNA
  • 23:25mismatch repair as it is
  • 23:26in hypoxia is suppressed in
  • 23:28response to,
  • 23:30sedarinib. And, this is the
  • 23:32heat map, and you can
  • 23:33see some western blots on
  • 23:35the right.
  • 23:37Okay.
  • 23:38So,
  • 23:39at this point,
  • 23:41Gary Outwerger, who is a,
  • 23:44assistant professor in the GYN
  • 23:45oncology,
  • 23:47department,
  • 23:48here, joined the lab with
  • 23:50an interest in uterine serous
  • 23:52cancer.
  • 23:53And so we knew that
  • 23:55siderinib caused a decrease in
  • 23:57DNA repair gene expression in
  • 23:59specific pathways.
  • 24:01But,
  • 24:01what impact might it have
  • 24:03in uterine cancer?
  • 24:05And could there be a
  • 24:05role for sudaredim in combination
  • 24:08with any DNA repair inhibitors
  • 24:09or cell cycle regulators
  • 24:11in uterine cancer? And part
  • 24:13of the reason we were
  • 24:14interested in this is that,
  • 24:17there's a fair proportion of
  • 24:18uterine cancers that are deficient
  • 24:20in DNA mismatch repair.
  • 24:22And the ones that are
  • 24:23deficient in MMR have a
  • 24:25better better natural history and
  • 24:27also
  • 24:28respond better
  • 24:30to immune checkpoint inhibitors.
  • 24:33So,
  • 24:34Gary went ahead and and
  • 24:36surveyed some uterine, cancer,
  • 24:38lines that we got from
  • 24:39Alessandro
  • 24:40Santin here in the GYNOC
  • 24:42department. And what he saw
  • 24:44was that in the ARC
  • 24:45one,
  • 24:46on the left and and
  • 24:46the HEK one b on
  • 24:47the right,
  • 24:49the mismatch repair factors
  • 24:51were suppressed in response to
  • 24:52sudernib at different levels of
  • 24:54sensitivity.
  • 24:55Interestingly, this ARC four cell
  • 24:57line did not show an
  • 24:58effect to sudernib alone.
  • 25:03We then tested the functional
  • 25:04effect on mismatch repair using
  • 25:06a reporter system in which
  • 25:08a dinucleotide
  • 25:09repeat is inserted at the
  • 25:11beginning of the reading frame
  • 25:13for the green fluorescent protein,
  • 25:15and and it's,
  • 25:16set up so it's out
  • 25:18of frame, so there is
  • 25:19no green in the cells.
  • 25:20But if there's a mismatch
  • 25:22repair deficiency leading to a
  • 25:24frame shift, you will see
  • 25:25green cells.
  • 25:26And so what you see
  • 25:27here on the right is
  • 25:28this reporter was put into
  • 25:30those cell lines. They were
  • 25:32treated or not with siderinib,
  • 25:33and you can see that
  • 25:34there's an increase in the
  • 25:36GFP positive fraction after siderinib
  • 25:39treatment, notably in the ARC
  • 25:41one and the HEK one
  • 25:42b
  • 25:42and a tiny one in
  • 25:44the ARC four.
  • 25:47Now
  • 25:48having seen this functional decrease,
  • 25:50we wondered how could we
  • 25:52exploit this?
  • 25:54Now we knew that,
  • 25:55you know, olaparib was was
  • 25:57not known to synergize with
  • 26:00mismatch repair deficiencies. So we
  • 26:03we,
  • 26:04hypothesized that maybe an inhibitor
  • 26:07of a cell cycle checkpoint,
  • 26:09namely,
  • 26:10we one inhibitor might
  • 26:12have some combination effect
  • 26:15because mismatch repair causes replication
  • 26:17stress,
  • 26:19on multiple levels.
  • 26:20And we we one is
  • 26:22a a checkpoint protein that
  • 26:24regulates,
  • 26:25cell cycle progression at multiple
  • 26:27points in the cell cycle
  • 26:28as illustrated here, intra s,
  • 26:30g two m, and mitotic
  • 26:32exit.
  • 26:33So we thought there potentially
  • 26:35could be an opportunity,
  • 26:37for a combined effect.
  • 26:39So, Gary went ahead and
  • 26:40did a study to look
  • 26:42for synergism. And and for
  • 26:44those of you not familiar,
  • 26:45this is, of cell viability
  • 26:47assay where different doses of
  • 26:49one agent are on one
  • 26:51axis and doses of another
  • 26:53on the other. And where
  • 26:55you see,
  • 26:56hills that are blue
  • 26:58are dose combinations where there's
  • 27:00statistical evidence for synergism.
  • 27:02So in all three cell
  • 27:03lines, we saw that these
  • 27:04two
  • 27:05agents, one cediranib and and
  • 27:07a v one inhibitor,
  • 27:09which in the slides we
  • 27:11mostly call m MK seventeen
  • 27:13seventy five or atadavosertib,
  • 27:17showed, good synergism.
  • 27:20Now,
  • 27:21interestingly, the arc four cells
  • 27:22had not shown a decrease
  • 27:24in mismatch repair
  • 27:25gene expression by sediranibalone.
  • 27:28But if you can see
  • 27:29it here, when we treated
  • 27:31them with the combination,
  • 27:33we actually saw that there
  • 27:34was strong suppression of, DNA
  • 27:37mismatch repair expression,
  • 27:38which you could measure in,
  • 27:40by the increase in, cells,
  • 27:43showing GFP expression using that
  • 27:45reporter vector that is visualized
  • 27:47here and quantified on the
  • 27:49right. The same is true
  • 27:50on the HEK1 b cells.
  • 27:54So what might be going
  • 27:55on? Well, it turns out
  • 27:57that
  • 27:58just like,
  • 27:59the BRCA
  • 28:00and Rad fifty one promoters,
  • 28:02the mismatch repair gene promoters
  • 28:04can also respond to e
  • 28:05two f and pocket protein,
  • 28:08transcription factor complexes.
  • 28:10And when we looked at
  • 28:12retinoblastoma
  • 28:13phosphorylation,
  • 28:14we could see that,
  • 28:16the we one inhibitor and
  • 28:18cediranib
  • 28:19synergized to
  • 28:21increase the hypophosphorylation
  • 28:23or decrease the phosphorylation of
  • 28:25r v RB,
  • 28:26which creates
  • 28:28the repressive
  • 28:29complex
  • 28:29that then acts on
  • 28:33the DNA repair gene promoters.
  • 28:35So that was
  • 28:37one step in the mechanism.
  • 28:39But
  • 28:40we wondered, well, why is
  • 28:41there synergistic
  • 28:43killing?
  • 28:45So,
  • 28:46we got a clue from
  • 28:47the literature.
  • 28:49There is a,
  • 28:52a group, now at, University
  • 28:54of Texas Southwestern led by
  • 28:55Guomin Lee who published,
  • 28:58this, very interesting paper. Excuse
  • 29:00me. I'm just
  • 29:02gonna get a little water.
  • 29:04Where he looked at
  • 29:05MLH one deficiency and its
  • 29:07effect on the c gasping
  • 29:09pathway.
  • 29:13And what he found was
  • 29:14when you knock down m
  • 29:16l h one,
  • 29:17you get an increase in
  • 29:19c gas sting signaling in
  • 29:21the innate immune,
  • 29:23pathway.
  • 29:25And his model was that,
  • 29:28it's known that MLH one
  • 29:31interacts with a exonuclease
  • 29:33called XO one. And this
  • 29:34is involved in DNA mismatch
  • 29:36repair, but also plays a
  • 29:37secondary role in end resection
  • 29:40during homologous recombination.
  • 29:42When MLH one is knocked
  • 29:44down,
  • 29:45XO one is unleashed
  • 29:48and could can
  • 29:50mediate,
  • 29:52basically dysregulated
  • 29:57exonuclease
  • 29:58activity on DNA ends,
  • 30:00creating,
  • 30:01DNA fragments and long single
  • 30:03stranded gaps.
  • 30:04And what, he's,
  • 30:06they showed in this paper
  • 30:07is that DNA then gets
  • 30:09released into the cytoplasm
  • 30:12and can activate the c
  • 30:13gas sting pathway, which is
  • 30:15the sensor of
  • 30:17chromosomal DNA and micronuclei
  • 30:19and other DNA, type fragments
  • 30:22in the
  • 30:23cytoplasm.
  • 30:24So the idea
  • 30:26is mismatch repair deficiency,
  • 30:28too much x o one
  • 30:29activity,
  • 30:30and then activation of stigast
  • 30:32deng. And one way to
  • 30:33score that is,
  • 30:34the stat one transcription factor
  • 30:37factor gets phosphorylated.
  • 30:38It's an easy marker of
  • 30:39activation of that innate signaling
  • 30:41pathway.
  • 30:43So we went ahead and
  • 30:44looked at that,
  • 30:46and we found, in fact,
  • 30:48that stat phosphostat
  • 30:49one was strongly induced
  • 30:52by the combination of cediranib
  • 30:54and the wee one inhibitor
  • 30:55as shown here,
  • 30:57and quantified its its, you
  • 30:59know, roughly,
  • 31:01ninety fold increase, which is
  • 31:03quite striking.
  • 31:05And,
  • 31:06we were fortunate
  • 31:08because,
  • 31:10Gary is on a k
  • 31:11award with the women's health
  • 31:12research
  • 31:13program here run by Vicky
  • 31:16Abrams and, Yu Taylor.
  • 31:18And on his mentoring committee
  • 31:19was Akiko Iwasaki
  • 31:21who saw this data. And,
  • 31:22actually, I had had the
  • 31:24privilege of working with Akiko
  • 31:25on a paper which reported
  • 31:28that ataxia telangiectasia
  • 31:31ATM
  • 31:32mutated mice,
  • 31:34which have,
  • 31:36a,
  • 31:38our ATM is known to
  • 31:40have cerebellar degeneration as one
  • 31:42of its phenotypes,
  • 31:47linked the ATM deficiency to
  • 31:49hyperactivation
  • 31:50of line one leading to
  • 31:52neurodegeneration.
  • 31:53So Akiko said, well, that
  • 31:55strong induction of innate immune
  • 31:57signaling,
  • 31:58that might be related to
  • 31:59line one. So we went
  • 32:00ahead and looked into that.
  • 32:02Now what is line one?
  • 32:04It's the long interspersed nuclear
  • 32:05elements, which are the, the
  • 32:08most common,
  • 32:09retro element in the human
  • 32:11genome. Most of them are
  • 32:12silenced, but some
  • 32:14can be expressed.
  • 32:16And, here's a diagram of
  • 32:18the locus, and it encodes
  • 32:19two open reading frames, ORF
  • 32:21one and ORF two. ORF
  • 32:22two is a reverse transcriptase.
  • 32:25And when it when it
  • 32:26becomes activated by transcription followed
  • 32:28by reverse transcription, it's linked
  • 32:30to genomic instability.
  • 32:33And and line one cDNA
  • 32:35in the cytoplasm is known
  • 32:37to activate c gas sting.
  • 32:39And, actually, this is sort
  • 32:40of a life cycle of
  • 32:41the line one elements. And
  • 32:43the key thing here is
  • 32:45if you can see, you
  • 32:46get expression of line one,
  • 32:48RNA,
  • 32:49and it gets,
  • 32:52turned into,
  • 32:54cDNA in the,
  • 32:57here in the cytoplasm and
  • 32:59that activates the c gas
  • 33:00sting pathway. No. It can
  • 33:02also go back into the
  • 33:03nucleus and then reinsert
  • 33:05and be another cause of
  • 33:06genetic instability.
  • 33:09So our hypothesis
  • 33:12was that there was
  • 33:14suppression of MLH one leading
  • 33:16to dysregulated
  • 33:17x o one
  • 33:19that could lead to line
  • 33:20one induction
  • 33:21and cDNA production and then
  • 33:24activate,
  • 33:25c gas sting as line
  • 33:27one is cDNA is known
  • 33:28to do.
  • 33:29So we looked again at,
  • 33:31the uterine cancer cell lines,
  • 33:33and we saw line one
  • 33:35is activated, increased. So this
  • 33:37is a western blot for
  • 33:38line one open reading frame
  • 33:39one, ORF one, is increased.
  • 33:42And that correlates with our
  • 33:43increase in phosphostat one as
  • 33:46seen by western blot in
  • 33:47the combination of,
  • 33:49cediranib
  • 33:50and the w one inhibitor
  • 33:52in both ARC four and
  • 33:53the HEK one b cell
  • 33:54lines.
  • 33:55So
  • 33:56this is fitting our model
  • 33:58that,
  • 33:59you get
  • 34:00a decreased mismatch of pair
  • 34:02leading to line one and
  • 34:03c gas sting,
  • 34:04and stat phosphostat one.
  • 34:07And so
  • 34:08the hypothesis still is that
  • 34:10exo one is playing a
  • 34:11role.
  • 34:13Okay.
  • 34:14Now
  • 34:14for one
  • 34:16one part of this, we
  • 34:17asked, okay. Is the line
  • 34:19one cDNA causing the phosphostat
  • 34:22one induction?
  • 34:23And one way to test
  • 34:24that is use a reverse
  • 34:26transcriptase inhibitor called three t
  • 34:28c.
  • 34:29And this would block
  • 34:31the production of the line
  • 34:33one cDNA
  • 34:34from the line one mRNA.
  • 34:37So if you look here,
  • 34:38this is,
  • 34:39control. This is the combination
  • 34:41of cediranib and the wee
  • 34:42one inhibitor. MLH one is
  • 34:44down.
  • 34:45Line one is induced,
  • 34:46and fostostat one is induced.
  • 34:49Now if you add three
  • 34:50t c,
  • 34:51you see line one
  • 34:54is suppressed back to baseline,
  • 34:56and so is fostostat one.
  • 34:58Now you can recapitulate
  • 35:00that instead of doing the
  • 35:01combination of cediranib and v
  • 35:03one inhibitor. You acutely knock
  • 35:05down MLH one with a
  • 35:07s I r n a.
  • 35:09You get induction of line
  • 35:11one
  • 35:12and phosphostat one. Now this
  • 35:13part was seen by the
  • 35:15Guoam and Li lab. What
  • 35:16they hadn't realized was that
  • 35:18line one might be playing
  • 35:19a role.
  • 35:21And this is blocked
  • 35:23similarly to the case with
  • 35:25the drugs
  • 35:26by the reverse transcriptase.
  • 35:29So it looked like this
  • 35:29is a similar mechanism.
  • 35:33Now we went on to
  • 35:34test the role for x
  • 35:35o one.
  • 35:36And in this case, we
  • 35:37used
  • 35:40siRNA
  • 35:40knockdown.
  • 35:42So you see here,
  • 35:43in this case, we're looking
  • 35:44at the impact of acute
  • 35:46MLH one knockdown.
  • 35:48MLH one knockdown leads to
  • 35:51actually a slight increase in
  • 35:52levels of x o one,
  • 35:54but also line one induction,
  • 35:56phosphostat one induction as we
  • 35:57saw before.
  • 35:59But if you also knock
  • 36:00down x o one,
  • 36:02you see there's less line
  • 36:04one induced and less phosphostat
  • 36:06one.
  • 36:07Then you you look at
  • 36:08that in the setting of
  • 36:09the combination of siderinib
  • 36:11and the wee one inhibitor.
  • 36:14So lipof lipofectamine
  • 36:16is just the control for
  • 36:17the s I r n
  • 36:18a to x o one.
  • 36:20And you see here that
  • 36:22you get the induction of
  • 36:23line one and stat one
  • 36:25phosphostat one as we saw
  • 36:26before with the combination of
  • 36:27the drugs.
  • 36:29But when you have knocked
  • 36:31down x o one,
  • 36:33it abrogates those increases.
  • 36:35So you see here there's
  • 36:36no induction of line one.
  • 36:38In fact, it's below the
  • 36:39baseline,
  • 36:40and you suppress the induction
  • 36:41of phosphostat one.
  • 36:45Okay. So now we return
  • 36:46to that synergistic killing,
  • 36:49and I wanna caution that
  • 36:50this is a
  • 36:51preliminary result that we are
  • 36:53trying to
  • 36:54confirm.
  • 36:56But it it fit the
  • 36:57story so well I couldn't
  • 36:58help but show it.
  • 37:00And what you see here
  • 37:01is that there is killing
  • 37:02of the uterine cancer cells
  • 37:04by the combination of sildernib
  • 37:06and v one inhibitor. But
  • 37:08when you add the reverse
  • 37:10transcriptase to block the induction
  • 37:11of line one, you rescue
  • 37:13the cell killing.
  • 37:17Now let's go back to
  • 37:19an in vivo model.
  • 37:22And so,
  • 37:24what we did was we
  • 37:25tested,
  • 37:25whether this applied to a
  • 37:28tumor model in mice, and
  • 37:29we used the ARC four
  • 37:30cells,
  • 37:31in
  • 37:33in as as a xenograft
  • 37:34in nude mice.
  • 37:35And you can see here,
  • 37:36the blue is the control
  • 37:38untreated.
  • 37:39These are the two agents,
  • 37:41independently,
  • 37:43siderinib and, we one inhibitor.
  • 37:45And here is the combination,
  • 37:47which essentially completely suppressed tumor
  • 37:50growth. And you can see
  • 37:51an example at
  • 37:53at at the time of
  • 37:54sacrifice of the animals. There's
  • 37:56basically scar tissue left in
  • 37:57the combination treatment.
  • 37:59And importantly, the mouse weights
  • 38:01were stable and so were
  • 38:03the blood counts. And this
  • 38:04is important because these agents
  • 38:06are known to effect,
  • 38:08cause myelosuppression.
  • 38:11And then we returned to
  • 38:12mechanism,
  • 38:13and we did immunohistochemistry
  • 38:15on those tumors
  • 38:17for line one
  • 38:18open reading frame one expression.
  • 38:20And you can see that
  • 38:21in the combination treatment, there's
  • 38:23an induction of line one
  • 38:25expression
  • 38:26consistent with, the model.
  • 38:31Now I didn't forget about
  • 38:32hypoxia, so we're a little
  • 38:34bit back to the future.
  • 38:35And it turns out Yuhang,
  • 38:37who had done all that
  • 38:38work on gene,
  • 38:40silencing,
  • 38:41has been looking at the
  • 38:42innate immune signaling pathway because
  • 38:44it turns out that there
  • 38:46is some
  • 38:47long term silencing of sting
  • 38:49in hypoxic cells.
  • 38:51But there's initially induction of
  • 38:53phosphostat one. So so based
  • 38:55on what, Gary had found,
  • 38:57we looked at line one
  • 38:58in hypoxia, and it turns
  • 39:00out line one is induced
  • 39:01in hypoxic cells.
  • 39:03But that induction
  • 39:05can be blocked by the
  • 39:06three TC,
  • 39:09reverse transcriptase,
  • 39:11inhibitors. So more to come
  • 39:12on that.
  • 39:14So just in summary, what
  • 39:16what I've told you is
  • 39:17that hypoxia,
  • 39:19drives changes in DNA repair
  • 39:20and genome instability
  • 39:22on multiple levels,
  • 39:24that cediranib,
  • 39:27phenocopies
  • 39:27the effect of hypoxia
  • 39:29on homology dependent repair and
  • 39:30mismatch repair by engaging a
  • 39:32similar signaling meth mechanism.
  • 39:36That creates a synthetic lethality
  • 39:38with PARP inhibitors that's that
  • 39:39has been observed in a
  • 39:41clinical trial.
  • 39:43And,
  • 39:44we have evidence that we
  • 39:46won inhibition will synergize
  • 39:48with siderinib
  • 39:49to both suppress MLH one
  • 39:51and activate line one
  • 39:53and innate immune signaling,
  • 39:55to,
  • 39:56kill uterine cancer cells,
  • 39:59presumably through immunogenic cell death,
  • 40:01although that mechanism needs to
  • 40:03be
  • 40:04fleshed out.
  • 40:06And,
  • 40:08we have recent evidence that
  • 40:09hypoxia also engages
  • 40:12some of the same, pathways
  • 40:14possibly through line one.
  • 40:16So future directions are to
  • 40:17dig a little deeper into
  • 40:18this mechanism.
  • 40:21As I said, I showed
  • 40:22some old,
  • 40:23material, but some new material,
  • 40:25so this is all still
  • 40:26a work in progress.
  • 40:27We want to extend to
  • 40:28other uterine cancer models and
  • 40:30other cancer types,
  • 40:32and, we would like to
  • 40:33combine with an immune checkpoint
  • 40:35inhibitor in a in an
  • 40:36immune competent model.
  • 40:38We we haven't done that
  • 40:39because those were human,
  • 40:41cancer lines,
  • 40:43not syngeneic with the,
  • 40:45immune competent mouse model. And
  • 40:47we would like to test
  • 40:49this combination in a clinical
  • 40:51trial.
  • 40:52So,
  • 40:53I'll stop there and,
  • 40:54happy to, take questions. Thank
  • 40:57you.
  • 41:08Tommy.
  • 41:26Right.
  • 41:31Right.
  • 41:58So so we we haven't
  • 42:00looked at that, but that's
  • 42:01very interesting. So Tommy was
  • 42:03asking about the fact that
  • 42:04three t's I'll go back
  • 42:06to the microphone.
  • 42:07Three three t c is
  • 42:09an antiviral.
  • 42:10And,
  • 42:12and so what what what
  • 42:13is seen clinically
  • 42:15that might be related to
  • 42:16what we've seen? And, the
  • 42:18answer is we don't know,
  • 42:19but it's possible that, that
  • 42:21could be affecting,
  • 42:23response to therapies.
  • 42:25The other interesting thing that
  • 42:27Gary has proposed is whether
  • 42:29three t c, if it
  • 42:31in fact suppresses
  • 42:33innate immune signaling and inflammation
  • 42:35in mismatch repair deficiency,
  • 42:38could be used as a
  • 42:39chemo preventive
  • 42:40for people with Lynch syndrome.
  • 42:45And,
  • 42:46you know, that remains to
  • 42:48be determined, but I think
  • 42:49it's something we would like
  • 42:51to see if we could
  • 42:52model in mice
  • 42:53or even in people.
  • 42:55Yeah.
  • 43:18Right.
  • 43:20Yeah. So we haven't looked
  • 43:22at small cell lung and,
  • 43:23of course, the Schlippet eleven
  • 43:25plays a key role in
  • 43:26our response,
  • 43:28but that would be, you
  • 43:29know, very interesting to look
  • 43:30at.
  • 43:32Yeah.
  • 43:33Yeah.
  • 43:41Yeah.
  • 44:00Yeah. So,
  • 44:02just to repeat that, the
  • 44:03question has to do with
  • 44:04have we you know, can
  • 44:06we detect ORF two related
  • 44:07to line one?
  • 44:10I think as see, as
  • 44:11a practical matter, the antibody
  • 44:13to ORF one is a
  • 44:14really good antibody, and so
  • 44:15that's what almost everyone uses
  • 44:16in the literature.
  • 44:18And so,
  • 44:19we haven't looked at ORF
  • 44:21two. Or if we did,
  • 44:22nobody showed me that data,
  • 44:23so I don't think it
  • 44:24worked.
  • 44:25But, yeah, that's a good
  • 44:27point. Now we have the
  • 44:28indirect evidence that the reverse
  • 44:30transcriptase inhibitor suppresses the,
  • 44:33effect, which makes sense because
  • 44:35we're looking for line one,
  • 44:37but we don't we haven't
  • 44:38directly measured or orf two.
  • 44:41Yeah. Roy. Peter, I have
  • 44:43a question about clinical trials.
  • 44:44Actually, two questions.
  • 44:46First, the trial of Jo
  • 44:47Kim with the Sedernet.
  • 44:49Looking at that curve, it
  • 44:50looks like there was a
  • 44:51positive PFS.
  • 44:52So where did that trial
  • 44:53go? Has it gone on
  • 44:54to a further study? Did
  • 44:56any of the molecular correlates
  • 44:58confirm some of the, scientific
  • 45:00advancements?
  • 45:01Yeah. I I I gotta
  • 45:02let Joe do it. He's
  • 45:03sitting behind you so he
  • 45:04can he can answer that.
  • 45:11Data before our trials. So
  • 45:13I did two trials. One
  • 45:14was in prostate cancer and
  • 45:15then the other was was
  • 45:16in advanced
  • 45:23which is shown here is
  • 45:24our positive data. So, again,
  • 45:25our our new hypothesis was
  • 45:27that we'll be able to
  • 45:28see the benefit
  • 45:30involving, you know, the jawline
  • 45:31or condition set up some
  • 45:33of the HR g calculations.
  • 45:35If you're told surprise, what
  • 45:36we saw was actually we
  • 45:37saw,
  • 45:38most of our benefits in
  • 45:39patients with HR proficiency. In
  • 45:41other words, the patients with
  • 45:42the mutations spread like for
  • 45:44those without the mutation, we
  • 45:45are able to it's the
  • 45:46benefit of the combination. So,
  • 45:47actually, our question become actually,
  • 45:50whether
  • 45:51the,
  • 45:52you know, whether this actually
  • 45:53prevents or delays the partner
  • 45:55need to resist. From that
  • 45:56one question to you is
  • 45:58that based on what you
  • 45:59have seen so far,
  • 46:00whether the again, again, it's
  • 46:02really a tough thing and
  • 46:03losing agent. We do see
  • 46:04this in patients
  • 46:05like the manifest as, like,
  • 46:06a bad the high blood
  • 46:08pressure, the fatigue, similar to
  • 46:10data, some of the losses
  • 46:11there is. If, you know,
  • 46:11we do have these adverse
  • 46:12strong hypoxia inducing agents. Whether
  • 46:14that actually plays a role
  • 46:16in getting the vetting or
  • 46:17delaying part of the little
  • 46:19tests, that's one. And then
  • 46:20just to kind of sort
  • 46:21of highlight on the,
  • 46:23small of the long range
  • 46:24data, actually, we have seen
  • 46:25we have to have image
  • 46:26at half the output of
  • 46:27CRM. We had to obtain
  • 46:29that part as a scan
  • 46:30before and after the same
  • 46:31amount of activity directed image
  • 46:33that I can see I
  • 46:34used by the, CRM. And
  • 46:36we actually,
  • 46:37saw some early antigen activity
  • 46:39in small alarm cancer. We
  • 46:41saw about thirty percent response
  • 46:43rate and then also in,
  • 46:44non small alarm and
  • 46:46also in the CNDC as
  • 46:47well. In pancreas, we're not
  • 46:48able to see,
  • 46:50no, you know, benefits at
  • 46:51all. So I'll just
  • 46:53Yeah. So my question to
  • 46:54you is whether
  • 46:59Yeah. So that's very interesting,
  • 47:01question. And I think what
  • 47:03might be going on is
  • 47:04that cediranib had has a
  • 47:06a little bit of a
  • 47:07broad based effect on a
  • 47:09number of repair factors in
  • 47:11the HDR pathway.
  • 47:12So some of the tumors
  • 47:14that might have, say, a
  • 47:15BRCA deficiency,
  • 47:18What sildernib also does is
  • 47:20suppress RAD fifty one and
  • 47:21some FANC b two and
  • 47:23some other
  • 47:24factors in the same pathway.
  • 47:25So
  • 47:26either
  • 47:27one is that HDR
  • 47:29deficiency occurs at different levels
  • 47:31and the sildernib takes it
  • 47:32down a little bit more.
  • 47:33Or if there's been a
  • 47:34reversion,
  • 47:36for example, like in BRCA2,
  • 47:37there's been some intragenic,
  • 47:39deletions that cause a reversion
  • 47:41in the phenotype.
  • 47:42The siderinib can still suppress
  • 47:44expression and cause
  • 47:47further
  • 47:47HDR deficiency.
  • 47:49So it could be that
  • 47:51that's the susceptible population where
  • 47:53siderinib is gonna have its
  • 47:54most effect.
  • 47:58And for your other clinical
  • 47:59trial with the pembrolizumab, which
  • 48:01looks very interesting.
  • 48:03I know you're waiting for
  • 48:04more preclinical data, but, you
  • 48:05know, that's gonna be very
  • 48:06hard. The animal models are
  • 48:07all good, but not so
  • 48:08good. Right. What are the
  • 48:09barriers that getting an IIT
  • 48:11going? Is there a specific
  • 48:12disease that might be best
  • 48:14that anybody do in the
  • 48:15phase one detector?
  • 48:17Where where is that?
  • 48:18Well,
  • 48:19so I don't know if
  • 48:21Gary's in the audience. He's
  • 48:22probably in the OR.
  • 48:23But he is looking to
  • 48:25to do a,
  • 48:27clinical trial in uterine.
  • 48:29That's his you know, that's
  • 48:31where this is leading for
  • 48:32him. I think for
  • 48:33other,
  • 48:34disease,
  • 48:35sites, for example,
  • 48:37Eric and I were talking
  • 48:38about breast.
  • 48:39You know, we we need
  • 48:40to survey,
  • 48:42based on, you know, genetic
  • 48:44characteristics of of different, tumor
  • 48:46types
  • 48:47where there's gonna be susceptibility
  • 48:49because we know there's variation.
  • 48:50So, for example, in breast,
  • 48:52is it triple negative? Is
  • 48:53it gonna be,
  • 48:54you know, some other subtype?
  • 48:56And the same is, you
  • 48:57know, there is we have
  • 48:59a hint of a difference
  • 49:00in lung between the KRAS
  • 49:01driven and the EGFR driven.
  • 49:04So there's more to learn
  • 49:06as far as what tells
  • 49:07us
  • 49:08that,
  • 49:10you know,
  • 49:11these strategies could work.
  • 49:13And in fact, you know,
  • 49:14Eric and I have briefly
  • 49:15talked about, you know, sport
  • 49:16projects. And I think
  • 49:18something in a sport project
  • 49:19could be care you know,
  • 49:20trying to figure out what's
  • 49:21subtype to take this into
  • 49:23a trial and then do
  • 49:24the trial.
  • 49:26Yeah.
  • 49:28Yeah.
  • 49:42Yes. So we did do
  • 49:44that, and that's in Alana's
  • 49:46paper. We did a kind
  • 49:47of a, I would say,
  • 49:48medium sized scale screen.
  • 49:50And and a fair number
  • 49:52do the same thing, especially
  • 49:54the ones that
  • 49:55strongly inhibit PDGFR.
  • 49:57So that's part of what
  • 49:58led to our hypothesis
  • 50:00of the pathway.
  • 50:02So, you know, I can
  • 50:04refer you to there's a
  • 50:05table in the supplementary
  • 50:06material that has couple hundred
  • 50:09agents in it.
  • 50:11Joe, you had a question.
  • 50:14Add on to that PDGFR
  • 50:16question.
  • 50:17Just start I mean, it's
  • 50:18great work and then about
  • 50:20a while. Just start me.
  • 50:20Have you looked at cells
  • 50:21that over trust PDGFR, or
  • 50:23are they did you get
  • 50:24a bigger response or mention
  • 50:26the p g f r?
  • 50:26He he yeah. We we
  • 50:27haven't done that, enough to
  • 50:29say anything. We I mean,
  • 50:29we we thought about doing
  • 50:29that, and we did some
  • 50:30knockout work and some overexpression
  • 50:33work. So
  • 50:39there is some correlation, but
  • 50:40we haven't done a broad
  • 50:41survey.
  • 50:42And that, for example, could
  • 50:43be something that could, you
  • 50:45know, go into a project
  • 50:46where we, you know, look
  • 50:48at, you know, the cell
  • 50:49you know, databases of cell
  • 50:51cancer cell lines and things
  • 50:52like that.
  • 50:55Right. Right.