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Biomarkers in Bladder Cancer

December 12, 2023
  • 00:00Good morning, everyone.
  • 00:03It really gives you a great joy to introduce
  • 00:05the speaker for Grand Mound today.
  • 00:07Today's speaker is Doctor Fad Galley.
  • 00:10He's our new recruit.
  • 00:11He joined us in August
  • 00:13last year from Fred Hutch.
  • 00:15So he's a urological oncologist who
  • 00:17specialized in taking care of patients
  • 00:19with bladder and the urinary tract
  • 00:21cancers and also test his cancer as well.
  • 00:24He finished his medical school at
  • 00:26Geyser School of Medicine at Dartmouth.
  • 00:28He then wanted to, you know,
  • 00:29UC San Diego for his surgical
  • 00:32internship and residency.
  • 00:33And then he went on to University of
  • 00:36Washington in Seattle for his suicide
  • 00:38of urology on College of Fellowship.
  • 00:40And then he joined us as a
  • 00:43faculty last August.
  • 00:44His research interests include
  • 00:46designing clinical trials,
  • 00:48environmental development
  • 00:48and urinary tract cancers,
  • 00:50and he has received multiple
  • 00:53awards and grants and publications.
  • 00:55Dr.
  • 00:56Gatti for those two years,
  • 01:03great. Thank you all for being here.
  • 01:05It's really an honor to get
  • 01:06to speak with all of you.
  • 01:07Like Doctor Kim has said,
  • 01:09I started just about three
  • 01:10months ago so this is early in
  • 01:12my in my stay here at Yale.
  • 01:14But it's it's it's really been
  • 01:15such a pleasure to meet all of
  • 01:17the other faculty and get to take
  • 01:18care of patients with you all.
  • 01:20So thanks for having me.
  • 01:24I'm going to speak today about biomarkers
  • 01:26within bladder cancer and this is sort of an,
  • 01:28it's a very, this is a broad title and
  • 01:29it's a bit of an ambitious maybe title.
  • 01:31So I think what's maybe more appropriate is
  • 01:34examples of biomarkers within bladder cancer.
  • 01:36And I'll sort of weave in a little
  • 01:38bit of overview of how we take
  • 01:40care of these patients,
  • 01:41talk about some of the work that we've
  • 01:43done and some of the work that's ongoing.
  • 01:45That's exciting disclosures,
  • 01:48none that are, none that are relevant
  • 01:51here and none that are ongoing.
  • 01:53And so like I say,
  • 01:54we'll sort of talk briefly about
  • 01:56an introduction to bladder
  • 01:58cancer patients and care,
  • 02:00we'll talk about non muscle invasive
  • 02:02bladder cancer which is sort of the early
  • 02:04part of the Natural History of the disease,
  • 02:06talk about advanced bladder cancer and
  • 02:08some of the ongoing clinical trials.
  • 02:09And then hopefully have some questions,
  • 02:11some time for questions at the conclusion.
  • 02:15So to start, bladder cancer is a common
  • 02:19and unfortunately lethal illness.
  • 02:21It affects about 82,000 Americans
  • 02:23per year and approximately 17,000
  • 02:25Americans succumb to the disease.
  • 02:27So 5th or 6th most common cause of
  • 02:29cancer death depending on the gender
  • 02:31of the patient and the prime the the
  • 02:35majority of patients that they experience
  • 02:38bladder cancer are in Medicare age,
  • 02:41so sort of 65 years of age and older.
  • 02:43So you can see here from from sincere
  • 02:46data that approximately 80 to 85%
  • 02:48of patients with bladder cancer
  • 02:50are are elderly and those are the
  • 02:52patients that bear the brunt of the
  • 02:54mortality of bladder cancer as well.
  • 02:56And so and so this is really a disease
  • 02:59that affects primarily elderly,
  • 03:01the elderly patients,
  • 03:02although of course not exclusively
  • 03:053/4 of patients that present
  • 03:07with bladder cancer, however,
  • 03:08do present in an early stage of the
  • 03:10disease what we call non muscle invasive.
  • 03:12And so you can see in the schematic,
  • 03:13which I am using here without permission,
  • 03:15without permission,
  • 03:16so hopefully that's OK.
  • 03:17But this is a schematic from the
  • 03:19Internet and shows you could see
  • 03:22that tumors in most patients present
  • 03:24in a fairly superficial stage of
  • 03:27the disease where either the mucosa
  • 03:29or the lamina propria are involved,
  • 03:31but not the deeper muscle layer
  • 03:34of the bladder.
  • 03:35And this is really a distinct
  • 03:37clinical entity because we can
  • 03:38often treat these patients with
  • 03:40bladder preserving modalities.
  • 03:42So these patients can be treated
  • 03:44with endoscopic resections of the
  • 03:46tumor and then intra vesicle therapy.
  • 03:48So we can actually instill a catheter
  • 03:50in the bladder and give either
  • 03:52immunotherapy in the form of BCG or
  • 03:55chemotherapies in the bladder and
  • 03:57and preserve preserve their bladder
  • 03:59in this early stage of the disease.
  • 04:02Unfortunately though recurrences
  • 04:03are very common.
  • 04:04Bladder cancer has a very not especially
  • 04:06non muscle invasive bladder cancer
  • 04:08has a very high recurrence rate.
  • 04:10So this is a study from the
  • 04:11University of Miami, Rich ET al.
  • 04:13And it's a really well done study.
  • 04:15It's approximately 500 patients
  • 04:16that they've taken care of with
  • 04:19really meticulous data review and
  • 04:22these patients were stratified
  • 04:23into risk strata that we use in non
  • 04:25muscle invasive bladder cancer and
  • 04:27they tracked progression despite
  • 04:29standard of care therapy.
  • 04:30And what you can see here is progression
  • 04:32free survival or recurrence free
  • 04:34survival I should say rather than
  • 04:35progression is pretty significant.
  • 04:37The very top line here the the black
  • 04:40line is low risk patients and you can
  • 04:43see after a few years approximately
  • 04:45half of them will have experienced a
  • 04:47recurrence in the bladder requiring
  • 04:49repeat surgery and so on.
  • 04:51High risk patients have even higher
  • 04:53recurrence rates in in this series
  • 04:55pretty significant rates of recurrence.
  • 04:57So to deal with this,
  • 05:00one of the things we do is we put
  • 05:02patients on long term surveillance
  • 05:04of their bladder cancer and this
  • 05:06is done through routine cystoscopy.
  • 05:08And I like this image image because
  • 05:11it it makes me feel uncomfortable
  • 05:12when I look at it.
  • 05:13It's sort of highlights I think the
  • 05:16discomfort that patients experience
  • 05:17undergoing this procedure And cystoscopy
  • 05:20is really a useful tool in urology,
  • 05:22but it's got major limitations.
  • 05:24For one,
  • 05:25it's not perfect.
  • 05:26It has you know approximately a
  • 05:2870 to 80% sensitivity for bladder
  • 05:31cancer recurrence depending on
  • 05:33the series that's looked at it,
  • 05:36it's uncomfortable.
  • 05:37Approximately 30 to 35% of patients
  • 05:40report experiencing significant anxieties
  • 05:43from cystoscopy and it's expensive.
  • 05:46So here are a couple of references
  • 05:48that we won't go into,
  • 05:49but these are references that
  • 05:50really highlight the significant
  • 05:52cost to the healthcare system for
  • 05:54long term surveillance of bladder
  • 05:55cancer making it one of the most
  • 05:57expensive cancers to to care for.
  • 06:00And so for those reasons I,
  • 06:01I I think there are lots of reasons why we
  • 06:04sort of you can see I made
  • 06:05my own my own figures here.
  • 06:06But you can see that there's a real
  • 06:08strong indication for biomarkers in the
  • 06:10non muscle invasive bladder cancer space.
  • 06:12Ideally a sensitive and specific marker
  • 06:15that can identify non invasively when
  • 06:18patients have recurred with bladder cancer.
  • 06:21There are ones that we use currently.
  • 06:23So cytology is a commonly used urinary
  • 06:26biomarker and and again without
  • 06:27sort of going too much into it,
  • 06:29cytology has its own major limitations
  • 06:32for for one it's it's quite,
  • 06:34it's quite intensive,
  • 06:35it requires A cytopathologist to
  • 06:37review their significant inter reader
  • 06:40variability between cytopathologists.
  • 06:42And on top of that it's despite
  • 06:44being labour intensive,
  • 06:45the performance of cytology is quite lacking.
  • 06:49Sensitivities have been reported
  • 06:50in the 50s to 60 percents with with
  • 06:54in all comers with bladder cancer
  • 06:56and then obviously substratifying
  • 06:58we had a little more granularity.
  • 07:00There are other biomarkers that
  • 07:01have been reported and I'm going
  • 07:02to just sort of show you a list
  • 07:04of what's been out there that are
  • 07:05protein based biomarkers,
  • 07:06cell based biomarkers and the sort of
  • 07:08in the interest of time what I would
  • 07:10say is none of them are recommended
  • 07:12for routine use or certainly for
  • 07:15replacement of cystoscopy because of
  • 07:17poor performance of these relative
  • 07:19to cystoscopies.
  • 07:22One real Ave. that's come to light in
  • 07:24the last several years especially with
  • 07:27the advent of widespread next generation
  • 07:29sequencing is the the question about urinary
  • 07:32tumor associated DNA as a biomarker.
  • 07:34And so I'm going to spend just a
  • 07:36few minutes talking about this.
  • 07:38This has been reported as a proof of
  • 07:40principle and several, several reports.
  • 07:41And so there are versions that have
  • 07:44been tested in the past and the
  • 07:47proof of principle does demonstrate
  • 07:48that it's a useful tool.
  • 07:50There are sensitivities
  • 07:51sometimes in the high 80s,
  • 07:52mid to high 80s for urinary DNA biomarkers,
  • 07:55especially in a tumor
  • 07:57informed mechanism for it.
  • 07:59But ultimately,
  • 07:59the sensitivities and specificities
  • 08:01don't seem to to be good enough to
  • 08:04replace cystoscopy with current with
  • 08:06current DNA sequencing technologies.
  • 08:09And one of the reasons for this
  • 08:11is some inherent limitations
  • 08:12with next generation sequencing.
  • 08:14So I'm going to talk just a
  • 08:15little bit about that.
  • 08:16This is a paper,
  • 08:17it's a little bit old now,
  • 08:18but it's a nice paper because it
  • 08:20reviews some various platforms.
  • 08:21I'm not going to go through
  • 08:22in detail all of this,
  • 08:23but what you can see here in
  • 08:25this column is actually just
  • 08:27various sequencing platforms here
  • 08:28and the error rates associated
  • 08:30with polymerase amplifications.
  • 08:32And what you can see is error
  • 08:34rates just from the amplification
  • 08:35process of next generation.
  • 08:36Sequencing can vary based on
  • 08:38the platform but it's can be
  • 08:41somewhere between point O1 to 1%
  • 08:44amplification error rates which is
  • 08:47not significant if you're checking
  • 08:50for somatic mutations or really
  • 08:52high volume mutations in a tumor.
  • 08:54But it can be a problem if you're
  • 08:57looking for heterogeneous low,
  • 09:00you know really infrequent mutations
  • 09:04in in something like a dilute sample
  • 09:07like urinary like a urine sample.
  • 09:10And so one example of I think a
  • 09:12helpful figure for me is if you look
  • 09:14at this sort of hundred well image
  • 09:16here and you could see that tumors
  • 09:18are we know tumors are heterogeneous,
  • 09:20they present different populate,
  • 09:22they have different populations
  • 09:24with different expressions
  • 09:25of tumor associated DN as.
  • 09:27And if you look at standard next generation
  • 09:29sequencing with the known error rates,
  • 09:31what you can see is that a lot
  • 09:32of the heterogeneity is missed.
  • 09:34There are certain subpopulations that
  • 09:36can't be captured very effectively and
  • 09:38there are tools to get around this.
  • 09:39We can do micro dissection for example
  • 09:41and then do next generation sequencing,
  • 09:44which adds a little bit of Labor.
  • 09:46It's has difficulty with scalability and
  • 09:48maybe capture some of these populations.
  • 09:50But again some of the heterogeneity
  • 09:52is missed.
  • 09:55What about single cell sequencing?
  • 09:56And again single single cell next
  • 09:58generation sequencing is really
  • 09:59effective at capturing rare events,
  • 10:01but scalability becomes an issue.
  • 10:04And when 1 zooms out and thinks
  • 10:06about the challenge that faces
  • 10:08urinary detecting tumor DNA in the
  • 10:10urine the the picture starts to look
  • 10:11a little bit more like this where
  • 10:13we're trying to capture very very,
  • 10:15very rare events and quite,
  • 10:17quite dilute solutions And and this,
  • 10:20this really can limit the
  • 10:22sensitivity and of an assay.
  • 10:24And and I think that's what's been
  • 10:26shown in in previous attempts at this.
  • 10:28One thing we've been looking at that
  • 10:30we looked at at the University of
  • 10:32Washington and are trying to develop is
  • 10:34using a tool called duplex sequencing
  • 10:35which was new to me as a fellows
  • 10:38developed in the lab in the labs at
  • 10:40the University of Washington with
  • 10:42Scott Kennedy and and colleagues.
  • 10:44And this is a tool that's really
  • 10:46helpful for the detection of ultra rare
  • 10:48mutations with quite high accuracy.
  • 10:51The reason this is helpful is
  • 10:53because of a computational tool.
  • 10:55Duplex sequencing is primarily A
  • 10:58computational tool which starts off
  • 10:59by using a sort of standard error
  • 11:02corrected next generation sequencing tools.
  • 11:04So you know DNA,
  • 11:06the DNA from specimens are fragmented.
  • 11:09We use a unique molecular identifier
  • 11:11that's ligated to the fragments and
  • 11:13then next generation sequencing is performed.
  • 11:16And if you can see here in this panel,
  • 11:18there's a true mutation demonstrated
  • 11:20here in green.
  • 11:20And then as amplification occurs,
  • 11:23there are amplification errors
  • 11:25that accumulate during the during
  • 11:27in various amplicons.
  • 11:29And sort of a standard pathway
  • 11:31would be to perform single strand
  • 11:34consensus so that if all of the
  • 11:36amplicons don't have a demonstrated
  • 11:38mutation that mutation is sort of
  • 11:41assumed to be an amplification error.
  • 11:43The technology here is using the
  • 11:46inherent complementarity of DNA to
  • 11:48identify double strand consensus
  • 11:49so that even early mutations,
  • 11:51even founder mutations in the
  • 11:54amplification process can be
  • 11:56identified and and sort of deleted
  • 11:58out of the final analysis.
  • 12:00And so only true mutations,
  • 12:01even very rare mutations are
  • 12:03identified in this that has been
  • 12:05reported on several times and and
  • 12:07it moves the error rate from one in
  • 12:09100 and to 1 to one in 1000 to one
  • 12:11in 10,000 in some series of standard
  • 12:13next generation sequencing to
  • 12:15something like one in 10 to the 7th.
  • 12:17So it really adds quite a significant amount
  • 12:19of quite a significant amount of accuracy.
  • 12:23So how would we use this?
  • 12:24I think the next step for us was if
  • 12:26we're going to try to apply this
  • 12:29technology to a screen to a surveillance
  • 12:31program for bladder cancer patients,
  • 12:33what genes are we going to look for?
  • 12:36Luckily there have been a couple of
  • 12:38publicly available and published series
  • 12:40that have sequenced very large number
  • 12:41or not very large numbers but large
  • 12:43numbers of bladder cancer tumors.
  • 12:45So this is the TCGA which was
  • 12:47published and updated several
  • 12:49times most recently in 2018.
  • 12:51This is a series from Memorial Sloan
  • 12:54Kettering which has sequenced some
  • 12:56non muscle invasive tumors and some
  • 12:59of the frequently mutated genes were
  • 13:03sort of analyzed from these data
  • 13:05and we came up with a list of some
  • 13:07pretty frequent genes and you all will
  • 13:09recognize many of these genes here.
  • 13:11So the the basic approach that we took
  • 13:14to developing at least the preliminary
  • 13:16data for our our surveillance study was
  • 13:19patients present with a a mass or hematuria,
  • 13:23they undergo transurethral resection
  • 13:25of bladder tumor and then after
  • 13:27the diagnosis is made,
  • 13:28a urine sample is taken immediately or
  • 13:31soon after surgery they receive therapy
  • 13:34intravesically and then a urine sample
  • 13:36is taken after their therapy and then
  • 13:39patients undergo cystoscopic surveillance.
  • 13:41And the goal of this was
  • 13:43to just understand one,
  • 13:44are we able to reliably detect
  • 13:46tumor associated genes?
  • 13:47And two,
  • 13:48do the do the levels of these tumor
  • 13:50associated genes relate to their
  • 13:52risk of recurrence moving forward?
  • 13:54So I'm going to show you some examples.
  • 13:55This is quite early work,
  • 13:57but I'd like to show you some examples
  • 13:59that got us excited about this.
  • 14:00This is,
  • 14:01this is data from a 77 year old
  • 14:03male who presented to us with high
  • 14:06grade T1 bladder cancer with no CIS.
  • 14:09And this is just an analysis of
  • 14:12their their pre and post urine
  • 14:14for the 10 genes that we analyzed.
  • 14:17It's important to note here that
  • 14:18this is a tumor naive approach.
  • 14:19So we're not sequencing the initial
  • 14:21tumor and then going on to try
  • 14:24to detect these lesions.
  • 14:25This is an off the shelf approach
  • 14:28which I think is really useful for
  • 14:30scalability in a setting like this.
  • 14:33And what you can see is the blue is
  • 14:35the levels of of the variants detected
  • 14:37for the common genes that we're detecting.
  • 14:40The blue is before and the orange which
  • 14:43is really almost difficult to see,
  • 14:46is the after treatment.
  • 14:48And I'll just I'll just point get
  • 14:50your attention here to the Y axis
  • 14:52and you could see that these are
  • 14:54very very rare events.
  • 14:55These varying allele fractions
  • 14:57are really quite low.
  • 14:58You know a a common varying allele
  • 15:01fraction for previously reported
  • 15:03assays would be .3 to .5 and so.
  • 15:07So we're detecting really low levels
  • 15:08and what you can see here is that
  • 15:11there's clearly some dynamics at
  • 15:13play here and this is the total
  • 15:15variolial fraction.
  • 15:15And you can see that this patient had
  • 15:18a significant reduction in the total
  • 15:21amount of detectable tumor associated
  • 15:23DNA and they're now 18 months out,
  • 15:26no, no recurrence.
  • 15:27And you can sort of contrast
  • 15:29that with this patient who had
  • 15:31quite low levels at the beginning
  • 15:33after surveillance or excuse me,
  • 15:35after therapy,
  • 15:36we were able to detect low levels
  • 15:39of of stack two ERD 1A and quite
  • 15:41significant levels of PIC three CA.
  • 15:43And this is sort of demonstrated here
  • 15:46really driven by this PIC three CA mutation.
  • 15:49And ultimately the patient in
  • 15:51about 6 1/2 months later
  • 15:53was found to have a detectable
  • 15:56recurrence on cystoscopy.
  • 15:57Obviously these are specific examples that
  • 15:59sort of just demonstrated this was feasible.
  • 16:02And so we have now collected a total of 50
  • 16:04patients and are working through the data.
  • 16:07Now this is just a a heat map showing
  • 16:09some of their some of their demographic
  • 16:12and and pathologic data and approximately
  • 16:1520 of them have experienced recurrences.
  • 16:17And the the future of this is we're now
  • 16:22working through their their clinical
  • 16:24outcomes and trying to understand
  • 16:26if we can reliably identify a lead
  • 16:29time for identifying these patients.
  • 16:30And so the the future of this is
  • 16:33we're working through the data now
  • 16:34trying to develop a a reliable way
  • 16:37to detect treatment response,
  • 16:38identify recurrences before they're
  • 16:40grossly visible and maybe identify
  • 16:43patients for whom early switching
  • 16:45of therapy before a visible tumours
  • 16:47identified and maybe be able to spare
  • 16:50those patients subsequent surgery
  • 16:51for example if we switch early.
  • 16:53And I just wanted to highlight Jonathan
  • 16:55Wright who's a a bladder cancer surgeon
  • 16:57and researcher at the University
  • 16:59of Washington who's my mentor and
  • 17:01and and developed this project with
  • 17:02me and Scott Kennedy of course,
  • 17:04who was part of the development
  • 17:07of this technology.
  • 17:08And Doctor Blaha is a biostatistician
  • 17:10here at Yale who as soon as I got here,
  • 17:12I was lucky enough to get to meet
  • 17:14him and and recruited him to work
  • 17:15on this project with us.
  • 17:16So have been really looking forward
  • 17:19to this And as we analyze this data,
  • 17:21the goal will be to develop a a larger
  • 17:24study where we can collect ongoing
  • 17:26urines with every cystoscopy and
  • 17:29hopefully be able to follow and monitor
  • 17:32these patients more longitudinally.
  • 17:35I think that data will be richer.
  • 17:36So we're preparing these,
  • 17:38we're preparing this analysis
  • 17:39now for hopefully some extramural
  • 17:41funding in the spring.
  • 17:43The thing that we're all trying to
  • 17:45prevent is progression of these
  • 17:47patients because progressing to
  • 17:48muscle invasive bladder cancer is,
  • 17:50is almost,
  • 17:50it's an entirely really a different
  • 17:52kind of clinical entity and it's
  • 17:55it's has significantly poor outcomes
  • 17:57associated with it.
  • 17:58So this is that same paper that
  • 18:00I showed you earlier,
  • 18:00those same 400 patients and this is
  • 18:03now progression rather than recurrence
  • 18:05and you can see that low risk patients
  • 18:06have a pretty low risk of progression,
  • 18:08but high risk patients especially
  • 18:11do progress significantly and many
  • 18:13of them will progress to like I
  • 18:15say this muscle invasive bladder
  • 18:17cancer phase in invading the muscle
  • 18:20or fat or or or onward.
  • 18:22And for those patients therapy really
  • 18:24does transition standard of care therapy
  • 18:27really transitions from the bladder,
  • 18:29you know the the less invasive
  • 18:32endoscopic approaches to therapy too
  • 18:34often much more involved therapy.
  • 18:36So I'll I'll talk briefly about that.
  • 18:38The management of muscle invasive
  • 18:40bladder cancer generally falls into two
  • 18:42broad categories for patients who are
  • 18:44candidates for for radical treatment.
  • 18:46The 1st is radical surgery,
  • 18:49radical cystectomy with lymph
  • 18:51node dissection preceded by
  • 18:53neoadjuvant chemotherapy.
  • 18:54And the other is what we call
  • 18:55trimodal therapy, which is the
  • 18:57first mode is maximal endoscopic
  • 19:00resection followed by chemo radiation.
  • 19:02So those are the three modes outcomes
  • 19:04are significantly poorer for patients
  • 19:06with muscle invasive bladder cancer.
  • 19:08This is a study that looked at data
  • 19:10from from the VA of all places.
  • 19:12These are Vinci data from the University
  • 19:14of California in San Diego and these
  • 19:16are multiple thousands of patients.
  • 19:18And you could see overall survival
  • 19:20plots for radical cystectomy with chemo,
  • 19:22radical cystectomy without neoadjuvant
  • 19:24chemotherapy are demonstrated here in
  • 19:27the in the dashed orange and the dark
  • 19:29blue line and trimodal therapy with
  • 19:31preferred chemotherapy regimens up here.
  • 19:34And you can see that survival is at
  • 19:36at best at least from these real world
  • 19:39data and admittedly somewhat sicker
  • 19:41patients are somewhere in the 40 to
  • 19:435545 to 55% range in the five year
  • 19:46survival data that they report here.
  • 19:47This varies a little bit based on
  • 19:49you know some other factors,
  • 19:50but that's what's reported here.
  • 19:53One thing to note is that trimodal
  • 19:55therapy with non preferred regimens
  • 19:56in these data show a significantly
  • 19:59poorer outcome that they were able to
  • 20:01detect a statistically significant.
  • 20:03So for for many decades now management of
  • 20:05muscle invasive bladder cancer has this this.
  • 20:08The central feature of it in the United
  • 20:10States at least has been radical
  • 20:11cystectomy with lymph node dissection.
  • 20:14We have learned in the last several
  • 20:16decades that chemotherapy prior to radical
  • 20:18surgery doesn't prove overall survival.
  • 20:21This was first shown in with level
  • 20:23one evidence in a study in 2003 which
  • 20:25administered M VAC prior to radical
  • 20:28cystectomy and locally advanced muscle
  • 20:31invasive bladder cancer and demonstrated
  • 20:33about a 5% overall survival benefit.
  • 20:35So you can see that's that top line
  • 20:38here and and the the charts separate.
  • 20:41Despite these data,
  • 20:42they're good real world data that
  • 20:44we do not use chemotherapy in the
  • 20:47neoadjuvant setting very frequently
  • 20:49or as frequently as we should.
  • 20:51So this is a study looking at SEER data,
  • 20:53It's now a little bit old 'cause it stops in.
  • 20:55It stopped in 2011 and we could see
  • 20:57sort of a trend upwards in the use
  • 20:59of neoadjuvant chemotherapy with
  • 21:01muscle invasive bladder cancer,
  • 21:02but it peaks at around in this
  • 21:04data here about around 23 to 25%.
  • 21:08More recent data using the National
  • 21:11Cancer Database reported that while
  • 21:13again it's still increasing the
  • 21:14use of neoadjuvant chemotherapy,
  • 21:16the highest that they were able
  • 21:17to detect was in the 35% range.
  • 21:19And and so we're not using it nearly
  • 21:23as frequently as as we could be.
  • 21:26And this is a potential real
  • 21:29opportunity for improving survival
  • 21:30without major new interventions,
  • 21:32without major new,
  • 21:34you know all of the new fancy drugs
  • 21:36that we have.
  • 21:37This is tried and true and and we're just
  • 21:40are not very effective at implementing it.
  • 21:42What about radiation?
  • 21:44And similarly there is high quality
  • 21:46data that suggests that chemotherapy
  • 21:49with radiation does improve outcomes
  • 21:52for muscle invasive bladder cancer.
  • 21:54This is the study out of
  • 21:55from 2012 James ET al.
  • 21:57But there's several others that have
  • 21:59also demonstrated that chemotherapy
  • 22:01administered with radiotherapy improves
  • 22:03at least local regional control.
  • 22:05And this is an overall survival plot
  • 22:07that wasn't statistically significant.
  • 22:08But you could see that chemoradiotherapy
  • 22:10out outperforms radiotherapy alone
  • 22:12at least in local regional control,
  • 22:14if not both.
  • 22:16Are we doing better with administering
  • 22:18chemotherapy with radiation?
  • 22:20We're doing better.
  • 22:22We looked at this at using the SEER,
  • 22:25the SEER Medicare data set.
  • 22:27We looked at a cohort of about
  • 22:292200 patients and sort of the
  • 22:32kind of summary of this data,
  • 22:34of the data that we found is that
  • 22:35in 2200 patients with muscle
  • 22:37invasive bladder cancer with
  • 22:39undergoing curative intent radiation,
  • 22:41approximately 40% of patients do not
  • 22:43receive any radiotherapy in in the
  • 22:46time that they're receiving radiation.
  • 22:48So again a significant opportunity
  • 22:50for improving,
  • 22:51improving care for these folks.
  • 22:53Similarly many about 20 to 25% of
  • 22:57patients are receiving what we would
  • 22:59call non preferred chemotherapeutic
  • 23:01regimens like carboplatin or dosataxel alone.
  • 23:04And these are therapies that that we
  • 23:07there are good data that they do not
  • 23:09perform quite as well as cisplatin
  • 23:11for example in in the setting and so.
  • 23:14So again these are this is just an
  • 23:16opportunity for for improvement in
  • 23:18patients undergoing radiation therapy.
  • 23:20This is a chart over time.
  • 23:22We're not.
  • 23:22We're getting better at
  • 23:24administering therapy,
  • 23:24but it's not significantly better
  • 23:26in terms of preferred regimens and
  • 23:28we did detect the difference in
  • 23:30overall survival in these patients,
  • 23:31although we should note that I should
  • 23:33note that level one evidence doesn't
  • 23:35demonstrate a clear survival benefit,
  • 23:37mostly local, regional,
  • 23:38but we did see an overall survival
  • 23:40benefit in these retrospective data
  • 23:44for patients undergoing bladder
  • 23:45sparing therapy or radical cystectomy
  • 23:47for muscle invasive bladder cancer.
  • 23:49The goal would be to also expand the
  • 23:51the idea of does urinary DNA play a role
  • 23:54in these for these patients as well,
  • 23:56establishing the utility of urinary
  • 23:58DNA as a biomarker in muscle invasive
  • 24:00bladder cancer could play a role
  • 24:02in predicting complete response
  • 24:04after neoadjuvant chemotherapy,
  • 24:05which I didn't show you data for,
  • 24:07but is known to be a good marker for
  • 24:09a good outcome for these patients.
  • 24:11And there's more and more interest in
  • 24:13trying to avoid radical surgery in
  • 24:15patients that respond to neoadjuvant
  • 24:17chemotherapy.
  • 24:17For those that are not responding well,
  • 24:19there's a question of would they
  • 24:21benefit from expedited surgery or
  • 24:23switching therapy and we don't know
  • 24:24the answer to that because we've not
  • 24:26had a good marker for assessing it.
  • 24:29Currently we just use cross-sectional imaging
  • 24:31which has a lot of limitations unfortunately.
  • 24:34And then of course for those
  • 24:36who retain their bladder,
  • 24:36there's a question of whether or not
  • 24:38a highly sensitive marker could be
  • 24:40useful for monitoring and surveilling
  • 24:42patients that underwent trimodal therapy.
  • 24:44And so these are questions that we
  • 24:46hope to interrogate in the future.
  • 24:48We have about 20 patients that
  • 24:50have muscle invasive bladder cancer
  • 24:51before and after chemotherapy that
  • 24:53have undergone radical cystectomy.
  • 24:55So we're hoping to look into that at
  • 24:57a small scale in the near future.
  • 25:00And ultimately muscle that urinary
  • 25:02DNA biomarker has to be integrated
  • 25:05with broader with other biomarkers
  • 25:07that are in development.
  • 25:09So that would be another goal is
  • 25:11to understand how it relates to
  • 25:13other biomarkers.
  • 25:14So I did want to talk about one other
  • 25:16biomarker which was not probably new
  • 25:17to to most of you as it's made-up quite
  • 25:19a splash in a lot of different cancers.
  • 25:21But I'm going to talk about its role
  • 25:24in bladder cancer is circulating
  • 25:25tumor DNA in in bladder cancer.
  • 25:28This is also a very exciting area of
  • 25:31our in this field in bladder cancer
  • 25:34and it sort of started at least
  • 25:36has come to the forefront in the
  • 25:38setting of another clinical trial.
  • 25:39This was a trial published in 2021,
  • 25:42the use of adjuvant A tezalizumab
  • 25:44for folks who have bladder cancer
  • 25:47to try to reduce basically increased
  • 25:50disease free survival in these folks.
  • 25:52So these are high risk folks that
  • 25:54had disease on final pathology after
  • 25:56cystectomy and they were randomized
  • 25:58to receipt the receipt of a checkpoint
  • 26:01inhibitor at tesolizumab and the
  • 26:03this trial unfortunately ultimately
  • 26:04was a negative trial didn't show an
  • 26:07improvement in disease free survival.
  • 26:09But one subsequent study that resulted
  • 26:12from analysis of these data was re
  • 26:15analyzing the clinical data based
  • 26:17on substrata for circulating tumor
  • 26:19DNA positivity.
  • 26:20And so I'm going to show you some of
  • 26:22the data from this paper published
  • 26:23in in in Nature 2021, May 2021.
  • 26:27You can see here that the data are
  • 26:31stratified by observation in the
  • 26:33orange versus the blue receipt of
  • 26:35a tesolizumab
  • 26:36in the adjuvant setting and circulating
  • 26:38tumor DNA negative up top and
  • 26:41circulating tumor DNA positive below.
  • 26:43And one thing that's clear is that
  • 26:45CT DNA this is a tumor informed
  • 26:46biomarker in this setting is
  • 26:48quite prognostic if nothing else.
  • 26:50It clearly distinguishes patients
  • 26:51who have poorer outcomes from
  • 26:53those who do better and it reflect,
  • 26:55it seems to reflect some residual disease
  • 26:59after cystectomy which is pretty intuitive.
  • 27:01But one of the signals that's really
  • 27:04important here is that the folks who
  • 27:06received atesalizumab with CTDNA
  • 27:08positivity clearly experienced the
  • 27:10benefit in disease free survival
  • 27:12based on this reanalysis and this
  • 27:14is an overall survival reanalysis.
  • 27:15Again, this is not a randomized trial.
  • 27:17This is, this is a reinterpretation
  • 27:20from this invigor 10 study.
  • 27:23And what you can see here again is
  • 27:25that is that adjuvant therapy for folks
  • 27:28who have detectable circulating tumor
  • 27:31DNA is is really seems to reflect
  • 27:34a benefit for adjuvant therapy.
  • 27:36It's pretty exciting because we know
  • 27:39that with adjuvant therapy we are
  • 27:41we're delivering a lot of therapy to
  • 27:44some patients who don't have any cancer.
  • 27:46These are all these patients have
  • 27:47no evidence of disease at the time,
  • 27:49they just have a risk of recurrence.
  • 27:51And so the idea of being able to parse
  • 27:54out residual disease and hopefully
  • 27:56make sort of the idea of adjuvant
  • 27:59therapy a little bit to move past
  • 28:01that would is a really exciting
  • 28:02thing I think for patients,
  • 28:03hopefully minimizing over
  • 28:05treatment of patients.
  • 28:07These results have led to the
  • 28:09development of a new study of Vigor 11,
  • 28:11which is a a biomarker driven randomized
  • 28:14trial to administer atizolizumab
  • 28:16for CT DNA positive patients.
  • 28:19So to try to validate these
  • 28:21in a prospective fashion,
  • 28:22I mean this is not,
  • 28:23I know this is a busy slide,
  • 28:24but this is not meant to be read just as
  • 28:27a reference for anyone who's interested.
  • 28:29So this is this trial's ongoing and it's,
  • 28:30it's very exciting and many of
  • 28:32you who treat other cancers will
  • 28:34know that they're really good data
  • 28:36for similar biomarkers,
  • 28:37circulating tumor biomarkers now
  • 28:39in colorectal cancer and lung
  • 28:42cancer and several other cancers.
  • 28:43This trial has a disease free survival
  • 28:46primary endpoint and I I do want to
  • 28:48touch on that a little bit because
  • 28:51the right way to answer this question
  • 28:53is a is a prospective clinical trial
  • 28:56that is the gold standard therapy
  • 28:58and excuse me gold standard approach
  • 28:59to answering a question like a
  • 29:02therapeutic intervention like this.
  • 29:03But clinical trials as many of you
  • 29:05know have significant challenges
  • 29:06and are difficult to conduct.
  • 29:08They're quite resource intensive
  • 29:10and they do face challenges for
  • 29:13accrual of patients and and and
  • 29:16completion within certain time points.
  • 29:19And so I did want to talk about one
  • 29:22particular challenge with these is
  • 29:24endpoint selection and clinical trials.
  • 29:26So surrogate endpoints have been a
  • 29:28a bit of a topic in clinical trial
  • 29:31design and implementation science over
  • 29:33the last 10-15 years or so at least.
  • 29:36And and just to define the term,
  • 29:38surrogate endpoints are are outcomes
  • 29:40that themselves are not known to
  • 29:43have a clinical benefit but are
  • 29:45thought or known to predict an
  • 29:47outcome that has a clinical benefit.
  • 29:49So they do not themselves carry
  • 29:52a lot of meaning.
  • 29:54They carry meaning because we think they're
  • 29:56related to something that carries meaning,
  • 29:57does that pretty, pretty reasonable.
  • 30:00So they're used as a substitute and
  • 30:02they're thought to predict clinical
  • 30:04endpoints and they're increasing in use,
  • 30:08they're becoming more and more frequent.
  • 30:09I really like this study from JAMA
  • 30:11Oncology which tracks the proportion
  • 30:13of randomized clinical trials and
  • 30:15these are endpoints that are used in
  • 30:18various clinical trials over time.
  • 30:20And you could see that overall survival's
  • 30:22the most common clinical endpoint.
  • 30:24And then you could see that it's
  • 30:25kind of become falling out of
  • 30:27favour in randomized trials.
  • 30:28While progression free survival for
  • 30:30example in is becoming more and more
  • 30:32popular in randomized clinical trials.
  • 30:34And I I think not UN coincidentally
  • 30:36industry funding is also significantly
  • 30:38increasing in these in these studies and
  • 30:40what the study concludes is that the use
  • 30:42of progression free survival is increasing.
  • 30:45Progression free survival is more likely
  • 30:48to be a positive trial if you use PFS
  • 30:50rather than OS in a clinical trial.
  • 30:53And and and it's becoming like I say it's
  • 30:57it's become the the major most common
  • 31:00endpoint used in clinical trials now.
  • 31:03So why should be should we be worried
  • 31:06or cautious about this trend?
  • 31:08Well,
  • 31:08the assumption when a surrogate
  • 31:11endpoint is used is that there's some
  • 31:13cause for the patient's illness,
  • 31:14you know their malignancy.
  • 31:16We detect some surrogate endpoint like
  • 31:19progression free survival and that in
  • 31:21turn leads to a clinical endpoint like
  • 31:24there's the patient's overall survival.
  • 31:26But as we all know that 'cause
  • 31:28this cause causality scheme,
  • 31:30this causation scheme is not always
  • 31:32quite as direct cause can be related to
  • 31:35the endpoint in multiple different ways.
  • 31:37And so we really have to be kind of
  • 31:39cautious about assuming this level
  • 31:41A and there are ways to validate
  • 31:43surrogate endpoints.
  • 31:44People have done this in the past
  • 31:46where they we can look at clinical
  • 31:48data and try to make sure to that
  • 31:50the surrogate endpoint is truly
  • 31:52causally linked or significantly
  • 31:54predictive of a clinical endpoint.
  • 31:55And the answer seems to be it kind
  • 31:57of varies whether or not a surrogate
  • 31:59endpoint is linked to a clinical endpoint.
  • 32:02It varies on,
  • 32:03it varies based on the cancer and
  • 32:05the specific clinical details.
  • 32:07So this is an another paper that looked
  • 32:09at the meta analysis of surrogate
  • 32:11endpoints in various trials and it's
  • 32:13not always the case that they do
  • 32:15predict the clinical endpoint with
  • 32:18with reliability. This is a big table.
  • 32:21We don't,
  • 32:21I'm not going to go through all of that.
  • 32:23This is not again not meant to be read,
  • 32:24but just to say that this meta analysis
  • 32:27looked at multiple various trials
  • 32:28in the past in areas of medicine
  • 32:30where we use the surrogate endpoint
  • 32:32and we found that
  • 32:33when the clinical endpoint was measured,
  • 32:35we really did ultimately find that
  • 32:37they were not predictive of each other.
  • 32:40And I think one really telling
  • 32:42example of this is the cast trials.
  • 32:44This was a trial in cardiology which
  • 32:46looked at patients who would experience
  • 32:48myocardial infarctions in the past
  • 32:50who had had ventric experienced
  • 32:53intermittent ventricular arrhythmia.
  • 32:54And the common thought prior to this
  • 32:57publication of the study in 1991
  • 32:59was medications anti arrhythmics
  • 33:02that decrease ventricular arrhythmia
  • 33:04would also decrease the risk of
  • 33:06sudden cardiac death in patients.
  • 33:07And so these were quite commonly
  • 33:09used at the time until a a pretty
  • 33:11heroic I think and really brave
  • 33:13study was performed this CAST trial
  • 33:15it was published in 1991 and what
  • 33:18they found was pretty striking.
  • 33:21Patients who received placebo
  • 33:22did significantly better than
  • 33:24patients who did who received anti
  • 33:26arrhythmics in the post MI period.
  • 33:28In fact mortality was was almost
  • 33:30double in the patients who
  • 33:32received the intervention arm.
  • 33:34And in you know,
  • 33:34as I was learning about this trial,
  • 33:36I read an editorial by a cardiologist
  • 33:38who was reflecting on this and said,
  • 33:40you know most Americans can
  • 33:41remember where they were when
  • 33:43President Kennedy was assassinated.
  • 33:44And every cardiologist can remember
  • 33:46where they were when the cast trial
  • 33:48was published because it was really
  • 33:50striking and and and it sort of
  • 33:52highlights I think the importance of
  • 33:54validating any assumed benefit from
  • 33:57clinical from surrogate endpoints.
  • 33:59So people have tried to do this
  • 34:00and like I say it kind of varies.
  • 34:02So this is again a big trial is a big
  • 34:04table not again not meant to be read here,
  • 34:06but what you can see is that
  • 34:08whether a surrogate endpoint is
  • 34:10helpful depends on the setting.
  • 34:11So this multiple studies have shown that
  • 34:14progression free survival and advanced
  • 34:16through metastatic colorectal cancer
  • 34:17is a reasonable surrogate for overall
  • 34:20survival in in many of these trials.
  • 34:22Whereas in breast cancer it seems to
  • 34:23not be a a good surrogate and and
  • 34:26it has to be done on an individual
  • 34:29basis for each cancer for each stage.
  • 34:32It's really quite quite important work
  • 34:34because we rely on them significantly.
  • 34:36This is a paper demonstrating
  • 34:37how much we rely on them.
  • 34:38This is a paper published in JAMA in
  • 34:412020 and what you what they demonstrate
  • 34:43by evaluating FDA acceptance based
  • 34:45on surrogate endpoints is that the
  • 34:47use of surrogate endpoints is is
  • 34:49increasing like we talked about
  • 34:51and 61% of new medication of of
  • 34:54medications that are approved based
  • 34:56on surrogate endpoints are based
  • 34:58on endpoints that have not been
  • 35:00validated or lack correlation studies.
  • 35:03So we really don't know if the surrogate
  • 35:05is related to the endpoint we really
  • 35:06care about which is making patients
  • 35:08live longer or making patients live happier,
  • 35:10healthier or you know lives that
  • 35:12are have better quality of life.
  • 35:14I guess 61% of the time we don't
  • 35:17have a a link,
  • 35:1916% of the time we use them
  • 35:21despite data demonstrating
  • 35:22a poor connect, a poor link between
  • 35:24surrogate endpoints and overall survival.
  • 35:26And only 5% of the time is there
  • 35:29a established high correlation.
  • 35:32There is a a post marketing requirement
  • 35:35for medications that are approved based
  • 35:37on surrogate endpoints and this paper
  • 35:39demonstrates that upwards of 1/3 of them,
  • 35:41third of trials don't report
  • 35:43within the time period.
  • 35:44So in bladder cancer,
  • 35:45we do use surrogate endpoints quite a bit.
  • 35:48We rely on them really heavily.
  • 35:51Here's an example from bladder cancer,
  • 35:52which we won't go into a whole lot,
  • 35:54but this is a paper published in 2017,
  • 35:56which is a single arm phase two
  • 35:58trial that evaluated atezalizumab
  • 36:00in a very difficult population.
  • 36:02This is cisplatin ineligible
  • 36:04patients in the second line setting.
  • 36:06This was about 119 patients were enrolled,
  • 36:09102 of them discontinued therapy
  • 36:11because of progression and objective
  • 36:13response rates were in 23% or so at a
  • 36:15median follow up of about 17 months.
  • 36:17So this wasn't a home run thing,
  • 36:19This wasn't, this was,
  • 36:20this was a a signal and a difficult
  • 36:23population and it resulted in
  • 36:25accelerated approval by the FDA
  • 36:27for atizalizumab in this setting.
  • 36:29And this is just as an aside,
  • 36:31multiple cost effectiveness analysis
  • 36:33of this drug show that it it's
  • 36:36really quite costly to administer,
  • 36:38you know,
  • 36:39upwards of $400,000 per quality adjusted
  • 36:42life here for a tesolizumab in this setting.
  • 36:45And we learned about five years
  • 36:47later that it was withdrawn.
  • 36:49And it was withdrawn because the final
  • 36:51data reported out that overall survival
  • 36:53benefits were not detected in this setting.
  • 36:56Now some might say,
  • 36:56all right, well that's,
  • 36:57that's, that's showbiz.
  • 36:58That's the cost of it.
  • 36:59You know sometimes you approve drugs
  • 37:01and you give patients drugs that
  • 37:03don't do that much benefit for them,
  • 37:05but at least they get them faster.
  • 37:07You know and what I would say is
  • 37:09that the the effect is can often be
  • 37:11more widespread than than we really
  • 37:13think about at least than than I
  • 37:14think about this is a a paper that
  • 37:19was published by the folks at the
  • 37:21University of Pennsylvania which
  • 37:22evaluated the Flatiron database.
  • 37:24So a kind of a,
  • 37:25a large national database for patients
  • 37:28who are exposed to cancer medications
  • 37:32that were then ultimately withdrawn.
  • 37:34And what they find is that it takes
  • 37:37about 46 months from accelerated
  • 37:39approval to withdrawal.
  • 37:40So we don't get, it's not a huge,
  • 37:42huge time period,
  • 37:43but it does result in approximately
  • 37:451/4 of patients with cancer in
  • 37:47the United States getting exposure
  • 37:49to therapy that ultimately is
  • 37:51demonstrated to not be beneficial.
  • 37:53And in bladder cancer, it's about 22%.
  • 37:56So it's a significant number of patients.
  • 37:58And this is an interesting editorial.
  • 38:00This is an editorial.
  • 38:01It's it's a letter that talks about
  • 38:04what the global impact of this
  • 38:06practice is for other countries,
  • 38:09especially low and middle income countries.
  • 38:12And here the the group Bashal Gawali's
  • 38:16a medical oncologist who writes and
  • 38:18thinks a lot about this problem.
  • 38:20And he highlights that often times
  • 38:23other countries,
  • 38:24especially low and middle income countries,
  • 38:26will approve medications
  • 38:28based on FDA recommendations.
  • 38:30And so the FDA approves these
  • 38:32medications conditionally,
  • 38:33they're accepted as FDA approved
  • 38:35medications in other countries and then
  • 38:38if they're withdrawn in the United States,
  • 38:39they continue to be approved in these
  • 38:41other countries and in fact are often
  • 38:44continue to be marketed in these other
  • 38:46countries for the indications for which
  • 38:48they're withdrawn here in the United States.
  • 38:51And that's a really striking
  • 38:53fact that I'm gonna,
  • 38:54these are long quotes,
  • 38:55but I think it's worth just
  • 38:57looking at this is from the paper.
  • 38:58Thus once a drug is approved by the FDA
  • 39:00via the accelerated approval pathway,
  • 39:03the drug can be marketed and
  • 39:04promoted in low middle income
  • 39:06countries as an FDA approved drug.
  • 39:09And then confirmatory trials confirm
  • 39:10they're negative and these are not
  • 39:12communicated to those same countries.
  • 39:14And this is an example,
  • 39:16example again from in this
  • 39:17case a tezalizumab,
  • 39:18which I've highlighted multiple Times Now,
  • 39:21but immediately after the
  • 39:23drugs withdraw from the market,
  • 39:24the company issued letters in this
  • 39:26case to India stating that the
  • 39:28Tezalism A tezalizumab would continue
  • 39:30to be marketed in that country.
  • 39:32And it's not just this country or
  • 39:34this medication or this company,
  • 39:35but this is they show nine other
  • 39:37examples in this in this paper.
  • 39:39So my point in all of this is that this
  • 39:41is a practice that has some real downsides,
  • 39:44should be really thought about
  • 39:45carefully and and of course many people
  • 39:47are thinking about it carefully,
  • 39:49but has does have global implications.
  • 39:51We wanted to look at what some
  • 39:53of these surrogate endpoints,
  • 39:54how they behave in bladder cancer because
  • 39:56again that's that's been my main interest.
  • 39:59And so we took a look at this.
  • 40:02We looked at the relationship
  • 40:04between commonly used surrogate
  • 40:05endpoints and overall survival
  • 40:06in metastatic bladder cancer.
  • 40:08And the methods were pretty straightforward.
  • 40:10We just did a review of clinical
  • 40:12trials in bladder cancer.
  • 40:14We looked at progression free survival
  • 40:16and response rate and some other
  • 40:18information and determined determined how
  • 40:21effectively it predicts overall survival.
  • 40:24So this is a big table.
  • 40:26We looked at all trials which were
  • 40:2762 trials and split them up into
  • 40:30immune checkpoint inhibitors and
  • 40:32non immune checkpoint inhibitors and
  • 40:34we can skip through some of this.
  • 40:35But you can see that the immune checkpoint
  • 40:38inhibition trials were performed,
  • 40:39the median year of publication was
  • 40:42later than the than the chemotherapy
  • 40:44trials and and tended to have much
  • 40:46larger ends compared to checkpoint
  • 40:48non checkpoint inhibitor trials,
  • 40:50which we can talk about why that matters
  • 40:53and we reported this earlier this year.
  • 40:55The first thing you can do to try to
  • 40:58understand sort of how well these two,
  • 40:59a surrogate endpoint and a clinical
  • 41:02endpoint relate is you can ask well
  • 41:04what is the R-squared coefficient for
  • 41:06the hazard ratio for progression free
  • 41:09survival compared to overall survival.
  • 41:11And you you can see here that
  • 41:12in this case
  • 41:13it was pretty reasonable,
  • 41:14it was about .6.
  • 41:15So it's not a strong predictor,
  • 41:17but it's not a strongly correlated,
  • 41:20but it's it's I would say
  • 41:22moderately correlated.
  • 41:221 can ask a second question,
  • 41:24which is what it's a metric called
  • 41:28surrogate threshold effect.
  • 41:29And what surrogate threshold effect is,
  • 41:31is what result from the hazard
  • 41:36ratio of progression free survival
  • 41:37do you need to see to give you
  • 41:4095% confidence that it's going to
  • 41:42reflect an overall survival benefit.
  • 41:44So you observe the surrogate and
  • 41:46it give and it gives you with
  • 41:4895% confidence an OS benefit.
  • 41:50And So what would that number be?
  • 41:51And so that turns out to be pretty,
  • 41:53again, pretty straightforward
  • 41:54to actually calculate.
  • 41:55The first thing you do is you get 95%
  • 41:57predictive sort of confidence interval
  • 42:01around your correlation line and
  • 42:03then you want a value that is below 1.
  • 42:06And so you see what hazard ratio
  • 42:09that for progression free survival
  • 42:11that number intersects at.
  • 42:13And for bladder cancer,
  • 42:14we found that that R-squared was .6 and
  • 42:17the surrogate threshold effect was .41,
  • 42:19which means if you want 95% confidence that
  • 42:22the OS is improved without observing it,
  • 42:25you should,
  • 42:26you should see APFS of .41.
  • 42:28It doesn't mean that you need to have
  • 42:31a .41 PFS to have an OS benefit.
  • 42:34It just means that if you're not
  • 42:35going to measure OS directly and
  • 42:37you want that confidence you that's
  • 42:39that's the value you need to get.
  • 42:41We did the same for objective
  • 42:43response rate here.
  • 42:44And what you can see is that
  • 42:46for for hazard ratio,
  • 42:47for objective response rate,
  • 42:48it actually never hits that
  • 42:5095% confidence interval line.
  • 42:51So for that our R-squared was .03 and
  • 42:55our surrogate threshold effect was not,
  • 42:57was not actually not reached,
  • 42:59it's it wasn't calculable.
  • 43:00And so from this study we sort of
  • 43:03conclude that you know surrogate
  • 43:05surrogate endpoints are poorly
  • 43:07characterized in bladder cancer and
  • 43:08there's sort of a weak to moderate
  • 43:10correlation for progression free survival,
  • 43:12but really quite a poor correlation
  • 43:14for response rate or tumor shrinkage
  • 43:17on cross-sectional imaging.
  • 43:18And so we really should be
  • 43:21deemphasizing response rate we
  • 43:23conclude as a primary endpoint when
  • 43:25possible in metastatic bladder
  • 43:26cancer clinical trials more broadly
  • 43:30I think outside of bladder cancer
  • 43:31sort of zooming out again you know
  • 43:33the question of clinical trials,
  • 43:35we've seen this trend of clinical
  • 43:36trials changing pretty significantly
  • 43:38and there it's responding to a
  • 43:39lot of pressures and you know I'm
  • 43:40not under the impression that this
  • 43:42is an easy thing to do.
  • 43:44But when you think about the major
  • 43:46stakeholders in clinical trials
  • 43:47that are involved in bringing a
  • 43:48new medication to patients,
  • 43:50you know you think about the FDA,
  • 43:53you think about the Pharmaceutical industry,
  • 43:55you think about the patients
  • 43:56themselves and and patient advocacy
  • 43:58groups and then physicians.
  • 44:01And you know I'm happy to have
  • 44:02a longer discussion about this
  • 44:03if people are interested.
  • 44:05But I think that if you look at each of
  • 44:07these factors individually,
  • 44:08I think that the onus really is and
  • 44:11has to be on physicians to protect the
  • 44:14scientific integrity of clinical trials
  • 44:16and make sure that we're we're really
  • 44:18cautious about some of these things.
  • 44:20I think I think while all of these
  • 44:24other factors are key players in
  • 44:26in bringing medications to patients
  • 44:29really we're we're we are the ones
  • 44:30who really are I think best equipped
  • 44:32and and the onus really falls on us to
  • 44:34think about how to do this and protect
  • 44:36patient clinical trial integrity.
  • 44:38So this is the thing I'm interested
  • 44:40in and I'd love to you know many,
  • 44:42many of you have have thought about this
  • 44:44of course and and and a lot of academic
  • 44:46scholarship about this here at Yale.
  • 44:47One of the first things I did when
  • 44:49coming here is I connected with the
  • 44:51copper Center and contacted Mike Leapin
  • 44:53and Carrie Gross and reached out to
  • 44:55him because Carrie Gross has of course
  • 44:56written quite a bit about this and
  • 44:58thought deeply about a lot of these problems.
  • 45:00And so we have started to work
  • 45:02together a little bit on,
  • 45:03on some projects that look at
  • 45:06topics related to this.
  • 45:07And I also wanted to highlight one other
  • 45:09organization with many of the folks
  • 45:11that I referenced in these other papers,
  • 45:13Christopher Booth and Bishal
  • 45:14who's who's also a part of this.
  • 45:16And this isn't not an organization
  • 45:19I'm I'm a part of,
  • 45:20but they did start up a program
  • 45:22called Common Sense Oncology and
  • 45:24it's for physicians primarily who
  • 45:26are interested in taking on the the,
  • 45:29the role of thinking about this
  • 45:32and and moving, moving.
  • 45:34I would say the conversation to
  • 45:37talking about endpoint design,
  • 45:38the appropriateness of crossover and
  • 45:41clinical trials and and some of the
  • 45:44sort of some of the implementation
  • 45:46signs around clinical trials.
  • 45:48So just wanted to make people aware of that.
  • 45:51So in conclusion,
  • 45:52there's a lot of important work
  • 45:53to be done in bladder cancer as I
  • 45:56hope I've highlighted,
  • 45:56there's a lot of room to
  • 45:58continue to improve patient care.
  • 46:00I think that urinary DNA has has
  • 46:02a potential role in that future.
  • 46:04We have very early data and there's
  • 46:06some more robust data out there and
  • 46:08we're hoping to continue to work and
  • 46:10validate this as a biomarker in in
  • 46:11both early and late bladder cancer.
  • 46:14We need to be giving more chemotherapy
  • 46:16and bladder cancer.
  • 46:17We need to be giving more chemotherapy
  • 46:19in for patients undergoing surgery
  • 46:21and for folks undergoing radiation.
  • 46:23And I hope I I showed you some
  • 46:24data to convince you of that.
  • 46:26And finally clinical trials are key,
  • 46:29they're really important for patients
  • 46:30and and especially in bladder cancer.
  • 46:32We've seen tremendous,
  • 46:33tremendous work and really
  • 46:35exciting data of late especially.
  • 46:37But I think it is the role of
  • 46:40physicians really to ensure the
  • 46:42integrity of the of the scientific
  • 46:43endeavour that is a clinical trial
  • 46:45and design answers that really focus
  • 46:47on questions that are meaningful
  • 46:49for patients making them live
  • 46:50longer, improving their quality of life.
  • 46:54Thank you very much for your attention.
  • 46:55I'm happy to to chat a bit
  • 46:57and answer some questions.
  • 47:04Thank you Doctor Gatley.
  • 47:07Any questions audience?
  • 47:09The Internet very good,
  • 47:12maybe I will set up for questions.
  • 47:14So it's very beautiful
  • 47:15talk about the urine DNA,
  • 47:16how it's being used for non most
  • 47:18invasive bladder cancer and some work
  • 47:19you did in in terms of visibility
  • 47:21and you also mentioned about the the
  • 47:23low sensitivity and the low yield,
  • 47:25you know where it sort of makes sense
  • 47:26because it's really superficial disease,
  • 47:28very low volume of disease.
  • 47:29I wonder if we can share any
  • 47:31data or any insights on using
  • 47:32that in most invasive disease,
  • 47:34maybe this is better setting
  • 47:35to use that in most invasive
  • 47:37setting how we can monitor,
  • 47:38you know,
  • 47:39treatment response from your agent chemo
  • 47:40or even chemo radiotherapy as well.
  • 47:42Yeah,
  • 47:44yeah, there's a couple of questions.
  • 47:46I think when when asking what its
  • 47:49role would what a marker like this,
  • 47:51what role it would play in
  • 47:53muscle invasive bladder cancer,
  • 47:54I think the first obvious thing
  • 47:56for me would be to ask for folks
  • 47:58who receive chemotherapy and
  • 47:59have a really strong response.
  • 48:02Can we identify patients who are
  • 48:05completely responded to chemotherapy
  • 48:07and we can maybe de escalate their
  • 48:09therapy and identify them for
  • 48:11not having radical cystectomy.
  • 48:13Right now people try to do this
  • 48:16with cytology or bladder biopsies
  • 48:18and it has reasonable sensitivities
  • 48:20again somewhere in the 80% or so.
  • 48:23But if you're going to forego cystectomy,
  • 48:26you would want to be really,
  • 48:27really sure that there is no residual
  • 48:30cancer because being wrong about that
  • 48:32has a real high cost I think for patients.
  • 48:35And so I think that that's one real
  • 48:37exciting place and I don't have any
  • 48:39data here to show you except to say
  • 48:41that we can definitely detect tumor
  • 48:43associated DNA before chemotherapy,
  • 48:45you know after resection but
  • 48:48before chemotherapy.
  • 48:49So those dynamics are at play and
  • 48:51we have seen decreases in that
  • 48:53number with chemotherapy,
  • 48:54but we've only,
  • 48:55I've only looked at about 10 patients or so.
  • 48:57So not enough to be able to say
  • 49:00yeah we can start eliminating
  • 49:01cystectomy in some of those,
  • 49:03but that I think that that
  • 49:04would be a key question.
  • 49:06Thank
  • 49:06you. We should definitely
  • 49:07do this study here as well.
  • 49:09Any other questions,
  • 49:12questions, so maybe I can ask
  • 49:14another question about this.
  • 49:15So with that design,
  • 49:17what would be the adequate endpoints?
  • 49:20You know you talked about
  • 49:21endpoints in metastatic setting.
  • 49:23You know we talked about the endpoints
  • 49:24in non most invasive disease,
  • 49:26most invasive disease.
  • 49:27With the introduction of
  • 49:29this novel biomarkers,
  • 49:30What do you think will be adequate
  • 49:32endpoints in studies like that?
  • 49:35To start a study like that would have to,
  • 49:37would have to be an I think a
  • 49:39prospective observational study.
  • 49:41I think I would start with urine
  • 49:43collections data analysis and then
  • 49:45undergoing radical cystectomy.
  • 49:47And the main endpoint I'd look for
  • 49:48is pathologic complete response
  • 49:50and the reason I choose that is
  • 49:51because I didn't share it here,
  • 49:53but from that 2003 paper with Grossman ET al.
  • 49:56That first showed us the benefit of M
  • 49:58Vac and muscle invasive bladder cancer.
  • 50:01But multiple other papers have shown that
  • 50:04patients who have pathologic complete
  • 50:06response on surgery do significantly,
  • 50:08significantly better.
  • 50:09It's a really nice surrogate.
  • 50:11So this is and this kind of ties
  • 50:13back to how we ended the talk is
  • 50:16that surrogates aren't all bad,
  • 50:17it just has to be a a validated useful
  • 50:20surrogate and I think pathologic
  • 50:22complete response is one of those.
  • 50:24So that's how I would do it to start.
  • 50:26And then ultimately I think that
  • 50:28the goal would be a prospective
  • 50:30study where you identify patients
  • 50:32who sort of are positive and then
  • 50:34become negative after chemotherapy.
  • 50:36So you biomarker select them into a
  • 50:38study and then you would randomize
  • 50:39those patients or at least you know
  • 50:41it's that's a tough thing to randomize
  • 50:43too but you would as much as you
  • 50:46can offer patients multiple arms to
  • 50:48treatment or no treatment and and and
  • 50:51then you know observe quite carefully
  • 50:54afterwards but you we would need,
  • 50:56I I think we'd need pretty good data
  • 50:58before we would you know withhold
  • 51:00surgery for patients in this setting.
  • 51:02I should say there's a study out
  • 51:04of Fox Chase that is doing this.
  • 51:05There's the retain study that's
  • 51:07looking at de escalating therapy and
  • 51:09you know it'll be exciting to see
  • 51:11the results but we got we we have
  • 51:13to be really careful I think in in
  • 51:15these patients because it's it's
  • 51:16a bad disease if we miss a window
  • 51:19very life changing treatment too
  • 51:20especially with the cystectomy as well.
  • 51:22Thank you. Any other questions,
  • 51:25questions, any questions from the online
  • 51:31do new therapies replace
  • 51:33chemotherapy, give up chemotherapy.
  • 51:38So yeah that's a that's a good question.
  • 51:42I think the so bladder cancer has
  • 51:44seen I think like a lot of solid
  • 51:46organ malignancies has really seen
  • 51:48kind of a revolution and how we
  • 51:49treat it in the last 1015 years.
  • 51:51We've seen the importance
  • 51:53of checkpoint inhibitors.
  • 51:54We have antibody drug conjugates and
  • 51:57several other important classes.
  • 51:59And I have seen you know a lot of
  • 52:01these medications move earlier and
  • 52:03earlier in the treatment paradigm.
  • 52:05Cisplatin is really quite a useful drug
  • 52:06I think in bladder cancer and Doctor
  • 52:08Kim of course could probably speak
  • 52:10about this much more than I could.
  • 52:11But I don't think that we'll ever
  • 52:13be at a phase where or at least
  • 52:15not anytime soon that I can think
  • 52:17of where chemotherapy has no role,
  • 52:18but no doubt checkpoint inhibitors
  • 52:20and these other therapies are
  • 52:22definitely moving earlier.
  • 52:23I think they're going to play
  • 52:24a bigger and bigger role in,
  • 52:25in bladder cancer patients.
  • 52:26We just I think for the first time saw
  • 52:29data that there's an overall survival
  • 52:31benefit in the frontline setting to
  • 52:33a regimen that isn't cisplatin based.
  • 52:35So we've we beat cisplatin in the
  • 52:37first line setting for the first
  • 52:39time with a combination of inforimab
  • 52:41Vidotin which is antibody drug
  • 52:43conjugate coupled with pembrolizumab,
  • 52:45A checkpoint inhibitor.
  • 52:45So those two agents you know
  • 52:47and that's a that's a big deal.
  • 52:48We've been using cisplatin for for
  • 52:50decades now and and and so it's
  • 52:53proven a really resilient regimen.
  • 52:54So big,
  • 52:55big news, they had a standing
  • 52:56ovation at the ASIMO meeting.
  • 52:58Yeah. All right, good again.
  • 53:01Thanks Doctor Kelly,
  • 53:02you have fantastic talk. Thank you.
  • 53:15That's a
  • 53:19funny one.