Biomarkers in Bladder Cancer

Transcript

• 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.