ctDNA Guiding Adjuvant Immunotherapy in Urothelial Carcinoma Journal Club – Christopher Wallis & Zachary Klaassen

September 4, 2021

Christopher Wallis and Zachary Klaassen discuss a recently published paper, entitled, “ctDNA Guiding Adjuvant Immunotherapy in Urothelial Carcinoma.” They discuss the basics of circulating tumor DNA (ctDNA). He specifically discusses how we can use ctDNA to identify molecularly, or microscopic, residual disease.  The study shows that ctDNA-positive patients with adjuvant atezolizumab, after surgery, had improved outcomes. 

Biographies:

Christopher J.D. Wallis, MD, Ph.D., Instructor in Urology, Vanderbilt University Medical Center, Nashville, Tennessee

Zachary Klaassen, MD, MSc, Urologic Oncologist, Assistant Professor Surgery/Urology at the Medical College of Georgia at Augusta University, Georgia Cancer Center


Read the Full Video Transcript

Christopher Wallis: Hello and thank you for joining us for this UroToday Journal Club. Today We're discussing a really interesting recently published paper, entitled, ctDNA Guiding Adjuvant Immunotherapy in Urothelial Carcinoma. I'm Chris Wallis, a Fellow in Urologic Oncology in Vanderbilt. With me is Zach Klassen, Assistant Professor in the Division of Urology at the Medical College of Georgia.

Here is the citation for this recent publication in nature, which was led by Tom Powles. By way of background, most UroToday viewers will recognize that these guidelines for the treatments of muscle-invasive bladder cancer and similar concepts apply for upper tract disease, wherein radical surgery remains the standard of care. However, we feel metastatic recurrence is common, so as a result, there's been interest in trying to optimize care. And in particular, we want to try and identify patients who may have residual disease after their surgical intervention and this is typically difficult to discern. We can use radiographic imaging, but this only detects macroscopic disease.

And so one way to identify molecularly residual disease or microscopic amounts of residual disease is to look for ctDNA, that's circulating tumor DNA, so this is free unbound, not within a cell and just existing in the bloodstream. And in the last couple of years, actually, in the last six months or so, we've seen the publication of two trials looking at the use of adjuvant immunotherapy. The first of these was IMvigor010, this looked at adjuvant atezolizumab. And the second was CheckMate-274, which looked at adjuvant nivolumab, and both of these are relatively similar design looking at patients with high-risk urothelial carcinoma and randomizing them to either adjuvant therapy or observation.

Focusing for a minute on IMvigor010, we can see both from the DFS curve at the top and the OS curve at the bottom, that there was not evidence of significant benefit from the addition of atezolizumab, and so this actually formed the basis of the data set to address the question in the paper we're discussing today, which is whether patients who are positive for molecular residual disease that is ctDNA-positive and has a higher likelihood of recurrence, can derive clinical benefit from adjuvant atezolizumab distinguishing them from those who are molecular residual disease negative and don't derive benefit as the hypothesis. And so this is really an effect modification question.

And so just to briefly reiterate this trial included patients with a high risk following surgical resection, so for patients who had not received neoadjuvant therapy, this was defined as PT3 or four, or node-positive disease. In those who did receive neoadjuvant, this could include those who had YPT2 to four or node-positive, and they had to have a negative postoperative staging.

And so to conduct the molecular analysis in this paper, the patients underwent a variety of profiling approaches, including the tumor, normal tissue and plasma. And so first DNA was extracted from the surgical specimen and there's PD-L1 expression testing. The authors then performed whole exome sequencing of both tumor and normal tissue to capture just under 20,000 genes. And then they map these to the referent human genome and perform quality checking.

Using a matched tumor and normal tissue, the authors then design the ctDNA assay, and they performed somatic variant calling using consensus method and filtered out previously reported germline variants. They then use the bioinformatics pipeline to identify putative clonal somatic single-nucleotide variance between the paired tumor tissue and normal tissue from each patient. And then they prioritized this list of variants to design PCR amplicons and performed multiplexed targeted PCR on the postoperative plasma samples to identify circulating free tumor DNA, and this was identified as positive if two or more mutations were identified.

So the authors assessed four related objectives within this context. And first, they compared the benefit of atezolizumab versus placebo on disease-free survival in patients who were positive for a circulating tumor DNA at cycle one, day one of their adjuvant therapy. They then assessed whether the presence of ctDNA at both cycle one, day one, and cycle three, day one were associated with decreased disease-free survival.
And then they looked at clearance of ctDNA, That is the presence of cycle one, day one converting to the absence of cycle three, day one being associated with improved DFS. And finally, they looked at whether this clearance was more common in patients who are receiving the adjuvant atezolizumab. And primarily they assessed a categorical version of ctDNA, which was either present or absent, and they looked also secondarily at continuous operationalizations of this.

In addition to DFS, they looked at a secondary outcome, including OS, and then looked at secondary exposures, which would be other characteristics that may modify this relationship, including standard clinical-pathological characteristics, PD-L1 expression, to a mutational burden, and other molecular gene signatures.

And at this point in time, I'm not going to hand it over to Zach to walk us through the results of this really interesting study that may help us select patients who are most appropriate for adjuvant therapy.

Zachary Klassen: 
Thanks, Chris. So if we look at the inclusion criteria for this ctDNA biomarker-evaluable population, on the right, you can see that there was 809 patients that were enrolled into the IMvigor010 trial, ultimately 619 patients had tumor DNA, matched normal DNA in at least one plasma sample available. And subsequently going down to the bottom, you can see that 581 patients had C1D1 plasma evaluated for ctDNA and passed quality control. So then these were then divided up into 281 patients in the observation group and 300 patients that were included in the atezolizumab group biomarker evaluable population.

So looking right to the main results of the study, this is the Kaplan-Meier estimate among evaluated patients with post-surgical ctDNA status, looking at DFS specifically, and essentially there's two Kaplan-Meier curves in this one graph. So if we look at the top curve, this is ctDNA-negative patients, the medians for DFS, between the atezolizumab in light blue and the observation group in light pink were not reached with a hazard ratio non-significance of 1.14 and 95% confidence interval of 0.81 to 1.62.

If we look below that in the ctDNA positive group, we see that the atezolizumab arm had a median DFS of 5.9 months, and the observation arm of 4.4 months, with a significant hazard ratio favoring the atezolizumab group in dark blue at 0.58 and 95% confidence interval of 0.43 to 0.79.
Probably the most important slide in this slide deck is this slide looking at the overall survival by ctDNA status. So at the top again, this is the ctDNA-negative group. Medians for overall survival not reached hazard ratio of 1.31. When we look at the bottom, this is the ctDNA-positive group, atezolizumab median overall survival of 25.8 months in the observation arm of 15.8 months with a hazard ratio favoring atezolizumab of 0.59 and a 95% confidence interval of 0.41 to 0.86.

This looks at the patients who were ctDNA-positive at C1D1, who converted to ctDNA-negative by cycle three, day one, so a positive to negative distribution. And this is compared to those who remained ctDNA-positive at cycle three, D1, otherwise positive to positive. So looking down at this figure, the main takeaway from this slide is that there 99 patients in the C1D1 for atezolizumab, 79 for observation. Ultimately 18.2% of patients converted to ctDNA-negative in the atezolizumab arm, compared to only 3.8% of patients that converted from positive to negative ctDNA in the observation arm.

In the next several Kaplan-Meier slides we'll look at overall survival and showing different ctDNA dynamics between cycle one, day one, and cycle three, day one, this is specific to the atezolizumab arm, and you can see here that the solid lines at the top of the Kaplan-Meier curve, dark blue is positive to negative and light blue solid is negative to negative. So almost essentially overlapping curves if you were started as ctDNA-negative and ended up negative, or if you started as ctDNA-positive and ended up negative by the end of this evaluation.
And similarly, you can see here positive to positive, the dark dash line compared to negative to positive and the light blue line, similar Kaplan-Meier curve. So once again, highlighting that, if you ended up with negative ctDNA at cycle three, day one, you had some outcomes compared to those that started at negative and continue to be negative ctDNA.

A similar care for the observation arm, but not quite as clean. You can see that there's more splitting of the curves depending on positive to negative, as well as negative to negative. We can see here that this is not quite as clean as the previous slide here looking at the atezolizumab arm as the observation arm.

So this figure looks at the differential gene expression analysis in this population. And so to the left of this dotted line here at zero is the ctDNA-negative arm and looking at common genes that were expressed and you can see that the majority of these are myogenesis genes. In looking at the right you can see that this is ctDNA-positive, a majority of their cell cycle and keratin genes, which is a nice graphical representation of what was distributed in each of these populations. This also highlights the gene set enrichment analysis looking at the ctDNA biomarker evaluable population. Everything to the right, which is also in red, was up-regulated in ctDNA, so we're talking about E2F targets, checkpoint, MYC targets, mitotic spindal, glycolysis, cholesterol homeostasis. And then also, as we highlighted on the previous slide in the ctDNA-negative arm, myogenesis genes were unregulated in these patients.

So several important discussion points from this seminal work from Dr. Powles and his colleagues. In looking at this study, initiating personalized treatment based on the identification of molecular residual disease, rather than treating unselected or waiting for relapse would be a substantial change in cancer treatment. This analysis identified a high-risk population, ctDNA-positive population who presumably have molecular residual disease after surgery, and who appeared to have improved outcomes with adjuvant atezolizumab.

As I showed in the previous slide, clearance of ctDNA with atezolizumab curve in 18% of patients, which also led to improved outcomes. As Chris highlighted at the beginning, other adjunct immunotherapy studies, such as CheckMate274, showed a DFS benefit among unselected patients who were PD-L1 positive, but there was no overall survival signal. And so interestingly, as the authors discussed in the discussion, a personalized approach to selecting patients with the molecular residual disease for immunotherapy may be required to demonstrate an overall survival benefit as we saw in this study.

So in conclusion, these findings demonstrate the use of ctDNA as a biomarker for molecular residual disease in response to atezolizumab and its linked ctDNA to the biology of the tumor. These results may change our understanding of post-surgical cancer care and it validated in this setting, as well as across other tumor types, that findings will also change clinical practice. Thank you very much. We hope you enjoyed this UroToday Journal Club.
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