Characterization of The Genomic Landscape of Post-Neoadjuvant Chemotherapy in MIBC Patients- Andrew Lenis
January 24, 2021
Dr. Lenis highlights a recent study highlighting the potential of genomics to identify those who will not benefit from neoadjuvant chemotherapy, which also aims to provide future targets for the adjuvant treatment in MIBC. The objective of this study was to characterize the genomic landscape of post-neoadjuvant chemotherapy bladder cancers. He and his team had hypothesized that there would be a lower frequency of DDR alterations in those samples and wanted to identify targetable alterations for adjuvant clinical trials. They used their prospective radical cystectomy database of over 3,000 patients to identify those with localized muscle-invasive bladder cancer and aimed to limit the sample to those with biologically chemotherapy-resistant disease, therefore including only patients who are treated with four cycles of gemcitabine and cisplatin.
Andrew Lenis, MD, Fellow, Urologic Oncology, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
Ashish Kamat, MD, MBBS, Professor, Department of Urology, Division of Surgery, University of Texas MD Anderson Cancer Center, President, International Bladder Cancer Group (IBCG), Houston, Texas
Ashish Kamat: Welcome to UroToday's Bladder Cancer Center of Excellence. I'm Ashish Kamat from MD Anderson Cancer Center in Houston. And it's my pleasure to welcome today, Andrew Lenis, who's a Fellow in Urologic Oncology at the other cancer center in New York, Memorial Sloan Kettering Cancer Center. And he's going to present to us work that he did in David Solit and Eugene Pietzak's lab on the genomic characterization of residual disease at radical cystectomy following neoadjuvant chemotherapy in patients with muscle-invasive bladder cancer. Andrew, the stage is yours.
Andrew Lenis: Great. First, I just want to thank Dr. Kamat and UroToday for the opportunity to present this work. So patients with residual disease after neoadjuvant chemotherapy have an especially poor prognosis. In a recent study of 129 patients with adverse pathology of radical cystectomy, the median time to recurrence was only 10 months and overall survival was less than two years. Unfortunately, there's no standard adjuvant therapy for these patients. There are a few adjuvant clinical trials that exist, three that are testing immunotherapy and two trials that are evaluating FGFR inhibitors.
Therefore, additional therapeutic options are needed, and understanding the impact of chemotherapy on your ethereal tumors could lead to new insights. There are two important recent studies that have shed light on the impact of chemotherapy on bladder tumors. The first study was by Dr. Faltas and colleagues who looked at paired pre and post-chemotherapy samples from patients with advanced disease. They described significant heterogeneity as indicated here in the light blue bars at the stacked bar graph. These are shared mutations between the pre and post-chemotherapy samples. They also identified early branching in the genomic evolution of these tumors as they progressed.
The second study by Dr. Liu and colleagues looked specifically at neoadjuvant-treated patients and found that actually little change in mutational load occurred between pre and post-chemotherapy samples. They also identified a unique cisplatin-associated mutational signature as indicated here, in purple, in the post-chemotherapy samples. Finally, they demonstrated that genomic heterogeneity was associated with worse clinical outcomes. While both of these studies have paved the way to understand chemotherapy-resistant tumors, additional work is needed to identify targets for future trials.
Therefore, the objectives of our study were to characterize the genomic landscape of post-neoadjuvant chemotherapy bladder cancers. And we had hypothesized that there would be a lower frequency of DDR alterations in those samples. And we also wanted to identify targetable alterations for adjuvant clinical trials. So we used our prospective radical cystectomy database of over 3,000 patients to identify those with localized muscle-invasive bladder cancer. We aimed to limit the sample to those with biologically chemotherapy-resistant disease and therefore included only patients who are treated with four cycles of gemcitabine and cisplatin.
We then identified those with residual disease, which we defined as greater than or equal to pT2 in the bladder and/or node-positive disease. We excluded patients treated with adjuvant therapy in order to study the natural history, which was presented at the SUO this year in a separate abstract. Finally, we identified patients from this clinical cohort with IMPACT testing. MSK-IMPACT is a next-generation sequencing platform that sequences now over 500 actionable cancer targets and tumor samples. We used the TCGA as a chemotherapy-naïve reference standard for muscle-invasive disease. We similarly identify those patients with residual disease and used them as our comparator cohort.
Here are the clinical characteristics of our chemoresistant and TCGA cohorts. The groups were comparable in terms of age and sex, and the median follow-up was similar between groups. The chemotherapy-resistant cohort had higher T stage and lymph node positivity. And because the chemoresistant cohort had a higher pass stage, they were more likely to recur and had a shorter time to recurrence. This is the genomic landscape of the chemoresistant cohort from our sample. On the left, we show the most commonly mutated genes. We see the TERT mutations and p53 mutations are the two most commonly altered genes in the sample. We also see a relatively high alteration frequency of several chromatin-modifying genes, which we know is very common in bladder cancer and probably an early event in carcinogenesis.
On the right here we have the number of alterations of each gene stacked into pathways including DDR pathway, RTK, p53, and chromatin-modifying genes. Again, we see high numbers of chromatin-modifying genes and p53 cell cycle alterations. We see fewer RTK pathway alterations and very few DDR alterations, which again was our a priori hypothesis. Here we have a chemotherapy-resistant cohort with the comparator TCGA cohort. We found similar frequencies of chromatin-modifying alterations between the chemoresistant cohort and the TCGA chemo-naïve cohort. However, we did see fewer p53 cell cycle and RTK pathway gene alterations in the chemoresistant cohort.
Further consistent with our hypothesis, we found that there were significantly fewer DDR mutations in the chemotherapy-resistant cohort. This likely reflects a treatment effect as tumors with DDR mutations are known to be more sensitive to cisplatin-containing chemotherapy. We used the nine gene panel used in the Alliance trial, which is a bladder sparing trial in genomically selected patients who demonstrate a clinical response to neoadjuvant chemotherapy. And you can see the genes here on the left that were used. Importantly, alterations were very specifically defined here. And when we look at the nine genes really the difference is in ERCC2 alterations, which we know from the lab confers cisplatin sensitivity.
This is just a slide to show that even if we expand the DDR gene panel to a more inclusive set of 34 genes, we still got a significantly lower frequency of DDR alterations in the chemotherapy-resistant cohort. Clinical implications of these findings are that neoadjuvant chemotherapy may limit DDR alterations which in turn could influence mutational load and therefore affects clinical outcomes. In the clinical cohort of chemotherapy-resistant tumors from MSK presented at the SUO in a separate abstract, LVI and lymph node metastasis were the strongest predictors of a poor outcome as indicated by the blue and green curves on this Kaplan-Meier.
Therefore, these patients were of particular interest to study from a genomic standpoint, as they represented those who would benefit the most from adjuvant therapy. Here are the alterations in patients stratified by the presence of LVI and/or lymph node metastases. We found that ARID1A was enriched in patients with LVI or lymph node metastasis. And if we look more specifically at these patients and stratify those into lymph node metastases with or without LVI, LVI alone, or with neither LVI nor lymph node metastases, we see again an enrichment of ARID1A in both lymph node metastases and LVI. But the difference is only significant in LVI patients likely due to sample size.
Finally, we sought to identify targetable alterations using OncoKB, which is a curated precision oncology database. Individual mutational events here are assigned a level of evidence-based on clinical actionability with level one being supported by either an FDA approved drug or by an FDA recognized biomarker. And we found that 60% of samples had at least one mutation associated with a current or future potential therapy or biomarker, and half of these were level one.
So in conclusion, we demonstrate the chemotherapy-resistant tumors have fewer DDR alterations likely reflecting a treatment effect as DDR mutations are known to be associated with chemotherapy sensitivity. We showed that samples with LVI and/or lymph node metastases were enriched in ARID1A alterations, which may be associated with poor outcomes as has been shown in other bladder cancer disease states such as BCG resistance. Finally, there are several targetable alterations that were identified based on OncoKB leveling, and these could help guide future adjuvant trials.
Moving forward, we've planned to investigate the clinical implications of fewer DDR alterations on clinical outcomes. And I'm very interested in exploring this LVI and lymph node metastasis findings in this chemotherapy-resistant cohort. So I'd like to thank my mentors at MSKCC, all of our co-authors, our institutional resources and funding support, and of course our patients and their families. Thank you.
Ashish Kamat: Thank you, Andrew. That was very nicely presented. Let me ask you a couple of questions. When you went about this study was it based on a hypothesis that you have that was independent of some of the work that's come out of, for example, Gopa Iyer and others? Where is this heading as far as hypothesis generation or derivation's concern?
Andrew Lenis: Right. Well, I think the impetus for the study was actually first to look at patients with chemotherapy-resistant disease. It was really a clinical question and that's what was presented in a separate abstract at SUO by Emily Bochner. I think the genomic analysis here, our hypothesis was based on a lot of Dr. Iyer's work and others looking at DDR alterations and specifically ERCC2. So that did form the basis for our hypothesis for this study.
Ashish Kamat: Okay, great. And you did allude to the potential clinical applications of this data. Could you expand a little bit on whether you see this being something that could help drive trials that look at immune therapy, IO combinations, or similar agents in these cohorts of patients that are chemoresistant?
Andrew Lenis: Yeah, I think that probably it might be too straight forward a way to look at it. But one line of thought is that while if patients, if these samples have fewer DDR alterations then they're going to have a lower tumor mutational burden and they may not respond as well to immunotherapy options. And that may explain why some of the adjuvant trials currently don't have the response rates that we were maybe hoping for. I think moving forward, some of the data that we're seeing from some of the data out of IMvigor ONO and looking at cell-free DNA may help move that field forward. But I think that was one of the things that we were looking at is whether DDR alterations translated to mutational load and how this ultimately affected response to immunotherapy.
Ashish Kamat: And that was actually going to be my next question, so I'm glad you brought this up. Have you done work or are you aware of work that's being done by any of your co-fellows or co-investigators to see the correlation between what you're finding at the tissue level and in circulating tumor DNA and/or the concordance between pre and post-cystectomy specimens?
Andrew Lenis: Yes. So we definitely looked in our sample to identify those with pre and post-chemotherapy samples. There has been a lot more work done in this respect, I mentioned Dr. Liu's study with Dr. Ben Allen's lab that looked at pre and post-chemotherapy samples. We have a few that have pre and post-chemotherapy samples and we're looking into that data, but it's not ready to be presented or published at this point. In terms of cell-free DNA, we do have something similar to MSK-IMPACT we have something called MSK-ACCESS, which looks at 129 genes, again targetable cancer genes in cell-free DNA. And there are ongoing studies looking at this in several different populations, and so we're hoping to combine some of that work, but again it's very preliminary at this point.
Ashish Kamat: Okay, great. So what next? What else are you doing with this data that you have? You talked about the LVI and of course, we know that LVI is a surrogate for micrometastatic disease, and of course, patients that have lymph node-positive disease, have frank metastatic disease. So it's not surprising that you would find some of these markers being associated with clinical parameters that are known to have adverse prognostic effect and chemoresistance. Are you looking at the lymph node metastases, for example, and then sequencing the tumors that are present in the lymph nodes after chemotherapy and correlating them with pre-chemotherapy specimens and trying to figure out a pathway there? Or is there some other avenue of exploration that you're embarking on?
Andrew Lenis: Yes. We do have several projects that are in the works right now looking at lymph node-positive disease. So we do have several matched pair projects that are looking at metastases from different sites and correlating that with the primary tumor. And there's some interesting data that will hopefully come out of that soon, specifically with regard to lymph node metastases, we do have and have presented data on matched primary tumor and lymph node metastases genomic data. And there does appear to be some discordance between the two from a genomic profile standpoint. And this may be clinically relevant as we select targeted therapies for patients, we generally look at biopsies or tumor samples from the primary tumor. But if the primary tumor and the metastases have different genomic profiles, we may want to think about targeting what's in the metastases as that's often a driver of the morbidity and mortality from malignancy in general. So we have several projects looking at this and hopefully more to come in the future.
Ashish Kamat: Right. Exactly. Well, this has been a great presentation and discussion. I want to give you the closing stage. So to sum up, if you could just take our audience through what you would think would be the top three key points from your work so far.
Andrew Lenis: Sure. I think our data shows from this study that chemotherapy-resistant tumors are obviously genomically distinct from their chemotherapy-naïve counterpoints. And basically, it provides further support albeit indirectly for the observation that DDR alterations specifically ERCC2 alterations are associated with chemotherapy sensitivity. I think this data also provides evidence for several potentially targetable alterations in chemotherapy-resistant tumors. And this may be the path forward for these patients, specifically, I think FGFR3 inhibitors are next on the docket and it's important to enroll in those trials, such as PROOF 302 and PEGASUS.
And then finally I think some of our data exploring the findings in lymph node metastases and LVI patients is important. Again, as we discussed targeting alterations that are in the metastasis and the lymph nodes may be more effective than targeting alterations that are in the primary tumor. So understanding the differences between primary tumor and metastasis and what's driving the metastasis is clearly an important next step for these patients.
Ashish Kamat: Great points. Once again Andrew, thank you so much for taking the time. Keep up the good work and looking forward to hearing a lot more from you as you move forward in your career. Thanks again.
Andrew Lenis: Thank you very much.