Cue Biopharma, Inc. (CUE) Earnings Call Transcript & Summary

Good afternoon, everybody. Thank you for coming today for the Morgan Stanley Healthcare Conference. Today, this afternoon, I have with me Dan Passeri, the CEO of Cue. And why don't I pass it off to Dan to introduce the rest of the management team? The format here will be a 10-minute overview of the company followed by a Q&A led by me. [Operator Instructions] Dan?

Okay. Thanks, Albert. Good afternoon, everyone. I'm joined here by -- with my colleague, Anish Suri, who's President and Chief Scientific Officer of Cue Biopharma. Just to remind everyone, Cue is a NASDAQ-listed company. Symbol is CUE. I also want to thank Morgan Stanley for giving us an opportunity to present. I'm going to be advancing slides here at our facility, and I'll tell you which slides we're on. You can advance them off of your computers directly. We're now moving to Slide 2. This presentation may contain some forward-looking statements. Now moving to Slide 3. So I'm going to provide a bit of a brief overview, and -- along with Anish to give you a context of what Cue is focused upon and why we are clearly differentiated in this very crowded immuno-oncology sector. Cue has a novel and unique platform which is predicated on protein engineering. It was launched out of the lab with Steve Almo at Albert Einstein College of Medicine. And the platform is meant to harness the power of the human immune system. And when we say harness, basically these proteins have been, in essence, reverse-engineered from studying the way that T cells our activated inside our bodies or modulated inside our bodies in a very selective, specific manner and exquisitely regulated through the interface of antigen-presenting cells and T cells. And I'll provide more details on that in a moment. So what we have, we consider to be a disruptive and transformative platform and that we believe we can accomplish something quite novel. And we're able to basically modulate disease-relevant T cells in vivo. And we'll walk you through how we do that in a moment. Our platform, the first iteration, is referred to as Immuno-STAT. Much like a rheostat for controlling temperature, we can dial activity up or down based on what disease indication we're attempting to address. STAT stands for Selective Targeting and Alteration of T cells. And again, we're able to target T cells by taking advantage of what's been observed at the interface between antigen-presenting cells and T cells. The platform is modular, and that modularity enables us to target numerous indications by swapping out an epitope. Also, we can alter the various components of the biologic. And Anish, again, will elaborate upon that in a moment. What I want to iterate here or emphasize is Immuno-STAT is our first iteration of the platform. These are fusion proteins that have various components to them. And what we've now done is take what we've learned from Immuno-STAT and derivatize it to launch what we call Neo-STAT. It's basically our next generation. It's the same molecule as Immuno-STAT except it does not contain the epitope in the MHC. We're able to stabilize the MHC pocket, so we can then subsequently chemically attach an epitope. And that provides us with a tremendous amount of flexibility but also dramatically enhances our productivity and scalability. And finally, I want to emphasize that we have deployed a focused clinical execution strategy to derisk and validate the platform. And what we mean by that is we've built our clinical trial design around our lead compound, which is representative and exemplary of the CUE-100 series, that's the IL-2-based series, and that the framework of the drug remains consistent. And by generating a set of data for 101 that derisks that molecule, by implication, it derisks the 100 series and the platform itself. So we're going to walk you through the datasets that we're generating. Next slide. All right, just to touch upon this and I'm going to hand it over to Anish, this is the reverse engineering we talked about where the antigen-presenting cell interfacing with a T cell with a signal transduction that allows for very selective modulation of T cells by taking advantage of the docking with a T cell receptor, which is where the specificity comes from. And that's through an MHC construct. It's basically a scaffold that holds an epitope, presenting it to a T cell. The T cell receptor then binds to that epitope, and that's signal 1. Now for a T cell to be effectively transformed into a cytolytic killer T cell, you need an amplitude on that signal, which comes from signal 2, which can come from a modulatory cytokine such as IL-2. Anish, I'm now going to turn it over for elaborating.

Sure. So just to build up on what Dan said, if you go to the next slide, Slide 5, the core expertise of the company is around protein engineering. And each of the module of an Immuno-STAT can be exchanged to put in specific determinants in a disease-relevant manner. So for example, when you've got a frame we've optimized for immuno-oncology, the peptide that you see here represented with a yellow dot can we swapped out to change indications at will. Our first one has a peptide from human papillomavirus, the E7 protein, to target HPV-driven cancers. The second one has got a Wilms' Tumor 1 epitope. We've gone after KRAS, the G12 mutated hotspot epitopes and so on and so forth. Similarly, one can target different HLA alleles. We've worked with HLA-A02, which is the dominant HLA in the Class I loci in North America, Western Europe, but we've also worked with HLA-A24 and A11 that are highly dominant in the Eastern Hemisphere, particularly China, Korea, Japan and those geographies. Besides the HLA part on Slide 5, you can also dial in different co-stimulatory or co-regulatory elements, again depending upon disease. The first iteration which we'll talk about has an activating modified IL-2 variant to direct it to tumor-specific T cells. We've worked with cell surface receptors with the B7 superfamily. We've worked with cell surface receptors in the TNF receptor superfamily like 4-1BB ligand, for example. And on the autoimmune side, we've worked with regulatory elements. And the principle is the same except in that case, you're controlling and modulating the pathogenic self-reactive or reactive T cells. And lastly, the Fc backbone of the molecule is a very important component because you can engineer it not only for effective function but from a structural stability and manufacturability, this provides a significant advantage. These molecules are made exactly like an antibody molecule in 2-plasmid systems using CMC processes from 3-plus decades of monoclonal experience and extremely stable. So just building up on that. If you go to Slide 6, this is the first series known as the CUE-100 series. And what makes the CUE-100 series is that in the middle, you've got the peptide HLA, as shown in the top-down view in the ribbon structure that you see in Slide 6, flanked by 2 molecules of interleukin 2, IL-2, which has been a validated target but of course has had issues with safety and systemic activation and lack of specificity. So in this context, when you look at the 100 series, you've got essentially an [ HS ] polyspecific, if you want to look at it. You've got the peptide HLA engaging the right T cell that matters, that's specific to the tumor antigen, along with a modified IL-2 where we made 2 critical changes. One, the abrogated binding to receptor alpha so you minimize the bias for regulatory T cell engagement as well as the engagement with the high-affinity IL-2 receptor-bearing cells that results in cytokine secretion or vascular leak syndrome, for example. But we also modulated binding to IL-2 receptor beta, and the reason for that was that allows the generation of an IL-2 product that's only active when the T cell receptor is actually docked to the central peptide HLA component that you see here. In other words, if this IL-2 bumps into an irrelevant nonantigen-specific T cell, which is the vast majority of the repertoire in a host, this IL-2 is relatively inert. We believe these 2 together, where the peptide HLA guides the IL-2 and the valency of IL-2 being 4 binding IL-2s as shown in the scaffold, allows for an avidity interaction that allows for appropriate signaling that's then driven by the T cell receptor engagement. And I think that's a significant differentiation from all other IL-2 modalities out there, including the nonalpha variants, where you minimize the Treg bias, but what you have is a molecule that's an equal opportunity engager of every T cell, the vast majority of which have nothing to do with tumor specificity. So -- and that's sort of -- that's all the biology. Okay. Well, moving on, 101 is our lead candidate that we've made most progress in the clinic that has a peptide from HPV-E7, as shown here on HLA-A02. The trial builds upon very straightforward stratification. If the patient's HLA-A02 positive and the tumor is HPV driven, you are eligible for the drug. And we make that qualification upfront before dosing, and that's a significant advantage to identify patients that are likely to respond. Dan, why don't you just cover the high-level options?

Sure. Let's go to the next, Slide 8, and these are the last 2 slides. So real quickly, to give you a summary, going from this idea of reverse engineering and emulating these SKUs that nature provides T cells, which is where our name comes from, we deployed rational protein engineering to design these core biologics, and our first 100 series is based upon the IL-2 cytokine. 101, which is our lead clinical candidate, we'll describe the dataset in a second. We obtained IND approval in May of 2019 for monotherapy of resistant metastatic head and neck cancer patients. Now -- so these are second line and beyond. These are patients that are basically resistant and progressing. It's a very difficult patient population to treat. And we're doing this as a monotherapy. So to date in our dose escalation, we have demonstrated the drug has a very favorable safety profile currently in Cohort 6 at 4 milligrams per kg. And that's equivalent to approximately 32-fold the amount of IL-2 one receives with Proleukin at its approved dose level. 101 exhibits a very attractive dose-proportional pharmacokinetic profile and exposure into patients. What we mean is as you increase the dose, you're seeing a corresponding increase in the Cmax in the area under the curve, which is its residence time for interacting with the T cells that you're targeting. It also demonstrates PD activity via expansion of the target T cell population that we are trying to expand. So that's all very attractive in these early goings. And most importantly, we've already seen -- in the monotherapy dose escalation, we've seen some signals demonstrating signs of clinical activity, including 2 cases of patients having a resist criteria confirmed stable disease and a couple of patients showing some reduction in tumor size. We'll be launching a second trial in parallel, which will be in combination with pembro, which is approved. It's an anti-PD-1 approved for front line of the same indication. And next slide, which we'll end on. So we're now on Slide 9, and this is just to show you the design of how we have gone from Cohort 1, which was the lowest dose of which we had FDA approval to launch the trial. And we have systematically been dosing up 3 patients at a time. We are now at Cohort 6, still demonstrating a very attractive safety profile. We've been showing, again, good dose-proportional exposure, PD activity. And most importantly, in this trial as we're dosing up, we're seeing signs of clinical activity. So we're really encouraged by the amount of dose we've been able to dose safely. We're now at dose ranges where we believe we're at substantive levels for potentially seeing more substantive clinical responses. So we've just expanded Cohort 4 out to the prospects of 9 patients. And we dosed our first patient in Cohort 6. We have the other 2 identified. And we have 6 patients continuing on study from the doses that we've -- the cohorts that we've dosed so far. And again, we have 2 stable disease confirmed. That means they have showed stable disease with 2 scans that is equal to 12 weeks in terms of the time duration. So on that Albert, I'll turn it back to you if we want to start the Q&A session.

Can't hear him. He's on mute.

Albert, are you on mute?

Albert, I think you're on mute.

Yes.

Sorry about that.

No problem.

It happens to me every time. So speaking of your ongoing trial, you mentioned you're in the sixth cohort. So I've heard you say some things like what multiple of Proleukin doses that you're equivalent to. What cohort do you think you would expect this to be therapeutically active? You've seen a couple of stable diseases. But when you were anticipating the trial, what was the expectation?

Yes. Albert, this is Anish. As you see the molecule coming along, when we had looked at the data from our preclinical projections from models, we had projected starting around Cohort 4 we should start seeing metrics of activity. And let me just qualify that. By that, meaning at least enough drug and coverage around to be able to engage and expand the right repertoire. And we've seen signals of that. And that gives us, again, a lot of encouragement and hope. And then further building on that, we think these current ranges of 5 and 6 further substantiate that. Dan highlighted the continued dose-proportional exposure. We thought that was a very important observation in order to have adequate coverage that we continue to build on that. So this is where that having this thing, the data support, what we had projected from our preclinical projections is a very important component of what we have sort of started to see in the clinic. Dan, do you want to add to that?

Yes. Thanks. So Albert, I think the important feature here is, first of all, when we're looking at this patient population, right, it's a very compromised, sick patient pool that we're trying to treat. And it's a spectrum. They're not all basically coming in with the same condition. So it's like a bell curve of patients. And when you're dosing 3 patients, it's like pulling 3 straws from a haystack. So we have to realize the meaning of the data we have with 3 patients. So what's really encouraging is, as Anish stated, we were expecting to see PD effect around -- emerging around 3, 4 cohort. And we saw both PD and therapeutic benefit in cohorts 1 and 2. In Cohort 1, we had a patient inappropriately get a 5x dose. And we saw some tumor shrinkage there. That patient actually had clinical benefit for multiple cycles. And then Cohort 2, we had a patient with about a 20% reduction in their target lesion. And that patient had a confirmed stable disease and stayed on drug for 19 cycles, I mean, 19 weeks. And that is very encouraging because we weren't really sure we'd even see PD effect at that level, which we did. So we're really encouraged by the activity that we've seen to date. So now at Cohorts 4, 5, 6, we're at a range where we're expecting to see even more robust clinical signal. We have another confirmed stable disease. We have 6 patients still on study. And this is where it begins to really get interesting for us. So we expanded Cohort 4 to 9 patients. So we have more confidence in the meaning of the data that we're looking at. And we'll likely do that with Cohorts 5 and 6 going forward.

Okay. So given that, what should investors be looking for here? Where are you going with the data? When are the next milestones? And are you planning to present it at a conference? What should they be looking forward to?

Yes. So first of all, we'll be presenting upcoming conference at SITC, and Anish can elaborate on the type of data we'll be presenting there. And I think that the key feature here from an investor's perspective is the fact that this is a truly novel approach where we have a biologic that we're infusing directly in the patient targeting relevant T cells. So it's not a global activation. And we've already demonstrated a very attractive profile in terms of the safety or the concentrations with dosing. We've demonstrated that we, in fact, are amplifying this targeted T cell population. By the way, these T cells have been validated in ex vivo approaches. We, for instance, with the Steve Rosenberg protocol have used the same epitope we're targeting when they take the T cells out of the body, amplify them, then infuse them in and give cycles of IL-2. So we're now utilizing that same epitope in this biologic that's being infused directly in the patients. So from an investor standpoint, the next quarter to 2 quarters is really an attractive time frame because we expect that we'll be generating substantive insights into the prospect of this drug having a monotherapy path forward. I believe we've already met substantive metrics for the rationale of the combination with pembro and that we're increasing the relevant T cell population that can attack the tumor when you take PD-1 blockade protection away with a blocking antibody. So this is a very interesting time point. Regarding the upcoming data metrics at SITC, Anish, do you want to elaborate on that?

Yes. I think we'll continue to build that, Albert, what we've already sort of disclosed up till Cohort 4. By then, we anticipate to have more data, Cohort 5. We've completed Cohort 6. By the end of this month, as Dan mentioned, we've got the 2 patients outlined. So it will be a continual build-out both in the PK/PD and clinical metrics. It will be presented by our investigators. So we're really looking forward to that meeting. Besides the 101, we also have our presentation on CUE-102 at SITC. That's on the next asset targeting Wilms' Tumor 1, again a very attractive oncofetal antigen both for hematological and solid tumors, where we've just got a very nice, strong preclinical data package with, again, ex vivo human cell data accompanied with a beautiful poly functionality and target cell killing. And I think included with that, we'll also present some of the early data on the KRAS G12 epitopes that we've started to target using this platform. So we very much look forward to that meeting. For us, that should be a very data-rich meeting.