Taylor Goodstein: Yeah, of course. Thanks so much for having me. This poster, this project was born out of what we got. We got some grant funding from the SUO-CTC CG Oncology to do some work looking at these newer gene therapy agents. And the multiplex immunofluorescence work that we did with cretostimogene was actually kind of like a side project to help validate what we were initially setting out to do and have successfully done looking at spatial transcriptomics. So they kind of married each other in a way and gave us some insight.
Sam Chang: Supportive of each other, is that correct?
Taylor Goodstein: Yeah, exactly. But to summarize, we had six patients who got cretostimogene and had oncologic data available. Two of them we qualified as being responder patients and four of them were being non-responder patients. And we had before and after tissue that we ran this panel, this T-cell panel looking at kind of whether we wanted to see if we could find immune changes that we could predict who was going to be a responder and who was going to be a non-responder. And when we first got all the data back, it didn't look like there was anything obvious that was showing up like there wasn't a clear signal for one cell type versus another that was statistically significant. But when we looked a little bit closer, one of the things we found is that our responder patients, they were expanding their T-cell population, but they were preferentially expanding their effector T-cell population.
Sam Chang: As opposed to any of the regulatory or suppressive T-cells, is that right?
Taylor Goodstein: Yes. So the non-responders were preferentially expanding this TCF1-positive T-cell population or basically like a stem-like or an exhausted progenitor T-cell. So they were having this massive increase in T-cells, but it was all this one type of T-cell, which is usually more of like a regulated or exhausted role than a truly effective-
Sam Chang: Effective...
Taylor Goodstein: Yeah, yeah, yeah, exactly, exactly.
Sam Chang: And so in the patients that responded, so this was a minority patients that responded that you looked at in this cohort and those that responded, was there also an increase in the other T-cell types or was it really focused on the T effector cells really exploded out? And so tell me if you could tease out any of the differences in terms of specific subtypes otherwise?
Taylor Goodstein: Yeah, no, it's interesting. I mean, the lines were exactly opposite. So it's like your responders, it's like effector T-cells went up, stem-like T-cells went down and it was the opposite for non-responders. So there's something that's happening where responders to this drug are somehow turning their T-cells into effective T-cells. And, again, we don't know why.
Sam Chang: Right. Small numbers. Although hypothesis is generating no question.
Taylor Goodstein: Exactly. Definitely.
Sam Chang: So I know you must have looked at some of the clinical data regarding these four responders versus these two... Or four non-responders or those that were not as successful versus those that were successfully treated. Have you been able to tease out anything clinical like younger, older, less DRBTs, more, et cetera? Tell me about that.
Taylor Goodstein: Yeah, yeah. It is a really small group, so it's hard to make any-
Sam Chang: Definitive statements.
Taylor Goodstein: Somebody was asking me recently, they were curious how many women, how many men, right? Because we're starting to see a lot of sex-related differences.
Sam Chang: Along with the androgen axis, and perhaps that could be influential.
Taylor Goodstein: I think there was only two women that were included in this, so not really easy to parse out any differences. But I will say the way that we defined response and non-response is important as it is in all these trials. So the way that we decided to define response in this was somebody that started getting their gene therapy and then a year later they still had not had a recurrence. So we had two responders. One of those patients has been on drug for three plus years and still hasn't had a recurrence.
Sam Chang: Okay.
Taylor Goodstein: Another patient made it about, I think, a couple years out before finally ended up having a recurrence of disease. So the one patient though that is our true responder, one of the things we found in his tissue was that he formed a bunch of tertiary lymphoid structures at his secondary TURBT. So it was one of those situations where had cancer, got induction, still had cancer, but that cancer had a bunch of these tertiary lymphoid structures then went on to respond to reinduction.
Sam Chang: Interesting, interesting.
Taylor Goodstein: And that's been shown, I think, in a lot of other facets of bladder cancer, muscle-invasive disease response to neoadjuvant. There was, I think, an interesting poster at AUA last year looking at BCG, whether or not you'd respond to reinduction BCG with forming tertiary lymphoid structures.
Sam Chang: Are able to actually mount that response.
Taylor Goodstein: Exactly.
Sam Chang: Okay. So we've got this small group early cohort incredibly exciting because it would be great to be able to obviously then predict who's going to respond and who's not. And then to have an idea of who should we perhaps do maintenance, who we can stop, all those types of things. So where are you going to go next in terms of, "Okay, we're now starting to look at this [inaudible 00:06:01]"? Where are you going next?
Taylor Goodstein: I mean, obviously you hit the nail on the head. Our main goal is like we're trying to define which patients are going to respond to therapy, who would be better served by getting cystectomy right after they fail BCG versus trying one of these other agents. And then another one of our questions was if somebody fails this drug, like if somebody fails one of these gene therapies, is it worth trying another one or does that mean that they're like done?
Sam Chang: Right. And maybe we switch to cytotoxics or do chemotherapy.
Taylor Goodstein: That actually was an interesting finding when we looked at population-based anecdotal data. A lot of these patients that didn't respond to gene therapy, I think there were seven or eight of them that did go on to have very long responses at getting Gem/Doce.
Sam Chang: Interesting, interesting.
Taylor Goodstein: Different mechanisms.
Sam Chang: Right, different mechanisms of actions.
Taylor Goodstein: But to answer your question, where are we going next? We've combined this with kind of spatial transcriptomics data. This was specifically the poster on cretostimogene, that we have run multiplex immunofluorescence on detalimogene and nadofaragene receiving patients. So we're trying to correlate or basically validate our creto findings using these other gene therapies to see if it's predictive across the board or prognostic, I guess across the board at this point.
Sam Chang: Yeah. I mean, you can clearly see that they attempt to be immunostimulatory in different ways. And then, for me, then it would be really fascinating, "Okay, they weren't able to actually really turn on the T effector cells. Well, is it a KIF? What about if you did a combination? Are you going to be able then to be able to turn it... ?" Who knows. So I think it's very, very important work and I wish you the best of luck as you start your career. It's going to be, I know, a fruitful one. I think Dr. Bohrer at Cincinnati, now you've become a Bearcat, you're ready to go.
Taylor Goodstein: I know, exactly. I have to start going to sports ball games.
Sam Chang: I know, you got all these things. So if there's anything that you have in the future, please touch base and we look forward to highlighting it in the future.
Taylor Goodstein: I'd love that. That'd be great. Thank you.