ESMO 2026 | Optimizing the tumor mutational burden cutoff for checkpoint inhibitors
Ines Pires da Silva, MD, PhD, Melanoma Institute Australia, Sydney, Australia, explores a large international multi-cohort analysis assessing the optimal tissue-agnostic tumor mutational burden threshold for predicting immune checkpoint inhibitor (ICI) efficacy. A higher cutoff of 16 mutations per megabase was more strongly associated with improved survival than the currently approved threshold for pembrolizumab, with patients in the intermediate range deriving limited benefit. This interview took place at the European Society for Medical Oncology (ESMO) 2026 Congress in Madrid, Spain.
These works are owned by Magdalen Medical Publishing (MMP) and are protected by copyright laws and treaties around the world. All rights are reserved.
Transcript
In fact, very interesting studies. So just a bit of background. So we know that FDA has defined tumor mutational burden, high tumor, in terms of tumor burden for those tumors that have 10 or more mutations per megabase, right? And why is it important? Because we know that those tumors are the ones that respond better to immune checkpoint inhibitors, right? And it is a specific approval for pembrolizumab in that context...
In fact, very interesting studies. So just a bit of background. So we know that FDA has defined tumor mutational burden, high tumor, in terms of tumor burden for those tumors that have 10 or more mutations per megabase, right? And why is it important? Because we know that those tumors are the ones that respond better to immune checkpoint inhibitors, right? And it is a specific approval for pembrolizumab in that context. So what this group, and then another thing is that FDA recently changed the definition from 10 to 13. What the authors of this study, they did was to suggest another threshold of 16. And they have very good compelling data, in fact, because they studied a cohort of about 3,000 patients across different cancer types to do anti-PD-1 or anti-PD-L1. And there was a very distinct PFS, or progression-free survival, and overall survival, so benefit of these patients of high tumor burden, so of 16 or more mutations per megabase compared to the other two groups, 10 to 16 and less than 10. So very, very clear data. But then they took it to a different level. They also looked at the genomic data and transcriptomic data, and they showed that those tumors that have 16 mutations per megabase or more they also have more altered genomic molecules but also they also have an immune activation in terms of interferon gamma in terms of T-cell activity so it’s also biologically so they showed not only clinically in terms of clinical endpoints but biologically that those tumors are distinct. So I personally was convinced, my main comment, because I had the pleasure of discussing this study, one of my main questions is how to integrate other biomarkers, because I believe once we start integrating other biomarkers, the weight of each biomarker changes. And also, I’m not convinced that this is one threshold for all cancer types. So that’s kind of the… But in terms of the data, I think it’s beautiful.
This transcript is AI-generated. While we strive for accuracy, please verify this copy with the video.
Read more...
