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I'm Edward Garin, uh, and I will be presenting now on precision patient selection. Um, this is, of course, going to focus on patients with non-small cell lung cancer. Before we begin, these are our disclosures. Please find here the detailed accreditation information. And finally, please take note of this information. We will begin with a polling question. Uh, this is a 60-year-old patient with non-small cell lung cancer, um, who has a tumor with PDL-1 expression of 0%. Uh, comprehensive genomic profiling reveals a very high non-synonymous tumor mutation burden. Um, we're discussing the rationale for utilizing immunotherapy despite the negative PDL-1 status. And Um, based on the foundational discovery cohorts evaluating the genomic landscape of non-small cell lung cancer, uh, from NARSvi and colleagues, uh, how does a non-synonymous, uh, tumor mutation burden correlate with clinical outcomes for patients treated with a PD1 pathway blockade? And the choices here are A, uh, high mutational burden is strongly associated with improved progression-free survival. Uh, B, high mutational burden only improves overall survival if the patient also has an EGFR mutation. C, high mutational burden is associated with worse PFS due to hyperprogression. Or D, high mutational burden has no correlation with progression-free survival. It only predicts toxicity. So, uh, standard of care for many years, uh, going into the mid 2000s was, uh, at least in the United States, a combination of carboplatin and paclitaxel, um, in this, uh, figure here, this is the pink bar, uh, noted as PC. Um, there was Uh, uh, what at the time was considered to be a major advance, uh, the addition of bevacizumab. Bevacizumab is a monoclonal antibody targeting VEGF. And, um, you can see in the dash blue line, the combination of bevacizumab, paclitaxel, and carboplatin. Uh, showed an improvement in overall survival. You can see the outcome data here with respect to response rate, um, overall survival, as well as progression-free survival, all favoring, uh, the bevacizumab, uh, arm. The, um, the curves eventually do appear to come together at the end. Um, but at least for the field psychologically, this was also a big advance is, in, in that it was the first time. Um, that we had really shown survival over a year, um, at that point in patients with, uh, stage 4 non-small cell lung cancer. Um, although it's not necessarily exactly what we think of when we think of, uh, precision medicine. Um, I think it's important to note that, uh, one thing that did shape the field is really two medicines, uh, that really separated the management of, uh, squamous cell disease from non-squamous, non-small cell lung cancer. One was the data I just showed about bevacizumab. Bevacizumab, Uh, when it was utilized in patients with squamous cell carcinoma, had an unacceptable rate of, uh, pulmonary hemorrhage, which unfortunately, in some cases was fatal. Um, and the other data set really was, uh, this study, which, uh, looked at cisplatin and Pemitrex, in which at the time was a fairly new chemotherapeutic versus cisplatin and, uh, gemcitabine. And what you can see here is that there were clear benefits with the pemitrexate, uh, arm doing, doing better in, in the adenocarcinoma. Whereas, um, really in the squamous, uh, it looked like the gemcitabine arm was Uh, a better arm. Then we saw what I would argue is real, uh, improvements in, uh, targeted therapy. But initially, we actually didn't know who the targets were. Um, this is a data set I was involved with years ago. And I just think graphically shows very nicely the outcome. You can see, um, On the left, you can see a patient who is, uh, you know, has extensive disease. You can see the results in the middle figure over here on the left. Um, actually, only a couple of weeks into therapy, um, followed by, by, by a couple of months, really, uh, significant improvement overall. Um, interestingly, this was with, uh, an EGFR inhibitor. And there was a time when there was really uh sort of uh quite considerable discussion about who are the patients who benefited from uh an EGFR inhibitor. There were some people who felt that it was really best assessed on clinical characteristics, some who were looking at EGFR, uh, gene copy number, like what is done with, uh, with the related gene HER2. Um, uh, and then that was really answered by, by Tony Mock and colleagues. Um, this study enrolled exclusively in East Asia. Patients had to have smoked less than 100 cigarettes per day. And what you can see here is if you look at the progression-free survival, when comparing, uh, dofinib in green to chemotherapy in yellow, On the left, you see these very bizarre progression-free survival curves that cross, uh, sort of right in the middle. And when you look at the right, you see why those curves crossed. And, um, they had, uh, sort of correlative data on many of the patients. And you can see that, uh, in the patients who had an EGFR mutation, the gefitinib, uh, the EGFR inhibitor in green, performed much better than chemotherapy. However, in the patients who did not have an EGFR mutation, Uh, the jafitinibine green was very, a very poor, uh, agent for treatment. And that is sort of two separate populations is what contributed to the overall sort of strange appearing progression for your survival curves. Um, EGFR was sort of the first, but you can see there were many different, um, of these. I list this as sort of a historical data set. Um, this was the Lung Cancer Mutation Consortium, which really broke, uh, patients with, uh, different Uh, mutations and adenocarcinoma into different sort of pie pieces here. Um, and, and the, this pie, uh, that you see, which separates different populations have become more refined over time. Um, and there even have been additional mutations that have been discovered. But these looking for driver mutations in many respects has revolutionized the management of non-small cell lung cancer. Um, well, the targeted therapy, uh, revolution was sort of, uh, ongoing. Another revolution in terms of selecting patients was coming in, uh, immunotherapy. Immunotherapy, um, is in many respects, a very different approach when compared to, um, sort of what we typically see for these targetable mutations, where we will have a tyrosine kinase inhibitor that directly blocks signaling. Um, but in this case, in many respects, the, the, the biomarkers still end up, uh, driving things. Here, you can see the original design of the keynote 001 study, which helped define the PDL1 biomarker for pembrolizumab. You can see as part of that, patients really were divided into three separate groupings. Those with PD1 expression in less than 1% of their cells, those with expression in 1 to 49% of their cells, and those with expression in at least half of their cells. Um, obviously, expression here is denoted in brown. The cutoff as part of that study was 50%. But what you can see is it's sort of a stepwise curve. Here, you see, um, in purple, the prevalence of PDL1 expression in all screened patients. Um, and then in blue, um, the response rate amongst those patients. And as you can see, um, by, by the, the blue here, um, the higher the patient's PDL one expression, the greater the likelihood that the patient would have a benefit from, uh, PD one inhibition. That was seen also with respect, uh, not only to response rate, but also progression-free survival shown here with the greater than 50% patients doing significantly better. And, uh, this also played out with respect to overall survival with those with high expression doing particularly well. At the time when, uh, when this was ongoing, people wouldn't Uh, weren't that excited about showing this data cause there was a lot of, uh, controversy about the PDL1 biomarker. But here you can see it compared to, uh, crizotinib, uh, in both, uh, on the left, AL gene rearranged, non-small cell lung cancer, and on the right, ROS1 gene rearranged, uh, non-small cell lung cancer. And as you can see, um, although pembrolizumab, uh, was not, the, the PDL1, uh, 50% or greater was not quite as predictive. Um, still, there are a lot of similarities between these curves. Um, and the time has sort of proven that this is a, uh, biomarker that has sort of, uh, continued to be part of our management. So it is not the only biomarker that we look at. Um, obviously, across histologies, people have looked at microsatellite instability. That tends not to be seen much very often with lung cancer. But one of the things that became very clear early on, um, this is data from the TCGA. And if you look, um, this is showing the number of mutations, uh, per tumor. And what you can see is melanoma on the right, followed by lung squamous cell, then lung adeno, um, then bladder. In many respects, it looks like you are going through, um, the, the approvals for PD one inhibitors, uh,