Updated Results on Lenvima-Keytruda Combo ‘Still Encouraging’ for Patients With Advanced Kidney Cancer, Expert Says

Although the data failed to identify a predictive biomarker in patients with advanced kidney cancer, an expert from Memorial Sloan Kettering Cancer Center in New York notes that the results indicate that no one should be excluded from receiving Lenvima plus Keytruda.

Results from an exploratory analysis of the KEYNOTE-146/study 111 trial demonstrated that Lenvima (lenvatinib) combined with Keytruda (pembrolizumab) induced high response rates across several groups of patients with advanced renal cell carcinoma — the most common type of kidney cancer — regardless of their biomarker status.

The findings — which were recently presented at the 2022 ASCO Genitourinary Cancers Symposium — should be reassuring to patients, according to lead study author Dr. Chung-Han Lee.

“It’s still encouraging,” Lee, an assistant attending physician in the Genitourinary Oncology Service at Memorial Sloan Kettering Cancer Center in New York, said in an interview with CURE®. “What we’ve noted is that there is no specific (patient) population that should be excluded from this type of treatment.”

The primary objective of the analysis was to identify if there was an association between patient outcomes and gene expression signatures generated via RNA sequencing and DNA variants for individual genes of interest via whole exome sequencing.

As of now, Lee explained, the field of kidney cancer is in its infancy stages in learning if there are good predictive biomarkers to identify which patients are likely to benefit from certain treatments.

“What we’ve done already is we’ve looked at various genomic and gene expression biomarkers in various settings. A lot of this comes from analysis of both phase 2 and phase 3 studies. Perhaps the most informative (data) recently has been looking within the first-line space,” he said. “And what they've demonstrated is there are specific gene expression patterns that have correlated with superior outcomes. However, where we really are lacking is the ability to translate this into clinical practice and having this type of information guide some of the clinical choices that we're making.”

In the past, Lee explained, providers have been able to analyze the genomics of patients who had yet to receive immunotherapy treatments and identify that high levels of HLA diversity were linked to an increased odds of response to Lenvima plus Keytruda.

In this exploratory analysis, Lee said, the study authors wanted to see if this prediction could be translated into patients who have been pretreated with immunotherapy.

“We're trying to understand whether or not treatment-naive tissue, can be predictive of outcomes for people who've already had multiple lines of systemic therapy,” he said. “So, we're trying to answer … whether or not there were good predictive biomarkers in the space and whether or not we could use older tissue? Or do the treatments that people have, potentially have an impact on whether or not some of the things that have worked can still continue to work?”

The phase 1b/2 KEYNOTE-146/study 111 trial comprised 147 patients (median age, 60 years; 78.2% male; 86.5% White), of which 80 (median age, 62 years; 75% male; 92.5% White) had available RNA sequencing and 60 had available whole exome sequencing (median age, 63.5 years; 78.3% male; 90% White).

A significant proportion of patients (71.4%) in the overall population had received prior anti–PD-1/PD-L1 therapy, as did patients in the RNA-sequencing population (87.5%) and whole exome sequencing population (88.3%). Few patients in the overall population, RNA-sequencing and whole exome sequencing population had yet to receive immunotherapy treatments (15.6%; 12.5%; 11.7%, respectively).

The findings showed that the objective response rate (proportion of patients who derive a complete or partial response to treatment) was similar among the three patient subgroups — 63.9% in the overall population, 66.2% in those with evaluable RNA sequencing and 68.3% in those with evaluable whole exome sequencing.

Moreover, the median progression-free survival (which is the time during and after treatment that a patient is alive without disease progression) was also similar across the three groups. The median progression-free survival in the overall population was 14.1 months, and 17.7 months in both the RNA-sequencing evaluable group and the whole exome sequencing-evaluable group.

The data also showed similar objective response rates across selected DNA variants including SETD2, BAP1, PBRM1 and VHL.

As for next steps, Lee noted that more analyses are warranted.

“It really is going to be looking to see whether or not we can get tissue that is closer to the time of systemic therapy and doing an analysis to see whether or not that is going to end up being predictive,” he said. “We certainly also want to see our ability to understand what are the changes that happened to the tumor as (a patient) gets treatment, because that may be very informative in terms of what the subsequent therapies you should think about.”

The hope, Lee explained, is to eventually identify a biomarker that is specific and sensitive enough that clinicians are able to make good clinical decisions.

Because, as Lee said, a provider may be able to tell a patient that they are more or less likely to receive benefit from a specific treatment. And although those results may be considered statistically significant in a research environment and lead to publication in a scientific journal, Lee stressed that information doesn’t mean anything to patients.

“(They’re) looking for a much more binary (decision),” he said. “Should I do this? Should I not do this? That’s where we need to be raising the bar to actually make a true impact for the patients.”

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