ESMO Virtual Congress 2020: Invited Discussant: Predictive Biomarkers in Metastatic Renal Cell Carcinoma

(UroToday.com) Dr. Walter Berger began his review with abstract 700O, the authors tested the predictive ability of three signatures: (1) a gene expression signature consistent with Teffector activity from IMmotion150 that when present enriched for responders to atezolizumab and bevacizumab. (2) a gene expression signature suggestive of Angiogenesis from IMmotion150 that when present in samples enriched for response to sunitinib. (3) the Kidney ccRCC Immune Classification (KIC) signature that identifies high or low levels of immune and stromal cell populations in each patient biopsy.



These signatures were applied to patients from the NIVOREN GETUG-AFU26 study, a real-world phase 2 study of nivolumab in ccRCC. The data presented suggest that patient samples with high Teffector signature and low Angiogenesis signature had higher response rates to nivolumab, and patient samples with KIC Immune-high and stromal-low cell population signatures also had higher response rates to nivolumab. Interestingly, the KIC Immune-high/stromal-low samples and Teff high/Angio low samples were not the same.


Dr. Berger raised several questions from the presented data including (1) What is the interplay between the Teff and Angio signatures, as the presence of a high Angio signature resulted in fewer responses to nivolumab even if Teff signature expression was high? (2) Is it feasible to apply genome-wide expression signatures in routine clinical practice? (3) How might these signatures impact therapy choice in the modern era of combined tyrosine kinase inhibitors and immune checkpoint inhibitors? Further study is required to address these issues.

He then went on to discuss abstract 701O looking at ctDNA-detected alterations in patients with mRCC and concordance between ctDNA and tissue FFPE profiling. These data suggest that ctDNA can detect dynamic changes in genomic alterations over time, though the concordance between tissue profiling and ctDNA is not high. Many questions arise, including (1) How much of the discordance is due to biology versus sequencing method? (2) Do changes in ctDNA profile reflect sampling heterogeneity, tumor heterogeneity, or response to treatment? (3) How do changes in ctDNA profile relate to treatment outcomes, especially immunotherapy outcomes?

Overall, Dr. Berger felt that these abstracts represented interesting data surrounding predictive biomarkers in mRCC, and further data will help clarify the eventual predictive utility of various gene expression profiles and ctDNA sampling.

Presented by: Walter Berger, PhD, Professor of Applied and Experimental Oncology, Institute of Cancer Research, Medical University Vienna, Austria

Written by: Alok Tewari, MD, PhD, Medical Oncologist at the Dana-Farber Cancer Institute, at the 2020 European Society for Medical Oncology Virtual Congress (#ESMO20), September 19th-September 21st, 2020.



Related Content:


ESMO Virtual Congress 2020: Clear Cell Renal Cell Carcinoma Immune Classification Enhances the Predictive Value of T Effector and Angiogenesis Signatures in Response to Nivolumab

ESMO Virtual Congress 2020: Assessment of Circulating Cell-Free Tumor DNA in 847 Patients with Metastatic Renal Cell Carcinoma and Concordance with Tissue-Based Testing