CABOSUN was a randomized phase II study which brought cabozantinib to the front line and compared it head to head against sunitinib. 157 patients were randomly assigned to therapy, and compared with sunitinib, cabozantinib increased median PFS (8.2 months vs 5.6 months, HR, 0.66, P = .012). The overall response rate to cabozantinib was 33% vs 12% for sunitinib. Based on this study, cabozantinib gained a role for front-line therapy of patients with intermediate or poor-risk mRCC.
This study examined tissue from both of these studies in order to determine whether or not PD-L1 expression could be a prognostic OR predictive biomarker for cabozantinib.
The investigators utilized a novel digital image analysis algorithm to assign a PD-L1 score for both tumor cells and immune cells. PFS and OS associations with PD-L1 were analyzed Cox regression.
Cabozantinib was associated with improved PFS and OS compared with everolimus or sunitinib, regardless of PD-L1 expression.
This study uses a novel imaging method to assess for PD-L1 status, utilizing a dual IHC staining method and then digital analysis. PD-L1 was not predictive for individualized therapy as it improved overall survival and progression-free survival over everolimus and sunitinib, irrespective of PD-L1 status. Much controversy exists over PD-L1 assays, and this novel method of scoring PD-L1 may prove useful in standardizing PD-L1 for future studies. This technology has utilized in cutaneous melanoma and several different groups are evaluating this technology as PD-L1 scoring guides therapy for certain tumor types2-4.
Presented by: Toni K. Choueiri, MD, Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, Massachusetts
Written by: Jason Zhu, MD. Fellow, Division of Hematology and Oncology, Duke University @TheRealJasonZhu at the 2018 European Society for Medical Oncology Congress (#ESMO18), October 19-23, 2018, Munich Germany
1. Choueiri TK, Escudier B, Powles T, et al. Cabozantinib versus everolimus in advanced renal cell carcinoma. The New England journal of medicine 2015;373:1814-23.
2. Koelzer VH, Gisler A, Hanhart JC, et al. Digital image analysis improves precision of PD‐L1 scoring in cutaneous melanoma. Histopathology 2018.
3. Kearney S, Black J, Aeffner F, Black J, Pratte L, Krueger J. Abstract 4582: Evaluating benefits of PD-L1 image analysis for the clinical setting. Cancer Research 2017;77:4582-.
4. Martin NT, Black JC, Pollack Z, Aeffner F, Krueger J. Abstract 661: Evaluating harmonization of PD-L1 assays using image analysis. Cancer Research 2017;77:661.
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