Soluble Immune Checkpoint Molecules as Predictors of Efficacy in Immuno-Oncology Combination Therapy in Advanced Renal Cell Carcinoma

Author:

Ueda Kosuke1ORCID,Uemura Keiichiro1,Ito Naoki1,Sakai Yuya1,Ohnishi Satoshi1,Suekane Hiroki1,Kurose Hirofumi1,Hiroshige Tasuku1,Chikui Katsuaki1,Nishihara Kiyoaki1,Nakiri Makoto1ORCID,Suekane Shigetaka1,Ogasawara Sachiko2,Yano Hirohisa2,Igawa Tsukasa1

Affiliation:

1. Department of Urology, Kurume University School of Medicine, Kurume 830-0011, Japan

2. Department of Pathology, Kurume University School of Medicine, Kurume 830-0011, Japan

Abstract

Immuno-oncology (IO) combination therapy is the first-line treatment for advanced renal cell carcinoma (RCC). However, biomarkers for predicting the response to IO combination therapy are lacking. Here, we investigated the association between the expression of soluble immune checkpoint molecules and the therapeutic efficacy of IO combination therapy in advanced RCC. The expression of soluble programmed cell death-1 (sPD-1), soluble programmed cell death ligand-1 (sPD-L1), soluble PD-L2 (sPD-L2), and lymphocyte activation gene-3 (sLAG-3) was assessed in plasma samples from 42 patients with advanced RCC who received first-line IO combination therapy. All IMDC risk classifications were represented among the patients, including 14.3, 57.1, and 28.6% with favorable, intermediate, and poor risk, respectively. Univariate analysis revealed that prior nephrectomy, sPD-L2 levels, and sLAG-3 levels were significant factors affecting progression-free survival (PFS), whereas multivariate analyses suggested that sPD-L2 and sLAG-3 levels were independent prognostic factors for PFS. In a univariate analysis of the overall survival, prior nephrectomy and sPD-L2 levels were significant factors; no significant differences were observed in the multivariate analysis. No significant correlation was observed between the sPD-L2 and sLAG-3 levels and PD-L2 and LAG-3 expression via immunohistochemistry. In conclusion, sPD-L2 and sLAG-3 expression may serve as a potential biomarker for predicting IO combination therapy efficacy.

Funder

JPSS KAKENHI

Publisher

MDPI AG

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