The landscape of objective response rate of anti-PD-1/L1 monotherapy across 31 types of cancer: a system review and novel biomarker investigating

Abstract

Background: Immune checkpoint inhibitors (ICIs) have dramatically changed the landscape of cancer treatment. However, only a few patients respond to ICI treatment. Thus, uncovering clinically accessible ICI biomarkers would help identify which patients will respond well to ICI treatment. A comprehensive objective response rate (ORR) data of anti-PD-1/PD-L1 monotherapy in pan-cancer would offer the original data to explore the new biomarkers for ICIs.

Methods: We systematically searched PubMed, Cochrane, and Embase for clinical trials on July 1, 2021, limited to the years 2017-2021, from which we obtained studies centering around anti-PD-1/PD-L1 monotherapy. Finally, 121 out of 3099 publications and 143 ORR data were included. All of the 31 tumor types/subtypes can be found in the TCGA database. The gene expression profiles and mutation data were downloaded from TCGA. A comprehensive genome-wide screening of ORR highly correlated mutations among 31 cancers was conducted by Pearson correlation analysis based on the TCGA database.

Results: According to the ORR, we classified 31 types of cancer into high, medium, and low response types. Further analysis uncovered that "high response" cancers had more T cell infiltration, more neoantigens, and less M2 macrophage infiltration. A panel of 28 biomarkers reviewed from recent articles were investigated with ORR. We also found the TMB as a traditional biomarker had a high correlation coefficient with ORR in pan-cancer, however, the correlation between ITH and ORR was low across pan-cancer. Moreover, we primarily identified 1044 ORR highly correlated mutations through a comprehensive screening of TCGA data, among which USH2A, ZFHX4 and PLCO mutations were found to be highly correlated to strengthened tumor immunogenicity and inflamed antitumor immunity, as well as improved outcomes for ICIs treatment among multiple immunotherapy cohorts.

Conclusion: Our study provides comprehensive data on ORR of anti-PD-1/PD-L1 monotherapy across 31 tumor types/subtypes and an essential reference of ORR to explore new biomarkers. We also screened out a list of 1044 immune response related genes and we showed that USH2A, ZFHX4 and PLCO mutations may act as good biomarkers for predicting patient response to anti-PD-1/PD-L1 ICIs.

Keywords: Genetic mutation; Immune response; Objective response; Overall survival; PD-1/PD-L1.