Tumor mutational burden, PD-1, negative Wnt/β-catenin regulators, and positive MHC class II antigen presentation regulators as predictors of longer survival after immune checkpoint inhibitors across cancers: A comprehensive analysis of 400 immunity biomarkers.

Abstract

2625 Background: Immune checkpoint inhibitors (ICIs) have become a standard treatment, yet no universal biomarker consistently predicts prolonged survival across cancer types. While multiple biomarkers have been proposed, they have not been systematically compared or evaluated in a tumor-agnostic manner. This study comprehensively investigates the impact of 397 immunoregulatory transcripts and other factors on survival in patients with cancer treated with ICIs. Methods: The Profile-Related Evidence Determining Individualized Cancer Therapy (PREDICT, NCT02478931) study enrolled 514 patients, including 217 treated with ICIs. The study analyzed the effect of bulk tumor transcriptomic expression of 397 immunoregulatory factors plus microsatellite instability [MSI], tumor mutational burden [TMB], and PD-L1 immunohistochemistry (total = 400 biomarkers) along with cancer type on overall survival (OS) and progression-free survival (PFS) following ICI therapy. Transcriptome expression was categorized into three groups based on percentile ranks compared to 735 controls spanning 35 histologies: “High” (75–100th percentile), “Intermediate” (25–74th percentile), and “Low” (0–24th percentile). Hazard ratios (HRs) for OS and PFS were estimated using a Cox regression model. Storey’s q-value correction accounted for multiple testing, and a multivariable analysis was performed to explore novel biomarkers and different TMB cutoffs (10 [mutations/mb], 16, 20, and continuous). Results: In the 217 ICI-treated patients (median age: 61.2 years; women: 56.2%), the most common ICI was anti-PD-1 therapy (83.4%, N = 181), and the median TMB was 5.0 mut/mb. MSI was detected in 9 patients (4.1%). In multivariable analysis adjusting for age, sex, significant markers (q < 0.05) and co-inhibitory checkpoints (p < 0.1 in univariate analysis), and TMB (with different cutoffs and as a continuous variable), high expression of CIITA, KREMEN1, and PD-1 (but not PD-L1), as well as higher TMB (≥10 mut/mb, ≥16 or ≥20 or continuous), were independently associated with longer OS (p≤0.05). In the PFS analysis, high KREMEN1 expression and higher TMB (≥16 or ≥20 or continuous but not ≥10 mut/mb) also independently correlated with longer PFS. Cancer type was not independently correlated with outcome. Conclusions: Our comprehensive biomarker analysis identified novel factors associated with ICI efficacy. In addition to confirming the predictive role of TMB, the study highlights CIITA, a regulator of MHC class II expression that enhances tumor antigen presentation, and KREMEN1, a suppressor of Wnt/β-catenin signaling that preserves antitumor immunity, as well as the PD-1 checkpoint, as predictive biomarkers for ICI therapy across cancers. Clinical trial information: NCT02478931 .