DNA Methylation Biomarkers Predict Objective Responses to PD-1/PD-L1 Inhibition Blockade

Abstract

Immune checkpoint inhibitor (ICI) treatment could bring long-lasting clinical benefits to patients with metastatic cancer. However, only a small proportion of patients respond to PD-1/PD-L1 blockade, so predictive biomarkers are needed. Here, based on DNA methylation profiles and the objective response rates (ORRs) of PD-1/PD-L1 inhibition therapy, we identified 269 CpG sites and developed an initial CpG-based model by Lasso to predict ORRs. Notably, as measured by the area under the receiver operating characteristic curve (AUC), our model can produce better performance (AUC = 0.92) than both a model based on tumor mutational burden (TMB) (AUC = 0.77) and a previously reported TMB model (AUC = 0.71). In addition, most CpGs also have additional synergies with TMB, which can achieve a higher prediction accuracy when joined with TMB. Furthermore, we identified CpGs that are associated with TMB at the individual level. DNA methylation modules defined by protein networks, Kyoto Encylopedia of Genes and Genomes (KEGG) pathways, and ligand-receptor gene pairs are also associated with ORRs. This method suggested novel immuno-oncology targets that might be beneficial when combined with PD-1/PD-L1 blockade. Thus, DNA methylation studies might hold great potential for individualized PD1/PD-L1 blockade or combinatory therapy.

Integration of Epigenetic Mechanisms into Non-Genotoxic Carcinogenicity Hazard Assessment: Focus on DNA Methylation and Histone Modifications

“…Overall, these experiments suggest that DNA methylation is one of the mechanisms that regulates PD-L1 expression, and in some cases, the promoter is the influential locus but in others, distant regulatory intergenic and intronic loci needs further investigation. A DNA methylation biomarker based on 269 CpG sites was recently proposed to predict success of PD-1/PD-L1 inhibition therapy [539]. Other ICL genes for which promoter methylation regulates their expression include Ctla4 (cytotoxic T lymphocyte-associated protein 4) [531].…”

Epigenetic Mechanisms of Resistance to Immune Checkpoint Inhibitors

“…However, its predictive value should be evaluated in prospective studies. In 2019, Xue et al [ 173 ] analyzed DNA methylation in 18 cancer types and identified epigenetic signatures based on the methylation status of 269 CpG (corresponding to 191 genes). The signatures were related to the PD-1/PD-L1 inhibitor objective response rates (ORR).…”

Progress Toward Identifying Exact Proxies for Predicting Response to Immunotherapies

“…DNA methylation has been studied in 18 cancer types in order to establish a relevant profile which could be correlated with the response rates to CPIs. This profile covers 191 genes from which 269 CpG signatures pertain to the developed profile (Xue et al, 2019). The CpG model out-performed the TMB score in many cancer types: adrenocortical-, bladder-, breast-, cervical-, endocervical-, esophageal, endometrial cancer, GBM, head and neck squamous cell carcinoma, kidney-, liver-lung cancer, mesothelioma, ovarian-, pancreatic cancer, melanoma and uveal melanoma (Xue et al, 2019).…”

“…This profile covers 191 genes from which 269 CpG signatures pertain to the developed profile (Xue et al, 2019). The CpG model out-performed the TMB score in many cancer types: adrenocortical-, bladder-, breast-, cervical-, endocervical-, esophageal, endometrial cancer, GBM, head and neck squamous cell carcinoma, kidney-, liver-lung cancer, mesothelioma, ovarian-, pancreatic cancer, melanoma and uveal melanoma (Xue et al, 2019). This type of an epigenetic assessment could be applied in conjunction with other immuno oncology biomarkers (such as TMB), to enable achieving better prediction performance in assisting oncologists' selection of patients with higher likelihood of benefiting from PD-1/PD-L1 inhibition therapy.…”