Clinical characteristics and influencing factors of anti-PD-1/PD-L1-related severe cardiac adverse event: based on FAERS and TCGA databases

• Published in: Scientific reports 2024-09, Vol.14 (1), p.22199-18, Article 22199
• Main Authors: Cheng, Xitong, Lin, Jierong, Wang, Bitao, Huang, Shunming, Liu, Maobai, Yang, Jing
• Format: Article
• Language: English
• Subjects: 631/250; 631/67; 692/499; Adolescent; Adult; Adverse Drug Reaction Reporting Systems; Adverse events; Aged; Aged, 80 and over; Anti-inflammatory agents; Anti-PD-1/PD-L1; Antibiotics; Apoptosis; B7-H1 Antigen - antagonists & inhibitors; B7-H1 Antigen - genetics; Cell death; Databases, Factual; FAERS; Female; Genetic analysis; Heart diseases; Humanities and Social Sciences; Humans; Immune Checkpoint Inhibitors - adverse effects; Immunosuppressive agents; Influence factors; Male; Middle Aged; mRNA; multidisciplinary; Myocarditis; Nonsteroidal anti-inflammatory drugs; PD-1 protein; PD-L1 protein; Programmed Cell Death 1 Receptor - antagonists & inhibitors; Programmed Cell Death 1 Receptor - genetics; Proton pump inhibitors; Receptor density; Regression analysis; Science; Science (multidisciplinary); Severe cardiac adverse events; Signal transduction; TCGA; Young Adult
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-72864-4

Combining the FDA Adverse Event Reporting System (FAERS) and the Cancer Genome Atlas (TCGA) databases, we aim to explore the factors that influence anti-programmed cell death protein-1 inhibitors/programmed death-ligand-1 (PD-1/PD-L1) related severe cardiac adverse events (cAEs). We obtained anti-PD-1/PD-L1 adverse event reports from January 2014 to December 2022 from the FAERS database. Disproportionality analysis was performed to find anti-PD-1/PD-L1-related cAEs using the proportional reporting ratio (PRR). We were exploring influencing factors based on multivariate logistic regression analysis. Finally, we utilized a strategy that combines FAERS and TCGA databases to explore the potential immune and genetic influencing factors associated with anti-PD-1/PD-L1-related severe cAEs. Reports of severe cAEs accounted for 7.10% of the overall anti-PD-1/PD-L1 adverse event reports in the FAERS database. Immune-mediated myocarditis (PRR = 77.01[59.77–99.23]) shows the strongest toxic signal. The elderly group (65–74: OR = 1.34[1.23–1.47], ≥ 75: OR = 1.64[1.49–1.81]), male (OR = 1.14[1.05–1.24]), anti-PD-L1 agents (OR = 1.17[1.03–1.33]), patients with other adverse events (OR = 2.38[2.17–2.60]), and the concomitant use of proton pump inhibitor (OR = 1.29[1.17–1.43]), nonsteroidal anti-inflammatory drugs (OR = 1.17[1.04–1.31]), or antibiotics (OR = 1.24[1.08–1.43]) may increase the risk of severe cAEs. In addition, PD-L1 mRNA (Rs = 0.71, FDR = 2.30 × 10 − 3 ) and low-density lipoprotein receptor-related protein 3 (LRP3) (Rs = 0.82, FDR = 2.17 × 10 − 2 ) may be immune and genetic influencing factors for severe cAEs. Severe cAEs may be related to antigen receptor-mediated signalling pathways. In this study, we found that age, gender, anti-PD-1/PD-L1 agents, concomitant other adverse events, concomitant medication, PD-L1 mRNA, and LRP3 may be influencing factors for anti-PD-1/PD-L1-related severe cAEs. However, our findings still require a large-scale prospective cohort validation.