IARC presentation
Background
Circadian biology is increasingly recognized as a critical determinant of cancer progression and treatment response. However, little is known about how biological timing influences the efficacy of immune checkpoint inhibition, particularly regarding PDCD1 (programmed cell death protein 1). PDCD1 encodes the PD-1 receptor, a major target for immunotherapies in lung cancer. Since immune function and gene expression follow circadian rhythms, understanding time-of-day variations in PDCD1 regulation is essential for optimizing therapeutic efficacy.
Objectives
We investigated whether circadian fluctuations in PDCD1 regulation could inform optimal dosing windows for PD-1–targeted therapy. The primary objective was to develop a data-driven framework to determine if genetically predicted PDCD1 modulation at different circadian phases causally influences lung cancer survival.
Methods
We performed sinusoidal genome-wide association studies (GWAS) of circulating PDCD1 protein levels using data from the UK Biobank. Time of day of blood draw was transformed into cosine and sine interaction terms to identify rhythmic genetic influences. We identified novel cis and trans variants regulating PDCD1 expression in a time-dependent manner. Variant effect estimates from the peak and trough of genetically controlled expression were extracted and incorporated into a chronotherapy Mendelian randomization (MR) framework. We then compared these phase-specific effects against standard MR analysis to test associations with lung cancer survival.
Results
The analysis revealed striking differences in survival outcomes based on circadian timing. Provisional results yielded a Hazard Ratio (HR) of 0.757 for a standard MR of PDCD1 on lung cancer survival, the chronotherapy MR framework demonstrated significant phase-dependent variation. The protective effect was most pronounced at the trough of genetically predicted expression, with an HR of 0.71. In contrast, at the peak of expression, the effect reversed, resulting in an HR of 1.33. These fluctuations suggest that the therapeutic window for PD-1 inhibition is highly sensitive to biological timing.
Conclusions and Implications for Practice or Policy
These findings validate the potential of chronogenomic MR to generate hypotheses regarding optimal dosing times for immunotherapies. By integrating genetic, proteomic, and temporal data, we demonstrated that large-scale biobank resources can uncover temporal dimensions of drug target biology. The results imply that aligning treatment with specific circadian phases, specifically the peak of PDCD1 expression, could significantly enhance survival outcomes. Future work will extend this framework to additional immunotherapy targets and well-powered positive controls, such as statins, while incorporating longitudinal survival data to refine chronotherapeutic predictions for clinical practice.