Brief Report: Methylation-Based ctDNA Serial Monitoring Correlates With Immunotherapy Response in NSCLC

This article will evaluate methylated circulating tumor DNA to monitor response to anti-PD1 based immunotherpy in non-small cell lung cancer. Purpose: Circulating tumor DNA (ctDNA) can reflect the genetic and epigenetic composition of malignancies and can serve as a noninvasive biomarker for cancer diagnostics and monitoring. This study aimed to evaluate the utility of a methylation-based ctDNA assay as a predictive tool in non-small cell lung cancer (NSCLC) anti-PD1 based immunotherapy monitoring. Methods: We evaluated a cohort of 20 patients with NSCLC treated with anti-PD1 based immunotherapy that had both baseline and follow-up blood draws as well as outcome data available. Tumor Methylation Scores (TMS) were measured with an amplicon-based, multiplexed cfDNA assay that utilizes quantitative counting templates (QCTs) in conjunction with next-generation sequencing to count the number of methylated molecules at more than 500 genomic locations that are hypermethylated in cancer tissue. The association between TMS and real-world progressionfree survival (rwPFS) on therapy was conducted using Cox proportional hazards model and plotted using the KaplanMeier method. Results: The change in TMS measured 4-10 weeks post-treatment initiation strongly correlated with immunotherapy response, as measured by rwPFS (P < 0.0001), compared to a weaker correlation of imaging RECIST v1.1 measurements with rwPFS (P = 0.55). Furthermore, TMS tracked with tumor burden on therapy in real-world cases. Conclusions: In this real-world dataset of NSCLC patients treated with anti-PD1 immunotherapy regimens, the TMS score measured within a 4-10 week window after treatment initiation can be predictive of response to therapy. Beyond this window, the TMS score can be associated with rwPFS and tumor dynamics. Early evidence suggests that changes in the methylation profile may be informative for monitoring occurrence of new somatic mutations. The cases presented demonstrate the application of using TMS for serial therapeutic response monitoring.