Abstract A027: DNA methylation-based fetal niche and repetitive element profiling predict overall survival in clear cell renal cell carcinoma

Abstract

Abstract Background: Fetal cell origin DNA methylation signature (FCO) estimates the proportion of cells in a mixture of cell types that are of fetal origin. Machine learning-based methods can predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. In this study, we applied the FCO signature and RE methylation prediction to clear cell renal cell carcinoma (ccRCC) samples to study FCO and RE alterations in ccRCC carcinogenesis and survival. Methods: The FCO algorithm was applied to 47 ccRCC tumor samples and four adjacent normal samples from the Dartmouth Renal Tumor Biobank. 319 ccRCC tumor samples and 160 adjacent normal samples from The Cancer Genome Atlas (TCGA) were used for external validation. Linear regression models were used to compare the FCO signal between ccRCC tumor and normal samples adjusting for sex and age. Cox proportional hazard models were employed to study FCO with overall survival outcome in ccRCC samples, adjusting for sex, age, and tumor stage. The survival groups were dichotomized to FCO = 0% vs. FCO > 0%. The REMP package from Bioconductor was used to project LINE1 element methylation in 47 ccRCC samples. LINE1 median level methylation was compared by tumor grade. Cox proportional hazard models were employed to study LINE1 methylation level as a continuous variable with overall survival in ccRCC samples, adjusting for sex, age, and tumor stage. Results: The FCO signal is significantly lower in Dartmouth Renal Tumor Biobank archived ccRCC tumor samples compared to adjacent normal samples (Δ = 42.9%, p = 5.7e-11). By comparing the overall survival between FCO = 0% and FCO > 0% groups, we observed significantly worse survival outcomes in ccRCC patients with zero levels of FCO (HR: 2.46, 95% CI: 1.16, 5.18). Similar results were observed in TCGA samples. A significant decrease of FCO was found in ccRCC tumor samples compared to adjacent normal samples (Δ = 32.9%, p = 2.2e-308). A 1% increase in FCO is significantly associated with a better survival outcome (HR: 0.97, 95%CI 0.95, 0.99). For RE methylation prediction, we observed that the median LINE1 methylation level decreases with ccRCC tumor grade. A higher level of LINE1 median methylation is significantly associated with a better survival outcome (p = 0.01). Conclusion: Normal kidney samples possess a fetal niche reflected by DNA methylation, while ccRCC tumorigenesis depletes the fetal cells in normal kidneys. The depletion of FCO is associated with worse survival outcomes in ccRCC. The repetitive element LINE1 methylation level decreases with tumor grade and is related to ccRCC survival outcomes. These findings promise future investigations on the epigenetically targetable fetal niche and repetitive elements in ccRCC carcinogenesis and therapeutics. Citation Format: Ze Zhang, Lucas Salas. DNA methylation-based fetal niche and repetitive element profiling predict overall survival in clear cell renal cell carcinoma [abstract]. In: Proceedings of the AACR Special Conference: Advances in Kidney Cancer Research; 2023 Jun 24-27; Austin, Texas. Philadelphia (PA): AACR; Cancer Res 2023;83(16 Suppl):Abstract nr A027.