Abstract
We evaluated the ability of plasma chromatin immunoprecipitation and sequencing (ChIP-seq) and methylated DNA immunoprecipitation sequencing (MeDIP-seq) to detect translocation renal cell carcinoma (tRCC), to distinguish tRCC from clear cell renal cell carcinoma (ccRCC), and to monitor the disease evolution. tRCC is an aggressive subtype of kidney cancer usually driven by a fusion involving the TFE3 gene. Due to histologic overlap with other subtypes of RCC, tRCC is frequently misclassified. Methods for accurate diagnosis and detection of this molecularly distinct entity are therefore a pressing need. Most cell-free DNA (cfDNA) technologies are genomic-based and not optimized for tRCC as molecular fusions are not easily detected in circulating tumor DNA (ctDNA), and 50% of tRCC cases do not have other alteration. Epigenomic profiling of ctDNA via ChIP-seq has recently emerged as a powerful tool to detect and molecularly subtype cancers and may offer a more sensitive and specific detection of fusion- driven tumors. We first identified differentially methylated regions (DMRs) and regulatory elements (REs) specific to tRCC vs. ccRCC via MeDIP-seq and H3K4me3/H3K27Ac ChIP-Seq, of 4 tRCC and 5 ccRCC cell lines. We also identified TFE3 transcription factor binding sites (TFBS) via TFE3 ChIP-seq in 3 tRCC cell lines. We collected 30 plasma samples from metastatic patients with tRCC, 12 with ccRCC and 9 healthy individuals. Ultra low pass whole genome sequencing (ulpWGS) was performed to infer ctDNA fraction (TF), and cfMeDIP-seq, H3K4me3/H3K27ac cfChIP-seq for epigenomic profiling. Signal at tRCC-specific regions derived from cell lines profiling was aggregated for each mark and normalized to common active REs/methylated regions and used to discriminate tRCC vs. ccRCC vs. healthy plasma. Classification performance was evaluated using the area under the receiver operating characteristic (AUROC) curve. Overall 10/30 tRCC and 5/12 ccRCC samples had >3% TF by ulpWGS. H3K4me3 cfChIP-seq signal was significantly higher in all tRCC samples compared to healthy plasma (AUROC=1) at tRCC-specific REs and TFE3 TFBS. Furthermore, H3K27ac and H3K4me3 cfChIP-seq signal in plasma were also significantly higher at tRCC-specific REs and TFE3 TFBS in tRCC samples compared to ccRCC (AUROC=0.86-0.89). A cfDNA-based classifier combining the four scores distinguished tRCC from ccRCC with an AUROC=0.94. MeDIP-seq could not discriminate between tRCC and ccRCC. Moreover, three patients had multiple time points, and the integrated cfChIP H3K4me3/H3K27Ac score was able to accurately monitor the evolution of the disease. In conclusion, although a majority of tRCC plasma samples profiled had TF <3%, all could be distinguished from healthy samples on the basis of cfChIP. The combined score of H3K27ac and H3K4me3 cfChIP-Seq was also discriminatory for tRCC vs. ccRCC. Epigenomic profiling of cfDNA appears as a powerful tool for both detection of tRCC and discrimination from ccRCC/healthy plasma, with potential implications for diagnosis, disease monitoring and guiding therapy.
Citation Format: Simon Garinet, Karl Semaan, John Caniff, Noa Phillips, Jacob Berchuck, Jiao Li, Kevin Lyons, Ananthan Sadagopan, Brad Fortunato, Mary Lee, Jack Horst, Rachel Trowbridge, Ji-Heui Seo, Matthew Freedman, Toni Choueiri, Sylvan Baca, Srinivas Viswanathan. Detection and monitoring of translocation renal cell carcinoma via epigenomic profiling of cell-free DNA [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B035.