Abstract 1084: EpiPanGI-Dx: A cell-free DNA methylation fingerprint for the early detection of gastrointestinal cancers
Authors: Raju Kandimalla, Jianfeng Xu, Alexander Link, Takatoshi Matsuyama, Kensuke Yamamura, Iqbal Parker, Hiroyuki Uetake, Eva Hernandez-Illan, Juanjo Lozano, Erkut Borazanci, Susan Tsai, Douglas Evans, Stephen J. Meltzer, Hideo Baba, Randall Brand, Daniel Von Hoff, Francesc Balaguer, Wei Li, Ajay Goel
Journal: Cancer Research (2020)

Abstract Purpose: In view of high cancer-specificity, DNA methylation alterations have emerged as front-runners in biomarker development, especially as cell-free DNA (cf-DNA) biomarkers for early detection of cancer. However, much effort to date has focused on developing cancer type-specific biomarkers, but have not explored the possibility of developing a pan-cancer diagnostic assay. In this context, gastrointestinal (GI) cancers, including colorectal (CRC), esophageal squamous cell and adenocarcinoma (ESCC and EAC), gastric (GC), liver (HCC) and pancreatic ductal adenocarcinoma (PDAC) constitute the second leading cause of cancer-related deaths worldwide; yet there is no blood-based assay for the early detection and population screening of GI cancers. Here we undertook a genomewide DNA methylation analysis for multiple GI cancers, followed by development of a novel cf-DNA methylation biomarker panels for the early detection of GI cancers (EpiPanGI Dx). Experimental design: By analyzing the DNA methylation data from 1940 tumor and adjacent normal tissues from TCGA and GSE72872 datasets, we first identified the differentially methylated regions (DMRs) between individual GI cancers and adjacent normal tissues, as well as across all GI cancers. We next prioritized a list of DMRs encompassing a 25.6 Mb genomic region by incorporating all identified DMRs across various GI cancers to design a custom SeqCap Epi, targeted bisulfite sequencing platform, optimized for analysis of low-abundance cf-DNA derived from plasma specimens. Using this approach, we sequenced 300 plasma specimens from all GI cancers, as well as age-matched healthy controls, with a 40X coverage. Finally, using machine learning algorithms, we identified unique DMR panels for the detection of various GI cancers. Results: Methylation profiling data from various GI tissues led to the identification of 67,832 DMRs with an adjusted p&amp;lt;0.001 and a delta beta value of 0.2, in all the comparisons across all GI cancers. Subsequent investigation of these tissue-specific DMRs in 300 cf-DNA specimens using our custom SeqCap panel led to the development of three distinct categories of DMR panels: 1) Cancer-specific biomarker panels with an AUC values of 0.98 (CRC), 0.94 (ESCC), 0.90 (EAC), 0.90 (GC), 0.98 (HCC), and 0.85 (PDAC); 2) A pan-GI biomarker panel that detected all GI cancers with an AUC of 0.90; and 3) A multi-cancer prediction panel, EpiPanGI Dx, with a prediction accuracy around 0.85 for most GI cancers. All three groups of DMR panels when trained and tested in the cf-DNA cohorts achieved excellent diagnostic accuracy with AUC values ranging from 0.74-0.98, even for each of the early-stage GI cancers. Conclusions: Utilizing a novel biomarker discovery approach, we provide first evidence for cell-free DNA methylation biomarkers that offer a robust diagnostic accuracy for the identification of specific cancer types, and demonstrate their potential clinical application as a Pan-cancer panel for the early detection of all gastrointestinal cancers. Citation Format: Raju Kandimalla, Jianfeng Xu, Alexander Link, Takatoshi Matsuyama, Kensuke Yamamura, Iqbal Parker, Hiroyuki Uetake, Eva Hernandez-Illan, Juanjo Lozano, Erkut Borazanci, Susan Tsai, Douglas Evans, Stephen J. Meltzer, Hideo Baba, Randall Brand, Daniel Von Hoff, Francesc Balaguer, Wei Li, Ajay Goel. EpiPanGI-Dx: A cell-free DNA methylation fingerprint for the early detection of gastrointestinal cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1084.