American Association for Cancer Research
10780432ccr211982-sup-266691_2_supp_7351933_qyypyq.pdf (91.71 kB)

Supplementary Fig. 10 from EpiPanGI Dx: A Cell-free DNA Methylation Fingerprint for the Early Detection of Gastrointestinal Cancers

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journal contribution
posted on 2023-03-31, 22:53 authored by Raju Kandimalla, Jianfeng Xu, Alexander Link, Takatoshi Matsuyama, Kensuke Yamamura, M. Iqbal Parker, Hiroyuki Uetake, Francesc Balaguer, Erkut Borazanci, Susan Tsai, Douglas Evans, Stephen J. Meltzer, Hideo Baba, Randall Brand, Daniel Von Hoff, Wei Li, Ajay Goel

Comparison of several machine learning classifiers




Cancer Prevention Research Institute of Texas

National Department of Health


UK Government's Newton Fund and GSK



DNA methylation alterations have emerged as front-runners in cell-free DNA (cfDNA) biomarker development. However, much effort to date has focused on single cancers. In this context, gastrointestinal (GI) cancers 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. Herein, we performed a genome-wide DNA methylation analysis of multiple GI cancers to develop a pan-GI diagnostic assay. By analyzing DNA methylation data from 1,781 tumor and adjacent normal tissues, we first identified differentially methylated regions (DMR) between individual GI cancers and adjacent normal, as well as across GI cancers. We next prioritized a list of 67,832 tissue DMRs by incorporating all significant DMRs across various GI cancers to design a custom, targeted bisulfite sequencing platform. We subsequently validated these tissue-specific DMRs in 300 cfDNA specimens and applied machine learning algorithms to develop three distinct categories of DMR panels We identified three distinct DMR panels: (i) cancer-specific biomarker panels with AUC values of 0.98 (colorectal cancer), 0.98 (hepatocellular carcinoma), 0.94 (esophageal squamous cell carcinoma), 0.90 (gastric cancer), 0.90 (esophageal adenocarcinoma), and 0.85 (pancreatic ductal adenocarcinoma); (ii) a pan-GI panel that detected all GI cancers with an AUC of 0.88; and (iii) a multi-cancer (tissue of origin) prediction panel, EpiPanGI Dx, with a prediction accuracy of 0.85–0.95 for most GI cancers. Using a novel biomarker discovery approach, we provide the first evidence for a cfDNA methylation assay that offers robust diagnostic accuracy for GI cancers.

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