Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection

Karen Funderburk
,
Sara R. Bang-Christensen
,
Brendan F. Miller
,
Hua Tan
ORCID logo ,
Gennady Margolin
,
Hanna M. Petrykowska
,
Catherine Baugher
,
Nader Jameel
,
David Holland
,
Naomi S. Altman
,
Laura Elnitski
*
Version 1 : Received: 23 August 2023 / Approved: 24 August 2023 / Online: 28 August 2023 (10:22:29 CEST)

A peer-reviewed article of this Preprint also exists.

Funderburk, K.; Bang-Christensen, S.R.; Miller, B.F.; Tan, H.; Margolin, G.; Petrykowska, H.M.; Baugher, C.; Farney, S.K.; Grimm, S.A.; Jameel, N.; Holland, D.O.; Altman, N.S.; Elnitski, L. Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection. Cancers 2023, 15, 4826. Funderburk, K.; Bang-Christensen, S.R.; Miller, B.F.; Tan, H.; Margolin, G.; Petrykowska, H.M.; Baugher, C.; Farney, S.K.; Grimm, S.A.; Jameel, N.; Holland, D.O.; Altman, N.S.; Elnitski, L. Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection. Cancers 2023, 15, 4826.

Abstract

Abstract: The ability to detect several types of cancer using a non-invasive, blood-based test holds the potential to revolutionize oncology screening. We mined tumor methylation array data from the Cancer Genome Atlas (TCGA) covering 14 cancer types and identified two novel, broadly oc-curring methylation markers at TLX1 and GALR1. To evaluate their performance as a general-ized blood-based screening approach, along with our previously reported methylation bi-omarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing the TCGA methylation data and applying logistic regression models within each individual cancer type, we found that the three-marker combination significantly increased the average area under the ROC curve (AUC) across the 14 tumor types compared to single markers (p= 1.158e-10; Friedman test). Furthermore, we simulated dilutions of tumor DNA into healthy blood cell DNA and demonstrated increased AUC of combined markers across all dilution levels. Finally, we evaluated assay performance in bisulfite sequenced DNA from patient tumors and plasma, in-cluding early-stage samples. When combining all three markers the assay achieved 100% sensi-tivity and specificity, as demonstrated in lung cancer plasma samples. In patient plasma from hepatocellular carcinoma, ZNF154 alone yielded the highest combined sensitivity and specificity values averaging 68% and 72%, whereas multiple markers could achieve higher sensitivity or specificity, but not both. Altogether this study presents a comprehensive pipeline for the identifi-cation, testing and validation of multi-cancer methylation biomarkers with a considerable poten-tial for detecting a broad range of cancer types in patient blood samples.

Keywords

Liquid biopsy; DNA methylation; biomarker; cancer; multi-cancer; bisulfite sequencing; diagnostics; screening

Subject

Biology and Life Sciences, Biology and Biotechnology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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