Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection

Author:

Funderburk Karen1,Bang-Christensen Sara R.1ORCID,Miller Brendan F.1,Tan Hua1ORCID,Margolin Gennady1,Petrykowska Hanna M.1,Baugher Catherine1,Farney S. Katie1ORCID,Grimm Sara A.2ORCID,Jameel Nader1,Holland David O.1ORCID,Altman Naomi S.3ORCID,Elnitski Laura1ORCID

Affiliation:

1. Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA

2. Integrative Bioinformatics Support Group, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health, Research Triangle Park, Durham, NC 27709, USA

3. Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA

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-occurring methylation markers at TLX1 and GALR1. To evaluate their performance as a generalized blood-based screening approach, along with our previously reported methylation biomarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing 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 = 1.158 × 10−10; 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, including early-stage samples. When combining all three markers, the assay correctly identified nine out of nine 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 identification, testing, and validation of multi-cancer methylation biomarkers with a considerable potential for detecting a broad range of cancer types in patient blood samples.

Funder

Carlsberg Foundation

National Human Genome Research Institutes

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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