Identifying ovarian cancer with machine learning DNA methylation pattern analysis

Jesus Gonzalez Bosquet; Vincent M Wagner; Douglas Russo; Henry D Reyes; Andreea M Newtson; David P Bender; Michael J Goodheart

doi:10.1038/s41598-025-05460-9

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Identifying ovarian cancer with machine learning DNA methylation pattern analysis

Journal article

Open access

Peer reviewed

Identifying ovarian cancer with machine learning DNA methylation pattern analysis

Jesus Gonzalez Bosquet, Vincent M Wagner, Douglas Russo, Henry D Reyes, Andreea M Newtson, David P Bender and Michael J Goodheart

Scientific reports, Vol.15(1), 20910

07/01/2025

DOI: 10.1038/s41598-025-05460-9

PMCID: PMC12218148

PMID: 40594531

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https://doi.org/10.1038/s41598-025-05460-9View

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Abstract

The majority of patients with epithelial ovarian cancer (EOC) continue to be diagnosed at an advanced stage despite great advances in this disease treatment. To impact overall survival, we need better methods of EOC early diagnosis. We performed a case control study to predict high-grade serous cancer (HGSC) using artificial intelligence methodology and methylated DNA from surgical specimens. Initial prediction models with MethylNet were accurate but complex (AUC = 100%). We optimized these models by selecting the most informative probes with univariate ANOVA analyses first, and then multivariate lasso regression modelling. This step-wise approach resulted in 9 methylated probes predicting HGSC with an AUC of 100%. These models were validated with different analytics and with an independent DNA-methylation experiment with excellent performances.

Machine Learning

Aged

Carcinoma, Ovarian Epithelial - diagnosis

Carcinoma, Ovarian Epithelial - genetics

Case-Control Studies

DNA Methylation

Female

Humans

Middle Aged

Ovarian Neoplasms - diagnosis

Ovarian Neoplasms - genetics

Ovarian Neoplasms - pathology

Details

Title: Subtitle: Identifying ovarian cancer with machine learning DNA methylation pattern analysis
Creators: Jesus Gonzalez Bosquet - Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA. jesus-gonzalezbosquet@uiowa.edu
Vincent M Wagner - University of Iowa
Douglas Russo - University of Chicago
Henry D Reyes - GPPC Network, Williamsville, NY, 14221, USA
Andreea M Newtson - Endeavor Health, Evanston, IL, 68198, USA
David P Bender - University of Iowa
Michael J Goodheart - University of Iowa
Resource Type: Journal article
Publication Details: Scientific reports, Vol.15(1), 20910
DOI: 10.1038/s41598-025-05460-9
PMID: 40594531
PMCID: PMC12218148
NLM abbreviation: Sci Rep
ISSN: 2045-2322
eISSN: 2045-2322
Publisher: Nature Publishing Group
Grant note: R01 CA099908 / NCI NIH HHS K12 HD063117 / NICHD NIH HHS P30 CA086862 / NCI NIH HHS 5R01CA99908-18 / NIH HHS AAOGF-2018 / American Association of Obstetricians and Gynecologists Foundation (AAOGF) Bridge Funding Award
Language: English
Date published: 07/01/2025
Academic Unit: Obstetrics and Gynecology
Record Identifier: 9984843603302771

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