{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:52:05Z","timestamp":1771469525191,"version":"3.50.1"},"reference-count":44,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,26]],"date-time":"2022-11-26T00:00:00Z","timestamp":1669420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NIH","award":["5R01CA99908-18"],"award-info":[{"award-number":["5R01CA99908-18"]}]},{"name":"NIH","award":["OC190352"],"award-info":[{"award-number":["OC190352"]}]},{"name":"Department of Defense","award":["5R01CA99908-18"],"award-info":[{"award-number":["5R01CA99908-18"]}]},{"name":"Department of Defense","award":["OC190352"],"award-info":[{"award-number":["OC190352"]}]},{"name":"American Association of Obstetricians and Gynecologists Foundation (AAOGF) Bridge Funding Award","award":["5R01CA99908-18"],"award-info":[{"award-number":["5R01CA99908-18"]}]},{"name":"American Association of Obstetricians and Gynecologists Foundation (AAOGF) Bridge Funding Award","award":["OC190352"],"award-info":[{"award-number":["OC190352"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>The preoperative diagnosis of pelvic masses has been elusive to date. Methods for characterization such as CA-125 have had limited specificity. We hypothesize that genomic variation can be used to create prediction models which accurately distinguish high grade serous ovarian cancer (HGSC) from benign tissue. Methods: In this retrospective, pilot study, we extracted DNA and RNA from HGSC specimens and from benign fallopian tubes. Then, we performed whole exome sequencing and RNA sequencing, and identified single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV). We used these variants to create prediction models to distinguish cancer from benign tissue. The models were then validated in independent datasets and with a machine learning platform. Results: The prediction model with SNV had an AUC of 1.00 (95% CI 1.00\u20131.00). The models with CNV and SV had AUC of 0.87 and 0.73, respectively. Validated models also had excellent performances. Conclusions: Genomic variation of HGSC can be used to create prediction models which accurately discriminate cancer from benign tissue. Further refining of these models (early-stage samples, other tumor types) has the potential to lead to detection of ovarian cancer in blood with cell free DNA, even in early stage.<\/jats:p>","DOI":"10.3390\/ijms232314814","type":"journal-article","created":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T04:58:50Z","timestamp":1669784330000},"page":"14814","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2079-4528","authenticated-orcid":false,"given":"Jesus","family":"Gonzalez-Bosquet","sequence":"first","affiliation":[{"name":"Department of Obstetrics and Gynecology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas D.","family":"Cardillo","sequence":"additional","affiliation":[{"name":"Hanjani Institute of Gynecologic Oncology, Thomas Jefferson University, Philadelphia, PA 19107, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Henry D.","family":"Reyes","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, University of Buffalo, Buffalo, NY 14203, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brian J.","family":"Smith","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Iowa, 145 N Riverside Dr., Iowa City, IA 52242, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kimberly K.","family":"Leslie","sequence":"additional","affiliation":[{"name":"Division of Molecular Medicine, Departments of Internal Medicine and Obstetrics and Gynecology, The University of New Mexico Comprehensive Cancer Center, 915 Camino de Salud, CRF 117, Albuquerque, NM 87131, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David P.","family":"Bender","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael J.","family":"Goodheart","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7131-8604","authenticated-orcid":false,"given":"Eric J.","family":"Devor","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.3322\/caac.21708","article-title":"Cancer statistics, 2022","volume":"72","author":"Siegel","year":"2022","journal-title":"CA Cancer J. 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