Cargando…

Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes

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 beni...

Descripción completa

Detalles Bibliográficos
Autores principales: Gonzalez-Bosquet, Jesus, Cardillo, Nicholas D., Reyes, Henry D., Smith, Brian J., Leslie, Kimberly K., Bender, David P., Goodheart, Michael J., Devor, Eric J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738935/
https://www.ncbi.nlm.nih.gov/pubmed/36499142
http://dx.doi.org/10.3390/ijms232314814
_version_ 1784847674472660992
author Gonzalez-Bosquet, Jesus
Cardillo, Nicholas D.
Reyes, Henry D.
Smith, Brian J.
Leslie, Kimberly K.
Bender, David P.
Goodheart, Michael J.
Devor, Eric J.
author_facet Gonzalez-Bosquet, Jesus
Cardillo, Nicholas D.
Reyes, Henry D.
Smith, Brian J.
Leslie, Kimberly K.
Bender, David P.
Goodheart, Michael J.
Devor, Eric J.
author_sort Gonzalez-Bosquet, Jesus
collection PubMed
description 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 1.00–1.00). 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.
format Online
Article
Text
id pubmed-9738935
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-97389352022-12-11 Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes Gonzalez-Bosquet, Jesus Cardillo, Nicholas D. Reyes, Henry D. Smith, Brian J. Leslie, Kimberly K. Bender, David P. Goodheart, Michael J. Devor, Eric J. Int J Mol Sci Article 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 1.00–1.00). 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. MDPI 2022-11-26 /pmc/articles/PMC9738935/ /pubmed/36499142 http://dx.doi.org/10.3390/ijms232314814 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gonzalez-Bosquet, Jesus
Cardillo, Nicholas D.
Reyes, Henry D.
Smith, Brian J.
Leslie, Kimberly K.
Bender, David P.
Goodheart, Michael J.
Devor, Eric J.
Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes
title Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes
title_full Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes
title_fullStr Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes
title_full_unstemmed Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes
title_short Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes
title_sort using genomic variation to distinguish ovarian high-grade serous carcinoma from benign fallopian tubes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738935/
https://www.ncbi.nlm.nih.gov/pubmed/36499142
http://dx.doi.org/10.3390/ijms232314814
work_keys_str_mv AT gonzalezbosquetjesus usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT cardillonicholasd usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT reyeshenryd usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT smithbrianj usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT lesliekimberlyk usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT benderdavidp usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT goodheartmichaelj usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes
AT devorericj usinggenomicvariationtodistinguishovarianhighgradeserouscarcinomafrombenignfallopiantubes