Cargando…
Applying low coverage whole genome sequencing to detect malignant ovarian mass
To evaluate whether low coverage whole genome sequencing is suitable for the detection of malignant pelvic mass and compare its diagnostic value with traditional tumor markers. We enrolled 63 patients with a pelvic mass suspicious for ovarian malignancy. Each patient underwent low coverage whole gen...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394143/ https://www.ncbi.nlm.nih.gov/pubmed/34446054 http://dx.doi.org/10.1186/s12967-021-03046-3 |
_version_ | 1783743880558018560 |
---|---|
author | Chen, Ming Zhong, Pengqiang Hong, Mengzhi Tan, Jinfeng Yu, Xuegao Huang, Hao Ouyang, Juan Lin, Xiaoping Chen, Peisong |
author_facet | Chen, Ming Zhong, Pengqiang Hong, Mengzhi Tan, Jinfeng Yu, Xuegao Huang, Hao Ouyang, Juan Lin, Xiaoping Chen, Peisong |
author_sort | Chen, Ming |
collection | PubMed |
description | To evaluate whether low coverage whole genome sequencing is suitable for the detection of malignant pelvic mass and compare its diagnostic value with traditional tumor markers. We enrolled 63 patients with a pelvic mass suspicious for ovarian malignancy. Each patient underwent low coverage whole genome sequencing (LCWGS) and traditional tumor markers test. The pelvic masses were finally confirmed via pathological examination. The copy number variants (CNVs) of whole genome were detected and the Stouffers Z-scores for each CNV was extracted. The risk of malignancy (RM) of each suspicious sample was calculated based on the CNV counts and Z-scores, which was subsequently compared with ovarian cancer markers CA125 and HE4, and the risk of ovarian malignancy algorithm (ROMA). Receiver Operating Characteristic Curve (ROC) were used to access the diagnostic value of variables. As confirmed by pathological diagnosis, 44 (70%) patients with malignancy and 19 patients with benign mass were identified. Our results showed that CA125 and HE4, the CNV, the mean of Z-scores (Zmean), the max of Z-scores (Zmax), the RM and the ROMA were significantly different between patients with malignant and benign masses. The area under curve (AUC) of CA125, HE4, CNV, Zmax, and Zmean was 0.775, 0.866, 0.786, 0.685 and 0.725 respectively. ROMA and RM showed similar AUC (0.876 and 0.837), but differed in sensitivity and specificity. In the validation cohort, the AUC of RM was higher than traditional serum markers. In conclusion, we develop a LCWGS based method for the identification of pelvic mass of suspicious ovarian cancer. LCWGS shows accurate result and could be complementary with the existing diagnostic methods. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-03046-3. |
format | Online Article Text |
id | pubmed-8394143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83941432021-08-30 Applying low coverage whole genome sequencing to detect malignant ovarian mass Chen, Ming Zhong, Pengqiang Hong, Mengzhi Tan, Jinfeng Yu, Xuegao Huang, Hao Ouyang, Juan Lin, Xiaoping Chen, Peisong J Transl Med Research To evaluate whether low coverage whole genome sequencing is suitable for the detection of malignant pelvic mass and compare its diagnostic value with traditional tumor markers. We enrolled 63 patients with a pelvic mass suspicious for ovarian malignancy. Each patient underwent low coverage whole genome sequencing (LCWGS) and traditional tumor markers test. The pelvic masses were finally confirmed via pathological examination. The copy number variants (CNVs) of whole genome were detected and the Stouffers Z-scores for each CNV was extracted. The risk of malignancy (RM) of each suspicious sample was calculated based on the CNV counts and Z-scores, which was subsequently compared with ovarian cancer markers CA125 and HE4, and the risk of ovarian malignancy algorithm (ROMA). Receiver Operating Characteristic Curve (ROC) were used to access the diagnostic value of variables. As confirmed by pathological diagnosis, 44 (70%) patients with malignancy and 19 patients with benign mass were identified. Our results showed that CA125 and HE4, the CNV, the mean of Z-scores (Zmean), the max of Z-scores (Zmax), the RM and the ROMA were significantly different between patients with malignant and benign masses. The area under curve (AUC) of CA125, HE4, CNV, Zmax, and Zmean was 0.775, 0.866, 0.786, 0.685 and 0.725 respectively. ROMA and RM showed similar AUC (0.876 and 0.837), but differed in sensitivity and specificity. In the validation cohort, the AUC of RM was higher than traditional serum markers. In conclusion, we develop a LCWGS based method for the identification of pelvic mass of suspicious ovarian cancer. LCWGS shows accurate result and could be complementary with the existing diagnostic methods. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-03046-3. BioMed Central 2021-08-26 /pmc/articles/PMC8394143/ /pubmed/34446054 http://dx.doi.org/10.1186/s12967-021-03046-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Chen, Ming Zhong, Pengqiang Hong, Mengzhi Tan, Jinfeng Yu, Xuegao Huang, Hao Ouyang, Juan Lin, Xiaoping Chen, Peisong Applying low coverage whole genome sequencing to detect malignant ovarian mass |
title | Applying low coverage whole genome sequencing to detect malignant ovarian mass |
title_full | Applying low coverage whole genome sequencing to detect malignant ovarian mass |
title_fullStr | Applying low coverage whole genome sequencing to detect malignant ovarian mass |
title_full_unstemmed | Applying low coverage whole genome sequencing to detect malignant ovarian mass |
title_short | Applying low coverage whole genome sequencing to detect malignant ovarian mass |
title_sort | applying low coverage whole genome sequencing to detect malignant ovarian mass |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394143/ https://www.ncbi.nlm.nih.gov/pubmed/34446054 http://dx.doi.org/10.1186/s12967-021-03046-3 |
work_keys_str_mv | AT chenming applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT zhongpengqiang applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT hongmengzhi applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT tanjinfeng applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT yuxuegao applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT huanghao applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT ouyangjuan applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT linxiaoping applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass AT chenpeisong applyinglowcoveragewholegenomesequencingtodetectmalignantovarianmass |