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Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing

Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant...

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Autores principales: Li, Jia, Ju, Jia, Zhao, Qiang, Liu, Weiqiang, Yuan, Yuying, Liu, Qiang, Zhou, Lijun, Han, Yuan, Yuan, Wen, Huang, Yonghua, Xie, Yingjun, Li, Zhihua, Chen, Jingsi, Huang, Shuyu, Chen, Rufang, Li, Wei, Tan, Meihua, Wang, Danchen, Zhou, Si, Zhang, Jian, Zeng, Fanwei, Yu, Nan, Su, Fengxia, Chen, Min, Ge, Yunsheng, Huang, Yanming, Jin, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900746/
https://www.ncbi.nlm.nih.gov/pubmed/35265103
http://dx.doi.org/10.3389/fgene.2022.802865
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author Li, Jia
Ju, Jia
Zhao, Qiang
Liu, Weiqiang
Yuan, Yuying
Liu, Qiang
Zhou, Lijun
Han, Yuan
Yuan, Wen
Huang, Yonghua
Xie, Yingjun
Li, Zhihua
Chen, Jingsi
Huang, Shuyu
Chen, Rufang
Li, Wei
Tan, Meihua
Wang, Danchen
Zhou, Si
Zhang, Jian
Zeng, Fanwei
Yu, Nan
Su, Fengxia
Chen, Min
Ge, Yunsheng
Huang, Yanming
Jin, Xin
author_facet Li, Jia
Ju, Jia
Zhao, Qiang
Liu, Weiqiang
Yuan, Yuying
Liu, Qiang
Zhou, Lijun
Han, Yuan
Yuan, Wen
Huang, Yonghua
Xie, Yingjun
Li, Zhihua
Chen, Jingsi
Huang, Shuyu
Chen, Rufang
Li, Wei
Tan, Meihua
Wang, Danchen
Zhou, Si
Zhang, Jian
Zeng, Fanwei
Yu, Nan
Su, Fengxia
Chen, Min
Ge, Yunsheng
Huang, Yanming
Jin, Xin
author_sort Li, Jia
collection PubMed
description Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant women with MCA results using NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results using NIPT and a random forest classifier to identify the tissue origin of common maternal cancer types. Methods: For examination, 496 participants with MCA results via NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed through the clinical follow-up. The cohort comprising 42 maternal cancer cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top five chromosome z scores (MTOP5Zscores). The remaining 160 participants enrolled from January 2018 to June 2019 were used to validate the performance of MTOP5Zscores. We established a random forest model to classify three common cancer types using normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes, and seven plasma tumor markers (PTMs) as predictor variables. Results: 62 maternal cancer cases were confirmed with breast cancer, liver cancer, and lymphoma, the most common cancer types. MTOP5Zscores showed a sensitivity of 85% (95% confidence interval (CI), 62.11–96.79%) and specificity of 80% (95% CI, 72.41–88.28%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 93.33, 66.67, and 50%, while specificity was 66.67, 90, and 97.06%, and positive predictive value (PPV) was 60.87, 72.73, and 80% for the prediction of breast cancer, liver cancer, and lymphoma, respectively. Conclusion: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results using NIPT, indicating it as a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost.
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spelling pubmed-89007462022-03-08 Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing Li, Jia Ju, Jia Zhao, Qiang Liu, Weiqiang Yuan, Yuying Liu, Qiang Zhou, Lijun Han, Yuan Yuan, Wen Huang, Yonghua Xie, Yingjun Li, Zhihua Chen, Jingsi Huang, Shuyu Chen, Rufang Li, Wei Tan, Meihua Wang, Danchen Zhou, Si Zhang, Jian Zeng, Fanwei Yu, Nan Su, Fengxia Chen, Min Ge, Yunsheng Huang, Yanming Jin, Xin Front Genet Genetics Background: The existence of maternal malignancy may cause false-positive results or failed tests of NIPT. Though recent studies have shown multiple chromosomal aneuploidies (MCA) are associated with malignancy, there is still no effective solution to identify maternal cancer patients from pregnant women with MCA results using NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results using NIPT and a random forest classifier to identify the tissue origin of common maternal cancer types. Methods: For examination, 496 participants with MCA results via NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed through the clinical follow-up. The cohort comprising 42 maternal cancer cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top five chromosome z scores (MTOP5Zscores). The remaining 160 participants enrolled from January 2018 to June 2019 were used to validate the performance of MTOP5Zscores. We established a random forest model to classify three common cancer types using normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes, and seven plasma tumor markers (PTMs) as predictor variables. Results: 62 maternal cancer cases were confirmed with breast cancer, liver cancer, and lymphoma, the most common cancer types. MTOP5Zscores showed a sensitivity of 85% (95% confidence interval (CI), 62.11–96.79%) and specificity of 80% (95% CI, 72.41–88.28%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 93.33, 66.67, and 50%, while specificity was 66.67, 90, and 97.06%, and positive predictive value (PPV) was 60.87, 72.73, and 80% for the prediction of breast cancer, liver cancer, and lymphoma, respectively. Conclusion: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results using NIPT, indicating it as a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost. Frontiers Media S.A. 2022-02-10 /pmc/articles/PMC8900746/ /pubmed/35265103 http://dx.doi.org/10.3389/fgene.2022.802865 Text en Copyright © 2022 Li, Ju, Zhao, Liu, Yuan, Liu, Zhou, Han, Yuan, Huang, Xie, Li, Chen, Huang, Chen, Li, Tan, Wang, Zhou, Zhang, Zeng, Yu, Su, Chen, Ge, Huang and Jin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Li, Jia
Ju, Jia
Zhao, Qiang
Liu, Weiqiang
Yuan, Yuying
Liu, Qiang
Zhou, Lijun
Han, Yuan
Yuan, Wen
Huang, Yonghua
Xie, Yingjun
Li, Zhihua
Chen, Jingsi
Huang, Shuyu
Chen, Rufang
Li, Wei
Tan, Meihua
Wang, Danchen
Zhou, Si
Zhang, Jian
Zeng, Fanwei
Yu, Nan
Su, Fengxia
Chen, Min
Ge, Yunsheng
Huang, Yanming
Jin, Xin
Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing
title Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing
title_full Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing
title_fullStr Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing
title_full_unstemmed Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing
title_short Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing
title_sort effective identification of maternal malignancies in pregnancies undergoing noninvasive prenatal testing
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900746/
https://www.ncbi.nlm.nih.gov/pubmed/35265103
http://dx.doi.org/10.3389/fgene.2022.802865
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