Xing Ji1,2, Jia Li3, Yonghua Huang4, Pi-Lin Sung5,6, Yuying Yuan3, Qiang Liu3, Yan Chen3, Jia Ju3, Yafeng Zhou3, Shujia Huang3, Fang Chen3, Yuan Han7, Wen Yuan7, Cheng Fan3, Qiang Zhao4, Haitao Wu8, Suihua Feng4, Weiqiang Liu9, Zhihua Li10, Jingsi Chen10, Min Chen10, Hong Yao11, Li Zeng12, Tao Ma13, Shushu Fan14, Jinman Zhang15,16, Ka Yiu Yuen17, So Hin Cheng17, Irene Wing Shan Chik17, Nien-Tzu Liu17, Jianyu Zhu3, Siyuan Lin17, Jeremy Cao17, Steve Tong17, Zhiyuan Shan18, Wenyan Li3, Mohammad Reza Hekmat19, Masoud Garshasbi19,20, Javier Suela21, Yaima Torres21, Juan C Cigudosa21, F J Pérez Ruiz22, Laura Rodríguez23, Mónica García23, Janez Bernik24, Eva Traven24, Uršula Reš25, Nataša Tul26, Ching-Fong Tseng27, Depeng Zhao28, Luming Sun28, Qiong Pan29, Li Shen30, Mengyao Dai1,2, Yuying Wang3, Jian Wang3,31, Huanming Yang3,31, Ye Yin3,32, Tao Duan28, Baosheng Zhu15,16, Mahesh Choolani33, Xin Jin34,35,36, Yingwei Chen37, Mao Mao38. 1. Center for Clinical Genetics, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China. 2. Department of Genetics, Shanghai Institute for Pediatric Research, Shanghai, China. 3. BGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China. 4. Department of Obstetrics and Gynecology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, Guangdong, China. 5. Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan. 6. Department of Obstetrics and Gynecology, School of Medicine, National Yang-Ming University, Taipei, Taiwan. 7. BGI-Wuhan, BGI-Shenzhen, Wuhan, Guangdong, China. 8. Reproductive Medicine Center, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, Guangdong, China. 9. Key Laboratory for Major Obstetric Diseases of Guangdong, Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China. 10. Department of Prenatal Diagnosis and Fetal Medicine, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China. 11. Prenatal Diagnosis Center, Southwest Hospital, Chongqing, China. 12. Department of Obstetrics and Gynecology, Bazhong Central Hospital, Bazhong, Sichuan, China. 13. Department of Obstetrics and Gynecology, Sichuan Provincial People's Hospital, Chengdu, Sichuan, China. 14. Genetic Diagnosis Center and Reproductive Center, Yue Bei People's Hospital, Shaoguan, Guangdong, China. 15. Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China. 16. Genetic Diagnosis Center, First People's Hospital of Yunnan, Kunming, Yunnan, China. 17. BGI HEALTH (HK), Hong Kong, China. 18. BGI Europe A/S, Copenhagen, Denmark. 19. Department of Medical Genetics, DeNA laboratory, Tehran, Iran. 20. Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran. 21. NIMGenetics, Madrid, Spain. 22. Servicio de Ginecología y Obstetricia, Hospital General San Jorge, Huesca, Spain. 23. Laboratorio de Genética Molecular AbaCid, Hospitales HM, Madrid, Spain. 24. GenePlanet Ltd, Ljubljana, Slovenia. 25. Dravlje Health Center-IVF, Ljubljana, Slovenia. 26. Division of Obstetrics and Gynecology, Department of Perinatology, University Medical Centre, Ljubljana, Slovenia. 27. Gene Health Co Ltd, Taipei, Taiwan. 28. Department of Prenatal Diagnosis and Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China. 29. Laboratory of Clinical Genetics, Huai'an Maternity and Child Health Care Hospital of Jiangsu Province, Yangzhou University, Huai'an, Jiangsu, China. 30. Department of Pathology, Shanghai Pu Nan Hospital, Shanghai, China. 31. James D. Watson Institute of Genome Sciences, Hangzhou, Zhejiang, China. 32. Department of Biology, University of Copenhagen, Copenhagen, Denmark. 33. Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 34. BGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China. jinxin@genomics.cn. 35. School of Medicine, South China University of Technology, Guangzhou, Guangdong, China. jinxin@genomics.cn. 36. BGI-Guangzhou Medical Laboratory, BGI-Shenzhen, Guangzhou, Guangdong, China. jinxin@genomics.cn. 37. Center for Clinical Genetics, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China. chenyingwei@xinhuamed.com.cn. 38. BGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China. maomao@genomics.cn.
Abstract
PURPOSE: Multiple chromosomal aneuploidies may be associated with maternal malignancies and can cause failure of noninvasive prenatal screening (NIPS) tests. However, multiple chromosomal aneuploidies show poor specificity and selectivity for diagnosing maternal malignancies. METHODS: This multicenter retrospective analysis evaluated 639 pregnant women who tested positive for multiple chromosomal aneuploidies on initial NIPS test between January 2016 and December 2017. Women were assessed using genome profiling of copy-number variations, which was translated to cancer risk using a novel bioinformatics algorithm called the cancer detection pipeline (CDP). Sensitivity, specificity, and positive predictive value (PPV) of diagnosing maternal malignancies were compared for multiple chromosomal aneuploidies, the CDP model, and the combination of CDP and plasma tumor markers. RESULTS: Of the 639 subjects, 41 maternal malignant cancer cases were diagnosed. Multiple chromosomal aneuploidies predicted maternal malignancies with a PPV of 7.6%. Application of the CDP algorithm to women with multiple chromosomal aneuploidies allowed 34 of the 41 (83%) cancer cases to be identified, while excluding 422 of 501 (84.2%) of the false positive cases. Combining the CDP with plasma tumor marker testing gave PPV of 75.0%. CONCLUSION: The CDP algorithm can diagnose occult maternal malignancies with a reasonable PPV in multiple chromosomal aneuploidies-positive pregnant women in NIPS tests. This performance can be further improved by incorporating findings for plasma tumor markers.
PURPOSE: Multiple chromosomal aneuploidies may be associated with maternal malignancies and can cause failure of noninvasive prenatal screening (NIPS) tests. However, multiple chromosomal aneuploidies show poor specificity and selectivity for diagnosing maternal malignancies. METHODS: This multicenter retrospective analysis evaluated 639 pregnant women who tested positive for multiple chromosomal aneuploidies on initial NIPS test between January 2016 and December 2017. Women were assessed using genome profiling of copy-number variations, which was translated to cancer risk using a novel bioinformatics algorithm called the cancer detection pipeline (CDP). Sensitivity, specificity, and positive predictive value (PPV) of diagnosing maternal malignancies were compared for multiple chromosomal aneuploidies, the CDP model, and the combination of CDP and plasma tumor markers. RESULTS: Of the 639 subjects, 41 maternal malignant cancer cases were diagnosed. Multiple chromosomal aneuploidies predicted maternal malignancies with a PPV of 7.6%. Application of the CDP algorithm to women with multiple chromosomal aneuploidies allowed 34 of the 41 (83%) cancer cases to be identified, while excluding 422 of 501 (84.2%) of the false positive cases. Combining the CDP with plasma tumor marker testing gave PPV of 75.0%. CONCLUSION: The CDP algorithm can diagnose occult maternal malignancies with a reasonable PPV in multiple chromosomal aneuploidies-positive pregnant women in NIPS tests. This performance can be further improved by incorporating findings for plasma tumor markers.
Authors: Liesbeth Lenaerts; Nathalie Brison; Charlotte Maggen; Leen Vancoillie; Huiwen Che; Peter Vandenberghe; Daan Dierickx; Lucienne Michaux; Barbara Dewaele; Patrick Neven; Giuseppe Floris; Thomas Tousseyn; Lore Lannoo; Tatjana Jatsenko; Isabelle Vanden Bempt; Kristel Van Calsteren; Vincent Vandecaveye; Luc Dehaspe; Koenraad Devriendt; Eric Legius; Kris Van Den Bogaert; Joris Robert Vermeesch; Frédéric Amant Journal: EClinicalMedicine Date: 2021-05-13
Authors: Jeff Simko; Charles Y Chiu; Wei Gu; Eric Talevich; Elaine Hsu; Zhongxia Qi; Anatoly Urisman; Scot Federman; Allan Gopez; Shaun Arevalo; Marc Gottschall; Linda Liao; Jack Tung; Lei Chen; Harumi Lim; Chandler Ho; Maya Kasowski; Jean Oak; Brittany J Holmes; Iwei Yeh; Jingwei Yu; Linlin Wang; Steve Miller; Joseph L DeRisi; Sonam Prakash Journal: Genome Med Date: 2021-06-01 Impact factor: 11.117