Circulating trophoblast cell clusters for early detection of placenta accreta spectrum disorders

Yalda Afshar, Jiantong Dong, Pan Zhao, Lei Li, Shan Wang, Ryan Y. Zhang, Ceng Zhang, Ophelia Yin, Christina S. Han, Brett D. Einerson, Tania L. Gonzalez, Huirong Zhang, Anqi Zhou, Zhuo Yang, Shih-Jie Chou, Na Sun, Ju Cheng, Henan Zhu, Jing Wang, Tiffany X. Zhang, Yi-Te Lee, Jasmine J. Wang, Pai-Chi Teng, Peng Yang, Dongping Qi, Meiping Zhao, Myung-Shin Sim, Ruilian Zhe, Jeffrey D. Goldstein, John Williams, Xietong Wang, Qingying Zhang, Lawrence D. Platt, Chang Zou (), Margareta D. Pisarska (), Hsian-Rong Tseng () and Yazhen Zhu ()
Additional contact information
Yalda Afshar: University of California, Los Angeles
Jiantong Dong: University of California, Los Angeles
Pan Zhao: The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital
Lei Li: University of California, Los Angeles
Shan Wang: University of California, Los Angeles
Ryan Y. Zhang: University of California, Los Angeles
Ceng Zhang: University of California, Los Angeles
Ophelia Yin: University of California, Los Angeles
Christina S. Han: University of California, Los Angeles
Brett D. Einerson: University of Utah Health
Tania L. Gonzalez: Cedars-Sinai Medical Center
Huirong Zhang: The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital
Anqi Zhou: University of California, Los Angeles
Zhuo Yang: University of California, Los Angeles
Shih-Jie Chou: University of California, Los Angeles
Na Sun: University of California, Los Angeles
Ju Cheng: University of California, Los Angeles
Henan Zhu: University of California, Los Angeles
Jing Wang: University of California, Los Angeles
Tiffany X. Zhang: University of California, Los Angeles
Yi-Te Lee: University of California, Los Angeles
Jasmine J. Wang: Cedars-Sinai Medical Center
Pai-Chi Teng: Cedars-Sinai Medical Center
Peng Yang: University of California, Los Angeles
Dongping Qi: University of California, Los Angeles
Meiping Zhao: Peking University
Myung-Shin Sim: University of California, Los Angeles
Ruilian Zhe: The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital
Jeffrey D. Goldstein: University of California, Los Angeles
John Williams: Cedars-Sinai Medical Center
Xietong Wang: Shandong Provincial Hospital Affiliated to Shandong University
Qingying Zhang: University of California, Los Angeles
Lawrence D. Platt: University of California, Los Angeles
Chang Zou: The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital
Margareta D. Pisarska: Cedars-Sinai Medical Center
Hsian-Rong Tseng: University of California, Los Angeles
Yazhen Zhu: University of California, Los Angeles

Nature Communications, 2021, vol. 12, issue 1, 1-14

Abstract: Abstract Placenta accreta spectrum (PAS) is a high-risk obstetrical condition associated with significant morbidity and mortality. Current clinical screening modalities for PAS are not always conclusive. Here, we report a nanostructure-embedded microchip that efficiently enriches both single and clustered circulating trophoblasts (cTBs) from maternal blood for detecting PAS. We discover a uniquely high prevalence of cTB-clusters in PAS and subsequently optimize the device to preserve the intactness of these clusters. Our feasibility study on the enumeration of cTBs and cTB-clusters from 168 pregnant women demonstrates excellent diagnostic performance for distinguishing PAS from non-PAS. A logistic regression model is constructed using a training cohort and then cross-validated and tested using an independent cohort. The combined cTB assay achieves an Area Under ROC Curve of 0.942 (throughout gestation) and 0.924 (early gestation) for distinguishing PAS from non-PAS. Our assay holds the potential to improve current diagnostic modalities for the early detection of PAS.

Date: 2021
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DOI: 10.1038/s41467-021-24627-2

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