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.

Jia Li

Jia Ju

Qiang Zhao

Weiqiang Liu

Yuying Yuan

Qiang Liu

Lijun Zhou

Yuan Han

Wen Yuan

Yonghua Huang

Yingjun Xie

Zhihua Li

Jingsi Chen

Shuyu Huang

Rufang Chen

Wei Li

Meihua Tan

Danchen Wang

Si Zhou

Jian Zhang

Fanwei Zeng

Nan Yu

Fengxia Su

Min Chen

Yunsheng Ge

Yanming Huang

Xin Jin

Frontiers in Genetics

FRONTIERS IN GENETICS 发表了经过严格同行评审的关于与生命的所有领域相关的基因和基因组的研究，从人类到植物，再到牲畜和其他模式生物。这本多学科、开放获取的期刊由世界领先专家组成的杰出编辑委员会领导，处于向研究人员、学者、临床医生、政策制定者和公众传播前沿研究的前沿。遗传研究及其影响各种生物过程的基因组有据可查。然而，大多数发现仍有待发现。一个新时代正在见证基因组功能和变异性、遗传和基因组工具的使用以及各种生物现象的遗传基础分析方面的重大发展。

Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes related to all fields of life, from humans to plants, livestock, and other model organisms. This multidisciplinary, open-access journal is led by a distinguished editorial board composed of world-leading experts, at the forefront of disseminating cutting-edge research to researchers, scholars, clinicians, policymakers, and the public. Genetic research and the genomic basis of its impact on various biological processes are well-documented; however, many discoveries remain to be made. We are witnessing a new era of significant advancements in the understanding of genomic functions and variability, the use of genetic and genomic tools, and the analysis of the genetic basis of various biological phenomena.

《Frontiers in Genetics》发表经过严格同行评审的研究，涵盖与生命相关的所有领域的基因和基因组，从人类到植物，再到牲畜和其他模式生物。这本多学科、开放获取的期刊由世界领先的专家组成的杰出编辑委员会领导，致力于向研究人员、学者、临床医生、政策制定者和公众传播前沿研究。遗传研究及其对各种生物过程的影响的基因组有据可查，但仍有许多发现待探索。我们正处于一个新时代，见证基因组功能和变异性、遗传和基因组工具的使用，以及对各种生物现象的遗传基础分析方面的重大进展。

Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing

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 is developed.

Category	Quartile
生物学	3
生物学, 遗传学	3

Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing

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