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 

TITLE=Effective Identification of Maternal Malignancies in Pregnancies Undergoing Noninvasive Prenatal Testing 

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.802865

DOI=10.3389/fgene.2022.802865

ISSN=1664-8021

ABSTRACT=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 in NIPT. We aimed to develop a new method to effectively detect maternal cancer in pregnant women with MCA results in NIPT tests and a random forest classifier to identify the tissue origin of common maternal cancer types. 
Methods: 496 participants with MCA results in NIPT were enrolled from January 2016 to June 2019 at BGI. Cancer and non-cancer participants were confirmed by the clinical follow-up. The cohort comprising 42 maternal cancers cases and 294 non-cancer cases enrolled from January 2016 to December 2017 was utilized to develop a method named mean of the top 5 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 the normalized Pearson correlation coefficient (NPCC) values, z scores of 22 chromosomes and 7 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 80% (95% confidence interval (CI) 51.9%-95.7%) and specificity of 87.6% (95% CI 79.0%-93.7%) in the detection of maternal cancer among pregnant women with MCA results. The sensitivity of the classifier was 100%, 75% and 62.5%, while specificity was 80%, 95.7% and 96.3%, and positive predictive value (PPV) was 79%, 90% and 83.3% for the prediction of breast cancer, liver cancer and lymphoma respectively. 
Conclusions: This study presents a solution to identify maternal cancer patients from pregnant women with MCA results in NIPT, indicating it is a value-added application of NIPT in the detection of maternal malignancies in addition to screening for fetal aneuploidies with no extra cost.