NEW YORK (GenomeWeb) – Researchers from BGI-Shenzhen, Xin Hua Hospital's Center for Clinical Genetics in Shanghai, and elsewhere have developed a computational approach for more accurately identifying maternal cancers in pregnant women with multiple chromosomal aneuploidies found by noninvasive prenatal screening (NIPS).
Starting with NIPS results from more than 1.9 million pregnant women, the researchers used a new bioinformatics algorithm — dubbed the cancer detection pipeline, or CDP — to assess low-coverage sequencing-based NIPS data for 639 pregnant women suspected of having undiagnosed malignancies because they tested positive for multiple chromosomal aneuploidies.
"Multiple chromosomal aneuploidies may be associated with maternal malignancies and can cause failure of noninvasive prenatal screening tests," the authors explained, though "multiple chromosomal aneuploidies show poor specificity and selectivity for diagnosing maternal malignancies."
The team's findings, published online last week in Genetics in Medicine, suggest that the CDP algorithm could largely distinguish between authentic maternal malignancies and false-positive cases identified by multiple chromosomal aneuploidies alone.
"Our results suggest that reproducible multiple chromosomal aneuploidies detectable in NIPS tests are associated with maternal malignant cancer risk, and that the combination of multiple chromosomal aneuploidies findings with our novel CDP algorithm, based on low-coverage NIPS test sequencing data, shows potential for detecting pre-symptomatic maternal malignancies," the authors reported.
For their study, the researchers analyzed low-coverage sequencing data from blood samples for 639 pregnant women with multiple chromosomal aneuploidies, selected from some 1.93 million pregnant women who received NIPS at one of several centers in China between January 2016 and December 2017.
Since the study was retrospective, the team knew that 41 of the women were ultimately diagnosed with cancer, making it possible to assess the positive predictive value of the CDP algorithm, which focuses on finding maternal malignancy using copy number variant data.
In the 639 women with multiple chromosomal aneuploidies, for example, the CDP correctly identified 34 of the 41 cancer cases, but misclassified seven of them as having low cancer risk. On the other hand, it predicted the absence of cancer in 422 of the 501 women who indeed did not develop cancer, leading to 79 false positives, or women placed in the high-risk group who have so far remained cancer-free.
The authors noted that it may be possible to further enhance the CDP algorithm's positive predictive value by bringing in blood markers related to specific primary tumor types. For example, they found that the inclusion of eight blood plasma tumor markers could boost the positive predictive value of the test to 75 percent. In contrast, multiple chromosomal aneuploidies alone had a positive predictive value of 7.6 percent for predicting maternal malignancy.
"Our findings lay the foundation for applying the NIPS test not just to screen for fetal aneuploidies, but also to uncover occult maternal malignancies," they concluded.