Center for Clinical Genetics, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Department of Genetics, Shanghai Institute for Pediatric Research, Shanghai, China.
Genet Med. 2019 Oct;21(10):2293-2302. doi: 10.1038/s41436-019-0510-5. Epub 2019 Apr 12.
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.
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.
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%.
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.
多种染色体非整倍体可能与母体恶性肿瘤有关,并可能导致非侵入性产前筛查(NIPS)检测失败。然而,多种染色体非整倍体对诊断母体恶性肿瘤的特异性和选择性较差。
这项多中心回顾性分析评估了 2016 年 1 月至 2017 年 12 月期间 639 名初始 NIPS 检测呈多种染色体非整倍体阳性的孕妇。使用拷贝数变异的基因组分析对女性进行评估,然后使用一种名为癌症检测管道(CDP)的新型生物信息学算法将其转化为癌症风险。比较了多种染色体非整倍体、CDP 模型以及 CDP 和血浆肿瘤标志物联合对诊断母体恶性肿瘤的敏感性、特异性和阳性预测值(PPV)。
在 639 名受试者中,诊断出 41 例母体恶性癌症病例。多种染色体非整倍体预测母体恶性肿瘤的 PPV 为 7.6%。将 CDP 算法应用于多种染色体非整倍体阳性的女性,可以识别出 41 例癌症病例中的 34 例,同时排除了 501 例假阳性病例中的 422 例。将 CDP 与血浆肿瘤标志物检测相结合,PPV 为 75.0%。
在 NIPS 检测中,CDP 算法可在多种染色体非整倍体阳性的孕妇中诊断出隐匿性母体恶性肿瘤,具有合理的 PPV。通过结合血浆肿瘤标志物的检测结果,可以进一步提高其性能。