Editors: Donna E. Hansel, MD, PhD, division head of pathology and laboratory medicine, MD Anderson Cancer Center, Houston; James Solomon, MD, PhD, assistant professor, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York; Erica Reinig, MD, assistant professor and medical director of molecular diagnostics, University of Wisconsin-Madison; Marcela Riveros Angel, MD, molecular genetic pathology fellow, Department of Pathology, Oregon Health and Science University, Portland; Maedeh Mohebnasab, MD, assistant professor of pathology, University of Pittsburgh; Alicia Dillard, MD, associate clinical laboratory director, Omniseq/Labcorp, Buffalo, NY; and Richard Wong, MD, PhD, assistant professor of pathology, University of California San Diego.
Use of deep sequencing to uncover the clonal intricacy of pediatric kidney cancers
August 2025—Childhood malignancies such as Wilms tumor—the most common type of kidney cancer in children—exhibit very few DNA changes when tested by traditional sequencing methods. Some of these types of tumors have fewer genetic anomalies than age-matched normal tissue. This raises the question, How can such genetically “quiet” malignancies emerge and progress without conventional driver mutations? To address this question, the authors employed high-resolution, ultra-deep sequencing to determine if hypomutation in juvenile kidney cancers characterized by a paucity of mutations, specifically Wilms tumor, is genuine or an artifact of conventional analytical constraints. By applying high-resolution duplex sequencing (Nanoseq) to Wilms tumors and matched normal kidneys from six pediatric patients, including four infants and two school-age children, the authors showed that standard bulk whole genome sequencing significantly underestimates the mutational burden in tumors from infants. They concluded that Wilms tumors are not hypomutated. The lack of mutations observed by standard whole genome sequencing was attributed to strong polyclonal diversification. Wilms tumors differ from the majority of adult malignancies in that they are composed of several tiny subclones, each possessing a distinct set of mutations. In contrast, most adult cancers contain a dominant clone with mutations that are common to all of the tumor cells. Based on this distinction, the authors determined that most mutations in Wilms tumors occur in a limited number of tumor cells and are not detected when sequencing many cells at once using standard methods. Nanoseq, on the other hand, shows these hidden variants, so the study investigators could see that the number of mutations in each cell was about the same as in normal tissue. Further analysis of the mutational patterns indicated that the clonal architecture of Wilms tumors more closely resembles that of normal, proliferating tissues than that of typical malignancies. This suggests that the evolutionary trajectory of Wilms tumors may parallel standard developmental mechanisms rather than progressing through robust clonal selection and proliferation. The finding challenges established notions about the emergence and evolution of malignancies, particularly pediatric cancers. This study clarifies the molecular complexity of Wilms tumors and emphasizes that high-resolution sequencing is imperative for assessing mutational burden. A more thorough understanding of clonal diversity is necessary to improve cancer diagnoses, risk stratification, and treatment strategies in pediatric oncology.
Lee-Six H, Treger TD, Dave M, et al. High resolution clonal architecture of hypomutated Wilms tumours. Nat Commun. 2025;16. doi.org/10.1038/s41467-025-59854-4
Correspondence: Dr. J. Ciaran Hutchinson at ciaran.hutchinson@gosh.nhs.uk
Predicting risk of preeclampsia using prenatal cell-free DNA screening
Preeclampsia is a serious pregnancy complication characterized by high blood pressure and organ damage and that most commonly affects the liver and kidneys. It typically develops after 20 weeks of gestation and remains a leading cause of maternal and perinatal morbidity and mortality worldwide. Screening approaches that rely on clinical risk factors or biophysical markers have limited predictive accuracy and often fail to identify cases until clinical symptoms present. The authors explored a novel and pragmatic approach to early preeclampsia prediction by leveraging data routinely collected during standard prenatal care. They investigated whether low-coverage whole genome sequencing of cell-free DNA (cfDNA) that is commonly used for fetal aneuploidy screening could be repurposed to assess the maternal risk of developing preeclampsia. Because cfDNA originates from fetal and placental tissue and circulates in the maternal bloodstream, it potentially is a rich source of information about the maternal-fetal interface. For their study, the authors examined 1,854 cfDNA samples obtained at a median gestational age of 12.1 weeks. They measured the levels of total cfDNA and determined the tissue of origin using shallow whole genome sequencing and fragmentomic analysis, such as nucleosome footprints. The latter served as an indirect method to assess gene activity and integrity within particular tissues. Because preeclampsia is believed to be associated with early malfunction of the placenta and maternal endothelium, these chromatin accessibility signals in cfDNA may operate as early indicators of the condition. The authors used computer analysis of nucleosome occupancy patterns to find unique markers linked to the risk of preeclampsia. The patterns were especially abundant in genomic areas associated with placental and endothelial biology, suggesting that tissue-specific dysregulation occurs before the clinical manifestation of disease. Using machine learning, the authors trained and validated a binary classifier combining cfDNA nucleosome features with two easily measured clinical factors: blood pressure and body mass index. The model performed well in predicting preeclampsia requiring preterm delivery. To extend this concept to clinical practice, the authors created a computational model named PEARL (Preeclampsia Early Assessment of Risk from Liquid Biopsy), which combines cfDNA characteristics with maternal body mass index and systolic blood pressure. The model showed strong predictive ability (81 percent sensitivity and 80 percent specificity) in finding pregnancies that were likely to develop preeclampsia. Higher levels of cfDNA were linked to earlier delivery and higher blood pressure. The authors’ findings indicate that routine prenatal cfDNA sequencing is useful for predicting risk of early preeclampsia. The technology could be widely employed without putting further stress on patients or clinicians since it uses the clinical infrastructure of noninvasive prenatal testing.
Adil M, Kolarova TR, Doebley AL, et al. Preeclampsia risk prediction from prenatal cell-free DNA screening. Nat Med. 2025;31:1312–1318.
Correspondence: Dr. Gavin Ha at gha@fredhutch.org