The Macro Importance of Microarray in the Diagnosis of Wilms Tumor
Jeremy Feury
Pro |
Presented at: Department of Pathology 2025 Research Day and Retreat
Date: 2025-05-28 00:00:00
Views: 20
Summary: Wilms tumor (WT) is the most common renal malignancy in children. Various cytogenetics abnormalities have been reported in WT with significant roles in prognostication and risk stratification. We hypothesized that integrating microarray testing with karyotype analysis allows for a comprehensive evaluation of the WT genome, potentially improving diagnostic accuracy and prognosis.
Fourteen WT patients (8 males and 6 females) tested at the UPMC Cytogenetics Laboratories during 2023-25 were included in the analysis. The affected patients were between 8 months and 8 years old, with an average age of 3 years. All specimens were cultured for karyotype, while DNA from fresh specimens were used for microarray analysis. Fluorescence in situ hybridization (FISH) was performed in only 2 patients.
Karyotype revealed abnormal results in 7 of 14 patients (50%). The most common finding was hyperdiploidy. Importantly, karyotype was inconclusive in four patients due to no growth or insufficient specimen. On the other hand, all patients had successful microarray analysis that identified genetic abnormalities in 13 out of 14 (93%) patients. Abnormalities detected by microarray ranged from hyperdiploidy and partial gain (1q) or loss (16q) of chromosomes which were consistent with karyotype findings (if available), to cryptic changes such as gain of 2p (MYCN) and loss of Xq11.2 (AMER1) which were not otherwise detectable by karyotype. Microarray was able to detect copy neutral loss of heterozygosity (CN-LOH) in 2 cases.
This study highlights the significant clinical utility of microarray analysis in WT genetic assessment. Our findings demonstrate higher yield of microarray analysis, quicker turnaround time and independence from cell culture. Incorporation of microarray into WT routine clinical diagnostics enhances risk stratification, guides treatment decisions, and ultimately improves patient outcomes. Yinghong Pan, Qian Wang, Catherine Gestrich, Justin Kurtz, Jennifer Picarsic, and Mahmoud Aarabi