scholarly journals Microarray Findings of Intraplacental Choriocarcinoma: A Report of Four Cases

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S151-S152
Author(s):  
A Emanuel ◽  
C Schandl ◽  
E Bruner

Abstract Introduction/Objective Gestational trophoblastic neoplasia (GTN) is a group of poorly understood diseases characterized by an abnormal and overtly malignant proliferation of trophoblastic tissue. Choriocarcinoma, which may also be nongestational in origin, is a particularly invasive and aggressive variant of GTN that is composed of a dimorphic trophoblast population. Many studies have attempted to define choriocarcinoma via various cytogenetic, molecular, and epigenetic means; however, the exact etiology and pathogenesis of this tumor remain unclear, in large part due to its rarity. Estimates of the incidence of choriocarcinoma range from 1 in 24,000 to 1 in 40,000 pregnancies. Intraplacental tumors are even less common with 62 reported cases and an estimated incidence of 1 in 160,000 placentas. In an effort to better understand the pathogenesis of this rare entity, four cases of choriocarcinoma (of which three are intraplacental and one is intrauterine occurring one year following an unremarkable pregnancy) diagnosed at our institution since 2010 were identified for chromosomal microarray. Methods DNA was extracted from formalin-fixed, paraffin-embedded blocks of four matched cases: tumor and normal placenta. Single nucleotide polymorphism (SNP) microarray analysis was performed to assess genomic copy number differences between the tumor and the placenta from which it arose (Infinium Global Diversity Array-8 v1.0 BeadChip with an I Scan System; Illumina, San Diego, CA). Analysis of a placenta not affected by tumor was also performed. Results Early partial data review demonstrates copy number aberrations in choriocarcinoma arising in placental tissue. Additional interpretation of the data is ongoing. Conclusion DNA chromosomal microarray analysis was performed to search for genomic copy number differences in between the tumor and the placenta from which it arose. Recent studies suggest gestational choriocarcinoma oncogenesis may differ from that of other malignancies, but this conclusion is based on a low number of recurrent DNA mutations. SNP microarray analysis may further refine the current understanding of the oncogenesis of gestational choriocarcinoma.

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253866
Author(s):  
Marta Larroya ◽  
Marta Tortajada ◽  
Eduard Mensión ◽  
Montse Pauta ◽  
Laia Rodriguez-Revenga ◽  
...  

The objective of this study was to determine whether maternal or paternal ages have any impact on the prenatal incidence of genomic copy number variants (CNV) in fetuses with structural anomalies. We conducted a non-paired case-control study (1:2 ratio) among pregnancies undergoing chromosomal microarray analysis (CMA) because of fetal ultrasound anomalies, from December 2012 to May 2020. Pregnancies with any pathogenic copy number variant (CNV), either microdeletion or microduplication, were defined as cases. Controls were selected as the next two pregnancies with the same indication for CMA but with a normal result. Logistic regression was used, adjusting by use of assisted reproductive technology (ART) and parental smoking. Stratified analysis was performed according to CNV type (de novo/inherited and recurrent/non-recurrent). The study included 189 pregnancies: 63 cases and 126 controls. Mean maternal age in cases was 33.1 (SD 4.6) years and 33.9 (SD 6.0) years in controls. Mean paternal mean age was 34.5 (SD 4.8) years in cases and 35.8 (SD 5.8) years in controls. No significant differences in maternal or paternal age were observed, neither in stratified analysis according to the CNV type. Moreover, the proportion of cases were not significantly different between non-advanced and advanced ages, either considering paternal or maternal ages. The presence of pathogenic CNV at CMA in fetuses with structural anomalies was not found to be associated with advanced paternal or maternal age.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chia-Hsiang Chen ◽  
Min-Chih Cheng ◽  
Tsung-Ming Hu ◽  
Lieh-Yung Ping

Schizophrenia is a chronic, devastating mental disorder with complex genetic components. Given the advancements in the molecular genetic research of schizophrenia in recent years, there is still a lack of genetic tests that can be used in clinical settings. Chromosomal microarray analysis (CMA) has been used as first-tier genetic testing for congenital abnormalities, developmental delay, and autism spectrum disorders. This study attempted to gain some experience in applying chromosomal microarray analysis as a first-tier genetic test for patients with schizophrenia. We consecutively enrolled patients with schizophrenia spectrum disorder from a clinical setting and conducted genome-wide copy number variation (CNV) analysis using a chromosomal microarray platform. We followed the 2020 “Technical Standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen)” to interpret the clinical significance of CNVs detected from patients. We recruited a total of 60 patients (36 females and 24 males) into this study. We detected three pathogenic CNVs and one likely pathogenic CNV in four patients, respectively. The detection rate was 6.7% (4/60, 95% CI: 0.004–0.13), comparable with previous studies in the literature. Also, we detected thirteen CNVs classified as uncertain clinical significance in nine patients. Detecting these CNVs can help establish the molecular genetic diagnosis of schizophrenia patients and provide helpful information for genetic counseling and clinical management. Also, it can increase our understanding of the pathogenesis of schizophrenia. Hence, we suggest CMA is a valuable genetic tool and considered first-tier genetic testing for schizophrenia spectrum disorders in clinical settings.


2021 ◽  
Vol Volume 14 ◽  
pp. 1431-1438
Author(s):  
Xiangqun Fan ◽  
Hailong Huang ◽  
Xiyao Lin ◽  
Huili Xue ◽  
Meiying Cai ◽  
...  

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