Project description:Purpose was to determine whether varying gestational trophoblastic disease samples exhibit differences in RNA expression and fusion transcripts.
Project description:The term gestational trophoblastic disease (GTD) describes a range of pathologies derived from the villous trophoblasts of the placenta. These include benign entities such as partial and complete hydatidiform mole as well as invasive cancers such as gestational choriocarcinoma, placental site trophoblastic tumors, and epithelioid trophoblastic tumors. Collectively, the malignant forms of GTD are known as gestational trophoblastic neoplasia (GTN). The risk of GTN following a complete molar pregnancy ranges between 8-25%. Low risk patients are expected to have a high likelihood of response to single agent chemotherapy with methotrexate or actinomycin D, but the incidence of resistance to single agent chemotherapy among low risk patients remains 25-50%. We used gene expression microarrays to compare methotrexate sensitive trophoblastic cell lines to sublines that were conditioned to become methotrexate resistant.
Project description:Gestational choriocarcinoma arises from the cells of conception and is usually characterized as a fast growing, invasive and aggressive malignancy. The overall incidence is approximately 1 case per 50,000 pregnancies and aside from increasing maternal age does not appear to have any other risk factors. In contrast to most malignancies, gestational choriocarcinoma is frequently treated on a clinical diagnosis without a biopsy and therefore tumor samples of sufficient quantity to permit detailed genetic analysis are exceptionally rare. As a result, no previous whole genome sequencing or methylation studies have been reported for this rare diagnosis. With the aim of investigating the potential contribution of epigenetic changes to the pathogenesis of this rare malignancy, we have performed a methylation analysis from routine processed FFPE material in a case of intra-placental choriocarcinoma.
Project description:Gestational trophoblastic diseases (GTDs) have not been investigated for their epigenetic marks and consequent transcriptomic changes. Here, we analyzed genome-wide DNA methylation and transcriptome data to reveal the epigenetic basis of disease pathways that may lead to benign or malignant GTDs. RNA-Seq, mRNA microarray, and Human Methylation 450 BeadChip data from complete moles and choriocarcinoma cells were bioinformatically analyzed. Paraffin-embedded tissues from complete moles and control placentas were used for tissue microarray construction, DNMT3B immunostaining and immunoscoring. We found that DNA methylation increases with disease severity in GTDs. Differentially expressed genes are mainly upregulated in moles while predominantly downregulated in choriocarcinoma. DNA methylation principally influences the gene expression of villous trophoblast differentiation-related or predominantly placenta-expressed genes in moles and choriocarcinoma cells. Affected genes in these subsets shared focal adhesion and actin cytoskeleton pathways in moles and choriocarcinoma. In moles, cell cycle and differentiation regulatory pathways, essential for trophoblast/placental development, were enriched. In choriocarcinoma cells, hormone biosynthetic, extracellular matrix-related, hypoxic gene regulatory, and differentiation-related signaling pathways were enriched. In moles, we found slight upregulation of DNMT3B protein, a developmentally important de novo DNA methylase, which is strongly overexpressed in choriocarcinoma cells that may partly be responsible for the large DNA methylation differences. Our findings provide new insights into the shared and disparate molecular pathways of disease in GTDs and may help in designing new diagnostic and therapeutic tools.
Project description:Detecting uncommon causal variants (minor allele frequency [MAF] < 5%) is difficult with commercial single-nucleotide polymorphism (SNP) arrays that are designed to capture common variants (MAF > 5%). Haplotypes can provide insights into underlying linkage disequilibrium (LD) structure and can tag uncommon variants that are not well tagged by common variants. In this work, we propose a wei-SIMc-matching test that inversely weights haplotype similarities with the estimated standard deviation of haplotype counts to boost the power of similarity-based approaches for detecting uncommon causal variants. We then compare the power of the wei-SIMc-matching test with that of several popular haplotype-based tests, including four other similarity-based tests, a global score test for haplotypes (global), a test based on the maximum score statistic over all haplotypes (max), and two newly proposed haplotype-based tests for rare variant detection. With systematic simulations under a wide range of LD patterns, the results show that wei-SIMc-matching and global are the two most powerful tests. Among these two tests, wei-SIMc-matching has reliable asymptotic P-values, whereas global needs permutations to obtain reliable P-values when the frequencies of some haplotype categories are low or when the trait is skewed. Therefore, we recommend wei-SIMc-matching for detecting uncommon causal variants with surrounding common SNPs, in light of its power and computational feasibility.
Project description:•We present two cases of postmolar gestational trophoblastic neoplasia (GTN).•Both cases presented with lung metastases after hydatidiform mole.•Both cases showed spontaneous regression without treatment.•The mechanism behind this phenomenon remains unclear.•Patients with postmolar GTN and declining hCG values may not need chemotherapy.