Epigenetic Dysregulation of Trophoblastic Gene Expression in Gestational Trophoblastic Disease.
Zoltan SzabolcsiAmanda DemeterPeter KiralyAndrea BaloghMelissa L WilsonJennifer R KingSzabolcs HeteyZsolt GelencserKoji MatsuoBeata HargitaiPaulette Mhawech-FaucegliaPetronella HupucziAndras SzilagyiZoltan PappLynda D RomanVictoria K CortessisNandor Gabor ThanPublished in: Biomedicines (2021)
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.
Keyphrases
- dna methylation
- genome wide
- gene expression
- induced apoptosis
- rna seq
- cell cycle arrest
- copy number
- cell cycle
- single cell
- signaling pathway
- extracellular matrix
- cell death
- endoplasmic reticulum stress
- cell proliferation
- big data
- weight gain
- machine learning
- oxidative stress
- long non coding rna
- single molecule
- transcription factor
- deep learning
- body mass index
- high resolution
- african american
- electronic health record
- pseudomonas aeruginosa
- physical activity
- birth weight
- candida albicans