👤 Sheela Sathyanarayana

Pre-pregnancy obesity (ppOB) is linked to pregnancy complications and abnormal fetal growth through placental mechanisms, and long non-coding RNAs (lncRNAs) may play an epigenetic role in these processes. We investigated overall and sex-specific associations of pre-pregnancy body mass index (ppBMI), ppOB, and birthweight with placental lncRNA transcripts in two birth cohorts. Study participants were mother-child dyads recruited to the CANDLE (Memphis, TN)( Show less

T(14;19) is an unusual but distinct genomic alteration reported in low-grade B-cell lymphomas. This structural rearrangement places BCL3 in juxtaposition with IGH inducing proliferation and has been found in chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), marginal zone lymphoma (MZL), and other low-grade B-cell lymphomas. While there are some case series describing this in the context of other cytogenetic alterations, there are limited clinical cases examined from a molecular perspective. We herein describe a case of a low-grade B-cell lymphoma with t(14;19) resulting in IGH::BCL3 fusion on which we performed whole exome sequencing to investigate genetic variants that could contribute to its pathogenesis. We found pathogenic alterations including a variant in CXCR4 which has been shown to be recurrently mutated in different low-grade B-cell lymphomas including lymphoplasmacytic lymphoma (LPL) and MZL. We describe this interesting case in the context of its genomic findings and how it contributes to the literature as a whole. Show less

The placenta is a vital fetal organ that plays an important role in maintaining fetal sex hormone homeostasis. Xenobiotics can alter placental sex-steroidogenic enzymes and transporters, including enzymes such as aromatase (CYP19A1) and the hydroxysteroid dehydrogenases (HSDs) but studying how compounds disrupt in vivo placental metabolism is complex. Utilizing high-throughput in vitro models is critical to predict the disruption of placental sex-steroidogenic enzymes and transporters, particularly by drug candidates in the early stages of drug discovery. JAR and JEG-3 cells are the most common, simple, and cost-effective placental cell models that are capable of high-throughput screening, but how well they express the sex-steroidogenic enzymes and transporters is not well known. Here, we compared the proteomes of JAR and JEG-3 cells in the presence and absence of physiologically relevant concentrations of dehydroepiandrosterone (DHEA, 8 µM) and testosterone (15 nM) to aid the characterization of sex-steroidogenic enzymes and transporters in these cell models. Global proteomics analysis detected 2931 and 3449 proteins in JAR cells and JEG-3 cells, respectively. However, dramatic differences in sex-steroidogenic enzymes and transporters were observed between these cells. In particular, the basal expression of steroid sulfatase (STS), HSD17B1, and HSD17B7 were unique to JEG-3 cells. JEG-3 cells also showed significantly higher protein levels of aldo-keto reductase (AKR) 1A1 and AKR1B1, while JAR cells showed significantly higher levels of HSD17B4 and HSDB12. Aldehyde dehydrogenase (ALDH) 3A2 and HSD17B11 enzymes as well as the transporters sterol O-acyltransferase (SOAT) 1 and ATP binding cassette subfamily G2 (ABCG2) were comparable between the cell lines, whereas sulfotransferases (SULTs) were uniquely present within JAR cells. Androgen treatments significantly lowered HSD17B11, HSD17B4, HSD17B12, and ALDH3A2 levels in JAR cells. DHEA treatment significantly raised the level of HSD17B1 by 51 % in JEG-3 cells, whereas CYP19A1 was increased to significant levels in both JAR and JEG-3 cells after androgen treatments. The proteomics data were supported by a complementary targeted metabolomics analysis of culture media in the DHEA (8 µM) and testosterone (15 nM) treated groups. This study has indicated that untreated JEG-3 cells express more sex-steroidogenic enzymes and transporters. Nevertheless, JEG-3 and JAR cells are unique and their respective proteomics data can be used to select the best model depending on the hypothesis. Show less