Abstract 680: Topoisomerase 2 beta facilitates chromatin reorganization during Androgen Receptor induced transcription and contributes to chromoplexy in prostate cancer

Prostate cancer (PCa) is the most common malignancy and second leading cause of cancer death in American men. Androgen Receptor (AR) mediated transcriptional program is central to normal prostate homeostasis and drives PCa growth and survival. Chromoplexy, a highly complex genomic architecture with several intra- and inter-chromosomal segments joined in a chain, is among the most prominent genetic alterations that drive both prostate cancer initiation and progression, and often involves sites of AR transcription. Previous studies have shown that AR induced, topoisomerase 2 beta (TOP2B) mediated double strand breaks were recombinogenic and led to de novo formation of TMPRSS2-ERG fusion gene, shedding light on the potential role of TOP2B in chromoplexy formation. However, the precise role of TOP2B in AR transcription was not well understood. Here, we hypothesize that TOP2B is recruited to resolve topological constraints arising during induction of AR transcriptional programs, and its catalytic activity is required to facilitate or maintain chromosomal interactions optimal for transcriptional induction. We performed Chromosomal Conformation Capture related techniques (3C and HiC) on LNCaP cells before and after androgen stimulation and observed an increase in chromatin interactions within 15kb from promoters of AR target genes upon androgen induction. These interactions depended on TOP2B, as TOP2B catalytic inhibition or knockdown reduced them significantly. Furthermore, TOP2B Hi-CHIP revealed that TOP2B is involved in key enhancer-promoter looping and in several interactions among gene body, enhancers, promoters of AR target genes, and nearby topological associated domain borders. We went on to isolate which steps during AR transcription induction required TOP2B by examining chromatin localization of the key factors, including AR, cohesin (SMC1A), CTCF, histone 3 lysine 27 acetylation (H3K27ac), and total and phosphorylated RNA Polymerase II (RNAPII) using ChIP-seq. These experiments revealed that TOP2B was not required for AR binding nor for localization of H3K27ac marks. However, it was required for recruitment of cohesin to AR binding sites as well as to AR target gene promoters and gene bodies, for displacement of CTCF near AR target genes, and for localization and phosphorylation of RNAPII at AR target genes. These data nominate TOP2B as a key AR coactivator, assisting in the proper assembly of cohesin during transcription induction, and maintaining chromosomal interactions optimal for binding and activation of RNAPII. Intriguingly, sites of binding of TOP2B, as well as of cohesin, were highly associated with sites of chromoplexy complex rearrangements in human prostate cancers. Taken together, this work elucidates the role of TOP2B in AR-induced transcription, and implicates its involvement in chromoplexy formation in PCa.

Citation Format: Minh-Tam N. Pham, Michael C. Haffner, Heather C. Wick, Jonathan B. Coulter, Anuj Gupta, Roshan V. Chikarmane, Harshath Gupta, Sarah Wheelan, William G. Nelson, Srinivasan Yegnasubramanian. Topoisomerase 2 beta facilitates chromatin reorganization during Androgen Receptor induced transcription and contributes to chromoplexy in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 680.

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

Global transcriptome dysregulation in second trimester fetuses with FMR1 expansions

OBJECTIVE

We tested the hypothesis that FMR1 expansions would result in global gene dysregulation as early as the second trimester of human fetal development.

METHOD

Using cell-free fetal RNA obtained from amniotic fluid supernatant and expression microarrays, we compared RNA levels in samples from fetuses with premutation or full mutation allele expansions with control samples.

RESULTS

We found clear signals of differential gene expression relating to a variety of cellular functions, including ubiquitination, mitochondrial function, and neuronal/synaptic architecture. Additionally, among the genes showing differential gene expression, we saw links to related diseases of intellectual disability and motor function. Finally, within the unique molecular phenotypes established for each mutation set, we saw clear signatures of mitochondrial dysfunction and disrupted neurological function. Patterns of differential gene expression were very different in male and female fetuses with premutation alleles.

CONCLUSION

These results support a model for which genetic misregulation during fetal development may set the stage for late clinical manifestations of FMR1-related disorders. © 2016 John Wiley & Sons, Ltd.

An Integrated Human/Murine Transcriptome and Pathway Approach To Identify Prenatal Treatments For Down Syndrome

Anatomical and functional brain abnormalities begin during fetal life in Down syndrome (DS). We hypothesize that novel prenatal treatments can be identified by targeting signaling pathways that are consistently perturbed in cell types/tissues obtained from human fetuses with DS and mouse embryos. We analyzed transcriptome data from fetuses with trisomy 21, age and sex-matched euploid controls, and embryonic day 15.5 forebrains from Ts1Cje, Ts65Dn, and Dp16 mice. The new datasets were compared to other publicly available datasets from humans with DS. We used the human Connectivity Map (CMap) database and created a murine adaptation to identify FDA-approved drugs that can rescue affected pathways. USP16 and TTC3 were dysregulated in all affected human cells and two mouse models. DS-associated pathway abnormalities were either the result of gene dosage specific effects or the consequence of a global cell stress response with activation of compensatory mechanisms. CMap analyses identified 56 molecules with high predictive scores to rescue abnormal gene expression in both species. Our novel integrated human/murine systems biology approach identified commonly dysregulated genes and pathways. This can help to prioritize therapeutic molecules on which to further test safety and efficacy. Additional studies in human cells are ongoing prior to pre-clinical prenatal treatment in mice.

Assessing the fetal effects of maternal obesity via transcriptomic analysis of cord blood: a prospective case-control study

OBJECTIVE

To analyse fetal gene expression at term using umbilical cord blood, in order to provide insights into the effects of maternal obesity on human development.

DESIGN

Prospective case-control study.

SETTING

Academic tertiary care centre.

POPULATION

Eight obese (body mass index ≥30 kg/m(2)) and eight lean (body mass index <25 kg/m(2)) pregnant women undergoing prelabour caesarean delivery at term.

METHODS

Women were matched for gestational age and fetal sex. Cord blood RNA was extracted and hybridised to gene expression arrays. Differentially regulated genes were identified using paired t-tests and the Benjamini-Hochberg correction. Functional analyses were performed using Ingenuity Pathway Analysis, BioGPS and Gene Set Enrichment Analysis with a fetal-specific annotation. Z-scores ≥2.0 or P-values <0.01 were considered significant.

MAIN OUTCOME MEASURE

Functions of differentially regulated genes in fetuses of obese women.

RESULTS

A total of 701 differentially regulated genes were identified, producing an expression profile implicating neurodegeneration, decreased survival of sensory neurons, and decreased neurogenesis in the fetuses of obese women. Upstream regulators related to inflammatory signalling were significantly activated; those related to insulin receptor signalling, lipid homeostasis, regulation of axonal guidance, and cellular response to oxidative stress were significantly inhibited. Of 26 tissue-specific genes that were differentially regulated in fetuses of obese women, six mapped to the fetal brain.

CONCLUSION

Maternal obesity affects fetal gene expression at term, implicating dysregulated brain development, inflammatory and immune signalling, glucose and lipid homeostasis, and oxidative stress. This may have implications for postnatal neurodevelopment and metabolism.

The pathway not taken: understanding 'omics data in the perinatal context

OBJECTIVE

'Omics analysis of large datasets has an increasingly important role in perinatal research, but understanding gene expression analyses in the fetal context remains a challenge. We compared the interpretation provided by a widely used systems biology resource (ingenuity pathway analysis [IPA]) with that from gene set enrichment analysis (GSEA) with functional annotation curated specifically for the fetus (Developmental FunctionaL Annotation at Tufts [DFLAT]).

STUDY DESIGN

Using amniotic fluid supernatant transcriptome datasets previously produced by our group, we analyzed 3 different developmental perturbations: aneuploidy (Trisomy 21 [T21]), hemodynamic (twin-twin transfusion syndrome [TTTS]), and metabolic (maternal obesity) vs sex- and gestational age-matched control subjects. Differentially expressed probe sets were identified with the use of paired t-tests with the Benjamini-Hochberg correction for multiple testing (P < .05). Functional analyses were performed with IPA and GSEA/DFLAT. Outputs were compared for biologic relevance to the fetus.

RESULTS

Compared with control subjects, there were 414 significantly dysregulated probe sets in T21 fetuses, 2226 in TTTS recipient twins, and 470 in fetuses of obese women. Each analytic output was unique but complementary. For T21, both IPA and GSEA/DFLAT identified dysregulation of brain, cardiovascular, and integumentary system development. For TTTS, both analytic tools identified dysregulation of cell growth/proliferation, immune and inflammatory signaling, brain, and cardiovascular development. For maternal obesity, both tools identified dysregulation of immune and inflammatory signaling, brain and musculoskeletal development, and cell death. GSEA/DFLAT identified substantially more dysregulated biologic functions in fetuses of obese women (1203 vs 151). For all 3 datasets, GSEA/DFLAT provided more comprehensive information about brain development. IPA consistently provided more detailed annotation about cell death. IPA produced many dysregulated terms that pertained to cancer (14 in T21, 109 in TTTS, 26 in maternal obesity); GSEA/DFLAT did not.

CONCLUSION

Interpretation of the fetal amniotic fluid supernatant transcriptome depends on the analytic program, which suggests that >1 resource should be used. Within IPA, physiologic cellular proliferation in the fetus produced many "false positive" annotations that pertained to cancer, which reflects its bias toward adult diseases. This study supports the use of gene annotation resources with a developmental focus, such as DFLAT, for 'omics studies in perinatal medicine.

The fetal brain transcriptome and neonatal behavioral phenotype in the Ts1Cje mouse model of Down syndrome

Human fetuses with Down syndrome demonstrate abnormal brain growth and reduced neurogenesis. Despite the prenatal onset of the phenotype, most therapeutic trials have been conducted in adults. Here, we present evidence for fetal brain molecular and neonatal behavioral alterations in the Ts1Cje mouse model of Down syndrome. Embryonic day 15.5 brain hemisphere RNA from Ts1Cje embryos (n = 5) and wild type littermates (n = 5) was processed and hybridized to mouse gene 1.0 ST arrays. Bioinformatic analyses were implemented to identify differential gene and pathway regulation during Ts1Cje fetal brain development. In separate experiments, the Fox scale, ultrasonic vocalization and homing tests were used to investigate behavioral deficits in Ts1Cje pups (n = 29) versus WT littermates (n = 64) at postnatal days 3-21. Ts1Cje fetal brains displayed more differentially regulated genes (n = 71) than adult (n = 31) when compared to their age-matched euploid brains. Ts1Cje embryonic brains showed up-regulation of cell cycle markers and down-regulation of the solute-carrier amino acid transporters. Several cellular processes were dysregulated at both stages, including apoptosis, inflammation, Jak/Stat signaling, G-protein signaling, and oxidoreductase activity. In addition, early behavioral deficits in surface righting, cliff aversion, negative geotaxis, forelimb grasp, ultrasonic vocalization, and the homing tests were observed. The Ts1Cje mouse model exhibits abnormal gene expression during fetal brain development, and significant neonatal behavioral deficits in the pre-weaning period. In combination with human studies, this suggests that the Down syndrome phenotype manifests prenatally and provides a rationale for prenatal therapy to improve perinatal brain development and postnatal neurocognition.

CSAX: Characterizing Systematic Anomalies in eXpression Data

Methods for translating gene expression signatures into clinically relevant information have typically relied upon having many samples from patients with similar molecular phenotypes. Here, we address the question of what can be done when it is relatively easy to obtain healthy patient samples, but when abnormalities corresponding to disease states may be rare and one-of-a-kind. The associated computational challenge, anomaly detection, is a well-studied machine-learning problem. However, due to the dimensionality and variability of expression data, existing methods based on feature space analysis or individual anomalously expressed genes are insufficient. We present a novel approach, CSAX, that identifies pathways in an individual sample in which the normal expression relationships are disrupted. To evaluate our approach, we have compiled and released a compendium of public expression data sets, reformulated to create a test bed for anomaly detection. We demonstrate the accuracy of CSAX on the data sets in our compendium, compare it to other leading methods, and show that CSAX aids in both identifying anomalies and explaining their underlying biology. We describe an approach to characterizing the difficulty of specific expression anomaly detection tasks. We then illustrate CSAX's value in two developmental case studies. Confirming prior hypotheses, CSAX highlights disruption of platelet activation pathways in a neonate with retinopathy of prematurity and identifies, for the first time, dysregulated oxidative stress response in second trimester amniotic fluid of fetuses with obese mothers. Our approach provides an important step toward identification of individual disease patterns in the era of precision medicine.

Amniotic fluid RNA gene expression profiling provides insights into the phenotype of Turner syndrome

Turner syndrome is a sex chromosome aneuploidy with characteristic malformations. Amniotic fluid, a complex biological material, could contribute to the understanding of Turner syndrome pathogenesis. In this pilot study, global gene expression analysis of cell-free RNA in amniotic fluid supernatant was utilized to identify specific genes/organ systems that may play a role in Turner syndrome pathophysiology. Cell-free RNA from amniotic fluid of five mid-trimester Turner syndrome fetuses and five euploid female fetuses matched for gestational age was extracted, amplified, and hybridized onto Affymetrix(®) U133 Plus 2.0 arrays. Significantly differentially regulated genes were identified using paired t tests. Biological interpretation was performed using Ingenuity Pathway Analysis and BioGPS gene expression atlas. There were 470 statistically significantly differentially expressed genes identified. They were widely distributed across the genome. XIST was significantly down-regulated (p < 0.0001); SHOX was not differentially expressed. One of the most highly represented organ systems was the hematologic/immune system, distinguishing the Turner syndrome transcriptome from other aneuploidies we previously studied. Manual curation of the differentially expressed gene list identified genes of possible pathologic significance, including NFATC3, IGFBP5, and LDLR. Transcriptomic differences in the amniotic fluid of Turner syndrome fetuses are due to genome-wide dysregulation. The hematologic/immune system differences may play a role in early-onset autoimmune dysfunction. Other genes identified with possible pathologic significance are associated with cardiac and skeletal systems, which are known to be affected in females with Turner syndrome. The discovery-driven approach described here may be useful in elucidating novel mechanisms of disease in Turner syndrome.

Analysis of adult cerebral cortex and hippocampus transcriptomes reveals unique molecular changes in the Ts1Cje mouse model of down syndrome

We investigated gene expression and functional differences between Ts1Cje mice and wild-type (WT) littermates in adult cerebral cortex and hippocampus. These two brain regions are affected in people with Down syndrome, but have not been previously molecularly characterized in Ts1Cje mice. Total RNA was prepared from the brains of 8-10-week-old Ts1Cje mice (n = 6) and WT littermates (n = 5) and hybridized to Affymetrix 1.0 ST gene mouse arrays. Differentially regulated genes were identified and used to perform in silico functional analyses to better characterize dysregulated pathways in both brain regions. Hippocampus had more significantly differentially expressed genes compared with cortex (30 vs. 7 at a Benjamini-Hochberg false discovery rate of 20%). We identified novel genes that were differentially regulated in adult brains, including Cyb5r1, Fsbp, Vmn2r110, Snd1 and Zhx2. Functional analyses in Ts1Cje mice highlighted the importance of NFAT signaling, oxidative stress, neuroinflammation and olfactory perception via G-protein signaling. In a comparison of adult Ts1Cje and WT brains, we identified new genes and pathway differences in the cortex and hippocampus. Our analyses identified physiologically relevant pathways that can serve as targets for the development of future treatments to improve neurocognition in Down syndrome.

RNA-Seq and expression microarray highlight different aspects of the fetal amniotic fluid transcriptome

OBJECTIVE

The aim of this study was to compare the complexity of the amniotic fluid supernatant cell-free fetal transcriptome as described by RNA Sequencing (RNA-Seq) and gene expression microarrays.

METHODS

Cell-free fetal RNA from the amniotic fluid supernatant of five euploid mid-trimester samples was divided and prepared in tandem for analysis by either the Affymetrix HG-U133 Plus 2.0 Gene Chip microarray or Illumina HiSeq. Transcriptomes were assembled and compared on the basis of the presence of signal, rank-order gene expression, and pathway enrichment using Ingenuity Pathway Analysis (IPA). RNA-Seq data were also examined for evidence of alternative splicing.

RESULTS

Within individual samples, gene expression was strongly correlated (R = 0.43-0.57). Fewer expressed genes were observed using RNA-Seq than gene expression microarrays (4158 vs 8842). Most of the top pathways in the 'Physiological Systems Development and Function' IPA category were shared between platforms, although RNA-Seq yielded more significant p-values. Using RNA-Seq, examples of known alternative splicing were detected in several genes including H19 and IGF2.

CONCLUSIONS

In this pilot study, we found that expression microarrays gave a broader view of overall gene expression, while RNA-Seq demonstrated alternative splicing and specific pathways relevant to the developing fetus. The degraded nature of cell-free fetal RNA presented technical challenges for the RNA-Seq approach.

Finding novel molecular connections between developmental processes and disease

Identifying molecular connections between developmental processes and disease can lead to new hypotheses about health risks at all stages of life. Here we introduce a new approach to identifying significant connections between gene sets and disease genes, and apply it to several gene sets related to human development. To overcome the limits of incomplete and imperfect information linking genes to disease, we pool genes within disease subtrees in the MeSH taxonomy, and we demonstrate that such pooling improves the power and accuracy of our approach. Significance is assessed through permutation. We created a web-based visualization tool to facilitate multi-scale exploration of this large collection of significant connections (http://gda.cs.tufts.edu/development). High-level analysis of the results reveals expected connections between tissue-specific developmental processes and diseases linked to those tissues, and widespread connections to developmental disorders and cancers. Yet interesting new hypotheses may be derived from examining the unexpected connections. We highlight and discuss the implications of three such connections, linking dementia with bone development, polycystic ovary syndrome with cardiovascular development, and retinopathy of prematurity with lung development. Our results provide additional evidence that plays a key role in the early pathogenesis of polycystic ovary syndrome. Our evidence also suggests that the VEGF pathway and downstream NFKB signaling may explain the complex relationship between bronchopulmonary dysplasia and retinopathy of prematurity, and may form a bridge between two currently-competing hypotheses about the molecular origins of bronchopulmonary dysplasia. Further data exploration and similar queries about other gene sets may generate a variety of new information about the molecular relationships between additional diseases.

Understanding the roles that genes involved in normal human development can play in disease processes is an important part of predicting disease risk and designing novel treatment approaches. In this study, we have identified classes of disease that are associated with a surprisingly large number of genes involved in any of several tissue-specific developmental processes. To do so, we developed a novel approach whose strength comes from pooling genetic information across related diseases, overcoming problems ordinarily posed by limited information about individual gene-disease relationships. We demonstrate the method's efficacy both by examining its ability to highlight connections between gene sets and disease classes that are known to be related, and by demonstrating that the approach recovers expected broad classes of connections, such as those between heart development and cardiovascular disorders. However, by examining unexpected connections in this data set, we are able to develop new understanding of some surprising disease relationships, such as the one between dementia and osteoporosis. Such connections may lead to a better overall understanding of the role of development in lifelong health, as well as to the design of new methods to treat a range of diseases.

DFLAT: functional annotation for human development

Background

Recent increases in genomic studies of the developing human fetus and neonate have led to a need for widespread characterization of the functional roles of genes at different developmental stages. The Gene Ontology (GO), a valuable and widely-used resource for characterizing gene function, offers perhaps the most suitable functional annotation system for this purpose. However, due in part to the difficulty of studying molecular genetic effects in humans, even the current collection of comprehensive GO annotations for human genes and gene products often lacks adequate developmental context for scientists wishing to study gene function in the human fetus.

Description

The Developmental FunctionaL Annotation at Tufts (DFLAT) project aims to improve the quality of analyses of fetal gene expression and regulation by curating human fetal gene functions using both manual and semi-automated GO procedures. Eligible annotations are then contributed to the GO database and included in GO releases of human data. DFLAT has produced a considerable body of functional annotation that we demonstrate provides valuable information about developmental genomics. A collection of gene sets (genes implicated in the same function or biological process), made by combining existing GO annotations with the 13,344 new DFLAT annotations, is available for use in novel analyses. Gene set analyses of expression in several data sets, including amniotic fluid RNA from fetuses with trisomies 21 and 18, umbilical cord blood, and blood from newborns with bronchopulmonary dysplasia, were conducted both with and without the DFLAT annotation.

Conclusions

Functional analysis of expression data using the DFLAT annotation increases the number of implicated gene sets, reflecting the DFLAT’s improved representation of current knowledge. Blinded literature review supports the validity of newly significant findings obtained with the DFLAT annotations. Newly implicated significant gene sets also suggest specific hypotheses for future research. Overall, the DFLAT project contributes new functional annotation and gene sets likely to enhance our ability to interpret genomic studies of human fetal and neonatal development.

Global gene expression analysis of amniotic fluid cell-free RNA from recipient twins with twin-twin transfusion syndrome

OBJECTIVE

The objective of this study was to understand the biological pathways involved in twin-twin transfusion syndrome (TTTS) by performing global gene expression analysis of amniotic fluid (AF) cell-free RNA.

METHODS

A prospective whole transcriptome microarray study analyzing cell-free RNA in AF from TTTS recipient twins and singleton controls was carried out. Significantly differentially regulated genes in TTTS cases (N = 8) versus matched controls (N = 8) were identified and pathways analyses performed. Significant gene expression differences between stage II TTTS recipients (N = 5) and stage III TTTS recipients with abnormal Doppler measurements (N = 5) were also analyzed.

RESULTS

Analysis of paired data from TTTS cases and controls revealed differential expression of 801 genes, which were significantly enriched for neurological disease and cardiovascular system pathways. We also identified cardiovascular genes and pathways associated with the presence of critically abnormal Doppler measurements in stage III TTTS recipients.

CONCLUSIONS

This study provides the first transcriptome-wide data on the impact of TTTS on fetal development. Our results show that gene expression involving neurological and cardiovascular pathways are altered in recipient fetuses prior to surgical treatment. This has relevance for the origins of long-term complications seen in survivors and for the development of future fetal biomarkers.

Comprehensive analysis of genes expressed by rare microchimeric fetal cells in the maternal mouse lung

During pregnancy, cells from each fetus travel into the maternal circulation and organs, resulting in the development of microchimerism. Identification of the cell types in this microchimeric population would permit better understanding of possible mechanisms by which they affect maternal health. However, comprehensive analysis of fetal cells has been hampered by their rarity. In this study, we sought to overcome this obstacle by combining flow cytometry with multidimensional gene expression microarray analysis of fetal cells isolated from the murine maternal lung during late pregnancy. Fetal cells were collected from the lungs of pregnant female mice. cDNA was amplified and hybridized to gene expression microarrays. The resulting fetal cell core transcriptome was interrogated using multiple methods including Ingenuity Pathway Analysis, the BioGPS gene expression database, principal component analysis, the Eurexpress gene expression atlas, and primary literature. Here we report that small numbers of fetal cells can be flow sorted from the maternal lung, facilitating discovery-driven gene expression analysis. We additionally show that gene expression data can provide functional information about fetal cells. Our results suggest that fetal cells in the murine maternal lung are a mixed population, consisting of trophoblasts, mesenchymal stem cells, and cells of the immune system. Detection of trophoblasts and immune cells in the maternal lung may facilitate future mechanistic studies related to the development of immune tolerance and pregnancy-related complications, such as pre-eclampsia. Furthermore, the presence and persistence of mesenchymal stem cells in maternal organs may have implications for long-term postpartum maternal health.

Novel neurodevelopmental information revealed in amniotic fluid supernatant transcripts from fetuses with trisomies 18 and 21

Trisomies 18 and 21 are the two most common live born autosomal aneuploidies in humans. While the anatomic abnormalities in affected fetuses are well documented, the dysregulated biological pathways associated with the development of the aneuploid phenotype are less clear. Amniotic fluid (AF) cell-free RNA is a valuable source of biological information obtainable from live fetuses. In this study, we mined gene expression data previously produced by our group from mid-trimester AF supernatant samples. We identified the euploid, trisomy 18 and trisomy 21 AF transcriptomes, and analyzed them with a particular focus on the nervous system. We used multiple bioinformatics resources, including DAVID, Ingenuity Pathway Analysis, and the BioGPS Gene Expression Atlas. Our analyses confirmed that AF supernatant from aneuploid fetuses is enriched for nervous system gene expression and neurological disease pathways. Tissue analysis showed that fetal brain cortex and Cajal-Retzius cells were significantly enriched for genes contained in the AF transcriptomes. We also examined AF transcripts known to be dysregulated in aneuploid fetuses compared with euploid controls and identified several brain-specific transcripts among them. Many of these genes play critical roles in nervous system development. NEUROD2, which was downregulated in trisomy 18, induces neurogenic differentiation. SOX11, downregulated in trisomy 21, is a transcription factor that is essential for pan-neuronal protein expression and axonal growth of sensory neurons. Our results show that whole transcriptome analysis of cell-free RNA in AF from live pregnancies permits discovery of biomarkers of abnormal human neurodevelopment and advances our understanding of the pathophysiology of aneuploidy.

Optimal techniques for mRNA extraction from neonatal salivary supernatant

BACKGROUND

Gene expression profiling of the salivary supernatant is emerging as a new and important source of real-time, systemic, biological information. However, existing technologies prevent RNA extraction of small quantities found in neonatal salivary supernatant.

OBJECTIVE

The aim of this study was to develop techniques to enhance extraction of cell-free RNA from neonatal salivary supernatant.

METHODS

Two saliva samples (10-100 μl) were serially collected from newborns (36-41 weeks' gestation) (n = 13) and stabilized. Total RNA was extracted from salivary supernatant with the use of two modified extraction techniques: Qiagen RNAprotect® Saliva Mini Kit (method 1) and the QIAamp Viral RNA Mini Kit (method 2). Quantitative RT-PCR amplification for GAPDH was performed on extracted salivary samples. Statistical analyses were performed on mean threshold cycle (Ct) levels to compare RNA yield from each protocol. Paired microarray analyses were made between neonatal whole saliva and supernatant (n = 3) to discern gene expression differences between these biolayers.

RESULTS

mRNA was successfully extracted and amplified from all salivary supernatant samples. Extraction with method 2 yielded more RNA than with method 1 (p = 0.008). There was a 7.5% discordance between paired gene expression analyses for whole saliva and supernatant. Genes that were statistically significantly upregulated in supernatant highlighted 16 distinct biological functions not seen in whole saliva. Conversely, only two biological functions were unique to whole saliva.

CONCLUSION

Neonatal cell-free salivary supernatant mRNA may be readily extracted and utilized on downstream applications. These technical enhancements allow for further exploration of the diagnostic potential of the neonatal salivary transcriptome.