Impact of the X Chromosome and sex on regulatory variation.

The X Chromosome, with its unique mode of inheritance, contributes to differences between the sexes at a molecular level, including sex-specific gene expression and sex-specific impact of genetic variation. Improving our understanding of these differences offers to elucidate the molecular mechanisms underlying sex-specific traits and diseases. However, to date, most studies have either ignored the X Chromosome or had insufficient power to test for the sex-specific impact of genetic variation. By analyzing whole blood transcriptomes of 922 individuals, we have conducted the first large-scale, genome-wide analysis of the impact of both sex and genetic variation on patterns of gene expression, including comparison between the X Chromosome and autosomes. We identified a depletion of expression quantitative trait loci (eQTL) on the X Chromosome, especially among genes under high selective constraint. In contrast, we discovered an enrichment of sex-specific regulatory variants on the X Chromosome. To resolve the molecular mechanisms underlying such effects, we generated chromatin accessibility data through ATAC-sequencing to connect sex-specific chromatin accessibility to sex-specific patterns of expression and regulatory variation. As sex-specific regulatory variants discovered in our study can inform sex differences in heritable disease prevalence, we integrated our data with genome-wide association study data for multiple immune traits identifying several traits with significant sex biases in genetic susceptibilities. Together, our study provides genome-wide insight into how genetic variation, the X Chromosome, and sex shape human gene regulation and disease.

Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration.

BACKGROUND: Epithelial to mesenchymal transition (EMT) is the process by which stationary epithelial cells transdifferentiate to mesenchymal cells with increased motility. EMT is integral in early stages of development and wound healing. Studies have shown that EMT could be a critical early event in tumor metastasis that is involved in acquisition of migratory and invasive properties in multiple carcinomas. METHODS: In this study, we used 15 published gene expression microarray datasets from Gene Expression Omnibus (GEO) that represent 12 cell lines from 6 cancer types across 95 observations (45 unique samples and 50 replicates) with different modes of induction of EMT or the reverse transition, mesenchymal to epithelial transition (MET). We integrated multiple gene expression datasets while considering study differences, batch effects, and noise in gene expression measurements. A universal differential EMT gene list was obtained by normalizing and correcting the data using four approaches, computing differential expression from each, and identifying a consensus ranking. We confirmed our discovery of novel EMT genes at mRNA and protein levels in an in vitro EMT model of prostate cancer - PC3 epi, EMT and Taxol resistant cell lines. We validate our discovery of C1orf116 as a novel EMT regulator by siRNA knockdown of C1orf116 in PC3 epithelial cells. RESULTS: Among differentially expressed genes, we found known epithelial and mesenchymal marker genes such as CDH1 and ZEB1. Additionally, we discovered genes known in a subset of carcinomas that were unknown in prostate cancer. This included epithelial specific LSR and S100A14 and mesenchymal specific DPYSL3. Furthermore, we also discovered novel EMT genes including a poorly-characterized gene C1orf116. We show that decreased expression of C1orf116 is associated with poor prognosis in lung and prostate cancer patients. We demonstrate that knockdown of C1orf116 expression induced expression of mesenchymal genes in epithelial prostate cancer cell line PC3-epi cells, suggesting it as a candidate driver of the epithelial phenotype. CONCLUSIONS: This comprehensive approach of statistical analysis and functional validation identified global expression patterns in EMT and candidate regulatory genes, thereby both extending current knowledge and identifying novel drivers of EMT.

The presence of androgen receptor elements regulates ZEB1 expression in the absence of androgen receptor.

Zinc finger E-box binding homeobox 1 (ZEB1) is a transcription factor that plays a central role in the epithelial to mesenchymal transition (EMT) of cancer cell lines. Studies on its regulation have mostly focused on the negative 3'UTR binding of miR200c. Interestingly, it has been previously reported that androgen receptor (AR) regulates ZEB1 expression in breast and prostate cancers. In order to validate this, various ZEB1 promoter deletions were cloned into a luciferase reporter system to elucidate the contribution of two putative androgen response elements (AREs). The in vivo contribution of AR was also assessed in cell lines after R1881 treatment using qPCR with prostate specific antigen (PSA) as the positive control. We discovered that AR upregulates the levels of expression of ZEB1 10-fold on a luciferase promoter that only contains the distal ARE. However, when the proximal ARE is included, no additional activation is apparent with AR or its hormone independent variant, AR-V7. Furthermore, we demonstrate here that a promoter construct containing both AREs activates transcription of ZEB1 even in the AR-null cell lines DU145 and PC3. Incubation of the AR-positive cell line, LNCaP with R1881, failed to substantially increase the expression levels of ZEB1. Despite the presence of AREs in the promoter region, it appears that ZEB1 expression can be induced even without AR. In addition, the region around the distal ARE is a potent repressor in AR-null cell lines.

Epithelial-mesenchymal transition in prostate cancer is associated with quantifiable changes in nuclear structure.

BACKGROUND: Prostate cancer progression is concomitant with quantifiable nuclear structure and texture changes as compared to non-cancer tissue. Malignant progression is associated with an epithelial-mesenchymal transition (EMT) program whereby epithelial cancer cells take on a mesenchymal phenotype and dissociate from a tumor mass, invade, and disseminate to distant metastatic sites. The objective of this study was to determine if epithelial and mesenchymal prostate cancer cells have different nuclear morphology. METHODS: Murine tibia injections of epithelial PC3 (PC3-Epi) and mesenchymal PC3 (PC3-EMT) prostate cancer cells were processed and stained with H&E. Cancer cell nuclear image data was obtained using commercially available image-processing software. Univariate and multivariate statistical analysis were used to compare the two phenotypes. Several non-parametric classifiers were constructed and permutation-tested at various training set fractions to ensure robustness of classification between PC3-Epi and PC3-EMT cells in vivo. RESULTS: PC3-Epi and PC3-EMT prostate cancer cells were separable at the single cell level in murine tibia injections on the basis of nuclear structure and texture remodeling associated with an EMT. Support vector machine and multinomial logistic regression models based on nuclear architecture features yielded AUC-ROC curves of 0.95 and 0.96, respectively, in separating PC3-Epi and PC3-EMT prostate cancer cells in vivo. CONCLUSIONS: Prostate cancer cells that have undergone an EMT demonstrated an altered nuclear structure. The association of nuclear changes and a mesenchymal phenotype demonstrates quantitative morphometric image analysis may be used to detect cancer cells that have undergone EMT. This morphometric measurement could provide valuable prognostic information in patients regarding the likelihood of [future] metastatic disease.

Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene co-expression networks.

Background: Gene co-expression networks (GCNs) describe relationships among expressed genes key to maintaining cellular identity and homeostasis. However, the small sample size of typical RNA-seq experiments which is several orders of magnitude fewer than the number of genes is too low to infer GCNs reliably. recount3, a publicly available dataset comprised of 316,443 uniformly processed human RNA-seq samples, provides an opportunity to improve power for accurate network reconstruction and obtain biological insight from the resulting networks. Results: We compared alternate aggregation strategies to identify an optimal workflow for GCN inference by data aggregation and inferred three consensus networks: a universal network, a non-cancer network, and a cancer network in addition to 27 tissue context-specific networks. Central network genes from our consensus networks were enriched for evolutionarily constrained genes and ubiquitous biological pathways, whereas central context-specific network genes included tissue-specific transcription factors and factorization based on the hubs led to clustering of related tissue contexts. We discovered that annotations corresponding to context-specific networks inferred from aggregated data were enriched for trait heritability beyond known functional genomic annotations and were significantly more enriched when we aggregated over a larger number of samples. Conclusion: This study outlines best practices for network GCN inference and evaluation by data aggregation. We recommend estimating and regressing confounders in each data set before aggregation and prioritizing large sample size studies for GCN reconstruction. Increased statistical power in inferring context-specific networks enabled the derivation of variant annotations that were enriched for concordant trait heritability independent of functional genomic annotations that are context-agnostic. While we observed strictly increasing held-out log-likelihood with data aggregation, we noted diminishing marginal improvements. Future directions aimed at alternate methods for estimating confounders and integrating orthogonal information from modalities such as Hi-C and ChIP-seq can further improve GCN inference.

Coexpression network architecture reveals the brain-wide and multiregional basis of disease susceptibility.

Gene networks have yielded numerous neurobiological insights, yet an integrated view across brain regions is lacking. We leverage RNA sequencing in 864 samples representing 12 brain regions to robustly identify 12 brain-wide, 50 cross-regional and 114 region-specific coexpression modules. Nearly 40% of genes fall into brain-wide modules, while 25% comprise region-specific modules reflecting regional biology, such as oxytocin signaling in the hypothalamus, or addiction pathways in the nucleus accumbens. Schizophrenia and autism genetic risk are enriched in brain-wide and multiregional modules, indicative of broad impact; these modules implicate neuronal proliferation and activity-dependent processes, including endocytosis and splicing, in disease pathophysiology. We find that cell-type-specific long noncoding RNA and gene isoforms contribute substantially to regional synaptic diversity and that constrained, mutation-intolerant genes are primarily enriched in neurons. We leverage these data using an omnigenic-inspired network framework to characterize how coexpression and gene regulatory networks reflect neuropsychiatric disease risk, supporting polygenic models.

The impact of sex on gene expression across human tissues.

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

Addressing confounding artifacts in reconstruction of gene co-expression networks.

Gene co-expression networks capture biological relationships between genes and are important tools in predicting gene function and understanding disease mechanisms. We show that technical and biological artifacts in gene expression data confound commonly used network reconstruction algorithms. We demonstrate theoretically, in simulation, and empirically, that principal component correction of gene expression measurements prior to network inference can reduce false discoveries. Using data from the GTEx project in multiple tissues, we show that this approach reduces false discoveries beyond correcting only for known confounders.

AXL Is a Putative Tumor Suppressor and Dormancy Regulator in Prostate Cancer.

Prostate cancer bone metastasis remains lethal and incurable, and often arises years after elimination of the primary tumor. It is unclear what underlies the decades-long clinical latency before recurrence, but evidence points to the existence of dormant residual tumor cells that disseminated before the primary tumor was eliminated. To design therapies to prevent progression of disseminated tumor cells (DTC) into lethal metastases, it is crucial to understand the mechanism(s) underlying this dormancy. The current study functionally validated our previous observation that implicated the GAS6/AXL axis in mediating DTC dormancy in the bone marrow. AXL-null and AXL-overexpressing prostate cancer cell lines were generated to determine if AXL was necessary and/or sufficient for dormancy. Characterization of these cells in vitro and using in vivo mouse models of DTC growth demonstrated that AXL was indeed sufficient to induce dormancy, but was unable to maintain it long-term and was not absolutely required for a dormancy period. Clinically, AXL expression correlated with longer survival in prostate cancer patients, and AXL was not expressed by cancer cells in primary or metastatic tissue. These data point to a tumor-suppressive role for AXL in prostate cancer, and future work is required to determine if AXL is expressed on human bone marrow DTCs. IMPLICATIONS: The ability of AXL to initiate but not maintain dormancy, coupled with its dispensability, suggests that targeting AXL alone will not prevent lethal metastatic outgrowth, and likely a cooperative network of factors exists to mediate long-term cellular dormancy.

Low-Level Endogenous PSMA Expression in Nonprostatic Tumor Xenografts Is Sufficient for In Vivo Tumor Targeting and Imaging.

Prostate-specific membrane antigen (PSMA) is highly expressed in prostate cancer and within the neovasculature of other solid tumors. The nonprostatic expression of PSMA has been reported exclusively within the neovasculature endothelial cells of nonprostatic cancers; however, there are few reports on PSMA expression in epithelial cells. Herein, we describe PSMA expression in nonprostatic epithelial cells and characterize the potential of PSMA-binding agents to noninvasively detect that expression. Methods: PSMA expression data were extracted from publicly available genomic databases. Genomic data were experimentally validated for PSMA expression-by quantitative reverse transcription polymerase chain reaction, flow cytometry, and Western blotting-in several nonprostatic cell lines and xenografts of melanoma and small cell lung cancer (SCLC) origin. The feasibility of PSMA detection in those tumor models was further established using PSMA-based nuclear and optical imaging agents and by biodistribution, blocking, and ex vivo molecular characterization studies. Results: We discovered that a small percentage of nonprostatic cancer cell lines and tumors express PSMA. Importantly, PSMA expression was sufficiently high to image established melanoma and SCLC xenografts using PSMA-based nuclear and optical imaging agents. Conclusion: These results indicate that PSMA expression in nonprostatic tumors may not be limited to the endothelium but may also include solid tumor tissue of nonprostatic cancers including melanoma and SCLC. Our observations indicate broader applicability of PSMA-targeted imaging and therapeutics.

Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis.

BACKGROUND: Previous approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts. RESULTS: We examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and > 3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication. CONCLUSIONS: We find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes.

The marrow niche controls the cancer stem cell phenotype of disseminated prostate cancer.

Dissemination of cancer stem cells (CSCs) serves as the basis of metastasis. Recently, we demonstrated that circulating prostate cancer targets the hematopoietic stem cell (HSCs) 'niche' in marrow during dissemination. Once in the niche, disseminated tumor cells (DTCs) may remain dormant for extended periods. As the major function of the HSC niche is to maintain stem cell functions, we hypothesized that the niche regulates CSC activities of DTCs. Here we show that DTCs recovered from marrow were significantly enriched for a CSC phenotype. Critically, the conversion of DTCs to CSCs is regulated by niche-derived GAS6 through the Mer/mTOR; molecules previously shown to regulate dormancy. The data demonstrate that the niche plays a significant role in maintaining tumor-initiating prostate cancer in marrow and suggests a functional relationship between CSCs and dormancy. Understanding how the marrow niche regulates the conversion of DTCs to CSCs is critical for the development of therapeutics specifically targeting skeletal bone metastasis and dormancy.

OVOL guides the epithelial-hybrid-mesenchymal transition.

Metastasis involves multiple cycles of Epithelial-to-Mesenchymal Transition (EMT) and its reverse-MET. Cells can also undergo partial transitions to attain a hybrid epithelial/mesenchymal (E/M) phenotype that has maximum cellular plasticity and allows migration of Circulating Tumor Cells (CTCs) as a cluster. Hence, deciphering the molecular players helping to maintain the hybrid E/M phenotype may inform anti-metastasis strategies. Here, we devised a mechanism-based mathematical model to couple the transcription factor OVOL with the core EMT regulatory network miR-200/ZEB that acts as a three-way switch between the E, E/M and M phenotypes. We show that OVOL can modulate cellular plasticity in multiple ways - restricting EMT, driving MET, expanding the existence of the hybrid E/M phenotype and turning both EMT and MET into two-step processes. Our theoretical framework explains the differences between the observed effects of OVOL in breast and prostate cancer, and provides a platform for investigating additional signals during metastasis.

Alterations of immune response of Non-Small Cell Lung Cancer with Azacytidine.

Innovative therapies are needed for advanced Non-Small Cell Lung Cancer (NSCLC). We have undertaken a genomics based, hypothesis driving, approach to query an emerging potential that epigenetic therapy may sensitize to immune checkpoint therapy targeting PD-L1/PD-1 interaction. NSCLC cell lines were treated with the DNA hypomethylating agent azacytidine (AZA - Vidaza) and genes and pathways altered were mapped by genome-wide expression and DNA methylation analyses. AZA-induced pathways were analyzed in The Cancer Genome Atlas (TCGA) project by mapping the derived gene signatures in hundreds of lung adeno (LUAD) and squamous cell carcinoma (LUSC) samples. AZA up-regulates genes and pathways related to both innate and adaptive immunity and genes related to immune evasion in a several NSCLC lines. DNA hypermethylation and low expression of IRF7, an interferon transcription factor, tracks with this signature particularly in LUSC. In concert with these events, AZA up-regulates PD-L1 transcripts and protein, a key ligand-mediator of immune tolerance. Analysis of TCGA samples demonstrates that a significant proportion of primary NSCLC have low expression of AZA-induced immune genes, including PD-L1. We hypothesize that epigenetic therapy combined with blockade of immune checkpoints - in particular the PD-1/PD-L1 pathway - may augment response of NSCLC by shifting the balance between immune activation and immune inhibition, particularly in a subset of NSCLC with low expression of these pathways. Our studies define a biomarker strategy for response in a recently initiated trial to examine the potential of epigenetic therapy to sensitize patients with NSCLC to PD-1 immune checkpoint blockade.