Functional analysis of the 1p34.3 risk locus implicates GNL2 in high-grade serous ovarian cancer.

The high-grade serous ovarian cancer (HGSOC) risk locus at chromosome 1p34.3 resides within a frequently amplified genomic region signifying the presence of an oncogene. Here, we integrate in silico variant-to-function analysis with functional studies to characterize the oncogenic potential of candidate genes in the 1p34.3 locus. Fine mapping of genome-wide association statistics identified candidate causal SNPs local to H3K27ac-demarcated enhancer regions that exhibit allele-specific binding for CTCF in HGSOC and normal fallopian tube secretory epithelium cells (FTSECs). SNP risk associations colocalized with eQTL for six genes (DNALI1, GNL2, RSPO1, SNIP1, MEAF6, and LINC01137) that are more highly expressed in carriers of the risk allele, and three (DNALI1, GNL2, and RSPO1) were upregulated in HGSOC compared to normal ovarian surface epithelium cells and/or FTSECs. Increased expression of GNL2 and MEAF6 was associated with shorter survival in HGSOC with 1p34.3 amplifications. Despite its activation of ß-catenin signaling, RSPO1 overexpression exerted no effects on proliferation or colony formation in our study of ovarian cancer and FTSECs. Instead, GNL2, MEAF6, and SNIP1 silencing impaired in vitro ovarian cancer cell growth. Additionally, GNL2 silencing diminished xenograft tumor formation, whereas overexpression stimulated proliferation and colony formation in FTSECs. GNL2 influences 60S ribosomal subunit maturation and global protein synthesis in ovarian cancer and FTSECs, providing a potential mechanism of how GNL2 upregulation might promote ovarian cancer development and mediate genetic susceptibility of HGSOC.

High-throughput mRNA-seq atlas of human placenta shows vast transcriptome remodeling from first to third trimester†.

The placenta, composed of chorionic villi, changes dramatically across gestation. Understanding differences in ongoing pregnancies are essential to identify the role of chorionic villi at specific times in gestation and develop biomarkers and prognostic indicators of maternal-fetal health. The normative mRNA profile is established using next-generation sequencing of 124 first trimester and 43 third trimester human placentas from ongoing healthy pregnancies. Stably expressed genes (SEGs) not different between trimesters and with low variability are identified. Differential expression analysis of first versus third trimester adjusted for fetal sex is performed, followed by a subanalysis with 23 matched pregnancies to control for subject variability using the same genetic and environmental background. Placenta expresses 14,979 polyadenylated genes above sequencing noise (transcripts per million > 0.66), with 10.7% SEGs across gestation. Differentially expressed genes (DEGs) account for 86.7% of genes in the full cohort [false discovery rate (FDR) < 0.05]. Fold changes highly correlate between the full cohort and subanalysis (Pearson = 0.98). At stricter thresholds (FDR < 0.001, fold change > 1.5), there remains 50.1% DEGs (3353 upregulated in first and 4155 upregulated in third trimester). This is the largest mRNA atlas of healthy human placenta across gestation, controlling for genetic and environmental factors, demonstrating substantial changes from first to third trimester in chorionic villi. Specific differences and SEGs may be used to understand the specific role of the chorionic villi throughout gestation and develop first trimester biomarkers of placental health that transpire across gestation, which can be used for future development of biomarkers for maternal-fetal health.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites.

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Sex differences in microRNA expression in first and third trimester human placenta†.

Maternal and fetal pregnancy outcomes related to placental function vary based on fetal sex, which may be due to sexually dimorphic epigenetic regulation of RNA expression. We identified sexually dimorphic miRNA expression throughout gestation in human placentae. Next-generation sequencing identified miRNA expression profiles in first and third trimester uncomplicated pregnancies using tissue obtained at chorionic villous sampling (n = 113) and parturition (n = 47). Sequencing analysis identified 986 expressed mature miRNAs from female and male placentae at first and third trimester (baseMean>10). Of these, 11 sexually dimorphic (FDR < 0.05) miRNAs were identified in the first and 4 in the third trimester, all upregulated in females, including miR-361-5p, significant in both trimesters. Sex-specific analyses across gestation identified 677 differentially expressed (DE) miRNAs at FDR < 0.05 and baseMean>10, with 508 DE miRNAs in common between female-specific and male-specific analysis (269 upregulated in first trimester, 239 upregulated in third trimester). Of those, miR-4483 had the highest fold changes across gestation. There were 62.5% more female exclusive differences with fold change>2 across gestation than male exclusive (52 miRNAs vs 32 miRNAs), indicating miRNA expression across human gestation is sexually dimorphic. Pathway enrichment analysis identified significant pathways that were differentially regulated in first and third trimester as well as across gestation. This work provides the normative sex dimorphic miRNA atlas in first and third trimester, as well as the sex-independent and sex-specific placenta miRNA atlas across gestation, which may be used to identify biomarkers of placental function and direct functional studies investigating placental sex differences.

Molecular signatures of X chromosome inactivation and associations with clinical outcomes in epithelial ovarian cancer.

X chromosome inactivation (XCI) is a key epigenetic gene expression regulatory process, which may play a role in women's cancer. In particular tissues, some genes are known to escape XCI, yet patterns of XCI in ovarian cancer (OC) and their clinical associations are largely unknown. To examine XCI in OC, we integrated germline genotype with tumor copy number, gene expression and DNA methylation information from 99 OC patients. Approximately 10% of genes showed different XCI status (either escaping or being subject to XCI) compared with the studies of other tissues. Many of these genes are known oncogenes or tumor suppressors (e.g. DDX3X, TRAPPC2 and TCEANC). We also observed strong association between cis promoter DNA methylation and allele-specific expression imbalance (P = 2.0 × 10-10). Cluster analyses of the integrated data identified two molecular subgroups of OC patients representing those with regulated (N = 47) and dysregulated (N = 52) XCI. This XCI cluster membership was associated with expression of X inactive specific transcript (P = 0.002), a known driver of XCI, as well as age, grade, stage, tumor histology and extent of residual disease following surgical debulking. Patients with dysregulated XCI (N = 52) had shorter time to recurrence (HR = 2.34, P = 0.001) and overall survival time (HR = 1.87, P = 0.02) than those with regulated XCI, although results were attenuated after covariate adjustment. Similar findings were observed when restricted to high-grade serous tumors. We found evidence of a unique OC XCI profile, suggesting that XCI may play an important role in OC biology. Additional studies to examine somatic changes with paired tumor-normal tissue are needed.

In vivo discovery of RNA proximal proteins via proximity-dependent biotinylation.

RNA molecules function as messenger RNAs (mRNAs) that encode proteins and noncoding transcripts that serve as adaptor molecules, structural components, and regulators of genome organization and gene expression. Their function and regulation are largely mediated by RNA binding proteins (RBPs). Here we present RNA proximity labelling (RPL), an RNA-centric method comprising the endonuclease-deficient Type VI CRISPR-Cas protein dCas13b fused to engineered ascorbate peroxidase APEX2. RPL discovers target RNA proximal proteins in vivo via proximity-based biotinylation. RPL applied to U1 identified proteins involved in both U1 canonical and noncanonical functions. Profiling of poly(A) tail proximal proteins uncovered expected categories of RBPs and provided additional evidence for 5'-3' proximity and unexplored subcellular localizations of poly(A)+ RNA. Our results suggest that RPL allows rapid identification of target RNA binding proteins in native cellular contexts, and is expected to pave the way for discovery of novel RNA-protein interactions important for health and disease.

Identification of novel epithelial ovarian cancer loci in women of African ancestry.

Women of African ancestry have lower incidence of epithelial ovarian cancer (EOC) yet worse survival compared to women of European ancestry. We conducted a genome-wide association study in African ancestry women with 755 EOC cases, including 537 high-grade serous ovarian carcinomas (HGSOC) and 1,235 controls. We identified four novel loci with suggestive evidence of association with EOC (p < 1 × 10-6 ), including rs4525119 (intronic to AKR1C3), rs7643459 (intronic to LOC101927394), rs4286604 (12 kb 3' of UGT2A2) and rs142091544 (5 kb 5' of WWC1). For HGSOC, we identified six loci with suggestive evidence of association including rs37792 (132 kb 5' of follistatin [FST]), rs57403204 (81 kb 3' of MAGEC1), rs79079890 (LOC105376360 intronic), rs66459581 (5 kb 5' of PRPSAP1), rs116046250 (GABRG3 intronic) and rs192876988 (32 kb 3' of GK2). Among the identified variants, two are near genes known to regulate hormones and diseases of the ovary (AKR1C3 and FST), and two are linked to cancer (AKR1C3 and MAGEC1). In follow-up studies of the 10 identified variants, the GK2 region SNP, rs192876988, showed an inverse association with EOC in European ancestry women (p = 0.002), increased risk of ER positive breast cancer in African ancestry women (p = 0.027) and decreased expression of GK2 in HGSOC tissue from African ancestry women (p = 0.004). A European ancestry-derived polygenic risk score showed positive associations with EOC and HGSOC in women of African ancestry suggesting shared genetic architecture. Our investigation presents evidence of variants for EOC shared among European and African ancestry women and identifies novel EOC risk loci in women of African ancestry.

Genomic heterogeneity in peritoneal implants: A differential analysis of gene expression using nanostring Human Cancer Reference panel identifies a malignant signature.

OBJECTIVES: Peritoneal implants of ovarian borderline serous tumors are diagnostically challenging. Distinguishing invasive from non-invasive cases is crucial for patient management. This study aims to develop a molecular signature to distinguish invasive implants with malignant potential from those with benign. METHODS: Archival formalin-fixed paraffin embedded tissues were retrieved from 3 institutions, with consensus histologic review. Lesions were classified as a non-invasive implant (n = 10), invasive implant (n = 9) or high grade (HG) peritoneal metastasis from HG serous ovarian carcinoma (n = 4). The nCounter® GX Human Cancer Gene Reference Assay was used to profile expression of 230 cancer genes and 6 control genes. The DEGs in HG peritoneal metastases compared to non-invasive implants were identified using T-tests performed in the NanoString Diff package, then used to cluster cases using the Eisen cluster 3.0 package. Lasso in glmnet package was used to select the subset of genes that most strongly correlate with a malignant potential. RESULTS: 37 genes were downregulated and 16 genes were upregulated in HG peritoneal metastases. Using this 53-gene signature, one of nine of the invasive implants clustered with the HG peritoneal metastasis. Expression of ABCB1, CDC2, CDKN1A, FAT1, MMP9, MSH2, NQO1 and TOP2A were sufficient to indicate malignant potential of implants. The HG peritoneal metastasis and one invasive implant exhibited a high malignant likelihood (>92%) whereas the non-invasive implants and eight invasive implants displayed a low malignant likelihood (≤0.1%). CONCLUSIONS: Invasive implants are heterogenous and often morphologically indistinguishable lesions with transcriptomes that may be classified as malignant or not. Additional research is needed to determine the importance of these genes as drivers and/or surrogates of malignant potential, and their utility for triaging invasive implants.

GENAVi: a shiny web application for gene expression normalization, analysis and visualization.

BACKGROUND: The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. RESULTS: We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. CONCLUSION: The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Genome-wide association studies identify susceptibility loci for epithelial ovarian cancer in east Asian women.

OBJECTIVE: Genome-wide association studies (GWASs) for epithelial ovarian cancer (EOC) have focused largely on populations of European ancestry. We aimed to identify common germline variants associated with EOC risk in Asian women. METHODS: Genotyping was performed as part of the OncoArray project. Samples with >60% Asian ancestry were included in the analysis. Genotyping was performed on 533,631 SNPs in 3238 Asian subjects diagnosed with invasive or borderline EOC and 4083 unaffected controls. After imputation, genotypes were available for 11,595,112 SNPs to identify associations. RESULTS: At chromosome 6p25.2, SNP rs7748275 was associated with risk of serous EOC (odds ratio [OR] = 1.34, P = 8.7 × 10-9) and high-grade serous EOC (HGSOC) (OR = 1.34, P = 4.3 × 10-9). SNP rs6902488 at 6p25.2 (r2 = 0.97 with rs7748275) lies in an active enhancer and is predicted to impact binding of STAT3, P300 and ELF1. We identified additional risk loci with low Bayesian false discovery probability (BFDP) scores, indicating they are likely to be true risk associations (BFDP <10%). At chromosome 20q11.22, rs74272064 was associated with HGSOC risk (OR = 1.27, P = 9.0 × 10-8). Overall EOC risk was associated with rs10260419 at chromosome 7p21.3 (OR = 1.33, P = 1.2 × 10-7) and rs74917072 at chromosome 2q37.3 (OR = 1.25, P = 4.7 × 10-7). At 2q37.3, expression quantitative trait locus analysis in 404 HGSOC tissues identified ESPNL as a putative candidate susceptibility gene (P = 1.2 × 10-7). CONCLUSION: While some risk loci were shared between East Asian and European populations, others were population-specific, indicating that the landscape of EOC risk in Asian women has both shared and unique features compared to women of European ancestry.

An integrative approach to assess X-chromosome inactivation using allele-specific expression with applications to epithelial ovarian cancer.

X-chromosome inactivation (XCI) epigenetically silences transcription of an X chromosome in females; patterns of XCI are thought to be aberrant in women's cancers, but are understudied due to statistical challenges. We develop a two-stage statistical framework to assess skewed XCI and evaluate gene-level patterns of XCI for an individual sample by integration of RNA sequence, copy number alteration, and genotype data. Our method relies on allele-specific expression (ASE) to directly measure XCI and does not rely on male samples or paired normal tissue for comparison. We model ASE using a two-component mixture of beta distributions, allowing estimation for a given sample of the degree of skewness (based on a composite likelihood ratio test) and the posterior probability that a given gene escapes XCI (using a Bayesian beta-binomial mixture model). To illustrate the utility of our approach, we applied these methods to data from tumors of ovarian cancer patients. Among 99 patients, 45 tumors were informative for analysis and showed evidence of XCI skewed toward a particular parental chromosome. For 397 X-linked genes, we observed tumor XCI patterns largely consistent with previously identified consensus states based on multiple normal tissue types. However, 37 genes differed in XCI state between ovarian tumors and the consensus state; 17 genes aberrantly escaped XCI in ovarian tumors (including many oncogenes), whereas 20 genes were unexpectedly inactivated in ovarian tumors (including many tumor suppressor genes). These results provide evidence of the importance of XCI in ovarian cancer and demonstrate the utility of our two-stage analysis.

Validity and prognostic significance of sperm protein 17 as a tumor biomarker for epithelial ovarian cancer: a retrospective study.

BACKGROUND: Prior small studies have shown increased expression of sperm protein 17 (Sp17) in epithelial ovarian cancer (EOC) tissue and suggest Sp17 as a potential biomarker for EOC. However, how Sp17 expression varies with histology, grade, and stage of EOC and its expression in other ovarian neoplasms has not been defined. It is unknown whether patients with EOC have elevated serum Sp17 levels or if Sp17 expression is associated with survival outcomes. METHODS: The study included 982 patients with benign, borderline, and malignant ovarian neoplasms and normal ovary. There were 878 patients with tissue only, 39 with serum only, and 65 with matching serum and tissue. Immunohistochemical (IHC) staining with anti-Sp17 antibody was performed on tissue specimens and the intensity scored as weak, moderate, or strong. A sandwich enzyme-linked immunosorbent assay (ELISA) was performed to measure Sp17 sera concentrations. RESULTS: Sp17 expression was most commonly seen in serous cystadenomas (83%) and serous borderline tumors (100%). Of the 773 EOC specimens, 223 (30%) expressed Sp17. Grade and histology were significantly associated with Sp17 expression among EOC specimens (p < 0.001) on both univariate and multivariable analysis, with grade 1 serous adenocarcinomas showing the highest expression (51%). Sp17 expression was limited in other benign and non-epithelial malignant neoplasms. Neither Sp17 tissue expression nor serum concentration correlated with survival outcomes. Serum concentrations were higher in patients with Sp17 tissue expression, and the highest concentrations were noted among patients with serous and clear cell adenocarcinomas. CONCLUSIONS: Sp17 is highly expressed in benign, borderline, and low grade malignant serous ovarian neoplasms and can be quantified in serum. Sp17 expression may have diagnostic significance in this subset of patients.

Inherited variation in circadian rhythm genes and risks of prostate cancer and three other cancer sites in combined cancer consortia.

Circadian disruption has been linked to carcinogenesis in animal models, but the evidence in humans is inconclusive. Genetic variation in circadian rhythm genes provides a tool to investigate such associations. We examined associations of genetic variation in nine core circadian rhythm genes and six melatonin pathway genes with risk of colorectal, lung, ovarian and prostate cancers using data from the Genetic Associations and Mechanisms in Oncology (GAME-ON) network. The major results for prostate cancer were replicated in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial, and for colorectal cancer in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). The total number of cancer cases and controls was 15,838/18,159 for colorectal, 14,818/14,227 for prostate, 12,537/17,285 for lung and 4,369/9,123 for ovary. For each cancer site, we conducted gene-based and pathway-based analyses by applying the summary-based Adaptive Rank Truncated Product method (sARTP) on the summary association statistics for each SNP within the candidate gene regions. Aggregate genetic variation in circadian rhythm and melatonin pathways were significantly associated with the risk of prostate cancer in data combining GAME-ON and PLCO, after Bonferroni correction (ppathway < 0.00625). The two most significant genes were NPAS2 (pgene = 0.0062) and AANAT (pgene = 0.00078); the latter being significant after Bonferroni correction. For colorectal cancer, we observed a suggestive association with the circadian rhythm pathway in GAME-ON (ppathway = 0.021); this association was not confirmed in GECCO (ppathway = 0.76) or the combined data (ppathway = 0.17). No significant association was observed for ovarian and lung cancer. These findings support a potential role for circadian rhythm and melatonin pathways in prostate carcinogenesis. Further functional studies are needed to better understand the underlying biologic mechanisms.

Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci.

Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most single-nucleotide polymorphisms (SNPs) associated with cancer risk lie in non-protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs) and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared with normal human mammary epithelial cells and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissue-specific regulatory signatures compared to non-gynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P = 3.8 × 10(-30)), OSECs (P = 2.4 × 10(-23)) and HMECs (P = 6.7 × 10(-15)) but not for EECs (P = 0.45) or LNCaP cells (P = 0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) suggesting both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets of germline genetic susceptibility variants for ovarian cancer.

Epithelial-Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk.

Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07-1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69-0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.

Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer.

Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene.

NPPB is a novel candidate biomarker expressed by cancer-associated fibroblasts in epithelial ovarian cancer.

Most solid tumors contain cancer-associated fibroblasts (CAFs) that support tumorigenesis and malignant progression. However, the cellular origins of CAFs in epithelial ovarian cancers (EOCs) remain poorly understood, and their utility as a source of clinical biomarkers for cancer diagnosis has not been explored in great depth. Here, we report establishing in vitro and in vivo models of CAFs in ovarian cancer development. Normal ovarian fibroblasts and mesenchymal stem cells cultured in the presence of EOC cells acquired a CAF-like phenotype, and promoted EOC cell migration in vitro. CAFs also promoted ovarian cancer growth in vivo in both subcutaneous and intraperitoneal murine xenograft assays. Molecular profiling of CAFs identified gene expression signatures that were highly enriched for extracellular and secreted proteins. We identified novel candidate CAF-specific biomarkers for ovarian cancer including NPPB, which was expressed in the stroma of 60% primary ovarian cancer tissues (n = 145) but not in the stroma of normal ovaries (n = 4). NPPB is a secreted protein that was also elevated in the blood of 50% of women with ovarian cancer (n = 8). Taken together, these data suggest that the tumor stroma is a novel source of biomarkers, including NPPB, that may be of clinical utility for detection of EOC.

Identification of novel candidate biomarkers of epithelial ovarian cancer by profiling the secretomes of three-dimensional genetic models of ovarian carcinogenesis.

Epithelial ovarian cancer (EOC) is still considered the most lethal gynecological malignancy and improved early detection of ovarian cancer is crucial to improving patient prognoses. To address this need, we tested whether candidate EOC biomarkers can be identified using three-dimensional (3D) in vitro models. We quantified changes in the abundance of secreted proteins in a 3D genetic model of early-stage EOC, generated by expressing CMYC and KRAS(G) (12) (V) in TERT-immortalized normal ovarian epithelial cells. Cellular proteins were labeled in live cells using stable isotopic amino acid analogues, and secreted proteins identified and quantified using liquid chromatography-tandem mass spectrometry. Thirty-seven and 55 proteins were differentially expressed by CMYC and CMYC+KRAS(G) (12) (V) expressing cells respectively (p < 0.05; >2-fold). We evaluated expression of the top candidate biomarkers in ∼210 primary EOCs: CHI3L1 and FKBP4 are both expressed by >96% of primary EOCs, and FASN and API5 are expressed by 86 and 75% of cases. High expression of CHI3L1 and FKBP4 was associated with worse patient survival (p = 0.042 and p = 0.002, respectively). Expression of LGALS3BP was positively associated with recurrence (p = 0.0001) and suboptimal debulking (p = 0.018) suggesting that these proteins may be novel prognostic biomarkers. Furthermore, within early stage tumours (I/II), high expression of API5, CHI3L1 and FASN was associated with high tumour grade (p = 3 × 10(-4) , p = 0.016, p = 0.010, respectively). We show in vitro cell biology models of early-stage cancer development can be used to identify novel candidate biomarkers for disease, and report the identification of proteins that represent novel potential candidate diagnostic and prognostic biomarkers for this highly lethal disease.

Loss of Scribble causes cell competition in mammalian cells.

In Drosophila, normal and transformed cells compete with each other for survival in a process called cell competition. However, it is not known whether comparable phenomena also occur in mammals. Scribble is a tumor suppressor protein in Drosophila and mammals. In this study we examine the interface between normal and Scribble-knockdown epithelial cells using Madin-Darby Canine Kidney (MDCK) cells expressing Scribble short hairpin RNA (shRNA) in a tetracycline-inducible manner. We observe that Scribble-knockdown cells undergo apoptosis and are apically extruded from the epithelium when surrounded by normal cells. Apoptosis does not occur when Scribble-knockdown cells are cultured alone, suggesting that the presence of surrounding normal cells induces the cell death. We also show that death of Scribble-knockdown cells occurs independently of apical extrusion. Finally, we demonstrate that apoptosis of Scribble-knockdown cells depends on activation of p38 mitogen-activated protein kinase (MAPK). This is the first demonstration that an oncogenic transformation within an epithelium induces cell competition in a mammalian cell culture system.

Src as a novel therapeutic target for endometriosis.

BACKGROUND: Endometriosis is a common condition that is associated with an increased risk of developing ovarian carcinoma. Improved in vitro models of this disease are needed to better understand how endometriosis, a benign disease, can undergo neoplastic transformation, and for the development of novel treatment strategies to prevent this progression. METHODS: We describe the generation and in vitro characterization of novel TERT immortalized ovarian endometriosis epithelial cell lines (EEC16-TERT). RESULTS: Expression of TERT alone was sufficient to immortalize endometriosis epithelial cells. TERT immortalization induces an epithelial-to-mesenchymal transition and perturbation in the expression of genes involved in the development of ovarian cancer. EEC16-TERT was non-tumorigenic when xenografted into immunocompromised mice but grew in anchorage-independent growth assays in an epidermal growth factor and hydrocortisone dependent manner. Colony formation in agar was abolished by inhibition of Src, and the Src pathway was found to be activated in human endometriosis lesions. CONCLUSIONS: This new in vitro model system mimics endometriosis and the early stages of neoplastic transformation in the development of endometriosis associated ovarian cancer. We demonstrate the potential clinical relevance of this model by identifying Src activation as a novel pathway in endometriosis that could be targeted therapeutically, perhaps as a novel strategy to manage endometriosis clinically, or to prevent the development of endometriosis-associated ovarian cancer.