We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk.

HNF1B is overexpressed in clear cell epithelial ovarian cancer, and we observed epigenetic silencing in serous epithelial ovarian cancer, leading us to hypothesize that variation in this gene differentially associates with epithelial ovarian cancer risk according to histological subtype. Here we comprehensively map variation in HNF1B with respect to epithelial ovarian cancer risk and analyse DNA methylation and expression profiles across histological subtypes. Different single-nucleotide polymorphisms associate with invasive serous (rs7405776 odds ratio (OR)=1.13, P=3.1 × 10(-10)) and clear cell (rs11651755 OR=0.77, P=1.6 × 10(-8)) epithelial ovarian cancer. Risk alleles for the serous subtype associate with higher HNF1B-promoter methylation in these tumours. Unmethylated, expressed HNF1B, primarily present in clear cell tumours, coincides with a CpG island methylator phenotype affecting numerous other promoters throughout the genome. Different variants in HNF1B associate with risk of serous and clear cell epithelial ovarian cancer; DNA methylation and expression patterns are also notably distinct between these subtypes. These findings underscore distinct mechanisms driving different epithelial ovarian cancer histological subtypes.

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php.

Cdc20 is an activator of the anaphase-promoting complex/cyclosome that initiates anaphase onset by ordering the destruction of cyclin B1 and securin in metaphase. To study the physiological significance of Cdc20 in higher eukaryotes, we generated hypomorphic mice that express small amounts of this essential cell cycle regulator. In this study, we show that these mice are healthy and not prone to cancer despite substantial aneuploidy. Cdc20 hypomorphism causes chromatin bridging and chromosome misalignment, revealing a requirement for Cdc20 in efficient sister chromosome separation and chromosome-microtubule attachment. We find that cyclin B1 is newly synthesized during mitosis via cytoplasmic polyadenylation element-binding protein-dependent translation, causing its rapid accumulation between prometaphase and metaphase of Cdc20 hypomorphic cells. Anaphase onset is significantly delayed in Cdc20 hypomorphic cells but not when translation is inhibited during mitosis. These data reveal that Cdc20 is particularly rate limiting for cyclin B1 destruction because of regulated de novo synthesis of this cyclin after prometaphase onset.

Pancreatic adenocarcinoma (PaC) is one of most difficult tumors to treat. Much of this is attributed to the late diagnosis. To identify biomarkers for early detection, we examined DNA methylation differences in leukocyte DNA between PaC cases and controls in a two-phase study. In phase I, we measured methylation levels at 1,505 CpG sites in treatment-naïve leukocyte DNA from 132 never-smoker PaC patients and 60 never-smoker healthy controls. We found significant differences in 110 CpG sites (false discovery rate <0.05). In phase II, we tested and validated 88 of 96 phase I selected CpG sites in 240 PaC cases and 240 matched controls (p≤0.05). Using penalized logistic regression, we built a prediction model consisting of five CpG sites (IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, TAL1_P817) that discriminated PaC patients from controls (C-statistic = 0.85 in phase I; 0.76 in phase II). Interestingly, one CpG site (LCN2_P86) alone could discriminate resectable patients from controls (C-statistic= 0.78 in phase I; 0.74 in phase II). We also performed methylation quantitative trait loci (methQTL) analysis and identified three CpG sites (AGXT_P180_F, ALOX12_E85_R, JAK3_P1075_R) where the methylation levels were significantly associated with single nucleotide polymorphisms (SNPs) (false discovery rate <0.05). Our results demonstrate that epigenetic variation in easily obtainable leukocyte DNA, manifested by reproducible methylation differences, may be used to detect PaC patients. The methylation differences at certain CpG sites are partially attributable to genetic variation. This study strongly supports future epigenome-wide association study using leukocyte DNA for biomarker discovery in human diseases.

The anaphase-promoting complex/cyclosome (APC/C) E3 ubiquitin ligase functions with the E2 ubiquitin-conjugating enzyme UbcH10 in the orderly progression through mitosis by marking key mitotic regulators for destruction by the 26-S proteasome. UbcH10 is overexpressed in many human cancer types and is associated with tumor progression. However, whether UbcH10 overexpression causes tumor formation is unknown. To address this central question and to define the molecular and cellular consequences of UbcH10 overexpression, we generated a series of transgenic mice in which UbcH10 was overexpressed in graded fashion. In this study, we show that UbcH10 overexpression leads to precocious degradation of cyclin B by the APC/C, supernumerary centrioles, lagging chromosomes, and aneuploidy. Importantly, we find that UbcH10 transgenic mice are prone to carcinogen-induced lung tumors and a broad spectrum of spontaneous tumors. Our results identify UbcH10 as a prominent protooncogene that causes whole chromosome instability and tumor formation over a wide gradient of overexpression levels.

Loss of the endosulfatase HSulf-1 is common in ovarian cancer, upregulates heparin binding growth factor signaling and potentiates tumorigenesis and angiogenesis. However, metabolic differences between isogenic cells with and without HSulf-1 have not been characterized upon HSulf-1 suppression in vitro. Since growth factor signaling is closely tied to metabolic alterations, we determined the extent to which HSulf-1 loss affects cancer cell metabolism.

Cancer progresses through distinct stages, and mouse models recapitulating traits of this progression are frequently used to explore genetic, morphological, and pharmacological aspects of tumor development. To complement genomic investigations of this process, we here quantify phosphoproteomic changes in skin cancer development using the SILAC mouse technology coupled to high-resolution mass spectrometry. We distill protein expression signatures from our data that distinguish between skin cancer stages. A distinct phosphoproteome of the two stages of cancer progression is identified that correlates with perturbed cell growth and implicates cell adhesion as a major driver of malignancy. Importantly, integrated analysis of phosphoproteomic data and prediction of kinase activity revealed PAK4-PKC/SRC network to be highly deregulated in SCC but not in papilloma. This detailed molecular picture, both at the proteome and phosphoproteome level, will prove useful for the study of mechanisms of tumor progression.

MicroRNAs play a role in regulating diverse biological processes and have considerable utility as molecular markers for diagnosis and monitoring of human disease. Several technologies are available commercially for measuring microRNA expression. However, cross-platform comparisons do not necessarily correlate well, making it difficult to determine which platform most closely represents the true microRNA expression level in a tissue. To address this issue, we have analyzed RNA derived from cell lines, as well as fresh frozen and formalin-fixed paraffin embedded tissues, using Affymetrix, Agilent, and Illumina microRNA arrays, NanoString counting, and Illumina Next Generation Sequencing. We compared the performance within- and between the different platforms, and then verified these results with those of quantitative PCR data. Our results demonstrate that the within-platform reproducibility for each method is consistently high and although the gene expression profiles from each platform show unique traits, comparison of genes that were commonly detectable showed that detection of microRNA transcripts was similar across multiple platforms.

Ductal carcinoma in situ (DCIS) of the breast is a heterogeneous group of proliferative cellular lesions that have the potential to become invasive. Very little is known about the molecular alterations involved in the progression from DCIS to invasive ductal carcinoma (IDC). Heparan endosulfatase (HSulf-2) edits sulfate moieties on heparan sulfate proteoglycans (HSPGs) and has been implicated in modulating heparin binding growth factor signaling, angiogenesis and tumorigenesis. However, the role of HSulf-2 in breast cancer progression is poorly understood. MCF10DCIS.com cells (referred as MCF10DCIS) express HSulf-2 and form comedo type DCIS and progress to IDC when transplanted in immune-deficient mice and, therefore, is an ideal model to study breast cancer progression. We evaluated the role of HSulf-2 in progression from DCIS to IDC using mouse fat pad mammary xenografts.

Cox regression is commonly used to predict the outcome by the time to an event of interest and in addition, identify relevant features for survival analysis in cancer genomics. Due to the high-dimensionality of high-throughput genomic data, existing Cox models trained on any particular dataset usually generalize poorly to other independent datasets. In this paper, we propose a network-based Cox regression model called Net-Cox and applied Net-Cox for a large-scale survival analysis across multiple ovarian cancer datasets. Net-Cox integrates gene network information into the Cox's proportional hazard model to explore the co-expression or functional relation among high-dimensional gene expression features in the gene network. Net-Cox was applied to analyze three independent gene expression datasets including the TCGA ovarian cancer dataset and two other public ovarian cancer datasets. Net-Cox with the network information from gene co-expression or functional relations identified highly consistent signature genes across the three datasets, and because of the better generalization across the datasets, Net-Cox also consistently improved the accuracy of survival prediction over the Cox models regularized by L(2) or L(1). This study focused on analyzing the death and recurrence outcomes in the treatment of ovarian carcinoma to identify signature genes that can more reliably predict the events. The signature genes comprise dense protein-protein interaction subnetworks, enriched by extracellular matrix receptors and modulators or by nuclear signaling components downstream of extracellular signal-regulated kinases. In the laboratory validation of the signature genes, a tumor array experiment by protein staining on an independent patient cohort from Mayo Clinic showed that the protein expression of the signature gene FBN1 is a biomarker significantly associated with the early recurrence after 12 months of the treatment in the ovarian cancer patients who are initially sensitive to chemotherapy. Net-Cox toolbox is available at http://compbio.cs.umn.edu/Net-Cox/.

Endometriosis is a highly prevalent, chronic, heterogeneous, fibro-inflammatory disease that remains recalcitrant to conventional therapy. We previously showed that loss of KLF11, a transcription factor implicated in uterine disease, results in progression of endometriosis. Despite extensive homology, co-expression, and human disease association, loss of the paralog Klf10 causes a unique inflammatory, cystic endometriosis phenotype in contrast to fibrotic progression seen with loss of Klf11. We identify here for the first time a novel role for KLF10 in endometriosis. In an animal endometriosis model, unlike wild-type controls, Klf10(-/-) animals developed cystic lesions with massive immune infiltrate and minimal peri-lesional fibrosis. The Klf10(-/-) disease progression phenotype also contrasted with prolific fibrosis and minimal immune cell infiltration seen in Klf11(-/-) animals. We further found that lesion genotype rather than that of the host determined each unique disease progression phenotype. Mechanistically, KLF10 regulated CD40/CD154-mediated immune pathways. Both inflammatory as well as fibrotic phenotypes are the commonest clinical manifestations in chronic fibro-inflammatory diseases such as endometriosis. The complementary, paralogous Klf10 and Klf11 models therefore offer novel insights into the mechanisms of inflammation and fibrosis in a disease-relevant context. Our data suggests that divergence in underlying gene dysregulation critically determines disease-phenotype predominance rather than the conventional paradigm of inflammation being precedent to fibrotic scarring. Heterogeneity in clinical progression and treatment response are thus likely from disparate gene regulation profiles. Characterization of disease phenotype-associated gene dysregulation offers novel approaches for developing targeted, individualized therapy for recurrent and recalcitrant chronic disease.

To assess gene signatures related to humoral response among healthy older subjects following seasonal influenza vaccination, we studied 94 healthy adults (50-74 years old) who received one documented dose of licensed trivalent influenza vaccine containing the A/California/7/2009 (H1N1)-like virus strain. Influenza-specific antibody (HAI) titer in serum samples and next-generation sequencing on PBMCs were performed using blood samples collected prior to (Day 0) and at two timepoints after (Days 3 and 28) vaccination. We identified a number of uncharacterized genes (ZNF300, NUP1333, KLK1 and others) and confirmed previous studies demonstrating specific genes/genesets that are important mediators of host immune responses and that displayed associations with antibody response to influenza A/H1N1 vaccine. These included interferon-regulatory transcription factors (IRF1/IRF2/IRF6/IRF7/IRF9), chemokine/chemokine receptors (CCR5/CCR9/CCL5), cytokine/cytokine receptors (IFNG/IL10RA/TNFRSF1A), protein kinases (MAP2K4/MAPK3), growth factor receptor (TGFBR1). The identification of gene signatures associated with antibody response represents an early stage in the science for which further research is needed. Such research may assist in the design of better vaccines to facilitate improved defenses against new influenza virus strains, as well as better understanding the genetic drivers of immune responses.

Mucinous ovarian carcinoma (MOC) is a unique subtype of ovarian cancer with an uncertain etiology, including whether it genuinely arises at the ovary or is metastatic disease from other organs. In addition, the molecular drivers of invasive progression, high-grade and metastatic disease are poorly defined. We perform genetic analysis of MOC across all histological grades, including benign and borderline mucinous ovarian tumors, and compare these to tumors from other potential extra-ovarian sites of origin. Here we show that MOC is distinct from tumors from other sites and supports a progressive model of evolution from borderline precursors to high-grade invasive MOC. Key drivers of progression identified are TP53 mutation and copy number aberrations, including a notable amplicon on 9p13. High copy number aberration burden is associated with worse prognosis in MOC. Our data conclusively demonstrate that MOC arise from benign and borderline precursors at the ovary and are not extra-ovarian metastases.

Idiopathic pulmonary fibrosis (IPF) is a fatal disease characterized by interstitial remodelling, leading to compromised lung function. Cellular senescence markers are detectable within IPF lung tissue and senescent cell deletion rejuvenates pulmonary health in aged mice. Whether and how senescent cells regulate IPF or if their removal may be an efficacious intervention strategy is unknown. Here we demonstrate elevated abundance of senescence biomarkers in IPF lung, with p16 expression increasing with disease severity. We show that the secretome of senescent fibroblasts, which are selectively killed by a senolytic cocktail, dasatinib plus quercetin (DQ), is fibrogenic. Leveraging the bleomycin-injury IPF model, we demonstrate that early-intervention suicide-gene-mediated senescent cell ablation improves pulmonary function and physical health, although lung fibrosis is visibly unaltered. DQ treatment replicates benefits of transgenic clearance. Thus, our findings establish that fibrotic lung disease is mediated, in part, by senescent cells, which can be targeted to improve health and function.

There are insufficient system-wide transcriptomic (or other) data that help explain the observed inter-individual variability in antibody titers after measles vaccination in otherwise healthy individuals.

Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10-6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. SIGNIFICANCE: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.

We aimed to assess whether endometrial cancer (EC) can be detected in shed DNA collected with vaginal tampon by analyzing copy number, methylation markers, and mutations.

CUB-domain containing protein 1 (CDCP1) is a cancer associated cell surface protein that amplifies pro-tumorigenic signalling by other receptors including EGFR and HER2. Its potential as a cancer target is supported by studies showing that anti-CDCP1 antibodies inhibit cell migration and survival in vitro, and tumor growth and metastasis in vivo. Here we characterize two anti-CDCP1 antibodies, focusing on immuno-conjugates of one of these as a tool to detect and inhibit ovarian cancer. Methods: A panel of ovarian cancer cell lines was examined for cell surface expression of CDCP1 and loss of expression induced by anti-CDCP1 antibodies 10D7 and 41-2 using flow cytometry and Western blot analysis. Surface plasmon resonance analysis and examination of truncation mutants was used to analyse the binding properties of the antibodies for CDCP1. Live-cell spinning-disk confocal microscopy of GFP-tagged CDCP1 was used to track internalization and intracellular trafficking of CDCP1/antibody complexes. In vivo, zirconium 89-labelled 10D7 was detected by positron-emission tomography imaging, of an ovarian cancer patient-derived xenograft grown intraperitoneally in mice. The efficacy of cytotoxin-conjugated 10D7 was examined against ovarian cancer cells in vitro and in vivo. Results: Our data indicate that each antibody binds with high affinity to the extracellular domain of CDCP1 causing rapid internalization of the receptor/antibody complex and degradation of CDCP1 via processes mediated by the kinase Src. Highlighting the potential clinical utility of CDCP1, positron-emission tomography imaging, using zirconium 89-labelled 10D7, was able to detect subcutaneous and intraperitoneal xenograft ovarian cancers in mice, including small (diameter <3 mm) tumor deposits of an ovarian cancer patient-derived xenograft grown intraperitoneally in mice. Furthermore, cytotoxin-conjugated 10D7 was effective at inhibiting growth of CDCP1-expressing ovarian cancer cells in vitro and in vivo. Conclusions: These data demonstrate that CDCP1 internalizing antibodies have potential for killing and detection of CDCP1 expressing ovarian cancer cells.

A major clinical challenge of ovarian cancer is the development of malignant ascites accompanied by widespread peritoneal metastasis. In ovarian clear cell carcinoma (OCCC), a challenging subtype of ovarian cancer, this problem is compounded by near-universal primary chemoresistance; patients with advanced stage OCCC thus lack effective therapies and face extremely poor survival rates. Here we show that tumor-cell-expressed serine protease inhibitor Kazal type 1 (SPINK1) is a key driver of OCCC progression and metastasis. Using cell culture models of human OCCC, we find that shRNA silencing of SPINK1 sensitizes tumor cells to anoikis and inhibits proliferation. Knockdown of SPINK1 in OCCC cells also profoundly suppresses peritoneal metastasis in mouse implantation models of human OCCC. We next identify a novel autocrine signaling axis in OCCC cells whereby tumor-cell-produced interleukin-6 (IL-6) regulates SPINK1 expression to stimulate a common protumorigenic gene expression pattern leading to anoikis resistance and proliferation of OCCC cells. We further demonstrate that this signaling pathway can be successfully interrupted with the IL-6Rα inhibitor tocilizumab, sensitizing cells to anoikis in vitro and reducing metastasis in vivo. These results suggest that clinical trials of IL-6 pathway inhibitors in OCCC may be warranted, and that SPINK1 might offer a candidate predictive biomarker in this population.