Browsing by Subject "ovarian cancer"
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Item Open Access Development and Characterization of a Luciferase Labeled, Syngeneic Murine Model of Ovarian Cancer.(Cancers, 2022-08) Russell, Shonagh; Lim, Felicia; Peters, Pamela N; Wardell, Suzanne E; Whitaker, Regina; Chang, Ching-Yi; Previs, Rebecca A; McDonnell, Donald PDespite advances in surgery and targeted therapies, the prognosis for women with high-grade serous ovarian cancer remains poor. Moreover, unlike other cancers, immunotherapy has minimally impacted outcomes in patients with ovarian cancer. Progress in this regard has been hindered by the lack of relevant syngeneic ovarian cancer models to study tumor immunity and evaluate immunotherapies. To address this problem, we developed a luciferase labeled murine model of high-grade serous ovarian cancer, STOSE.M1 luc. We defined its growth characteristics, immune cell repertoire, and response to anti PD-L1 immunotherapy. As with human ovarian cancer, we demonstrated that this model is poorly sensitive to immune checkpoint modulators. By developing the STOSE.M1 luc model, it will be possible to probe the mechanisms underlying resistance to immunotherapies and evaluate new therapeutic approaches to treat ovarian cancer.Item Open Access Epigenetic Regulation of Claudin-1 in the Development of Ovarian Cancer Recurrence and Drug Resistance.(Frontiers in oncology, 2021-01) Visco, Zachary R; Sfakianos, Gregory; Grenier, Carole; Boudreau, Marie-Helene; Simpson, Sabrina; Rodriguez, Isabel; Whitaker, Regina; Yao, Derek Y; Berchuck, Andrew; Murphy, Susan K; Huang, ZhiqingOver 21,000 women are diagnosed with ovarian cancer (OC) in the United States each year and over half that number succumb to this disease annually, often due to recurrent disease. A deeper understanding of the molecular events associated with recurrent disease is needed to identify potential targets. Using genome-scale DNA methylation and gene expression data for 16 matched primary-recurrent advanced stage serous epithelial OCs, we discovered that Claudin-1 (CLDN1), a tight junction protein, shows a stronger correlation between expression and methylation in recurrent versus primary OC at multiple CpG sites (R= -0.47 to -0.64 versus R= -0.32 to -0.57, respectively). An independent dataset showed that this correlation is stronger in tumors from short-term (<3y) survivors than in tumors from long-term (>7y) survivors (R= -0.41 to -0.46 versus R= 0.06 to -0.19, respectively). The presence of this inverse correlation in short-term survivors and recurrent tumors suggests an important role for this relationship and potential predictive value for disease prognosis. CLDN1 expression increased following pharmacologic inhibition of DNA methyltransferase activity (p< 0.001), thus validating the role of methylation in CLDN1 gene inhibition. CLDN1 knockdown enhanced chemosensitivity and suppressed cell proliferation, migration, and wound healing (p< 0.05). Stable CLDN1 knockdown in vivo resulted in reduced xenograft tumor growth but did not reach significance. Our results indicate that the relationship between CLDN1 methylation and expression plays an important role in OC aggressiveness and recurrence.Item Embargo Investigating the Metabolic Reprogramming of Ovarian Cancer(2023) Bose, ShreeOvarian cancer (OC) is the most lethal gynecological malignancy, with aggressive metastatic disease responsible for the majority of ovarian cancer related deaths. Despite the clinical significance of OC omental metastases, the precise molecular mechanisms which drive this phenomenon have not been well characterized, making the resulting aggressive phenotype even more puzzling. Recent evidence has highlighted the importance of metabolic reprograming in driving this tumoral behavior, with OC metastases adapting to utilize nutrients available in the metastatic niche to rapidly proliferate. To better understand the metabolic changes that underlie the aggressive nature of OC, we undertook a broad investigation to better characterize metabolic reprogramming in ovarian cancer, with a focus on omental metastasis and chemoresistance. Firstly, we sought to expand the arsenal of tools used to study OC metabolism. In particular, we were interested in using organoids, self-organizing, expanding 3D cultures derived from stem cells, to study OC. Using tissue derived from patients, these miniaturized models have been shown to recapitulate various aspects of patient physiology and disease phenotypes including genetic profiles and drug sensitivities. However, as metabolism modeling in these 3D cultures remains yet unexplored, we aimed to introduce genetically encoded, fluorescent biosensors as robust tools to interrogate metabolism in this context. In Chapter 2, we detail our investigation in which we transfected plasmids encoding the metabolic biosensors HyPer, iNap, Peredox, and Perceval into 15 ovarian cancer cell lines to assay oxidative stress, NADPH/NADP+, NADH/NAD+, and ATP/ADP, respectively. Fluorescence readings were used to assay dynamic metabolic responses to omental conditioned media (OCM) and 100 μM carboplatin treatment. SKOV3 cells expressing HyPer were imaged as 2D monolayers, 3D organoids, and as in vivo metastases via an intravital omental window. We further established organoids from ascites collected from Stage III/IV OC patients with carboplatin-resistant or carboplatin-sensitive tumors (n=8 total). These patient-derived organoids (PDOs) were engineered to express HyPer, and metabolic readings of oxidative stress were performed during treatment with 100 μM carboplatin. Exposure to OCM or carboplatin induced heterogenous metabolic changes in 15 OC cell lines, as measured using metabolic sensors. Oxidative stress of in vivo omental metastases, measured via intravital imaging of metastasizing SKOV3-HyPer cells, was more closely recapitulated by SKOV3-HyPer organoids than by 2D monolayers. Finally, carboplatin treatment of HyPer-expressing PDOs induced higher oxidative stress in organoids derived from carboplatin-resistant patients than from those derived from carboplatin-sensitive patients. Our study showed that biosensors provide a useful method of studying dynamic metabolic changes in preclinical models of OC, including 3D organoids and intravital imaging. As 3D models of OC continue to evolve, the repertoire of biosensors will likely serve as valuable tools to probe the metabolic changes of clinical importance in OC. Secondly, in Chapter 3, we focused on characterizing the role of the pentose phosphate pathway (PPP), a metabolic pathway responsible for producing nucleotide pentose precursors through a nonoxidative series of reactions and the reducing equivalent NADPH through a distinct oxidative branch. Using computational analysis of gene expression data, metabolomics analysis, and biochemical approaches, we observed upregulation of the pentose phosphate pathway (PPP), a key cellular redox homeostasis mechanism, of metastatic OC cells in the omentum compared to primary OC tumors. We established these increases coincided with increased oxidative stress experienced by OC cells in the omental microenvironment, using both established oxidative stress assays and genetically encoded biosensors; and sought to understand if the PPP was an important cellular mechanism to compensate for this metabolic pressure. Indeed, both shRNA-mediated and pharmacological inhibition of G6PD, the rate-limiting enzyme of the PPP, reduces tumor burden in pre-clinical models of OC, suggesting this adaptive metabolic dependency is important for OC omental metastasis. This work collectively illustrates the importance of characterizing OC metabolism and supports future efforts to develop tools to more effectively investigate and target aspects of metabolic reprogramming in OC which drive metastasis and chemoresistance.
Item Open Access Pleiotropic MLLT10 variation confers risk of meningioma and estrogen-mediated cancers.(Neuro-oncology advances, 2022-01) Walsh, Kyle M; Zhang, Chenan; Calvocoressi, Lisa; Hansen, Helen M; Berchuck, Andrew; Schildkraut, Joellen M; Bondy, Melissa L; Wrensch, Margaret; Wiemels, Joseph L; Claus, Elizabeth BBackground
Risk of tumors of the breast, ovary, and meninges has been associated with hormonal factors and with one another. Genome-wide association studies (GWAS) identified a meningioma risk locus on 10p12 near previous GWAS hits for breast and ovarian cancers, raising the possibility of genetic pleiotropy.Methods
We performed imputation-based fine-mapping in three case-control datasets of meningioma (927 cases, 790 controls), female breast cancer (28 108 cases, 22 209 controls), and ovarian cancer (25 509 cases, 40 941 controls). Analyses were stratified by sex (meningioma), estrogen receptor (ER) status (breast), and histotype (ovarian), then combined using subset-based meta-analysis in ASSET. Lead variants were assessed for association with additional traits in UK Biobank to identify potential effect-mediators.Results
Two-sided subset-based meta-analysis identified rs7084454, an expression quantitative trait locus (eQTL) near the MLLT10 promoter, as lead variant (5.7 × 10-14). The minor allele was associated with increased risk of meningioma in females (odds ratio (OR) = 1.42, 95% Confidence Interval (95%CI):1.20-1.69), but not males (OR = 1.19, 95%CI: 0.91-1.57). It was positively associated with ovarian (OR = 1.09, 95%CI:1.06-1.12) and ER+ breast (OR = 1.05, 95%CI: 1.02-1.08) cancers, and negatively associated with ER- breast cancer (OR = 0.91, 95%CI: 0.86-0.96). It was also associated with several adiposity traits (P < 5.0 × 10-8), but adjusting for body mass index did not attenuate its association with meningioma. MLLT10 and ESR1 expression were positively correlated in normal meninges (P = .058) and meningioma tumors (P = .0065).Conclusions
We identify a MLLT10 eQTL positively associated with risk of female meningioma, ER+ breast cancer, ovarian cancer, and obesity, and implicate a potential estrogenic mechanism underlying this pleiotropy.Item Open Access Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.(Am J Epidemiol, 2016-10-15) Clyde, Merlise A; Palmieri Weber, Rachel; Iversen, Edwin S; Poole, Elizabeth M; Doherty, Jennifer A; Goodman, Marc T; Ness, Roberta B; Risch, Harvey A; Rossing, Mary Anne; Terry, Kathryn L; Wentzensen, Nicolas; Whittemore, Alice S; Anton-Culver, Hoda; Bandera, Elisa V; Berchuck, Andrew; Carney, Michael E; Cramer, Daniel W; Cunningham, Julie M; Cushing-Haugen, Kara L; Edwards, Robert P; Fridley, Brooke L; Goode, Ellen L; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B; Olson, Sara H; Pearce, Celeste Leigh; Pike, Malcolm C; Rothstein, Joseph H; Sellers, Thomas A; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J; Vierkant, Robert A; Wicklund, Kristine G; Wu, Anna H; Ziogas, Argyrios; Tworoger, Shelley S; Schildkraut, Joellen MPreviously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.Item Open Access The Role of the Myelin and Lymphocyte Protein (MAL) in Breast and Ovarian Cancer(2010) Horne, HisaniMAL (myelin and lymphocyte protein), has been implicated in several malignancies including esophageal, gastric, and cervical cancers. We have demonstrated that the MAL protein is expressed in the normal breast epithelium, and aberrantly expressed in breast cancer. Bisulfite sequencing of the MAL promoter CpG island revealed hypermethylation in breast cancer cell lines and 69% of primary tumors analyzed compared with normal breast epithelial cells. Differential methylation between normal and cancer DNA was confined to the proximal promoter region. In a subset of breast cancer cell lines, promoter methylation correlated with transcriptional silencing that was reversible with the methylation inhibitor decitabine. Furthermore, exogenous expression of MAL in breast cancer cell lines resulted in decreased cell proliferation, motility, reduced cell invasion through Matrigel and suppressed anchorage-independent growth in soft agar. In a cohort of 122 primary breast tumors, immunohistochemical analysis revealed that the MAL protein was an independent predictor of benefit from adjuvant chemotherapy. Moreover, overexpression of MAL in triple-negative MDA-MB-468 and BT20 breast cancer cell lines was sufficient to confer sensitivity to epidermal growth factor receptor (EGFR)-tyrosine kinase inhibition and was associated with reduced phosphatidylinositol-3 kinase (PI3K)/Akt signaling. Immunohistochemistry studies conducted on 144 late-stage serous ovarian cancers showed that MAL expression was a significant predictor of survival. Knockdown of MAL expression in the SKOV8 ovarian cancer cell line reduced cell proliferation and resulted in increased sensitivity to the chemotherapeutic drug carboplatin. Thus, we have identified the MAL gene as a novel epigenetically regulated gene in breast cancer with implications for response to chemotherapy in both breast and ovarian cancer. Furthermore, we have shown that the MAL protein has predictive and prognostic value in breast and ovarian cancers, respectively.
Item Open Access The Synthetic Curcumin Analog HO-3867 Rescues Suppression of PLAC1 Expression in Ovarian Cancer Cells.(Pharmaceuticals (Basel, Switzerland), 2021-09-21) Devor, Eric J; Schickling, Brandon M; Lapierre, Jace R; Bender, David P; Gonzalez-Bosquet, Jesus; Leslie, Kimberly KElevated expression of placenta-specific protein 1 (PLAC1) is associated with the increased proliferation and invasiveness of a variety of human cancers, including ovarian cancer. Recent studies have shown that the tumor suppressor p53 directly suppresses PLAC1 transcription. However, mutations in p53 lead to the loss of PLAC1 transcriptional suppression. Small molecules that structurally convert mutant p53 proteins to wild-type conformations are emerging. Our objective was to determine whether the restoration of the wild-type function of mutated p53 could rescue PLAC1 transcriptional suppression in tumors harboring certain TP53 mutations. Ovarian cancer cells OVCAR3 and ES-2, both harboring TP53 missense mutations, were treated with the p53 reactivator HO-3867. Treatment with HO-3867 successfully rescued PLAC1 transcriptional suppression. In addition, cell proliferation was inhibited and cell death through apoptosis was increased in both cell lines. We conclude that the use of HO-3867 as an adjuvant to conventional therapeutics in ovarian cancers harboring TP53 missense mutations could improve patient outcomes. Validation of this conclusion must, however, come from an appropriately designed clinical trial.