In vivo modeling of metastatic human high-grade serous ovarian cancer in mice

Beyond 2D cell cultures: how 3D models are changing the in vitro study of ovarian cancer and how to make the most of them

3D cell cultures are a fundamental tool in ovarian cancer research that can enable more effective study of the main features of this lethal disease, including the high rates of recurrence and chemoresistance. A clearer, more comprehensive understanding of the biological underpinnings of these phenomena could aid the development of more effective treatments thus improving patient outcomes. Selecting the most appropriate model to investigate the different aspects of cell biology that are relevant to cancer is challenging, especially since the assays available for the study of 3D cultures are not fully established yet. To maximise the usefulness of 3D cell cultures of ovarian cancer, we undertook an in-depth review of the currently available models, taking into consideration the strengths and limitations of each approach and of the assay techniques used to evaluate the results. This integrated analysis provides insight into which model-assay pair is best suited to study different parameters of ovarian cancer biology such as cell proliferation, gene expression or treatment response. We also describe how the combined use of multiple models is likely to be the most effective strategy for the in vitro characterisation of complex behaviours.

Reciprocal crosstalk between Th17 and mesothelial cells promotes metastasis-associated adhesion of ovarian cancer cells

BACKGROUND

IL-17A and TNF synergistically promote inflammation and tumorigenesis. Their interplay and impact on ovarian carcinoma (OC) progression are, however, poorly understood. We addressed this question focusing on mesothelial cells, whose interaction with tumor cells is known to play a pivotal role in transcoelomic metastasis formation.

METHODS

Flow-cytometry and immunohistochemistry experiments were employed to identify cellular sources of IL-17A and TNF. Changes in transcriptomes and secretomes were determined by bulk and single cell RNA sequencing as well as affinity proteomics. Functional consequences were investigated by microscopic analyses and tumor cell adhesion assays. Potential clinical implications were assessed by immunohistochemistry and survival analyses.

RESULTS

We identified Th17 cells as the main population of IL-17A- and TNF producers in ascites and detected their accumulation in early omental metastases. Both IL-17A and its receptor subunit IL-17RC were associated with short survival of OC patients, pointing to a role in clinical progression. IL-17A and TNF synergistically induced the reprogramming of mesothelial cells towards a pro-inflammatory mesenchymal phenotype, concomitantly with a loss of tight junctions and an impairment of mesothelial monolayer integrity, thereby promoting cancer cell adhesion. IL-17A and TNF synergistically induced the Th17-promoting cytokines IL-6 and IL-1β as well as the Th17-attracting chemokine CCL20 in mesothelial cells, indicating a reciprocal crosstalk that potentiates the tumor-promoting role of Th17 cells in OC.

CONCLUSIONS

Our findings reveal a novel function for Th17 cells in the OC microenvironment, which entails the IL-17A/TNF-mediated induction of mesothelial-mesenchymal transition, disruption of mesothelial layer integrity and consequently promotion of OC cell adhesion. These effects are potentiated by a positive feedback loop between mesothelial and Th17 cells. Together with the observed clinical associations and accumulation of Th17 cells in omental micrometastases, our observations point to a potential role in early metastases formation and thus to new therapeutic options.

Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

TRAIL-dependent apoptosis of peritoneal mesothelial cells by NK cells promotes ovarian cancer invasion

A crucial requirement for metastasis formation in ovarian high-grade serous carcinoma (HGSC) is the disruption of the protective peritoneal mesothelium. Using co-culture systems of primary human cells, we discovered that tumor-associated NK cells induce TRAIL-dependent apoptosis in mesothelial cells via death receptors DR4 and DR5 upon encounter with activated T cells. Upregulation of TRAIL expression in NK cells concomitant with enhanced cytotoxicity toward mesothelial cells was driven predominantly by T-cell-derived TNFα, as shown by affinity proteomics-based analysis of the T cell secretome in conjunction with functional studies. Consistent with these findings, we detected apoptotic mesothelial cells in the peritoneal fluid of HGSC patients. In contrast to mesothelial cells, HGSC cells express negligible levels of both DR4 and DR5 and are TRAIL resistant, indicating cell-type-selective killing by NK cells. Our data point to a cooperative action of T and NK in breaching the mesothelial barrier in HGSC patients.

Ultrahigh Resolution Lipid Mass Spectrometry Imaging of High-Grade Serous Ovarian Cancer Mouse Models

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights on how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and a triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide a direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Untargeted metabolomics analysis on kidney tissues from mice reveals potential hypoxia biomarkers

Chronic hypoxia may have a huge impact on the cardiovascular and renal systems. Advancements in microscopy, metabolomics, and bioinformatics provide opportunities to identify new biomarkers. In this study, we aimed at elucidating the metabolic alterations in kidney tissues induced by chronic hypoxia using untargeted metabolomic analyses. Reverse phase ultrahigh performance liquid chromatography-mass spectroscopy/mass spectroscopy (RP-UPLC-MS/MS) and hydrophilic interaction liquid chromatography (HILIC)-UPLC-MS/MS methods with positive and negative ion mode electrospray ionization were used for metabolic profiling. The metabolomic profiling revealed an increase in metabolites related to carnitine synthesis and purine metabolism. Additionally, there was a notable increase in bilirubin. Heme, N-acetyl-L-aspartic acid, thyroxine, and 3-beta-Hydroxy-5-cholestenoate were found to be significantly downregulated. 3-beta-Hydroxy-5-cholestenoate was downregulated more significantly in male than female kidneys. Trichome Staining also showed remarkable kidney fibrosis in mice subjected to chronic hypoxia. Our study offers potential intracellular metabolite signatures for hypoxic kidneys.

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipid alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer.

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages, and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipids alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer.

Teaser

Time-resolved lipidome remodeling in an ovarian cancer model is studied through lipidomics and machine learning.

In Vitro Models of Ovarian Cancer: Bridging the Gap between Pathophysiology and Mechanistic Models

Ovarian cancer (OC) is a disease of major concern with a survival rate of about 40% at five years. This is attributed to the lack of visible and reliable symptoms during the onset of the disease, which leads over 80% of patients to be diagnosed at advanced stages. This implies that metastatic activity has advanced to the peritoneal cavity. It is associated with both genetic and phenotypic heterogeneity, which considerably increase the risks of relapse and reduce the survival rate. To understand ovarian cancer pathophysiology and strengthen the ability for drug screening, further development of relevant in vitro models that recapitulate the complexity of OC microenvironment and dynamics of OC cell population is required. In this line, the recent advances of tridimensional (3D) cell culture and microfluidics have allowed the development of highly innovative models that could bridge the gap between pathophysiology and mechanistic models for clinical research. This review first describes the pathophysiology of OC before detailing the engineering strategies developed to recapitulate those main biological features.

L1CAM is required for early dissemination of fallopian tube carcinoma precursors to the ovary

Most ovarian high-grade serous carcinomas (HGSC) arise from Serous Tubal Intraepithelial Carcinoma (STIC) lesions in the distal end of the fallopian tube (FT). Formation of STIC lesions from FT secretory cells leads to seeding of the ovarian surface, with rapid tumor dissemination to other abdominal structures thereafter. It remains unclear how nascent malignant cells leave the FT to colonize the ovary. This report provides evidence that the L1 cell adhesion molecule (L1CAM) contributes to the ability of transformed FT secretory cells (FTSEC) to detach from the tube, survive under anchorage-independent conditions, and seed the ovarian surface. L1CAM was highly expressed on the apical cells of STIC lesions and contributed to ovarian colonization by upregulating integrins and fibronectin in malignant cells and activating the AKT and ERK pathways. These changes increased cell survival under ultra-low attachment conditions that mimic transit from the FT to the ovary. To study dissemination to the ovary, we developed a tumor-ovary co-culture model. We showed that L1CAM expression was important for FT cells to invade the ovary as a cohesive group. Our results indicate that in the early stages of HGSC development, transformed FTSECs disseminate from the FT to the ovary in a L1CAM-dependent manner.

Hippo Signaling in the Ovary: Emerging Roles in Development, Fertility, and Disease

Emerging studies indicate that the Hippo pathway, a highly conserved pathway that regulates organ size control, plays an important role in governing ovarian physiology, fertility, and pathology. Specific to the ovary, the spatiotemporal expression of the major components of the Hippo signaling cascade are observed throughout the reproductive lifespan. Observations from multiple species begin to elucidate the functional diversity and molecular mechanisms of Hippo signaling in the ovary in addition to the identification of interactions with other signaling pathways and responses to various external stimuli. Hippo pathway components play important roles in follicle growth and activation, as well as steroidogenesis, by regulating several key biological processes through mechanisms of cell proliferation, migration, differentiation, and cell fate determination. Given the importance of these processes, dysregulation of the Hippo pathway contributes to loss of follicular homeostasis and reproductive disorders such as polycystic ovary syndrome (PCOS), premature ovarian insufficiency, and ovarian cancers. This review highlights what is currently known about the Hippo pathway core components in ovarian physiology, including ovarian development, follicle development, and oocyte maturation, while identifying areas for future research to better understand Hippo signaling as a multifunctional pathway in reproductive health and biology.

Space- and Time-Resolved Metabolomics of a High-Grade Serous Ovarian Cancer Mouse Model

The dismally low survival rate of ovarian cancer patients diagnosed with high-grade serous carcinoma (HGSC) emphasizes the lack of effective screening strategies. One major obstacle is the limited knowledge of the underlying mechanisms of HGSC pathogenesis at very early stages. Here, we present the first 10-month time-resolved serum metabolic profile of a triple mutant (TKO) HGSC mouse model, along with the spatial lipidome profile of its entire reproductive system. A high-coverage liquid chromatography mass spectrometry-based metabolomics approach was applied to longitudinally collected serum samples from both TKO (n = 15) and TKO control mice (n = 15), tracking metabolome and lipidome changes from premalignant stages to tumor initiation, early stages, and advanced stages until mouse death. Time-resolved analysis showed specific temporal trends for 17 lipid classes, amino acids, and TCA cycle metabolites, associated with HGSC progression. Spatial lipid distributions within the reproductive system were also mapped via ultrahigh-resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry and compared with serum lipid profiles for various lipid classes. Altogether, our results show that the remodeling of lipid and fatty acid metabolism, amino acid biosynthesis, TCA cycle and ovarian steroidogenesis are critical components of HGSC onset and development. These metabolic alterations are accompanied by changes in energy metabolism, mitochondrial and peroxisomal function, redox homeostasis, and inflammatory response, collectively supporting tumorigenesis.

USP13 promotes development and metastasis of high-grade serous ovarian carcinoma in a novel mouse model

Epithelial ovarian cancer is the most lethal gynecologic malignancy and one of the most common causes of cancer mortality among women worldwide. Ubiquitin-Specific Peptidase 13 (USP13) gene copy is strongly amplified in human epithelial ovarian cancer, and high USP13 expression is correlated with poor survival outcomes. Yet, its pathological contribution to ovarian tumorigenesis remains unknown. We crossed a conditional Usp13 overexpressing knock-in mouse with a conditional knockout of Trp53 and Pten mouse and generated a novel ovarian cancer genetically engineered mouse model (GEMM), which closely recapitulates the genetic changes driving ovarian cancer in humans. Overexpression of USP13 with deletion of Trp53 and Pten in murine ovarian surface epithelium accelerated ovarian tumorigenesis and led to decreased survival in mice. Notably, USP13 greatly enhanced peritoneal metastasis of ovarian tumors with frequent development of hemorrhagic ascites. The primary and metastatic tumors exhibited morphology and clinical behavior similar to human high-grade serous ovarian cancer. Co-inhibition of USP13 and AKT significantly decreased the viability of the primary murine ovarian cancer cells isolated from the GEMM. USP13 also increased the tumorigenic and metastatic abilities of primary murine ovarian cancer cells in a syngeneic mouse study. These findings suggest a critical role of USP13 in ovarian cancer development and reveal USP13 as a potential therapeutic target for ovarian cancer.

Intra-Tumoral Nerve-Tracing in a Novel Syngeneic Model of High-Grade Serous Ovarian Carcinoma

Dense tumor innervation is associated with enhanced cancer progression and poor prognosis. We observed innervation in breast, prostate, pancreatic, lung, liver, ovarian, and colon cancers. Defining innervation in high-grade serous ovarian carcinoma (HGSOC) was a focus since sensory innervation was observed whereas the normal tissue contains predominantly sympathetic input. The origin, specific nerve type, and the mechanisms promoting innervation and driving nerve-cancer cell communications in ovarian cancer remain largely unknown. The technique of neuro-tracing enhances the study of tumor innervation by offering a means for identification and mapping of nerve sources that may directly and indirectly affect the tumor microenvironment. Here, we establish a murine model of HGSOC and utilize image-guided microinjections of retrograde neuro-tracer to label tumor-infiltrating peripheral neurons, mapping their source and circuitry. We show that regional sensory neurons innervate HGSOC tumors. Interestingly, the axons within the tumor trace back to local dorsal root ganglia as well as jugular-nodose ganglia. Further manipulations of these tumor projecting neurons may define the neuronal contributions in tumor growth, invasion, metastasis, and responses to therapeutics.

A Benzenesulfonamide-Based Mitochondrial Uncoupler Induces Endoplasmic Reticulum Stress and Immunogenic Cell Death in Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the leading cause of death from gynecologic malignancies and requires new therapeutic strategies to improve clinical outcomes. EOC metastasizes in the abdominal cavity through dissemination in the peritoneal fluid and ascites, efficiently adapt to the nutrient-deprived microenvironment, and resist current chemotherapeutic agents. Accumulating evidence suggests that mitochondrial oxidative phosphorylation is critical for the adaptation of EOC cells to this otherwise hostile microenvironment. Although chemical mitochondrial uncouplers can impair mitochondrial functions and thereby target multiple, essential pathways for cancer cell proliferation, traditional mitochondria uncouplers often cause toxicity that precludes their clinical application. In this study, we demonstrated that a mitochondrial uncoupler, specifically 2,5-dichloro-N-(4-nitronaphthalen-1-yl)benzenesulfonamide, hereinafter named Y3, was an antineoplastic agent in ovarian cancer models. Y3 treatment activated AMP-activated protein kinase and resulted in the activation of endoplasmic reticulum stress sensors as well as growth inhibition and apoptosis in ovarian cancer cells in vitro Y3 was well tolerated in vivo and effectively suppressed tumor progression in three mouse models of EOC, and Y3 also induced immunogenic cell death of cancer cells that involved the release of damage-associated molecular patterns and the activation of antitumor adaptive immune responses. These findings suggest that mitochondrial uncouplers hold promise in developing new anticancer therapies that delay tumor progression and protect patients with ovarian cancer against relapse.

Silencing of SBF2-AS1 inhibits cell growth and invasion by sponging microRNA-338-3p in serous ovarian carcinoma

Long noncoding RNA SET-binding factor 2 (SBF2) antisense RNA 1 (AS1) is associated with the growth and metastasis of multiple cancer types, but its biological roles in serous ovarian carcinoma (SOC) remain unclear. In this study, the aberrant upregulation of SBF2-AS1 is detected in SOC after analysis of differentially expressed genes between SOC tissues and normal fallopian tubes from the public Gene Expression Omnibus (GEO) database. We determine that knockdown of SBF2-AS1 inhibits SOC cell proliferation and invasion by sponging miR-338-3p. MiR-338-3p acts as a tumor suppressor in SOC, and E26 transformation specific-1 (ETS1) is identified as a potential target of miR-338-3p regulation. Furthermore, SBF2-AS1 could modulate ETS1 by operating as a competing endogenous RNA for miR-338-3p. This finding elucidates a new mechanism for SBF2-AS1 in SOC development and provides a potential target for SOC therapeutic intervention.

Insights into the Role of Oxidative Stress in Ovarian Cancer

Oxidative stress (OS) arises when the body is subjected to harmful endogenous or exogenous factors that overwhelm the antioxidant system. There is increasing evidence that OS is involved in a number of diseases, including ovarian cancer (OC). OC is the most lethal gynecological malignancy, and risk factors include genetic factors, age, infertility, nulliparity, microbial infections, obesity, smoking, etc. OS can promote the proliferation, metastasis, and therapy resistance of OC, while high levels of OS have cytotoxic effects and induce apoptosis in OC cells. This review focuses on the relationship between OS and the development of OC from four aspects: genetic alterations, signaling pathways, transcription factors, and the tumor microenvironment. Furthermore, strategies to target aberrant OS in OC are summarized and discussed, with a view to providing new ideas for clinical treatment.

Effect of exercise on peritoneal microenvironment and progression of ovarian cancer

Ovarian cancer is one of the deadliest gynecological malignancies and lacks treatments that do not significantly impact patient health-related quality of life. Exercise has been associated with reduced cancer risk and improved clinical outcomes; however the underlying molecular mechanisms are unknown. In this study, we utilized a treadmill-running exercise model to investigate the effects of exercise on high-grade serous ovarian carcinoma (HGSOC) progression and chemotherapy outcomes. We found that treadmill-running suppressed peritoneal colonization of tumors in a syngeneic mouse ovarian cancer model. Acute exercise stimulated the production of CCL2 and IL-15 in the peritoneal microenvironment while downregulating CCL22, VEGF, and CCL12. Using a co-culture model, we demonstrated the role of CCL2 in mediating the activity of peritoneal cells to inhibit cancer cell viability. We showed that the activation of M1 macrophages may contribute to the exercise-induced changes in the peritoneal microenvironment. We identified that chronic exercise modulates gene expression of intraperitoneal fat tissues related to lipid formation, thermogenesis, browning, and inflammation, which can contribute to inhibiting the colonization of metastatic ovarian cancer. Treadmill running also lowered blood urea nitrogen levels and reduced incidence of neutropenia and thrombocytopenia during chemotherapy in a mouse model, suggesting the potential beneficial effects of exercise in improving chemotherapy outcomes. Our data provided new insights into the acute and chronic effects of physical activity on ovarian cancer at the molecular and in vivo levels.

Comprehensive Analysis of 5-Methylcytosine Profiles of Messenger RNA in Human High-Grade Serous Ovarian Cancer by MeRIP Sequencing

Background

Accumulating evidence has indicated that methylation status is closely related to tumourigenesis and a few aggressive features of diverse cancers. However, as an important methylation regulation modification, the distribution of 5-methylcytosine (m5C) in high-grade serous ovarian cancer (HGSOC) remains unclear.

Materials and Methods

We collected three pairs of human HGSOC tissues and adjacent non-tumour tissues to analyse the transcriptome-wide m5C methylation of messenger RNAs (mRNAs) by methylated RNA immunoprecipitation sequencing. Gene ontology (GO) enrichment analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis were performed to eExplore the potential biological functions of these genes and important cancer pathways. We used immunohistochemistry to analyse the expression of the m5C modification regulatory gene MAP2K3 in 80 HGSOC tissue samples, and their associations with clinical parameters were analyzed using the Spearman-rho test. Univariate and multivariate Cox regression analyses were performed to identify potential prognostic factors. Kaplan–Meier analysis was performed to analyze overall survival.

Results

We identified 2050 dysregulated m5C peaks, 1767 of which were significantly upregulated, while 283 were significantly downregulated. GO enrichment analysis showed that genes altered by the m5C peak played a key role in system development, transporter complex, and transporter activity. KEGG pathway analysis revealed that these genes were enriched in some important pathways in cancer regulation, such as inflammatory mediator regulation of the TRP channels pathway, Wnt signalling pathway, and focal adhesion pathways. In addition, through joint analysis of MeRIP-seq and RNA-seq data, we identified 125 differentially methylated m5C peaks and synchronous differentially expressed genes. These genes play key roles in cell growth, maintenance, plasma membranes, and cell adhesion molecule activity. Immunohistochemical staining results showed that high expression of MAP2K3 was significantly correlated with CA125 level (p < 0.001), tumour size (p = 0.001), lymph node metastasis (p = 0.008), depth of myometrial invasion (p < 0.001), and FIGO stage (p < 0.001), indicating a poor prognosis.

Conclusion

Our results reveal the different distribution patterns of m5C in HGSOC and adjacent tissues and the possible involvement of m5C in HGSOC cell functions. Our study provides new insights into the epi-transcriptomic dysregulation of m5C in the tumourigenesis of HGSOC.

Incidence of malignant transformation in the oviductal fimbria in laying hens, a preclinical model of spontaneous ovarian cancer

Ovarian high grade serous carcinoma (HGSC) is a lethal form of ovarian cancer (OVCA). In most cases it is detected at late stages as the symptoms are non-specific during early stages. Emerging information suggests that the oviductal fimbria is a site of origin of ovarian HGSC. Currently available tests cannot detect ovarian HGSC at early stage. The lack of a preclinical model with oviductal fimbria that develops spontaneous ovarian HGSC is a significant barrier to developing an early detection test for this disease. The goal of this study was to examine if the oviductal fimbria in hens is a site of origin of HGSC and whether it expresses several putative markers expressed in ovarian HGSC in patients. A total of 135 laying hens (4 years old) were selected from a flock using transvaginal ultrasound (TVUS) imaging, followed by euthanasia and gross examination for the presence of solid masses and ascites. Histological types of carcinomas were determined by hematoxylin and eosin staining. Expression of WT-1, mutant p53, CA-125, PAX2 and Ki67 in normal or malignant fimbriae or ovaries were examined using immunohistochemistry, immunoblotting and gene expression assays. This study detected tumors in oviductal fimbriae in hens and routine staining revealed ovarian HGSC-like microscopic features in these tumors. These tumors showed similarities to ovarian HGSC in patients in expressing several markers. Compared with normal fimbriae, intensities of expression of WT-1, mutant p53, CA-125, and Ki67 were significantly (P<0.05) higher in fimbrial tumors. In contrast, expression of PAX2 decreased gradually as the tumor progressed to late stages. The patterns of expression of these markers were similar to those in ovarian HGSC patients. Thus, tumors of the oviductal fimbria in hens may offer a preclinical model to study different aspects of spontaneous ovarian HGSC in women including its early detection.

Neutrophil Extracellular Traps: A New Player in Cancer Metastasis and Therapeutic Target

Neutrophil Extracellular Traps (NETs) are neutrophil-derived extracellular scaffolds, which typically consist of fibrous decondensed chromatins decorated with histones and granule proteins. Initially discovered as a host defence mechanism of neutrophil against pathogens, they have also been implicated in the progression of sterile inflammation-associated diseases such as autoimmune disease, diabetes, and cancer. In this review, we highlight and discuss the more recent studies on the roles of NETs in cancer development, with a special focus on cancer metastasis. Moreover, we present the strategies for targeting NETs in pre-clinical models, but also the challenging questions that need to be answered in the field.

FOXM1: A Multifunctional Oncoprotein and Emerging Therapeutic Target in Ovarian Cancer

Forkhead box M1 (FOXM1) is a member of the conserved forkhead box (FOX) transcription factor family. Over the last two decades, FOXM1 has emerged as a multifunctional oncoprotein and a robust biomarker of poor prognosis in many human malignancies. In this review article, we address the current knowledge regarding the mechanisms of regulation and oncogenic functions of FOXM1, particularly in the context of ovarian cancer. FOXM1 and its associated oncogenic transcriptional signature are enriched in >85% of ovarian cancer cases and FOXM1 expression and activity can be enhanced by a plethora of genomic, transcriptional, post-transcriptional, and post-translational mechanisms. As a master transcriptional regulator, FOXM1 promotes critical oncogenic phenotypes in ovarian cancer, including: (1) cell proliferation, (2) invasion and metastasis, (3) chemotherapy resistance, (4) cancer stem cell (CSC) properties, (5) genomic instability, and (6) altered cellular metabolism. We additionally discuss the evidence for FOXM1 as a cancer biomarker, describe the rationale for FOXM1 as a cancer therapeutic target, and provide an overview of therapeutic strategies used to target FOXM1 for cancer treatment.

Modelling the Functions of Polo-Like Kinases in Mice and Their Applications as Cancer Targets with a Special Focus on Ovarian Cancer

Polo-like kinases (PLKs) belong to a five-membered family of highly conserved serine/threonine kinases (PLK1-5) that play differentiated and essential roles as key mitotic kinases and cell cycle regulators and with this in proliferation and cellular growth. Besides, evidence is accumulating for complex and vital non-mitotic functions of PLKs. Dysregulation of PLKs is widely associated with tumorigenesis and by this, PLKs have gained increasing significance as attractive targets in cancer with diagnostic, prognostic and therapeutic potential. PLK1 has proved to have strong clinical relevance as it was found to be over-expressed in different cancer types and linked to poor patient prognosis. Targeting the diverse functions of PLKs (tumor suppressor, oncogenic) are currently at the center of numerous investigations in particular with the inhibition of PLK1 and PLK4, respectively in multiple cancer trials. Functions of PLKs and the effects of their inhibition have been extensively studied in cancer cell culture models but information is rare on how these drugs affect benign tissues and organs. As a step further towards clinical application as cancer targets, mouse models therefore play a central role. Modelling PLK function in animal models, e.g., by gene disruption or by treatment with small molecule PLK inhibitors offers promising possibilities to unveil the biological significance of PLKs in cancer maintenance and progression and give important information on PLKs' applicability as cancer targets. In this review we aim at summarizing the approaches of modelling PLK function in mice so far with a special glimpse on the significance of PLKs in ovarian cancer and of orthotopic cancer models used in this fatal malignancy.

Cellular models of development of ovarian high-grade serous carcinoma: A review of cell of origin and mechanisms of carcinogenesis

High-grade serous carcinoma (HGSC) is the most common and malignant histological type of epithelial ovarian cancer, the origin of which remains controversial. Currently, the secretory epithelial cells of the fallopian tube are regarded as the main origin and the ovarian surface epithelial cells as a minor origin. In tubal epithelium, these cells acquire TP53 mutations and expand to a morphologically normal 'p53 signature' lesion, transform to serous tubal intraepithelial carcinoma and metastasize to the ovaries and peritoneum where they develop into HGSC. This shifting paradigm of the main cell of origin has revolutionarily changed the focus of HGSC research. Various cell lines have been derived from the two cellular origins by acquiring immortalization via overexpression of hTERT plus disruption of TP53 and the CDK4/RB pathway. Malignant transformation was achieved by adding canonical driver mutations (such as gain of CCNE1) revealed by The Cancer Genome Atlas or by noncanonical gain of YAP and miR181a. Alternatively, because of the extreme chromosomal instability, spontaneous transformation can be achieved by long passage of murine immortalized cells, whereas in humans, it requires ovulatory follicular fluid, containing regenerating growth factors to facilitate spontaneous transformation. These artificially and spontaneously transformed cell systems in both humans and mice have been widely used to discover carcinogens, oncogenic pathways and malignant behaviours in the development of HGSC. Here, we review the origin, aetiology and carcinogenic mechanism of HGSC and comprehensively summarize the cell models used to study this fatal cancer having multiple cells of origin and overt genomic instability.

Global miRNA/proteomic analyses identify miRNAs at 14q32 and 3p21, which contribute to features of chronic iron-exposed fallopian tube epithelial cells

Malignant transformation of fallopian tube secretory epithelial cells (FTSECs) is a key contributing event to the development of high-grade serous ovarian carcinoma (HGSOC). Our recent findings implicate oncogenic transformative events in chronic iron-exposed FTSECs, including increased expression of oncogenic mediators, increased telomerase transcripts, and increased growth/migratory potential. Herein, we extend these studies by implementing an integrated transcriptomic and mass spectrometry-based proteomics approach to identify global miRNA and protein alterations, for which we also investigate a subset of these targets to iron-induced functional alterations. Proteomic analysis identified > 4500 proteins, of which 243 targets were differentially expressed. Sixty-five differentially expressed miRNAs were identified, of which 35 were associated with the “top” proteomic molecules (> fourfold change) identified by Ingenuity Pathway Analysis. Twenty of these 35 miRNAs are at the 14q32 locus (encoding a cluster of 54 miRNAs) with potential to be regulated by DNA methylation and histone deacetylation. At 14q32, miR-432-5p and miR-127-3p were ~ 100-fold downregulated whereas miR-138-5p was 16-fold downregulated at 3p21 in chronic iron-exposed FTSECs. Combinatorial treatment with methyltransferase and deacetylation inhibitors reversed expression of these miRNAs, suggesting chronic iron exposure alters miRNA expression via epigenetic alterations. In addition, PAX8, an important target in HGSOC and a potential miRNA target (from IPA) was epigenetically deregulated in iron-exposed FTSECs. However, both PAX8 and ALDH1A2 (another IPA-predicted target) were experimentally identified to be independently regulated by these miRNAs although TERT RNA was partially regulated by miR-138-5p. Interestingly, overexpression of miR-432-5p diminished cell numbers induced by long-term iron exposure in FTSECs. Collectively, our global profiling approaches uncovered patterns of miRNA and proteomic alterations that may be regulated by genome-wide epigenetic alterations and contribute to functional alterations induced by chronic iron exposure in FTSECs. This study may provide a platform to identify future biomarkers for early ovarian cancer detection and new targets for therapy.

Mouse Models of Peritoneal Carcinomatosis to Develop Clinical Applications

Simple Summary

Peritoneal carcinomatosis mouse models as a platform to test, improve and/or predict the appropriate therapeutic interventions in patients are crucial to providing medical advances. Here, we overview reported mouse models to explore peritoneal carcinomatosis in translational biomedical research.

Abstract

Peritoneal carcinomatosis of primary tumors originating in gastrointestinal (e.g., colorectal cancer, gastric cancer) or gynecologic (e.g., ovarian cancer) malignancies is a widespread type of tumor dissemination in the peritoneal cavity for which few therapeutic options are available. Therefore, reliable preclinical models are crucial for research and development of efficacious treatments for this condition. To date, a number of animal models have attempted to reproduce as accurately as possible the complexity of the tumor microenvironment of human peritoneal carcinomatosis. These include: Syngeneic tumor cell lines, human xenografts, patient-derived xenografts, genetically induced tumors, and 3D scaffold biomimetics. Each experimental model has its own strengths and limitations, all of which can influence the subsequent translational results concerning anticancer and immunomodulatory drugs under exploration. This review highlights the current status of peritoneal carcinomatosis mouse models for preclinical development of anticancer drugs or immunotherapeutic agents.

3D Models for Ovarian Cancer

The main reasons for the slow progress in improving survival outcomes for ovarian cancer are the 'one-size-fits-all' therapy and lack of clinically relevant experimental models that represent the advanced stages of the human disease. The interaction of tumour cells with their surrounding niche, the tumour microenvironment, influences the spread of ovarian cancer cells within the peritoneum and their responses to therapeutics. Scientists are increasingly using 3D cell culture models to dissect the role of the tumour microenvironment in cancer development and progression and the treatment of this disease. In this chapter, we will briefly describe the tumour microenvironment of ovarian cancer. Then, we will review some of the clinically relevant experimental approaches, such as spheroid, organoid and organotypic models, that have been developed for the 3D culture of ovarian cancer cells using different tools, including hydrogels, scaffolds and cancer-on-a-chip devices, to mimic selected components of the tumour microenvironment.

Targeting progesterone signaling prevents metastatic ovarian cancer

Effective cancer prevention requires the discovery and intervention of a factor critical to cancer development. Here we show that ovarian progesterone is a crucial endogenous factor inducing the development of primary tumors progressing to metastatic ovarian cancer in a mouse model of high-grade serous carcinoma (HGSC), the most common and deadliest ovarian cancer type. Blocking progesterone signaling by the pharmacologic inhibitor mifepristone or by genetic deletion of the progesterone receptor (PR) effectively suppressed HGSC development and its peritoneal metastases. Strikingly, mifepristone treatment profoundly improved mouse survival (∼18 human years). Hence, targeting progesterone/PR signaling could offer an effective chemopreventive strategy, particularly in high-risk populations of women carrying a deleterious mutation in the BRCA gene.