Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours

Chronic arsenic exposure of ovarian surface and fallopian tube cultures induces giant and/or multinucleated cells with phagocytosis-like properties and an inflammatory phenotype

Chronic exposure to arsenic, a toxic metalloid frequently found in groundwater and food, represents a significant environmental health risk and has been implicated in the etiology of several cancers, including ovarian cancer. However, the precise pathways through which arsenic exerts its toxic impact on the ovary are not fully understood. This study investigates the impact of chronic arsenic exposure at environmentally relevant concentrations (75 ppb or μg/L) on primary human ovarian surface (OCE1) and fallopian tube (FNE1) cultures derived from the same donor. These heterogeneous cultures provide a unique, human-relevant platform to investigate how chronic arsenic exposure influences distinct cell types within a shared microenvironment. Prolonged arsenic exposure induced significant cytotoxicity and promoted the formation of giant and/or multinucleated cells in both cultures. These cells exhibited phagocytosis-like properties, actively engulfing apoptotic debris. Transcriptomic analyses and pathway enrichment revealed robust activation of pro-inflammatory signaling, notably the canonical NF-κB pathway. This was marked by nuclear translocation of the NF-κB p65 subunit and elevated expression and secretion of pro-inflammatory cytokines, including TNFα, IL-6, and IL-8, driving a sustained inflammatory response. Moreover, arsenic-exposed cells displayed persistent DNA damage, as indicated by increased γ-H2AX foci, accompanied by nuclear structural alterations and elevated expression of cancer stem cell markers, including OCT2, CD133, and ALDH1. These findings suggest that arsenic-induced inflammation and genomic instability converge to promote a tumor-supportive microenvironment, highlighting the potential role of chronic arsenic exposure in ovarian carcinogenesis, particularly in the context of inflammation-driven carcinogenesis.

The CXCL8-CXCR2 axis promotes M2 macrophage polarization in ovarian cancer via RASGRP4-mediated mTOR-STAT3 signaling

This study aimed to investigate whether CXCL8-CXCR2 axis in regulating M2 macrophage polarization via RASGRP4 related signaling in ovarian cancer. Data from The Cancer Genome Atlas (TCGA) database was used to assess the correlation between CXCR2 expression and M2 macrophage infiltration. THP-1 human monocytic cells were utilized to analyze the effects of CXCL8 on RASGRP4 expression and M2 polarization. In vivo experiments were conducted using xenograft models to evaluate the impact of CXCL8 and RASGRP4 on tumor growth and macrophage polarization. Among the CXCR2 co-expressed genes, RASGRP4 showed the highest positive correlation with M2 macrophage infiltration in ovarian cancer. Higher expression of RASGRP4 is associated with poorer progression-free survival in patients with serous ovarian cancer. CXCR2 knockdown or inhibition (using SB225002) reduced IL-8-induced upregulation of RASGRP4 mRNA and protein in THP-1 cells. Additionally, PLCβ2 silencing attenuated IL-8-induced RASGRP4 expression. Knockdown of RASGRP4 in THP-1 cells reduced M2 polarization, while overexpression restored it. The CXCL8-CXCR2 axis further enhances M2 polarization through RASGRP4-mediated mTOR-STAT3 signaling. In xenograft ovarian tumor models, knockdown of CXCL8, CXCR2, or RASGRP4 reduced tumor growth and M2 macrophage infiltration. In summary, the CXCL8-CXCR2 axis promotes M2 macrophage polarization via RASGRP4-mediated mTOR-STAT3 signaling in ovarian cancer. Targeting this pathway may be a promising therapeutic strategy to reprogram tumor-associated macrophages and enhance treatment efficacy.

Signalomics for molecular tumor boards and precision oncology of breast and gynecological cancers

Precision oncology led to the establishment and widespread application of molecular tumor boards (MTBs)-multidisciplinary units combining molecular and clinical assessment of individual cancer cases for swift selection of personalized treatments. Whole-exome or gene panel sequencing, combined with transcriptomic, immunohistochemical, and other molecular analyses, often permits dissection of molecular drivers of a tumor and identification of its potential targetable vulnerabilities, instructing clinical oncologists on sometimes unconventional treatment options. However, cancer drivers are often unleashed mutation-independently, especially in breast and gynecological cancers, and deleterious mutations are not always pathogenic. To complement the MTB arsenal, we chart here the molecular toolset we call Signalomics that permits fast and robust assessment of a panel of oncogenic signaling pathways in fresh tumor samples. Using transcriptional reporters introduced in primary tumor cells, this approach identifies the pathways overactivated in a given tumor and validates their sensitivity to targeted therapies, providing actionable insights for personalized treatment strategies. Integration of Signalomics into MTB workflows bridges the gap between molecular profiling and functional pathway analysis, refining clinical treatment decisions and advancing precision oncology.

3D Microtumors Representing Ovarian Cancer Minimal Residual Disease Respond to the Fatty Acid Oxidation Inhibitor Perhexiline

The poor survival of ovarian cancer patients is linked to their high likelihood of relapse. In spite of full apparent macroscopic clearance, tumor recurrences arise from cells that are resistant to primary chemotherapy in the form of minimal residual disease (MRD). MRD exhibits distinct molecular drivers from bulk cancer and therefore necessitates alternative therapeutic strategies. However, there is a lack of 3D models that faithfully recapitulate MRD ex vivo for therapy development. This study constructs microfluidics-based 3D microtumors to generate a clinically-relevant model for ovarian cancer MRD. The microtumors recapitulate the non-genetic heterogeneity of ovarian cancer, capturing the "Oxford Classic" five molecular signatures. Gene expression in the 3D microtumors aligns closely with MRD from ovarian cancer patients and features the upregulation of fatty acid metabolism genes. Finally, the MRD 3D microtumors respond to the approved fatty acid oxidation inhibitor, perhexiline, demonstrating their utility in drug discovery. This system might be used as a drug-testing platform for the discovery of novel MRD-specific therapies in ovarian cancer.

Current status of in vitro models for rare gynaecological cancer research

Gynaecological cancers originate within the female reproductive system and are classified according to the site in the reproductive system where they arise. However, over 50 % of these malignancies are categorized as rare, encompassing 30 distinct histological subtypes, which complicates their diagnosis and treatment. The focus of this review is to give an overview of established in vitro models for the investigation of rare gynaecological cancers, as well as an overview of available online databases that contain detailed descriptions of cell line characteristics. Cell lines represent the main models for the research of carcinogenesis, drug resistance, pharmacodynamics and novel therapy treatment options. Nowadays, classic 2D cell models are increasingly being replaced with 3D cell models, such as spheroids, organoids, and tumoroids because they provide a more accurate representation of numerous tumour characteristics, and their response to therapy differs from the response of adherent cell lines. It is crucial to use the correct cell line model, as rare tumour types can show characteristics that differ from the most common tumour types and can therefore respond unexpectedly to classic treatment. Additionally, some cell lines have been misclassified or misidentified, which could lead to false results. Even though rare gynaecological cancers are rare, this review will demonstrate that there are available options for investigation of such cancers in vitro on biologically relevant models.

Precision preclinical modeling to advance cancer treatment

A new era of cancer management is underway in which treatments are being developed for the entire continuum of the disease process. The availability of genetically engineered and naturally occurring preclinical models serves as instructive platforms for evaluating therapeutic mechanisms. However, a major clinical challenge is that the entire malignancy process occurs across multiple scales including genetic mutations, malignant changes in cell behavior, dysregulated tumor microenvironments, and systemic adaptations in the host. A multidisciplinary group of investigators coalesced at the National Cancer Institute Oncology Models Forum with the overall goal to provide updates on the use of precision preclinical models of cancer. The benefits and limitations of preclinical models were discussed to identify strategies for maximizing opportunities in modeling that could inform future cancer prevention and treatment approaches. Our shared perspective is that the continuum of single cell, multicell, organoid, and in situ models are remarkable resources for the clinical challenges ahead. We provide a roadmap for parsing already available models and include preliminary recommendations for the application of next-generation preclinical modeling in cancer intervention.

Basal cell adhesion molecule (BCAM) promotes mesothelial-to-mesenchymal transition and tumor angiogenesis through paracrine signaling

BACKGROUND

High expression of basal cell adhesion molecule (BCAM) is a hallmark of ovarian cancer (OC) progression. BCAM facilitates transcoelomic dissemination by promoting mesothelial cell clearance at peritoneal attachment sites of tumor cell spheroids. We investigated how BCAM mediates this effect and potentially drives other pro-metastatic functions.

METHODS

The impact of BCAM on the tumor cell secretome and the mesothelial cell phenotype was analyzed by affinity proteomics, bulk and single-cell RNA sequencing, life-cell and multiphoton microscopy, biochemical and functional in vitro assays as well as a murine tumor model. BCAM manipulation involved ectopic overexpression, inducible expression and treatment with soluble BCAM.

RESULTS

All forms of BCAM enhanced the secretion of cytokines that impact cell motility, mesenchymal differentiation and angiogenesis, including AREG, CXCL family members, FGF2, TGFB2, and VEGF. Notably, their levels in OC ascites were correlated with BCAM expression, and recombinant BCAM-induced cytokines triggered mesothelial-mesenchymal transition (MMT). Mesothelial cells undergoing MMT exhibited enhanced motility away from attaching tumor spheroids, leading to mesothelial clearance at spheroid attachment sites. BCAM-mediated MMT-associated transcriptional changes were also observed in subpopulations of omental mesothelial cells from OC patients, and were associated with poor survival. Consistent with the secretome data, BCAM induced endothelial tube formation in vitro and markedly promoted tumor angiogenesis in a mouse model.

CONCLUSION

We have identified previously unknown functions of the BCAM-induced secretome potentially impacting distinct stages of OC metastasis. While BCAM's impact on MMT may facilitate initiation of micrometastases, neo-angiogenesis is essential for tumor growth. Taken together with the observed clinical adverse association, our findings underscore the potential of BCAM as a therapeutic target.

Establishment of a human ovarian endometrioid carcinoma cell line by constitutive expression of cyclin-dependent kinase 4, cyclin D1 and telomerase reverse transcriptase

Only a few human ovarian endometrioid carcinoma cell lines are currently available, partly due to the difficulty of establishing cell lines from low-grade cancers. Here, using a cell immortalization strategy consisting of i) inactivation of the p16INK4a-pRb pathway by constitutive expression of mutant cyclin-dependent kinase 4 (R24C) (CDK4R24C) and cyclin D1, and ii) acquisition of telomerase reverse transcriptase (TERT) activity, we established a human ovarian endometrioid carcinoma cell line from a 46-year-old Japanese woman. That line, designated JFE-21, has proliferated continuously for over 6 months with a doubling time of ~ 55 h. JFE-21 cells exhibit polygonal shapes and proliferate without contact inhibition to form a monolayer in a jigsaw puzzle-like arrangement. Ultrastructurally, JFE-21 cells exhibit well-developed rough endoplasmic reticulum, mitochondria and lysosomes in the cytoplasm, with cells contacting each other via desmosomes. G-band karyotype analysis indicated that cells had a near-tetraploid karyotype. Immunofluorescence staining revealed that the expression profile of a series of ovarian carcinoma markers in JFE-21 cells was consistent with ovarian endometrioid carcinoma. Moreover, Sanger sequencing of DNA polymerase ε (POLE) gene and immunohistochemical analysis of mismatch repair (MMR) proteins revealed that JFE-21 cells were classified as the no specific molecular profile (NSMP) subtype. In addition, JFE-21 cells were sensitive to paclitaxel and carboplatin administered to the donor as therapy. These findings indicate that constitutive expression of CDK4R24C, cyclin D1 and TERT genes may be an option to establish cell lines from low-grade cancers, including ovarian endometrioid carcinoma.

Methods for assessing and removing non-specific photoimmunotherapy damage in patient-derived tumor cell culture models

Tumor-targeted, activatable photoimmunotherapy (taPIT) has been shown to selectively destroy tumor in a metastatic mouse model. However, the photoimmunoconjugate (PIC) used for taPIT includes a small fraction of non-covalently associated (free) benzoporphyrin derivative (BPD), which leads to non-specific killing in vitro. Here, we report a new treatment protocol for patient-derived primary tumor cell cultures ultrasensitive to BPD photodynamic therapy (BPD-PDT). Based on free BPD efflux dynamics, the updated in vitro taPIT protocol precludes non-specific BPD-PDT by silencing the effect of free BPD. Following incubation with PIC, incubating cells with PIC-free medium allows time for expulsion of free BPD whereas BPD covalently bound to PIC fragments is retained. Administration of the light dose after the intracellular free BPD drops below the threshold for inducing cell death helps to mitigate non-specific damage. In this study, we tested two primary ovarian tumor cell lines that are intrinsically chemoresistant, yet ultrasensitive to BPD-PDT such that small amounts of free BPD (a few percent of the total BPD dose) lead to potent induction of cell death upon irradiation. The modifications in the protocol suggested here improve in vitro taPIT experiments that lack in vivo mechanisms of free BPD clearance (i.e., lymph and blood flow).

Silencing of Epidermal Growth Factor-like Domain 8 Promotes Proliferation and Cancer Aggressiveness in Human Ovarian Cancer Cells by Activating ERK/MAPK Signaling Cascades

Ovarian cancer (OC) is the second most common female reproductive cancer and the most lethal gynecological malignancy worldwide. Most human OCs are characterized by high rates of drug resistance and metastasis, leading to poor prognosis. Improving the outcomes of patients with relapsed and treatment-resistant OC remains a challenge. This study aimed to investigate the role of epidermal growth factor-like domain 8 (EGFL8) in human OC by examining the effects of siRNA-mediated EGFL8 knockdown on cancer progression. EGFL8 knockdown in human OC cells promoted aggressive traits associated with cancer progression, including enhanced proliferation, colony formation, migration, invasion, chemoresistance, and reduced apoptosis. Additionally, knockdown upregulated the expression of epithelial-mesenchymal transition (EMT) markers (Snail, Twist1, Zeb1, Zeb2, and vimentin) and cancer stem cell biomarkers (Oct4, Sox2, Nanog, KLF4, and ALDH1A1), and increased the expression of matrix metallopeptidases (MMP-2 and MMP-9), drug resistance genes (MDR1 and MRP1), and Notch1. Low EGFL8 expression also correlated with poor prognosis in human OC. Overall, this study provides crucial evidence that EGFL8 inhibits the proliferation and cancer aggressiveness of human OC cells by suppressing ERK/MAPK signaling. Therefore, EGFL8 may serve as a valuable prognostic biomarker and a potential target for developing novel human OC therapies.

Protocol for detecting homologous recombination activity in cancer cells by adenovirus-based functional assay

Cancer cells with homologous recombination deficiency (HRD) exhibit a distinctive vulnerability to poly(ADP-ribose) polymerase inhibitors (PARPis). To address the limitations of existing methodologies incapable of providing real-time insights into homologous recombination (HR) status, we present an adenovirus-based functional assay designed to quantify cellular HR activity. Here, we delineate the step-by-step procedure for producing the adenovirus harboring an HR reporter, processing primary cells, and assessing HR activity in primary ovarian cancer cells. For complete details on the use and execution of this protocol, please refer to Lee et al.1.

Intrinsic PARG inhibitor sensitivity is mimicked by TIMELESS haploinsufficiency and rescued by nucleoside supplementation

A subset of cancer cells are intrinsically sensitive to inhibitors targeting PARG, the poly(ADP-ribose) glycohydrolase that degrades PAR chains. Sensitivity is accompanied by persistent DNA replication stress, and can be induced by inhibition of TIMELESS, a replisome accelerator. However, the nature of the vulnerability responsible for intrinsic sensitivity remains undetermined. To understand PARG activity dependency, we analysed Timeless model systems and intrinsically sensitive ovarian cancer cells. We show that nucleoside supplementation rescues all phenotypes associated with PARG inhibitor sensitivity, including replisome speed and fork stalling, S-phase completion and mitotic entry, proliferation dynamics and clonogenic potential. Importantly nucleoside supplementation restores PARG inhibitor resistance despite the continued presence of PAR chains, indicating that sensitivity does not correlate with PAR levels. In addition, we show that inhibition of thymidylate synthase, an enzyme required for dNTP homeostasis, induces PARG-dependency. Together, these observations suggest that PARG inhibitor sensitivity reflects an inability to control replisome speed and/or maintain helicase-polymerase coupling in response to nucleotide imbalances.

Synergistic antitumor effect of liposomal-based formulations of olaparib and topotecan in primary epithelial ovarian cancer cells

BACKGROUND

Olaparib is a PARP inhibitor inducing synthetic lethality in tumors with deficient homologous recombination (HRD) caused by BRCA1/2 mutations. The FDA has approved monotherapy for first-line platinum-sensitive, recurrent high-grade epithelial ovarian cancer. Combination therapy alongside DNA-damaging therapeutics is a promising solution to overcome the limited efficacy in patients with HRD. The present study was designed to develop topotecan- and olaparib-loaded liposomes (TLL and OLL) and assess the effectiveness of their combination in patient-derived ovarian cancer samples.

METHODS

We used HEOC, four clear-cell tumors (EOC 1-4), malignant ascites, and an OCI-E1p endometrioid primary ovarian cancer cell line and performed NGS analysis of BRCA1/2 mutation status. Antiproliferative activity was determined with the MTT assay. The Chou-Talalay algorithm was used to investigate the in vitro pharmacodynamic interactions of TLLs and OLLs.

RESULTS

The OLL showed significantly higher efficacy in all ovarian cancer types with wild-type BRCA1/2 than a conventional formulation, suggesting potential for increased in vivo efficacy. The TLL revealed substantially higher toxicity to EOC 1, EOC 3, ascites and lower toxicity to HEOC than the standard formulation, suggesting better therapeutic efficacy and safety profile. The combination of studied compounds showed a higher reduction in cell viability than drugs used individually, demonstrating a synergistic antitumor effect at most of the selected concentrations.

CONCLUSIONS

The concentration-dependent response of different ovarian cancer cell types to combination therapy confirms the need for in vitro optimization to maximize drug cytotoxicity. The OLL and TLL combination is a promising formulation for further animal studies, especially for eliminating epithelial ovarian cancer with wild-type BRCA1/2.

Establishment of a human ovarian clear cell carcinoma cell line mutant in PIK3CB but not PIK3CA

A human ovarian clear cell carcinoma cell line was established from a 46-year-old Japanese woman. That line, designated MTC-22, has proliferated continuously for over 6 months in conventional RPMI 1640 medium supplemented with 10% foetal bovine serum and has been passaged over 50 times. MTC-22 doubling-time is ~ 18 h, which is much shorter than most ovarian clear cell carcinoma lines reported to date. Morphologically, MTC-22 cells exhibit polygonal shapes and proliferate to form a monolayer in a jigsaw puzzle-like arrangement without contact inhibition. Ultrastructurally, cells exhibit numerous intracytoplasmic glycogen granules and well-developed mitochondria. G-band karyotype analysis indicated that cells have a complex karyotype close to tetraploid. We observed that the expression pattern of a series of ovarian carcinoma-related molecules in MTC-22 cells was identical to that seen in the patient's tumour tissue. Notably, MTC-22 cells, and the patient's carcinoma tissue, expressed low-sulphated keratan sulphate recognised by R-10G and 294-1B1 monoclonal antibodies, a hallmark of non-mucinous ovarian carcinoma, and particularly of clear cell ovarian carcinoma. Moreover, characteristic point mutations-one in ARID1A, which encodes the AT-rich interaction domain containing protein 1A, and the other in PIK3CB, which encodes the catalytic subunit of phosphoinositide 3-kinase-were seen in the patient's tumour tissue and retained in MTC-22 cells. Collectively, these findings indicate that MTC-22 cells could serve as a valuable tool for investigating the pathophysiology of ovarian clear cell carcinoma, particularly that harbouring PIK3CB mutations, and for developing and validating new diagnostic and therapeutic approaches to this life-threatening malignancy.

Tumor microenvironment-induced FOXM1 regulates ovarian cancer stemness

In ovarian tumors, the omental microenvironment profoundly influences the behavior of cancer cells and sustains the acquisition of stem-like traits, with major impacts on tumor aggressiveness and relapse. Here, we leverage a patient-derived platform of organotypic cultures to study the crosstalk between the tumor microenvironment and ovarian cancer stem cells. We discovered that the pro-tumorigenic transcription factor FOXM1 is specifically induced by the microenvironment in ovarian cancer stem cells, through activation of FAK/YAP signaling. The microenvironment-induced FOXM1 sustains stemness, and its inactivation reduces cancer stem cells survival in the omental niche and enhances their response to the PARP inhibitor Olaparib. By unveiling the novel role of FOXM1 in ovarian cancer stemness, our findings highlight patient-derived organotypic co-cultures as a powerful tool to capture clinically relevant mechanisms of the microenvironment/cancer stem cells crosstalk, contributing to the identification of tumor vulnerabilities.

Platinum-induced upregulation of ITGA6 promotes chemoresistance and spreading in ovarian cancer

Platinum (PT)-resistant Epithelial Ovarian Cancer (EOC) grows as a metastatic disease, disseminating in the abdomen and pelvis. Very few options are available for PT-resistant EOC patients, and little is known about how the acquisition of PT-resistance mediates the increased spreading capabilities of EOC. Here, using isogenic PT-resistant cells, genetic and pharmacological approaches, and patient-derived models, we report that Integrin α6 (ITGA6) is overexpressed by PT-resistant cells and is necessary to sustain EOC metastatic ability and adhesion-dependent PT-resistance. Using in vitro approaches, we showed that PT induces a positive loop that, by stimulating ITGA6 transcription and secretion, contributes to the formation of a pre-metastatic niche enabling EOC cells to disseminate. At molecular level, ITGA6 engagement regulates the production and availability of insulin-like growth factors (IGFs), over-stimulating the IGF1R pathway and upregulating Snail expression. In vitro data were recapitulated using in vivo models in which the targeting of ITGA6 prevents PT-resistant EOC dissemination and improves PT-activity, supporting ITGA6 as a promising druggable target for EOC patients.

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.

LncRNA-CCAT5-mediated crosstalk between Wnt/β-Catenin and STAT3 signaling suggests novel therapeutic approaches for metastatic gastric cancer with high Wnt activity

BACKGROUND

Although the constitutively activated Wnt/β-catenin signaling pathway plays vital roles in gastric cancer (GC) progression, few Wnt inhibitors are approved for clinical use. Additionally, the clinical significance of long non-coding RNAs (lncRNAs) in GC intraperitoneal dissemination (IPD) remains elusive. Here, we investigated the function and therapeutic potential of Wnt-transactivated lncRNA, colon cancer-associated transcript 5 (CCAT5), in GC metastasis.

METHODS

LncRNA-sequencing assay was performed to document abundance changes of lncRNAs induced by Wnt family member 3A (Wnt3a) and degradation-resistant β-catenin (S33Y mutated) in ascites-derived GC cells with low Wnt activity. Luciferase reporter, Chromatin immunoprecipitation (ChIP)-re-ChIP assays were performed to determine how CCAT5 was transcribed. The clinical significance of CCAT5 was examined in 2 cohorts of GC patients. The biological function of CCAT5 was investigated through gain- and loss-of-function studies. The molecular mechanism was explored through RNA-sequencing, mass spectrometry, and CRISPR/Cas9-knocknout system. The therapeutic potential of CCAT5 was examined through RNAi-based cell xenograft model and patient-derived xenograft (PDX) model of IPD.

RESULTS

We identified a novel Wnt-regulated lncRNA, CCAT5, which was transactivated by the β-catenin/transcription factor 3 (TCF3) complex. CCAT5 was significantly upregulated in GC and predicted poor prognosis. Functional studies confirmed the promotive role of CCAT5 in GC growth and metastasis. Mechanistically, CCAT5 bound to the C-end domain of signal transducer and activator of transcription 3 (STAT3) and blocks Src homology 2 domain-containing protein tyrosine phosphatase 1 (SHP-1)-mediated STAT3Y705 dephosphorylation, leading to STAT3 nuclear entry and transactivation, thus accelerating GC progression. Furthermore, we demonstrated that both Wnt3a and β-catenin acted as activator of STAT3 signaling pathway, and the interplay between CCAT5 and STAT3 was functionally essential for Wnt-drived STAT3 signaling and tumor evolution. Finally, we revealed in vivo si-CCAT5 selectively attenuated growth and metastasis of Wnthigh GC, but not Wntlow GC. The combination of si-CCAT5 and oxaliplatin displayed obvious synergistic therapeutic effects on Wnthigh PDX mice.

CONCLUSIONS

We identified a novel Wnt-transactivated lncRNA, CCAT5. Our study revealed a mechanism of STAT3 signaling regulation via canonical Wnt signaling and the functional significance of CCAT5 as critical mediator. We provided conceptual advance that lncRNAs serve as therapeutic targets reversing GC progression.

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.

An activity-based functional test for identifying homologous recombination deficiencies across cancer types in real time

Homologous recombination (HR)-mediated DNA repair is a prerequisite for maintaining genome stability. Cancer cells displaying HR deficiency (HRD) are selectively eliminated by poly(ADP-ribose) polymerase inhibitors (PARPis). To date, sequencing of HR-associated genes and analyzing genome instability have been used as clinical predictions for PARPi therapy. However, these genetic tests cannot reflect dynamic changes in the HR status. Here, we have developed a virus- and activity-based functional assay to quantify real-time HR activity directly. Instead of focusing on a few HR-associated genes, our functional assay detects endpoint HR activity and establishes an activity threshold for identifying HRD across cancer types, validated by PARPi sensitivity and BRCA status. Notably, this fluorescence-based assay can be applied to primary ovarian cancer cells from patients to reflect their level of HRD, which is associated with survival benefits. Thus, our work provides a functional test to predict the response of primary cancer cells to PARPis.

Effect of Polyplex Size on Penetration into Tumor Spheroids

Ovarian cancer is one of the most lethal gynecological cancers in the world. In recent years, nucleic acid (NA)-based formulations have been shown to be promising treatments for ovarian cancer, including tumor nodules. However, gene therapy is not that far advanced in clinical reality due to unfavorable physicochemical properties of the NAs, such as high molecular weight, poor cellular uptake, rapid degradation by nucleases, etc. One of the strategies used to overcome these drawbacks is the complexation of anionic NAs via electrostatic interactions with cationic polymers, resulting in the formation of so-called polyplexes. In this work, the role of the size of pDNA and siRNA polyplexes on their penetration into ovarian-cancer-based tumor spheroids was investigated. For this, a methoxypoly(ethylene glycol) poly(2-(dimethylamino)ethyl methacrylate) (mPEG-pDMAEMA) diblock copolymer was synthesized as a polymeric carrier for NA binding and condensation with either plasmid DNA (pDNA) or short interfering RNA (siRNA). When prepared in HEPES buffer (10 mM, pH 7.4) at a nitrogen/phosphate (N/P) charge ratio of 5 and pDNA polyplexes were formed with a size of 162 ± 11 nm, while siRNA-based polyplexes displayed a size of 25 ± 2 nm. The polyplexes had a slightly positive zeta potential of +7-8 mV in the same buffer. SiRNA and pDNA polyplexes were tracked in vitro into tumor spheroids, resembling in vivo avascular ovarian tumor nodules. For this purpose, reproducible spheroids were obtained by coculturing ovarian carcinoma cells with primary mouse embryonic fibroblasts in different ratios (5:2, 1:1, and 2:5). Penetration studies revealed that after 24 h of incubation, siRNA polyplexes were able to penetrate deeper into the homospheroids (composed of only cancer cells) and heterospheroids (cancer cells cocultured with fibroblasts) compared to pDNA polyplexes which were mainly located in the rim. The penetration of the polyplexes was slowed when increasing the fraction of fibroblasts present in the spheroids. Furthermore, in the presence of serum siRNA polyplexes encoding for luciferase showed a high cellular uptake in 2D cells resulting in ∼50% silencing of luciferase expression. Taken together, these findings show that self-assembled small siRNA polyplexes have good potential as a platform to test ovarian tumor nodulus penetration..

Development and characterization of a recombinant silk network for 3D culture of immortalized and fresh tumor-derived breast cancer cells

Traditional cancer models rely on 2D cell cultures or 3D spheroids, which fail to recapitulate cell-extracellular matrix (ECM) interactions, a key element of tumor development. Existing hydrogel-based 3D alternatives lack mechanical support for cell growth and often suffer from low reproducibility. Here we report a novel strategy to make 3D models of breast cancer using a tissue-like, well-defined network environment based on recombinant spider silk, functionalized with a cell adhesion motif from fibronectin (FN-silk). With this approach, the canonical cancer cells SK-BR-3, MCF-7, and MDA-MB-231, maintain their characteristic expression of markers (i.e., ERα, HER2, and PGR) while developing distinct morphology. Transcriptomic analyses demonstrate how culture in the FN-silk networks modulates the biological processes of cell adhesion and migration while affecting physiological events involved in malignancy, such as inflammation, remodeling of the ECM, and resistance to anticancer drugs. Finally, we show that integration in FN-silk networks promotes the viability of cells obtained from the superficial scraping of patients' breast tumors.

Exploiting a living biobank to delineate mechanisms underlying disease-specific chromosome instability

Chromosome instability (CIN) is a cancer hallmark that drives tumour heterogeneity, phenotypic adaptation, drug resistance and poor prognosis. High-grade serous ovarian cancer (HGSOC), one of the most chromosomally unstable tumour types, has a 5-year survival rate of only ~30% - largely due to late diagnosis and rapid development of drug resistance, e.g., via CIN-driven ABCB1 translocations. However, CIN is also a cell cycle vulnerability that can be exploited to specifically target tumour cells, illustrated by the success of PARP inhibitors to target homologous recombination deficiency (HRD). However, a lack of appropriate models with ongoing CIN has been a barrier to fully exploiting disease-specific CIN mechanisms. This barrier is now being overcome with the development of patient-derived cell cultures and organoids. In this review, we describe our progress building a Living Biobank of over 120 patient-derived ovarian cancer models (OCMs), predominantly from HGSOC. OCMs are highly purified tumour fractions with extensive proliferative potential that can be analysed at early passage. OCMs have diverse karyotypes, display intra- and inter-patient heterogeneity and mitotic abnormality rates far higher than established cell lines. OCMs encompass a broad-spectrum of HGSOC hallmarks, including a range of p53 alterations and BRCA1/2 mutations, and display drug resistance mechanisms seen in the clinic, e.g., ABCB1 translocations and BRCA2 reversion. OCMs are amenable to functional analysis, drug-sensitivity profiling, and multi-omics, including single-cell next-generation sequencing, and thus represent a platform for delineating HGSOC-specific CIN mechanisms. In turn, our vision is that this understanding will inform the design of new therapeutic strategies.

Insights into high-grade serous carcinoma pathobiology using three-dimensional culture model systems

Epithelial ovarian cancer (EOC) research has become more complex as researchers try to fully understand the metastatic process. Especially as we delve into the concept of tumour dormancy, where cells transition between proliferative and dormant states to survive during disease progression. Thus, the in vitro models used to conduct this research need to reflect this vast biological complexity. The innovation behind the many three-dimensional (3D) spheroid models has been refined to easily generate reproducible spheroids so that we may understand the various molecular signaling changes of cells during metastasis and determine therapeutic efficacy of treatments. This ingenuity was then used to develop the 3D ex vivo patient-derived organoid model, as well as multiple co-culture model systems for EOC research. Although, researchers need to continue to push the boundaries of these current models for in vitro and even in vivo work in the future. In this review, we describe the 3D models already in use, where these models can be developed further and how we can use these models to gain the most knowledge on EOC pathogenesis and discover new targeted therapies.

Patient-Derived In Vitro Models of Ovarian Cancer: Powerful Tools to Explore the Biology of the Disease and Develop Personalized Treatments

Epithelial ovarian cancer (OC) is the most lethal gynecological malignancy worldwide due to a late diagnosis caused by the lack of specific symptoms and rapid dissemination into the peritoneal cavity. The standard of care for OC treatment is surgical cytoreduction followed by platinum-based chemotherapy. While a response to this frontline treatment is common, most patients undergo relapse within 2 years and frequently develop a chemoresistant disease that has become unresponsive to standard treatments. Moreover, also due to the lack of actionable mutations, very few alternative therapeutic strategies have been designed as yet for the treatment of recurrent OC. This dismal clinical perspective raises the need for pre-clinical models that faithfully recapitulate the original disease and therefore offer suitable tools to design novel therapeutic approaches. In this regard, patient-derived models are endowed with high translational relevance, as they can better capture specific aspects of OC such as (i) the high inter- and intra-tumor heterogeneity, (ii) the role of cancer stem cells (a small subset of tumor cells endowed with tumor-initiating ability, which can sustain tumor spreading, recurrence and chemoresistance), and (iii) the involvement of the tumor microenvironment, which interacts with tumor cells and modulates their behavior. This review describes the different in vitro patient-derived models that have been developed in recent years in the field of OC research, focusing on their ability to recapitulate specific features of this disease. We also discuss the possibilities of leveraging such models as personalized platforms to design new therapeutic approaches and guide clinical decisions.

The lysophosphatidic acid-regulated signal transduction network in ovarian cancer cells and its role in actomyosin dynamics, cell migration and entosis

Lysophosphatidic acid (LPA) species accumulate in the ascites of ovarian high-grade serous cancer (HGSC) and are associated with short relapse-free survival. LPA is known to support metastatic spread of cancer cells by activating a multitude of signaling pathways via G-protein-coupled receptors of the LPAR family. Systematic unbiased analyses of the LPA-regulated signal transduction network in ovarian cancer cells have, however, not been reported to date. Methods: LPA-induced signaling pathways were identified by phosphoproteomics of both patient-derived and OVCAR8 cells, RNA sequencing, measurements of intracellular Ca²⁺ and cAMP as well as cell imaging. The function of LPARs and downstream signaling components in migration and entosis were analyzed by selective pharmacological inhibitors and RNA interference. Results: Phosphoproteomic analyses identified > 1100 LPA-regulated sites in > 800 proteins and revealed interconnected LPAR1, ROCK/RAC, PKC/D and ERK pathways to play a prominent role within a comprehensive signaling network. These pathways regulate essential processes, including transcriptional responses, actomyosin dynamics, cell migration and entosis. A critical component of this signaling network is MYPT1, a stimulatory subunit of protein phosphatase 1 (PP1), which in turn is a negative regulator of myosin light chain 2 (MLC2). LPA induces phosphorylation of MYPT1 through ROCK (T853) and PKC/ERK (S507), which is majorly driven by LPAR1. Inhibition of MYPT1, PKC or ERK impedes both LPA-induced cell migration and entosis, while interference with ROCK activity and MLC2 phosphorylation selectively blocks entosis, suggesting that MYPT1 figures in both ROCK/MLC2-dependent and -independent pathways. We finally show a novel pathway governed by LPAR2 and the RAC-GEF DOCK7 to be indispensable for the induction of entosis. Conclusion: We have identified a comprehensive LPA-induced signal transduction network controlling LPA-triggered cytoskeletal changes, cell migration and entosis in HGSC cells. Due to its pivotal role in this network, MYPT1 may represent a promising target for interfering with specific functions of PP1 essential for HGSC progression.

Multiple-low-dose therapy: effective killing of high-grade serous ovarian cancer cells with ATR and CHK1 inhibitors

High-grade serous ovarian cancer (HGSOC) is an aggressive disease that typically develops drug resistance, thus novel biomarker-driven strategies are required. Targeted therapy focuses on synthetic lethality-pioneered by PARP inhibition of BRCA1/2-mutant disease. Subsequently, targeting the DNA replication stress response (RSR) is of clinical interest. However, further mechanistic insight is required for biomarker discovery, requiring sensitive models that closely recapitulate HGSOC. We describe an optimized proliferation assay that we use to screen 16 patient-derived ovarian cancer models (OCMs) for response to RSR inhibitors (CHK1i, WEE1i, ATRi, PARGi). Despite genomic heterogeneity characteristic of HGSOC, measurement of OCM proliferation was reproducible and reflected intrinsic tumour-cell properties. Surprisingly, RSR targeting drugs were not interchangeable, as sensitivity to the four inhibitors was not correlated. Therefore, to overcome RSR redundancy, we screened the OCMs with all two-, three- and four-drug combinations in a multiple-low-dose strategy. We found that low-dose CHK1i-ATRi had a potent anti-proliferative effect on 15 of the 16 OCMs, and was synergistic with potential to minimise treatment resistance and toxicity. Low-dose ATRi-CHK1i induced replication catastrophe followed by mitotic exit and post-mitotic arrest or death. Therefore, this study demonstrates the potential of the living biobank of OCMs as a drug discovery platform for HGSOC.

Molecular, cellular and systemic aspects of epithelial ovarian cancer and its tumor microenvironment

Ovarian cancer encompasses a heterogeneous group of malignancies that involve the ovaries, fallopian tubes and the peritoneal cavity. Despite major advances made within the field of cancer, the majority of patients with ovarian cancer are still being diagnosed at an advanced stage of the disease due to lack of effective screening tools. The overall survival of these patients has, therefore, not substantially improved over the past decades. Most patients undergo debulking surgery and treatment with chemotherapy, but often micrometastases remain and acquire resistance to the therapy, eventually leading to disease recurrence. Here, we summarize the current knowledge in epithelial ovarian cancer development and metastatic progression. For the most common subtypes, we focus further on the properties and functions of the immunosuppressive tumor microenvironment, including the extracellular matrix. Current and future treatment modalities are discussed and finally we provide an overview of the different experimental models used to develop novel therapies.

A novel cell line panel reveals non-genetic mediators of platinum resistance and phenotypic diversity in high grade serous ovarian cancer

OBJECTIVES

Resistance to cancer therapy is an enduring challenge and accurate and reliable preclinical models are lacking. We interrogated this unmet need using high grade serous ovarian cancer (HGSC) as a disease model.

METHODS

We created five in vitro and two in vivo platinum-resistant HGSC models and characterised the entire cell panel via whole genome sequencing, RNASeq and creation of intraperitoneal models.

RESULTS

Mutational signature analysis indicated that platinum-resistant cell lines evolved from a pre-existing ancestral clone but a unifying mutational cause for drug resistance was not identified. However, cisplatin-resistant and carboplatin-resistant cells evolved recurrent changes in gene expression that significantly overlapped with independent samples obtained from multiple patients with relapsed HGSC. Gene Ontology Biological Pathways (GOBP) related to the tumour microenvironment, particularly the extracellular matrix, were repeatedly enriched in cisplatin-resistant cells, carboplatin-resistant cells and also in human resistant/refractory samples. The majority of significantly over-represented GOBP however, evolved uniquely in either cisplatin- or carboplatin-resistant cell lines resulting in diverse intraperitoneal behaviours that reflect different clinical manifestations of relapsed human HGSC.

CONCLUSIONS

Our clinically relevant and usable models reveal a key role for non-genetic factors in the evolution of chemotherapy resistance. Biological pathways relevant to the extracellular matrix were repeatedly expressed by resistant cancer cells in multiple settings. This suggests that recurrent gene expression changes provide a fitness advantage during platinum therapy and also that cancer cell-intrinsic mechanisms influence the tumour microenvironment during the evolution of drug resistance. Candidate genes and pathways identified here could reveal therapeutic opportunities in platinum-resistant HGSC.

Hydrogel Nanoarchitectonics: An Evolving Paradigm for Ultrasensitive Biosensing

The integration of nanoarchitectonics and hydrogel into conventional biosensing platforms offers the opportunities to design physically and chemically controlled and optimized soft structures with superior biocompatibility, better immobilization of biomolecules, and specific and sensitive biosensor design. The physical and chemical properties of 3D hydrogel structures can be modified by integrating with nanostructures. Such modifications can enhance their responsiveness to mechanical, optical, thermal, magnetic, and electric stimuli, which in turn can enhance the practicality of biosensors in clinical settings. This review describes the synthesis and kinetics of gel networks and exploitation of nanostructure-integrated hydrogels in biosensing. With an emphasis on different integration strategies of hydrogel with nanostructures, this review highlights the importance of hydrogel nanostructures as one of the most favorable candidates for developing ultrasensitive biosensors. Moreover, hydrogel nanoarchitectonics are also portrayed as a promising candidate for fabricating next-generation robust biosensors.

Preclinical models of epithelial ovarian cancer: practical considerations and challenges for a meaningful application

Despite many improvements in ovarian cancer diagnosis and treatment, until now, conventional chemotherapy and new biological drugs have not been shown to cure the disease, and the overall prognosis remains poor. Over 90% of ovarian malignancies are categorized as epithelial ovarian cancers (EOC), a collection of different types of neoplasms with distinctive disease biology, response to chemotherapy, and outcome. Advances in our understanding of the histopathology and molecular features of EOC subtypes, as well as the cellular origins of these cancers, have given a boost to the development of clinically relevant experimental models. The overall goal of this review is to provide a comprehensive description of the available preclinical investigational approaches aimed at better characterizing disease development and progression and at identifying new therapeutic strategies. Systems discussed comprise monolayer (2D) and three-dimensional (3D) cultures of established and primary cancer cell lines, organoids and patient-derived explants, animal models, including carcinogen-induced, syngeneic, genetically engineered mouse, xenografts, patient-derived xenografts (PDX), humanized PDX, and the zebrafish and the laying hen models. Recent advances in tumour-on-a-chip platforms are also detailed. The critical analysis of strengths and weaknesses of each experimental model will aid in identifying opportunities to optimize their translational value.

Identification of Prognosis Biomarkers for High-Grade Serous Ovarian Cancer Based on Stemness

In this paper, high-grade serous ovarian cancer (HGSOC) is studied, which is the most common histological subtype of ovarian cancer. We use a new analytical procedure to combine the bulk RNA-Seq sample for ovarian cancer, mRNA expression-based stemness index (mRNAsi), and single-cell data for ovarian cancer. Through integrating bulk RNA-Seq sample of cancer samples from TCGA, UCSC Xena and single-cell RNA-Seq (scRNA-Seq) data of HGSOC from GEO, and performing a series of computational analyses on them, we identify stemness markers and survival-related markers, explore stem cell populations in ovarian cancer, and provide potential treatment recommendation. As a result, 171 key genes for capturing stem cell characteristics are screened and one vital cancer stem cell subpopulation is identified. Through further analysis of these key genes and cancer stem cell subpopulation, more critical genes can be obtained as LCP2, FCGR3A, COL1A1, COL1A2, MT-CYB, CCT5, and PAPPA, are closely associated with ovarian cancer. So these genes have the potential to be used as prognostic biomarkers for ovarian cancer.

Quantitative Biophysical Metrics for Rapid Evaluation of Ovarian Cancer Metastatic Potential

Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous sub-mesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here, we fabricated extracellular-matrix mimicking suspended fiber networks: crosshatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying inter-fiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease, while force-disease biphasic relationship exhibited f-actin stress-fiber network dependence. However, unique to suspended fibers, coiling occurring at tips of protrusions and not the length or breadth of protrusions displayed strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on time scale of hours. [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text].

Reduced RBPMS Levels Promote Cell Proliferation and Decrease Cisplatin Sensitivity in Ovarian Cancer Cells

Worldwide, the number of cancer-related deaths continues to increase due to the ability of cancer cells to become chemotherapy-resistant and metastasize. For women with ovarian cancer, a staggering 70% will become resistant to the front-line therapy, cisplatin. Although many mechanisms of cisplatin resistance have been proposed, the key mechanisms of such resistance remain elusive. The RNA binding protein with multiple splicing (RBPMS) binds to nascent RNA transcripts and regulates splicing, transport, localization, and stability. Evidence indicates that RBPMS also binds to protein members of the AP-1 transcription factor complex repressing its activity. Until now, little has been known about the biological function of RBPMS in ovarian cancer. Accordingly, we interrogated available Internet databases and found that ovarian cancer patients with high RBPMS levels live longer compared to patients with low RBPMS levels. Similarly, immunohistochemical (IHC) analysis in a tissue array of ovarian cancer patient samples showed that serous ovarian cancer tissues showed weaker RBPMS staining when compared with normal ovarian tissues. We generated clustered regularly interspaced short palindromic repeats (CRISPR)-mediated RBPMS knockout vectors that were stably transfected in the high-grade serous ovarian cancer cell line, OVCAR3. The knockout of RBPMS in these cells was confirmed via bioinformatics analysis, real-time PCR, and Western blot analysis. We found that the RBPMS knockout clones grew faster and had increased invasiveness than the control CRISPR clones. RBPMS knockout also reduced the sensitivity of the OVCAR3 cells to cisplatin treatment. Moreover, β-galactosidase (β-Gal) measurements showed that RBPMS knockdown induced senescence in ovarian cancer cells. We performed RNAseq in the RBPMS knockout clones and identified several downstream-RBPMS transcripts, including non-coding RNAs (ncRNAs) and protein-coding genes associated with alteration of the tumor microenvironment as well as those with oncogenic or tumor suppressor capabilities. Moreover, proteomic studies confirmed that RBPMS regulates the expression of proteins involved in cell detoxification, RNA processing, and cytoskeleton network and cell integrity. Interrogation of the Kaplan-Meier (KM) plotter database identified multiple downstream-RBPMS effectors that could be used as prognostic and response-to-therapy biomarkers in ovarian cancer. These studies suggest that RBPMS acts as a tumor suppressor gene and that lower levels of RBPMS promote the cisplatin resistance of ovarian cancer cells.

Photodynamic Treatments for Disseminated Cancer Metastases Using Fiber-Optic Technologies

Tumor-targeted and -activatable photosensitizer delivery platforms are creating new opportunities to develop photodynamic therapy (PDT) of metastatic disease. This is possible by confining the activity of the photosensitizing chemical (i.e., the PDT agent) to the tumor in combination with diffuse near-infrared light irradiation for wide-field treatment. This chapter outlines protocols and research tools for preclinical development of light-activated therapies of cancer metastases using advanced-stage ovarian cancer as a model system. We also describe an in vivo molecular imaging approach that uniquely enables tracking intraperitoneal micrometastatic burden and responses to treatment using fluorescence microendoscopy.

MFmap: A semi-supervised generative model matching cell lines to tumours and cancer subtypes

Translating in vitro results from experiments with cancer cell lines to clinical applications requires the selection of appropriate cell line models. Here we present MFmap (model fidelity map), a machine learning model to simultaneously predict the cancer subtype of a cell line and its similarity to an individual tumour sample. The MFmap is a semi-supervised generative model, which compresses high dimensional gene expression, copy number variation and mutation data into cancer subtype informed low dimensional latent representations. The accuracy (test set F₁ score >90%) of the MFmap subtype prediction is validated in ten different cancer datasets. We use breast cancer and glioblastoma cohorts as examples to show how subtype specific drug sensitivity can be translated to individual tumour samples. The low dimensional latent representations extracted by MFmap explain known and novel subtype specific features and enable the analysis of cell-state transformations between different subtypes. From a methodological perspective, we report that MFmap is a semi-supervised method which simultaneously achieves good generative and predictive performance and thus opens opportunities in other areas of computational biology.

Multicellular Ovarian Cancer Model for Evaluation of Nanovector Delivery in Ascites and Metastatic Environments

A novel multicellular model composed of epithelial ovarian cancer and fibroblast cells was developed as an in vitro platform to evaluate nanovector delivery and ultimately aid the development of targeted therapies. We hypothesized that the inclusion of peptide-based scaffold (PuraMatrix) in the spheroid matrix, to represent in vivo tumor microenvironment alterations along with metastatic site conditions, would enhance spheroid cell growth and migration and alter nanovector transport. The model was evaluated by comparing the growth and migration of ovarian cancer cells exposed to stromal cell activation and tissue hypoxia. Fibroblast activation was achieved via the TGF-β1 mediated pathway and tissue hypoxia via 3D spheroids incubated in hypoxia. Surface-modified nanovector transport was assessed via fluorescence and confocal microscopy. Consistent with previous in vivo observations in ascites and at distal metastases, spheroids exposed to activated stromal microenvironment were denser, more contractile and with more migratory cells than nonactivated counterparts. The hypoxic conditions resulted in negative radial spheroid growth over 5 d compared to a radial increase in normoxia. Nanovector penetration attenuated in PuraMatrix regardless of surface modification due to a denser environment. This platform may serve to evaluate nanovector transport based on ovarian ascites and metastatic environments, and longer term, it provide a means to evaluate nanotherapeutic efficacy.

Replication catastrophe is responsible for intrinsic PAR glycohydrolase inhibitor-sensitivity in patient-derived ovarian cancer models

BACKGROUND

Patients with ovarian cancer often present at advanced stage and, following initial treatment success, develop recurrent drug-resistant disease. PARP inhibitors (PARPi) are yielding unprecedented survival benefits for women with BRCA-deficient disease. However, options remain limited for disease that is platinum-resistant and/or has inherent or acquired PARPi-resistance. PARG, the PAR glycohydrolase that counterbalances PARP activity, is an emerging target with potential to selectively kill tumour cells harbouring oncogene-induced DNA replication and metabolic vulnerabilities. Clinical development of PARG inhibitors (PARGi) will however require predictive biomarkers, in turn requiring an understanding of their mode of action. Furthermore, differential sensitivity to PARPi is key for expanding treatment options available for patients.

METHODS

A panel of 10 ovarian cancer cell lines and a living biobank of patient-derived ovarian cancer models (OCMs) were screened for PARGi-sensitivity using short- and long-term growth assays. PARGi-sensitivity was characterized using established markers for DNA replication stress, namely replication fibre asymmetry, RPA foci, KAP1 and Chk1 phosphorylation, and pan-nuclear γH2AX, indicating DNA replication catastrophe. Finally, gene expression in sensitive and resistant cells was also examined using NanoString or RNAseq.

RESULTS

PARGi sensitivity was identified in both ovarian cancer cell lines and patient-derived OCMs, with sensitivity accompanied by markers of persistent replication stress, and a pre-mitotic cell cycle block. Moreover, DNA replication genes are down-regulated in PARGi-sensitive cell lines consistent with an inherent DNA replication vulnerability. However, DNA replication gene expression did not predict PARGi-sensitivity in OCMs. The subset of patient-derived OCMs that are sensitive to single-agent PARG inhibition, includes models that are PARPi- and/or platinum-resistant, indicating that PARG inhibitors may represent an alternative treatment strategy for women with otherwise limited therapeutic options.

CONCLUSIONS

We discover that a subset of ovarian cancers are intrinsically sensitive to pharmacological PARG blockade, including drug-resistant disease, underpinned by a common mechanism of replication catastrophe. We explore the use of a transcript-based biomarker, and provide insight into the design of future clinical trials of PARGi in patients with ovarian cancer. However, our results highlight the complexity of developing a predictive biomarker for PARGi sensitivity.

(In)Distinctive Role of Long Non-Coding RNAs in Common and Rare Ovarian Cancers

Rare ovarian cancers (ROCs) are OCs with an annual incidence of fewer than 6 cases per 100,000 women. They affect women of all ages, but due to their low incidence and the potential clinical inexperience in management, there can be a delay in diagnosis, leading to a poor prognosis. The underlying causes for these tumors are varied, but generally, the tumors arise due to alterations in gene/protein expression in cellular processes that regulate normal proliferation and its checkpoints. Dysregulation of the cellular processes that lead to cancer includes gene mutations, epimutations, non-coding RNA (ncRNA) regulation, posttranscriptional and posttranslational modifications. Long non-coding RNA (lncRNA) are defined as transcribed RNA molecules, more than 200 nucleotides in length which are not translated into proteins. They regulate gene expression through several mechanisms and therefore add another level of complexity to the regulatory mechanisms affecting tumor development. Since few studies have been performed on ROCs, in this review we summarize the mechanisms of action of lncRNA in OC, with an emphasis on ROCs.

Advancements in Microfluidic Systems for the Study of Female Reproductive Biology

The female reproductive tract is a highly complex physiological system that consists of the ovaries, fallopian tubes, uterus, cervix, and vagina. An enhanced understanding of the molecular, cellular, and genetic mechanisms of the tract will allow for the development of more effective assisted reproductive technologies, therapeutics, and screening strategies for female specific disorders. Traditional 2-dimensional and 3-dimensional static culture systems may not always reflect the cellular and physical contexts or physicochemical microenvironment necessary to understand the dynamic exchange that is crucial for the functioning of the reproductive system. Microfluidic systems present a unique opportunity to study the female reproductive tract, as these systems recapitulate the multicellular architecture, contacts between different tissues, and microenvironmental cues that largely influence cell structure, function, behavior, and growth. This review discusses examples, challenges, and benefits of using microfluidic systems to model ovaries, fallopian tubes, endometrium, and placenta. Additionally, this review also briefly discusses the use of these systems in studying the effects of endocrine disrupting chemicals and diseases such as ovarian cancer, preeclampsia, and polycystic ovarian syndrome.

CCNE1 copy number is a biomarker for response to combination WEE1-ATR inhibition in ovarian and endometrial cancer models

CCNE1-amplified ovarian cancers (OVCAs) and endometrial cancers (EMCAs) are associated with platinum resistance and poor survival, representing a clinically unmet need. We hypothesized that dysregulated cell-cycle progression promoted by CCNE1 overexpression would lead to increased sensitivity to low-dose WEE1 inhibition and ataxia telangiectasia and Rad3-related (ATR) inhibition (WEE1i-ATRi), thereby optimizing efficacy and tolerability. The addition of ATRi to WEE1i is required to block feedback activation of ATR signaling mediated by WEE1i. Low-dose WEE1i-ATRi synergistically decreases viability and colony formation and increases replication fork collapse and double-strand breaks (DSBs) in a CCNE1 copy number (CN)-dependent manner. Only upon CCNE1 induction does WEE1i perturb DNA synthesis at S-phase entry, and addition of ATRi increases DSBs during DNA synthesis. Inherent resistance to WEE1i is overcome with WEE1i-ATRi, with notable durable tumor regressions and improved survival in patient-derived xenograft (PDX) models in a CCNE1-level-dependent manner. These studies demonstrate that CCNE1 CN is a clinically tractable biomarker predicting responsiveness to low-dose WEE1i-ATRi for aggressive subsets of OVCAs/EMCAs.

Distinct transcriptional programs stratify ovarian cancer cell lines into the five major histological subtypes

BACKGROUND

Epithelial ovarian cancer (OC) is a heterogenous disease consisting of five major histologically distinct subtypes: high-grade serous (HGSOC), low-grade serous (LGSOC), endometrioid (ENOC), clear cell (CCOC) and mucinous (MOC). Although HGSOC is the most prevalent subtype, representing 70-80% of cases, a 2013 landmark study by Domcke et al. found that the most frequently used OC cell lines are not molecularly representative of this subtype. This raises the question, if not HGSOC, from which subtype do these cell lines derive? Indeed, non-HGSOC subtypes often respond poorly to chemotherapy; therefore, representative models are imperative for developing new targeted therapeutics.

METHODS

Non-negative matrix factorisation (NMF) was applied to transcriptomic data from 44 OC cell lines in the Cancer Cell Line Encyclopedia, assessing the quality of clustering into 2-10 groups. Epithelial OC subtypes were assigned to cell lines optimally clustered into five transcriptionally distinct classes, confirmed by integration with subtype-specific mutations. A transcriptional subtype classifier was then developed by trialling three machine learning algorithms using subtype-specific metagenes defined by NMF. The ability of classifiers to predict subtype was tested using RNA sequencing of a living biobank of patient-derived OC models.

RESULTS

Application of NMF optimally clustered the 44 cell lines into five transcriptionally distinct groups. Close inspection of orthogonal datasets revealed this five-cluster delineation corresponds to the five major OC subtypes. This NMF-based classification validates the Domcke et al. analysis, in identifying lines most representative of HGSOC, and additionally identifies models representing the four other subtypes. However, NMF of the cell lines into two clusters did not align with the dualistic model of OC and suggests this classification is an oversimplification. Subtype designation of patient-derived models by a random forest transcriptional classifier aligned with prior diagnosis in 76% of unambiguous cases. In cases where there was disagreement, this often indicated potential alternative diagnosis, supported by a review of histological, molecular and clinical features.

CONCLUSIONS

This robust classification informs the selection of the most appropriate models for all five histotypes. Following further refinement on larger training cohorts, the transcriptional classification may represent a useful tool to support the classification of new model systems of OC subtypes.

Nuclear HKII-P-p53 (Ser15) Interaction is a Prognostic Biomarker for Chemoresponsiveness and Glycolytic Regulation in Epithelial Ovarian Cancer

Simple Summary

Hexokinase II (HKII) is a key glycolysis enzyme associated with tumorigenesis, but its molecular mechanism and pathophysiological role in chemoresistant ovarian cancer remain elusive. In this study, we delineate the novel mechanism showing that activated phosphorylated-p53 (P-p53 Ser15) is required for the regulation of HKII intracellular trafficking and metabolic regulation in chemosensitive ovarian cancer, but not in chemoresistant ovarian cancer harboring p53 mutation. We have observed that increased nuclear HKII-P-p53 (Ser15) interaction is likely associated with chemosensitivity and better survival outcomes in epithelial ovarian cell lines, human primary epithelial ovarian cancer cells, and tumor sections. Nuclear HKII-P-p53 (Ser15) interaction may function as a promising prognostic biomarker, enabling prediction of patients with poor prognosis for deciding better clinical strategies.

Abstract

In epithelial ovarian cancer (EOC), carboplatin/cisplatin-induced chemoresistance is a major hurdle to successful treatment. Aerobic glycolysis is a common characteristic of cancer. However, the role of glycolytic metabolism in chemoresistance and its impact on clinical outcomes in EOC are not clear. Here, we show a functional interaction between the key glycolytic enzyme hexokinase II (HKII) and activated P-p53 (Ser15) in the regulation of bioenergetics and chemosensitivity. Using translational approaches with proximity ligation assessment in cancer cells and human EOC tumor sections, we showed that nuclear HKII-P-p53 (Ser15) interaction is increased after chemotherapy, and functions as a determinant of chemoresponsiveness as a prognostic biomarker. We also demonstrated that p53 is required for the intracellular nuclear HKII trafficking in the control of glycolysis in EOC, associated with chemosensitivity. Mechanistically, cisplatin-induced P-p53 (Ser15) recruits HKII and apoptosis-inducing factor (AIF) in chemosensitive EOC cells, enabling their translocation from the mitochondria to the nucleus, eliciting AIF-induced apoptosis. Conversely, in p53-defective chemoresistant EOC cells, HKII and AIF are strongly bound in the mitochondria and, therefore, apoptosis is suppressed. Collectively, our findings implicate nuclear HKII-P-p53(Ser15) interaction in chemosensitivity and could provide an effective clinical strategy as a promising biomarker during platinum-based therapy.

Antiparasitic mebendazole (MBZ) effectively overcomes cisplatin resistance in human ovarian cancer cells by inhibiting multiple cancer-associated signaling pathways

Ovarian cancer is the third most common cancer and the second most common cause of gynecologic cancer death in women. Its routine clinical management includes surgical resection and systemic therapy with chemotherapeutics. While the first-line systemic therapy requires the combined use of platinum-based agents and paclitaxel, many ovarian cancer patients have recurrence and eventually succumb to chemoresistance. Thus, it is imperative to develop new strategies to overcome recurrence and chemoresistance of ovarian cancer. Repurposing previously-approved drugs is a cost-effective strategy for cancer drug discovery. The antiparasitic drug mebendazole (MBZ) is one of the most promising drugs with repurposing potential. Here, we investigate whether MBZ can overcome cisplatin resistance and sensitize chemoresistant ovarian cancer cells to cisplatin. We first established and characterized two stable and robust cisplatin-resistant (CR) human ovarian cancer lines and demonstrated that MBZ markedly inhibited cell proliferation, suppressed cell wounding healing/migration, and induced apoptosis in both parental and CR cells at low micromole range. Mechanistically, MBZ was revealed to inhibit multiple cancer-related signal pathways including ELK/SRF, NFKB, MYC/MAX, and E2F/DP1 in cisplatin-resistant ovarian cancer cells. We further showed that MBZ synergized with cisplatin to suppress cell proliferation, induce cell apoptosis, and blunt tumor growth in xenograft tumor model of human cisplatin-resistant ovarian cancer cells. Collectively, our findings suggest that MBZ may be repurposed as a synergistic sensitizer of cisplatin in treating chemoresistant human ovarian cancer, which warrants further clinical studies.

CELLector: Genomics-Guided Selection of Cancer In Vitro Models

Selecting appropriate cancer models is a key prerequisite for maximizing translational potential and clinical relevance of in vitro oncology studies. We developed CELLector: an R package and R Shiny application allowing researchers to select the most relevant cancer cell lines in a patient-genomic-guided fashion. CELLector leverages tumor genomics to identify recurrent subtypes with associated genomic signatures. It then evaluates these signatures in cancer cell lines to prioritize their selection. This enables users to choose appropriate in vitro models for inclusion or exclusion in retrospective analyses and future studies. Moreover, this allows bridging outcomes from cancer cell line screens to precisely defined sub-cohorts of primary tumors. Here, we demonstrate the usefulness and applicability of CELLector, showing how it can aid prioritization of in vitro models for future development and unveil patient-derived multivariate prognostic and therapeutic markers. CELLector is freely available at https://ot-cellector.shinyapps.io/CELLector_App/ (code at https://github.com/francescojm/CELLector and https://github.com/francescojm/CELLector_App).

Joint IARC/NCI International Cancer Seminar Series Report: expert consensus on future directions for ovarian carcinoma research

Recently, ovarian cancer research has evolved considerably because of the emerging recognition that rather than a single disease, ovarian carcinomas comprise several different histotypes that vary by etiologic origin, risk factors, molecular profiles, therapeutic approaches and clinical outcome. Despite significant progress in our understanding of the etiologic heterogeneity of ovarian cancer, as well as important clinical advances, it remains the eighth most frequently diagnosed cancer in women worldwide and the most fatal gynecologic cancer. The International Agency for Research on Cancer and the United States National Cancer Institute jointly convened an expert panel on ovarian carcinoma to develop consensus research priorities based on evolving scientific discoveries. Expertise ranged from etiology, prevention, early detection, pathology, model systems, molecular characterization and treatment/clinical management. This report summarizes the current state of knowledge and highlights expert consensus on future directions to continue advancing etiologic, epidemiologic and prognostic research on ovarian carcinoma.

Super-Enhancer Redistribution as a Mechanism of Broad Gene Dysregulation in Repeatedly Drug-Treated Cancer Cells

Cisplatin is an antineoplastic drug administered at suboptimal and intermittent doses to avoid life-threatening effects. Although this regimen shortly improves symptoms in the short term, it also leads to more malignant disease in the long term. We describe a multilayered analysis ranging from chromatin to translation-integrating chromatin immunoprecipitation sequencing (ChIP-seq), global run-on sequencing (GRO-seq), RNA sequencing (RNA-seq), and ribosome profiling-to understand how cisplatin confers (pre)malignant features by using a well-established ovarian cancer model of cisplatin exposure. This approach allows us to segregate the human transcriptome into gene modules representing distinct regulatory principles and to characterize that the most cisplatin-disrupted modules are associated with underlying events of super-enhancer plasticity. These events arise when cancer cells initiate without ultimately ending the program of drug-stimulated death. Using a PageRank-based algorithm, we predict super-enhancer regulator ISL1 as a driver of this plasticity and validate this prediction by using CRISPR/dCas9-KRAB inhibition (CRISPRi) and CRISPR/dCas9-VP64 activation (CRISPRa) tools. Together, we propose that cisplatin reprograms cancer cells when inducing them to undergo near-to-death experiences.

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.

Mouse models of epithelial ovarian cancer for preclinical studies

Epithelial ovarian cancer (EOC) is the leading cause of gynecological cancer-related mortality in the developed world. EOC is a heterogeneous disease represented by several histological and molecular subtypes. Therefore, exploration of relevant preclinical animal models that consider the heterogenic nature of EOC is of great importance for the development of novel therapeutic strategies that can be translated clinically to combat this devastating disease. In this review, we discuss recent progress in the development of preclinical mouse models for EOC study as well as their advantages and limitations.

The Correlation between Targeted Contrast-Enhanced Ultrasound Imaging and Tumor Neovascularization of Ovarian Cancer Xenografts in Nude Mice

In order to explore the correlation between targeted contrast-enhanced ultrasound imaging and tumor neovascularization of ovarian cancer xenografts in nude mice, a total of 49 nude mice were selected and randomly divided into 1-week group, 2-week group, 3-week group, 4-week group, 5-week group, 6-week group, and 7-week group according to their ovarian cancer xenografts' growth time, with 7 ovarian cancer xenografts in each group. After preparing antibody-carrying targeted contrast agent, each group of xenografts performed normal and targeted contrast ultrasound examinations to obtain peak intensity, time to peak, and other imaging parameters; then, those ovarian cancer xenografts were sacrificed for pathological analysis: the neovascular density and antibody expression of the cancer xenografts at different stages were observed and counted, and the correlation between targeted contrast-enhanced ultrasound parameters and tumor neovascular densities of the ovarian cancer xenografts was analyzed. The results show that the peak intensities of targeted contrast ultrasound imaging are greater than that of ordinary ultrasound imaging in the 2-, 3-, 4-, and 5-week groups with statistically significant differences (P < 0.05); the time to peak of targeted contrast ultrasound imaging is shorter than that of ordinary ultrasound imaging in the 2-, 3-, 4-, and 5-week groups with statistically significant differences (P < 0.05); there is a positive correlation between the peak intensities of targeted contrast ultrasound imaging and tumor neovascular densities of the ovarian cancer xenografts in the 2-, 3-, and 4-week group (r 2 = 0.645, r 3 = 0.668, and r 4 = 0.693, P < 0.05); there is a negative correlation between the time to peak of targeted contrast ultrasound imaging and tumor neovascular densities of the ovarian cancer xenografts in the 2-, 3-, and 4-week groups (r 2 = -0.669, r 3 = -0.692, and r 4 = -0.704, P < 0.05). Therefore, the targeted contrast-enhanced ultrasound imaging parameters have a certain correlation with tumor neovascular density of ovarian cancer xenografts in nude mice and this correlation is more significant in the early stage of ovarian cancer; hence, targeted contrast-enhanced ultrasound imaging may provide a new method, new idea, and new basis for the diagnosis of early ovarian cancer.