Generation of a Three-Dimensional in Vitro Ovarian Cancer Co-Culture Model for Drug Screening Assays

Preclinical evaluation of the third-generation, bi-steric mechanistic target of rapamycin complex 1-selective inhibitor RMC-6272 in NF2-deficient models

Background

NF2-associated meningiomas are progressive, highly morbid, and nonresponsive to chemotherapies, highlighting the need for improved treatments. We have established aberrant activation of the mechanistic target of rapamycin (mTOR) signaling in NF2-deficient tumors, leading to clinical trials with first- and second-generation mTOR inhibitors. However, results have been mixed, showing stabilized tumor growth without shrinkage offset by adverse side effects. To address these limitations, here we explored the potential of third-generation, bi-steric mTOR complex 1 (mTORC1) inhibitors using the preclinical tool compound RMC-6272.

Methods

Employing human NF2-deficient meningioma lines, we compared mTOR inhibitors rapamycin (first-generation), INK128 (second-generation), and RMC-6272 (third-generation) using in vitro dose-response testing, cell-cycle analysis, and immunoblotting. Furthermore, the efficacy of RMC-6272 was assessed in NF2-null 3D-spheroid meningioma models, and its in vivo potential was evaluated in 2 orthotopic meningioma mouse models.

Results

Treatment of meningioma cells revealed that, unlike rapamycin, RMC-6272 demonstrated superior growth inhibitory effects, cell-cycle arrest, and complete inhibition of phosphorylated 4E-BP1 (mTORC1 readout). Moreover, RMC-6272 had a longer retention time than INK128 and inhibited the expression of several eIF4E-sensitive targets on the protein level. RMC-6272 treatment of NF2 spheroids showed significant shrinkage in size as well as reduced proliferation. Furthermore, in vivo studies in mice revealed effective blockage of meningioma growth by RMC-6272, compared with vehicle controls.

Conclusions

Our study in preclinical models of NF2 supports possible future clinical evaluation of third-generation, investigational mTORC1 inhibitors, such as RMC-5552, as a potential treatment strategy for NF2.

Patient-derived organoid culture in epithelial ovarian cancers-Techniques, applications, and future perspectives

Epithelial ovarian cancer (EOC) is a heterogeneous disease composed of different cell types with different molecular aberrations. Traditional cell lines and mice models cannot recapitulate the human tumor biology and tumor microenvironment (TME). Patient-derived organoids (PDOs) are freshly derived from patients' tissues and are then cultured with extracellular matrix and conditioned medium. The high concordance of epigenetic, genomic, and proteomic landscapes between the parental tumors and PDOs suggests that PDOs can provide more reliable results in studying cancer biology, allowing high throughput drug screening, and identifying their associated signaling pathways and resistance mechanisms. However, despite having a heterogeneity of cells in PDOs, some cells in TME will be lost during the culture process. Next-generation organoids have been developed to circumvent some of the limitations. Genetically engineered organoids involving targeted gene editing can facilitate the understanding of tumorigenesis and drug response. Co-culture systems where PDOs are cultured with different cell components like immune cells can allow research using immunotherapy which is otherwise impossible in conventional cell lines. In this review, the limitations of the traditional in vitro and in vivo assays, the use of PDOs, the challenges including some tips and tricks of PDO generation in EOC, and the future perspectives, will be discussed.

The response and resistance to drugs in ovarian cancer cell lines in 2D monolayers and 3D spheroids

Ovarian cancer is the most common type of gynecologic cancer. One of the leading causes of high mortality is chemoresistance, developed primarily or during treatment. Different mechanisms of drug resistance appear at the cellular and cancer tissue organization levels. We examined the differences in response to the cytotoxic drugs CIS, MTX, DOX, VIN, PAC, and TOP using 2D (two-dimensional) and 3D (three-dimensional) culture methods. We tested the drug-sensitive ovarian cancer cell line W1 and established resistant cell lines to appropriate cytotoxic drugs. The following qualitative and quantitative methods were used to assess: 1) morphology - inverted microscope and hematoxylin & eosin staining; 2) viability - MTT assay; 3) gene expression - a quantitative polymerase chain reaction; 4) identification of proteins - immunohistochemistry, and immunofluorescence. Our results indicate that the drug-sensitive and drug-resistant cells cultured in 3D conditions exhibit stronger resistance than the cells cultured in 2D conditions. A traditional 2D model shows that drug resistance of cancer cells is caused mainly by changes in the expression of genes encoding ATP-binding cassette transporter proteins, components of the extracellular matrix, "new" established genes related to drug resistance in ovarian cancer cell lines, and universal marker of cancer stem cells. Whereas in a 3D model, the drug resistance in spheroids can be related to other mechanisms such as the structure of the spheroid (dense or loose), the cell type (necrotic, quiescent, proliferating cells), drug concentrations or drug diffusion into the dense cellular/ECM structure.

Novel Ex Vivo Models of Epithelial Ovarian Cancer: The Future of Biomarker and Therapeutic Research

Epithelial ovarian cancer (EOC) is a heterogenous disease associated with variations in presentation, pathology and prognosis. Advanced EOC is typified by frequent relapse and a historical 5-year survival of less than 30% despite improvements in surgical and systemic treatment. The advent of next generation sequencing has led to notable advances in the field of personalised medicine for many cancer types. Success in achieving cure in advanced EOC has however been limited, although significant prolongation of survival has been demonstrated. Development of novel research platforms is therefore necessary to address the rapidly advancing field of early diagnostics and therapeutics, whilst also acknowledging the significant tumour heterogeneity associated with EOC. Within available tumour models, patient-derived organoids (PDO) and explant tumour slices have demonstrated particular promise as novel ex vivo systems to model different cancer types including ovarian cancer. PDOs are organ specific 3D tumour cultures that can accurately represent the histology and genomics of their native tumour, as well as offer the possibility as models for pharmaceutical drug testing platforms, offering timing advantages and potential use as prospective personalised models to guide clinical decision-making. Such applications could maximise the benefit of drug treatments to patients on an individual level whilst minimising use of less effective, yet toxic, therapies. PDOs are likely to play a greater role in both academic research and drug development in the future and have the potential to revolutionise future patient treatment and clinical trial pathways. Similarly, ex vivo tumour slices or explants have also shown recent renewed promise in their ability to provide a fast, specific, platform for drug testing that accurately represents in vivo tumour response. Tumour explants retain tissue architecture, and thus incorporate the majority of tumour microenvironment making them an attractive method to re-capitulate in vivo conditions, again with significant timing and personalisation of treatment advantages for patients. This review will discuss the current treatment landscape and research models for EOC, their development and new advances towards the discovery of novel biomarkers or combinational therapeutic strategies to increase treatment options for women with ovarian cancer.

Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine

Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.

Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology

Among gynecologic malignancies, ovarian cancer (OC) has the poorest survival rate, and its clinical management remains challenging due to the high rate of recurrence and chemoresistance. Improving survival for these patients is critical, although this requires the ability to translate preclinical studies to actual patient care: bench to bedside and back. Our objective was to develop a preclinical model that accurately represents tumor biology and its microenvironment. We utilized SKOV-3, OVCAR-8, and CS-99 cell lines to show that this model was suitable for in vitro assessment of cell proliferation. We tested OC cells independently and in co-culture with cancer associated fibroblasts (CAFs) or immune cells. Additionally, we used patient-derived ovarian carcinoma and carcinosarcoma samples to show that the system maintains the histologic morphology of the primary tissue after 7 days. Moreover, we tested the response to chemotherapy using both cell lines and patient-derived tumor specimens and confirmed that cell death was significantly higher in the treated group compared to the vehicle group. Finally, we immune profiled the 3-D model containing patient tissue after several days in the bioreactor system and revealed that the immune populations are still present. Our data suggest that this model is a suitable preclinical model to aid in research that will ultimately impact the treatment of patients with gynecologic cancer.