Patient-derived tumor models are attractive tools to repurpose drugs for ovarian cancer treatment: Pre-clinical updates

Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.

Oncogenic Pathways and Targeted Therapies in Ovarian Cancer

Epithelial ovarian cancer (EOC) is one of the most aggressive forms of gynaecological malignancies. Survival rates for women diagnosed with OC remain poor as most patients are diagnosed with advanced disease. Debulking surgery and platinum-based therapies are the current mainstay for OC treatment. However, and despite achieving initial remission, a significant portion of patients will relapse because of innate and acquired resistance, at which point the disease is considered incurable. In view of this, novel detection strategies and therapeutic approaches are needed to improve outcomes and survival of OC patients. In this review, we summarize our current knowledge of the genetic landscape and molecular pathways underpinning OC and its many subtypes. By examining therapeutic strategies explored in preclinical and clinical settings, we highlight the importance of decoding how single and convergent genetic alterations co-exist and drive OC progression and resistance to current treatments. We also propose that core signalling pathways such as the PI3K and MAPK pathways play critical roles in the origin of diverse OC subtypes and can become new targets in combination with known DNA damage repair pathways for the development of tailored and more effective anti-cancer treatments.

Zebrafish Avatars: Toward Functional Precision Medicine in Low-Grade Serous Ovarian Cancer

Ovarian cancer (OC) is an umbrella term for cancerous malignancies affecting the ovaries, yet treatment options for all subtypes are predominantly derived from high-grade serous ovarian cancer, the largest subgroup. The concept of "functional precision medicine" involves gaining personalized insights on therapy choice, based on direct exposure of patient tissues to drugs. This especially holds promise for rare subtypes like low-grade serous ovarian cancer (LGSOC). This study aims to establish an in vivo model for LGSOC using zebrafish embryos, comparing treatment responses previously observed in mouse PDX models, cell lines and 3D tumor models. To address this goal, a well-characterized patient-derived LGSOC cell line with the KRAS mutation c.35 G>T (p.(Gly12Val)) was used. Fluorescently labeled tumor cells were injected into the perivitelline space of 2 days' post-fertilization zebrafish embryos. At 1 day post-injection, xenografts were assessed for tumor size, followed by random allocation into treatment groups with trametinib, luminespib and trametinib + luminespib. Subsequently, xenografts were euthanized and analyzed for apoptosis and proliferation by confocal microscopy. Tumor cells formed compact tumor masses (n = 84) in vivo, with clear Ki67 staining, indicating proliferation. Zebrafish xenografts exhibited sensitivity to trametinib and luminespib, individually or combined, within a two-week period, establishing them as a rapid and complementary tool to existing in vitro and in vivo models for evaluating targeted therapies in LGSOC.

Creation and Validation of Patient-Derived Cancer Model Using Peritoneal and Pleural Effusion in Patients with Advanced Ovarian Cancer: An Early Experience

Background: The application of personalized cancer treatment based on genetic information and surgical samples has begun in the field of cancer medicine. However, a biopsy may be painful for patients with advanced diseases that do not qualify for surgical resection. Patient-derived xenografts (PDXs) are cancer models in which patient samples are transplanted into immunodeficient mice. PDXs are expected to be useful for personalized medicine. The aim of this study was to establish a PDX from body fluid (PDX-BF), such as peritoneal and pleural effusion samples, to provide personalized medicine without surgery. Methods: PDXs-BF were created from patients with ovarian cancer who had positive cytology findings based on peritoneal and pleural effusion samples. PDXs were also prepared from each primary tumor. The pathological findings based on immunohistochemistry were compared between the primary tumor, PDX, and PDX-BF. Further, genomic profiles and gene expression were evaluated using DNA and RNA sequencing to compare primary tumors, PDXs, and PDX-BF. Results: Among the 15 patients, PDX-BF was established for 8 patients (5 high-grade serous carcinoma, 1 carcinosarcoma, 1 low-grade serous carcinoma, and 1 clear cell carcinoma); the success rate was 53%. Histologically, PDXs-BF have features similar to those of primary tumors and PDXs. In particular, PDXs-BF had similar gene mutations and expression patterns to primary tumors and PDXs. Conclusions: PDX-BF reproduced primary tumors in terms of pathological features and genomic profiles, including gene mutation and expression. Thus, PDX-BF may be a potential alternative to surgical resection for patients with advanced disease.

Clinical significance of the CD98hc-CD147 complex in ovarian cancer: a bioinformatics analysis

Ovarian cancer is one of the most common malignant tumours affecting the female reproductive organs. CD147 (BSG) and CD98hc (SLC3A2) are oncogenes that form the CD98hc-CD147 complex, which regulates the proliferation, metastasis, metabolism, and cell cycle of cancer cells. The roles of the CD98hc-CD147 complex in ovarian cancer remain unclear. We analysed the expression and prognostic value of CD147 and CD98hc in ovarian cancer using the TCGA and ICGC databases. The effect of CD147 and CD98hc on the tumour immune response was analysed using the TIMER database. CD98hc was more highly expressed in normal tissues than primary tumour tissues, while CD147 was more highly expressed in primary tumour tissues than normal tissues. CD98hc expression was significantly associated with neutrophil and dendritic cell levels. CD147 and CD98hc were correlated with DNA repair, the cell cycle, and DNA replication. The CD98hc-CD147 complex could serve as a target for ovarian cancer treatment.

Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin

The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.

Comparative analysis of response to treatments and molecular features of tumor-derived organoids versus cell lines and PDX derived from the same ovarian clear cell carcinoma

BACKGROUND

In the era of personalized medicine, the establishment of preclinical models of cancer that faithfully recapitulate original tumors is essential to potentially guide clinical decisions.

METHODS

We established 7 models [4 cell lines, 2 Patient-Derived Tumor Organoids (PDTO) and 1 Patient-Derived Xenograft (PDX)], all derived from the same Ovarian Clear Cell Carcinoma (OCCC). To determine the relevance of each of these models, comprehensive characterization was performed based on morphological, histological, and transcriptomic analyses as well as on the evaluation of their response to the treatments received by the patient. These results were compared to the clinical data.

RESULTS

Only the PDX and PDTO models derived from the patient tumor were able to recapitulate the patient tumor heterogeneity. The patient was refractory to carboplatin, doxorubicin and gemcitabine, while tumor cell lines were sensitive to these treatments. In contrast, PDX and PDTO models displayed resistance to the 3 drugs. The transcriptomic analysis was consistent with these results since the models recapitulating faithfully the clinical response grouped together away from the other classical 2D cell culture models. We next investigated the potential of drugs that have not been used in the patient clinical management and we identified the HDAC inhibitor belinostat as a potential effective treatment based on PDTO response.

CONCLUSIONS

PDX and PDTO appear to be the most relevant models, but only PDTO seem to present all the necessary prerequisites for predictive purposes and could constitute relevant tools for therapeutic decision support in the context of these particularly aggressive cancers refractory to conventional treatments.

A Scalable 3D High-Content Imaging Protocol for Measuring a Drug Induced DNA Damage Response Using Immunofluorescent Subnuclear γH2AX Spots in Patient Derived Ovarian Cancer Organoids

The high morbidity rate of ovarian cancer has remained unchanged during the past four decades, partly due to a lack of understanding of disease mechanisms and difficulties in developing new targeted therapies. Defective DNA damage detection and repair is one of the hallmarks of cancer cells and is a defining characteristic of ovarian cancer. Most in vitro studies to date involve viability measurements at scale using relevant cancer cell lines; however, the translation to the clinic is often lacking. The use of patient derived organoids is closing that translational gap, yet the 3D nature of organoid cultures presents challenges for assay measurements beyond viability measurements. In particular, high-content imaging has the potential for screening at scale, providing a better understanding of the mechanism of action of drugs or genetic perturbagens. In this study we report a semiautomated and scalable immunofluorescence imaging assay utilizing the development of a 384-well plate based subnuclear staining and clearing protocol and optimization of 3D confocal image analysis for studying DNA damage dose response in human ovarian cancer organoids. The assay was validated in four organoid models and demonstrated a predictable response to etoposide drug treatment with the lowest efficacy observed in the clinically most resistant model. This imaging and analysis method can be applied to other 3D organoid and spheroid models for use in high content screening.

The Proteolytic Landscape of Ovarian Cancer: Applications in Nanomedicine

Ovarian cancer (OvCa) is one of the leading causes of mortality globally with an overall 5-year survival of 47%. The predominant subtype of OvCa is epithelial carcinoma, which can be highly aggressive. This review launches with a summary of the clinical features of OvCa, including staging and current techniques for diagnosis and therapy. Further, the important role of proteases in OvCa progression and dissemination is described. Proteases contribute to tumor angiogenesis, remodeling of extracellular matrix, migration and invasion, major processes in OvCa pathology. Multiple proteases, such as metalloproteinases, trypsin, cathepsin and others, are overexpressed in the tumor tissue. Presence of these catabolic enzymes in OvCa tissue can be exploited for improving early diagnosis and therapeutic options in advanced cases. Nanomedicine, being on the interface of molecular and cellular scales, can be designed to be activated by proteases in the OvCa microenvironment. Various types of protease-enabled nanomedicines are described and the studies that focus on their diagnostic, therapeutic and theranostic potential are reviewed.