Exploring the Potential of Drug Response Assays for Precision Medicine in Ovarian Cancer

Successful post-incomplete resection management of gastrointestinal stromal tumor using imatinib based on adenosine triphosphate-based tumor sensitivity assay in a dog

Gastrointestinal stromal tumors arising from gastric cardia are uncommon in dogs. A few studies have shown the effectiveness of tyrosine kinase inhibitors in the treatment of canine gastrointestinal stromal tumors, but no standardized protocols are currently available. An 11-year-old spayed female Maltese dog was diagnosed with a gastrointestinal stromal tumor using histopathological and immunohistochemical analyses. An adenosine triphosphate-based tumor chemosensitivity assay revealed that imatinib at lower concentrations had a stronger inhibitory effect than toceranib. Based on the results of the assay, the dog was treated with imatinib after surgery. After 28 mo of therapy, there was no recurrence of the tumor. Key clinical message: Adenosine triphosphate-based tumor chemosensitivity assays may help clinicians to select appropriate postoperative chemotherapeutic drugs for incompletely resected gastrointestinal stromal tumors in dogs.

The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients

Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DET3Ct (Drug Efficacy Testing in 3D Cultures), where the response of patient cells to drugs and drug combinations are quantified with live-cell imaging. We demonstrate the delivery of individual drug sensitivity profiles in 20 samples from 16 patients with ovarian cancer in both 2D and 3D culture formats, achieving over 90% success rate in providing results six days after operation. In this cohort all patients received carboplatin. The carboplatin sensitivity scores were significantly different for patients with a progression free interval (PFI) less than or equal to 12 months and those with more than 12 months (p < 0.05). We find that the 3D culture format better retains proliferation and characteristics of the in vivo setting. Using the DET3Ct platform we evaluate 27 tailored combinations with results available 10 days after operation. Notably, carboplatin and A-1331852 (Bcl-xL inhibitor) showed an additive effect in four of eight OC samples tested, while afatinib and A-1331852 led to synergy in five of seven OC models. In conclusion, our 3D DET3Ct platform can rapidly define potential, clinically relevant data on efficacy of existing drugs in OC for precision medicine purposes, as well as provide insights on emerging drugs and drug combinations that warrant testing in clinical trials.

Current Trends on Bioengineering Approaches for Ovarian Microenvironment Reconstruction

Ovarian tissue has a unique microarchitecture and a complex cellular and molecular dynamics that are essential for follicular survival and development. Due to this great complexity, several factors may lead to ovarian insufficiency, and therefore to systemic metabolic disorders and female infertility. Techniques currently used in the reproductive clinic such as oocyte cryopreservation or even ovarian tissue transplant, although effective, have several limitations, which impair their wide application. In this scenario, mimetic ovarian tissue reconstruction comes as an innovative alternative to develop new methodologies for germ cells preservation and ovarian functions restoration. The ovarian extracellular matrix (ECM) is crucial for oocyte viability maintenance, once it acts actively in folliculogenesis. One of the key components of ovarian bioengineering is biomaterials application that mimics ECM and provides conditions for cell anchorage, proliferation, and differentiation. Therefore, this review aims at describing ovarian tissue engineering approaches and listing the main limitations of current methods for preservation and reestablishment of ovarian fertility. In addition, we describe the main elements that structure this study field, highlighting the main advances and the challenges to overcome to develop innovative methodologies to be applied in reproductive medicine. Impact Statement This review presents the main advances in the application of tissue bioengineering in the ovarian tissue reconstruction to develop innovative solutions for ovarian fertility reestablishment.

Therapy for Recurrent High-Grade Epithelial Ovarian Cancer—The Current Status and Future Trends

Ovarian malignancy is the seventh most frequently diagnosed cancer among women. The most common type is epithelial ovarian cancer. Several subtypes with distinct biological and molecular properties exist, and there is inconsistency in availability of and access to different modalities of treatment. The standard first-line management is combining surgery and platinum-based chemotherapy. Most of them are diagnosed at an advanced stage due to which they have poor outcomes. The existing screening tests have a low predictive value. Even with the best available upfront treatment, high rates of recurrences are observed. As a result, there have been major advances in the treatment of recurrences with the development of anti-angiogenic agents and PARP inhibitors. It has led to the improvement in survival and quality of life among the relapsed epithelial ovarian cancers. This review is focused on the management of recurrent epithelial ovarian cancers and future directions based on current evidence. The application of a personalized and structured approach will meaningfully bring changes in the paradigm of care in these groups of patients.

Interpatient Heterogeneity in Drug Response and Protein Biomarker Expression of Recurrent Ovarian Cancer

Recurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. A variety of guideline-recommended second-line therapies are available, but they frequently result in trial-and-error treatment. Alterations and adjustments are common in the treatment of recurrent ovarian cancer. The drug response of 30 lesions obtained from 22 relapsed ovarian cancer patients to different chemotherapeutic and molecular agents was analyzed with the patient-derived ovarian-cancer spheroid model. The profile of druggable biomarkers was immunohistochemically assessed. The second-line combination therapy of carboplatin with gemcitabine was significantly superior to the combination of carboplatin with PEGylated liposomal doxorubicin (p < 0.0001) or paclitaxel (p = 0.0007). Except for treosulfan, all nonplatinum treatments tested showed a lesser effect on tumor spheroids compared to that of platinum-based therapies. Treosulfan showed the highest efficacy of all nonplatinum agents, with significant advantage over vinorelbine (p < 0.0001) and topotecan (p < 0.0001), the next best agents. The comparative testing of a variety of treatment options in the ovarian-cancer spheroid model resulted in the identification of more effective regimens for 30% of patients compared to guideline-recommended therapies. Recurrent cancers obtained from different patients revealed profound interpatient heterogeneity in the expression pattern of druggable protein biomarkers. In contrast, different lesions obtained from the same patient revealed a similar drug response and biomarker expression profile. Biological heterogeneity observed in recurrent ovarian cancers might explain the strong differences in the clinical drug response of these patients. Preclinical drug testing and biomarker profiling in the ovarian-cancer spheroid model might help in optimizing treatment management for individual patients.

Tumor spheroids and organoids as preclinical model systems

The generation of three-dimensional (3D) cancer models is a novel and fascinating development in the study of personalized medicine and tumor-specific drug delivery. In addition to the classical two-dimensional (2D) adherent cell culture models, 3D spheroid and organoid cancer models that mimic the microenvironment of cancer tissue are emerging as an important preclinical model system. 3D cancer models form, similar to cancer, multiple cell-cell and cell-extracellular matrix interactions and activate different cellular cascades/pathways, like proliferation, quiescence, senescence, and necrotic or apoptotic cell death. Further, it is possible to analyze genetic variations and mutations, the microenvironment of cell-cell interactions, and the uptake of therapeutics and nanoparticles in nanomedicine. Important is also the analysis of cancer stem cells (CSCs), which could play key roles in resistance to therapy and cancer recurrence. Tumor spheroids can be generated from one tumor-derived cell line or from co-culture of two or more cell lines. Tumor organoids can be derived from tumors or may be generated from CSCs that differentiate into multiple facets of cancerous tissue. Similarly, tumorspheres can be generated from a single CSC. By transplanting spheroids and organoids into immune-deficient mice, patient-derived xenografts can serve as a preclinical model to test therapeutics in vivo. Although the handling and analysis of 3D tumor spheroids and organoids is more complex, it will provide insights into various cancer processes that cannot be provided by 2D culture. Here a short overview of 3D tumor systems as preclinical models is provided.

Analogs of a Natural Peptaibol Exert Anticancer Activity in Both Cisplatin- and Doxorubicin-Resistant Cells and in Multicellular Tumor Spheroids

Peptaibols, by disturbing the permeability of phospholipid membranes, can overcome anticancer drug resistance, but their natural hydrophobicity hampers their administration. By a green peptide synthesis protocol, we produced two water-soluble analogs of the peptaibol trichogin GA IV, termed K6-Lol and K6-NH2. To reduce production costs, we successfully explored the possibility of changing the naturally occurring 1,2-aminoalcohol leucinol to a C-terminal amide. Peptaibol activity was evaluated in ovarian cancer (OvCa) and Hodgkin lymphoma (HL) cell lines. Peptaibols exerted comparable cytotoxic effects in cancer cell lines that were sensitive—and had acquired resistance—to cisplatin and doxorubicin, as well as in the extrinsic-drug-resistant OvCa 3-dimensional spheroids. Peptaibols, rapidly taken up by tumor cells, deeply penetrated and killed OvCa-spheroids. They led to cell membrane permeabilization and phosphatidylserine exposure and were taken up faster by cancer cells than normal cells. They were resistant to proteolysis and maintained a stable helical structure in the presence of cancer cells. In conclusion, these promising results strongly point out the need for further preclinical evaluation of our peptaibols as new anticancer agents.

Gynecology Meets Big Data in the Disruptive Innovation Medical Era: State-of-Art and Future Prospects

Tremendous scientific and technological achievements have been revolutionizing the current medical era, changing the way in which physicians practice their profession and deliver healthcare provisions. This is due to the convergence of various advancements related to digitalization and the use of information and communication technologies (ICTs)—ranging from the internet of things (IoT) and the internet of medical things (IoMT) to the fields of robotics, virtual and augmented reality, and massively parallel and cloud computing. Further progress has been made in the fields of addictive manufacturing and three-dimensional (3D) printing, sophisticated statistical tools such as big data visualization and analytics (BDVA) and artificial intelligence (AI), the use of mobile and smartphone applications (apps), remote monitoring and wearable sensors, and e-learning, among others. Within this new conceptual framework, big data represents a massive set of data characterized by different properties and features. These can be categorized both from a quantitative and qualitative standpoint, and include data generated from wet-lab and microarrays (molecular big data), databases and registries (clinical/computational big data), imaging techniques (such as radiomics, imaging big data) and web searches (the so-called infodemiology, digital big data). The present review aims to show how big and smart data can revolutionize gynecology by shedding light on female reproductive health, both in terms of physiology and pathophysiology. More specifically, they appear to have potential uses in the field of gynecology to increase its accuracy and precision, stratify patients, provide opportunities for personalized treatment options rather than delivering a package of “one-size-fits-it-all” healthcare management provisions, and enhance its effectiveness at each stage (health promotion, prevention, diagnosis, prognosis, and therapeutics).

Polymeric Nanoparticle Delivery of Combination Therapy with Synergistic Effects in Ovarian Cancer

Treatment of ovarian cancer is challenging due to late stage diagnosis, acquired drug resistance mechanisms, and systemic toxicity of chemotherapeutic agents. Combination chemotherapy has the potential to enhance treatment efficacy by activation of multiple downstream pathways to overcome drug resistance and reducing required dosages. Sequence of delivery and the dosing schedule can further enhance treatment efficacy. Formulation of drug combinations into nanoparticles can further enhance treatment efficacy. Due to their versatility, polymer-based nanoparticles are an especially promising tool for clinical translation of combination therapies with tunable dosing schedules. We review polymer nanoparticle (e.g., micelles, dendrimers, and lipid nanoparticles) carriers of drug combinations formulated to treat ovarian cancer. In particular, the focus on this review is combinations of platinum and taxane agents (commonly used first line treatments for ovarian cancer) combined with other small molecule therapeutic agents. In vitro and in vivo drug potency are discussed with a focus on quantifiable synergistic effects. The effect of drug sequence and dosing schedule is examined. Computational approaches as a tool to predict synergistic drug combinations and dosing schedules as a tool for future nanoparticle design are also briefly discussed.

In Ovarian Cancer Multicellular Spheroids, Platelet Releasate Promotes Growth, Expansion of ALDH+ and CD133+ Cancer Stem Cells, and Protection against the Cytotoxic Effects of Cisplatin, Carboplatin and Paclitaxel

A high platelet count is associated with a poor prognosis in ovarian cancer (OvCa). Despite good clinical responses with platinating agents in combination with taxanes, numerous OvCa patients relapse due to chemotherapy resistance. Here, we report that treatment of OvCa cells A2780, OVCAR5 and MDAH with releasate from activated platelets (PR) promoted multicellular tumor spheroid (MCTS) formation. These OvCa-MCTSs had increased percentages of CD133+ and aldehyde dehydrogenase (ALDH)+ cells, bona fide markers of OvCa cancer stem cells (CSCs). PR increased OVCAR5- and MDAH-MCTS viability and decreased the cytotoxic and pro-apoptotic effects of paclitaxel, cisplatin and carboplatin. PR increased the volume of spontaneously formed OVCAR8-MCTSs and counteracted their size reduction due to cisplatin, carboplatin and paclitaxel treatment. PR promoted the survival of ALDH+ and CD133+ OvCa cells during cisplatin, carboplatin and paclitaxel treatment. In conclusion, molecules and growth factors released by activated platelets (EGF, PDGF, TGF-β, IGF and CCL5) may protect tumor cells from chemotherapy by promoting the expansion of ALDH+ and CD133+ OvCa-CSCs, favoring drug resistance and tumor relapse.