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Abstract Background Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage I primary invasive, stage II-IV primary invasive, or secondary metastatic. Methods This retrospective cohort study used 5909 patients recruited from 1999 to 2012 for model development, and 3199 patients recruited from 2012 to 2015 for model validation. Patients were recruited at oncology referral or general centers and underwent an ultrasound examination and surgery ≤ 120 days later. We developed models using standard multinomial logistic regression (MLR), Ridge MLR, random forest (RF), XGBoost, neural networks (NN), and support vector machines (SVM). We used nine clinical and ultrasound predictors but developed models with or without CA125. Results Most tumors were benign (3980 in development and 1688 in validation data), secondary metastatic tumors were least common (246 and 172). The c-statistic (AUROC) to discriminate benign from any type of malignant tumor ranged from 0.89 to 0.92 for models with CA125, from 0.89 to 0.91 for models without. The multiclass c-statistic ranged from 0.41 (SVM) to 0.55 (XGBoost) for models with CA125, and from 0.42 (SVM) to 0.51 (standard MLR) for models without. Multiclass calibration was best for RF and XGBoost. Estimated probabilities for a benign tumor in the same patient often differed by more than 0.2 (20% points) depending on the model. Net Benefit for diagnosing malignancy was similar for algorithms at the commonly used 10% risk threshold, but was slightly higher for RF at higher thresholds. Comparing models, between 3% (XGBoost vs. NN, with CA125) and 30% (NN vs. SVM, without CA125) of patients fell on opposite sides of the 10% threshold. Conclusion Although several models had similarly good performance, individual probability estimates varied substantially.

Immune checkpoint inhibitors (ICI) have been revolutionary in the field of cancer therapy. However, their success is limited to specific indications and cancer types. Recently, the combination treatment of ICI and chemotherapy has gained more attention to overcome this limitation. Unfortunately, many clinical trials testing these combinations have provided limited success. This can partly be attributed to an inadequate choice of preclinical models and the lack of scientific rationale to select the most effective immune-oncological combination. In this review, we have analyzed the existing preclinical evidence on this topic, which is only limitedly available. Furthermore, this preclinical data indicates that besides the selection of a specific drug and dose, also the sequence or order of the combination treatment influences the study outcome. Therefore, we conclude that the success of clinical combination trials could be enhanced by improving the preclinical set up, in order to identify the optimal treatment combination and schedule to enhance the anti-tumor immunity.

A novel alpha-therapy consisting of 224Ra-labeled calcium carbonate microparticles (224Ra-CaCO3-MP) has been designed to treat micrometastatic peritoneal disease via intraperitoneal (IP) administration. This preclinical study aimed to evaluate its efficacy and tolerability when given as a single treatment or in combination with standard of care chemotherapy regimens, in a syngeneic model of ovarian cancer in immune competent mice. Female C57BL/6 mice bearing ID8-fLuc ovarian cancer were treated with 224Ra-CaCO3-MP 1 day after IP tumor cell inoculation. The activity dosages of 224Ra ranged from 14 to 39 kBq/mouse. Additionally, 224Ra-CaCO3-MP treatment was followed by either carboplatin (80 mg/kg)-pegylated liposomal doxorubicin (PLD, 1.6 mg/kg) or carboplatin (60 mg/kg)-paclitaxel (10 mg/kg) on day 14 post tumor cell inoculation. All treatments were administered via IP injections. Readouts included survival, clinical signs, and body weight development over time. There was a slight therapeutic benefit after single treatment with 224Ra-CaCO3-MP compared to the vehicle control, with median survival ratios (MSRs) ranging between 1.1 and 1.3. The sequential administration of 224Ra-CaCO3-MP with either carboplatin-paclitaxel or carboplatin-PLD indicated a synergistic effect on overall survival at certain 224Ra activities. Moreover, the combinations tested appeared well tolerated in terms of weight assessment in the first 4 weeks after treatment. Overall, this research supports the further evaluation of 224Ra-CaCO3-MP in patients with ovarian cancer. However, the most optimal chemotherapy regimen to combine with 224Ra-CaCO3-MP should be identified to fully exploit its therapeutic potential.

Chemotherapy induces a variety of immunological changes. Studying these effects can reveal opportunities for successful combining chemotherapy and immunotherapy. Immuno-chemotherapeutic combinations in ovarian cancer are currently not generating the anticipated positive effects. To date, only scattered and inconsistent information is available about the immune-induced changes by chemotherapy in ovarian cancer. In this study, we compared six common chemotherapeutics used in ovarian cancer patients (carboplatin, paclitaxel, pegylated liposomal doxorubicin, gemcitabine, carboplatin-paclitaxel and carboplatin-gemcitabine) and studied their effects on the immune system in an ovarian cancer mouse model. Mice received a single chemotherapy or vehicle injection 21 days after tumor inoculation with ID8-fluc cells. One week after therapy administration, we collected peritoneal washings for flow cytometry, serum for cytokine analysis with cytometric bead array and tumor biopsies for immunohistochemistry. Carboplatin-paclitaxel showed the most favorable profile with a decrease in immunosuppressive cells in the peritoneal cavity and an increase of interferon-gamma in serum. In contrast, carboplatin-gemcitabine seemed to promote a hostile immune environment with an increase in regulatory T-cells in tumor tissue and an increase of macrophage-inflammatory-protein-1-beta in the serum.

Novel treatment strategies are needed to provide a better prognosis for ovarian cancer. For this purpose, the current study was designed to evaluate the effects of different types of particle drug carriers on tumor response and on the tumor immune microenvironment (TME) after intraperitoneal (IP) administration in a murine tumor model. Mice with ID8-fLuc ovarian cancer were injected IP with pegylated liposomes, hydroxyapatite, polystyrene, poly(lactic-co-glycolic acid) (PLGA) and calcium carbonate (CaCO3) microparticles to evaluate the effect of the candidate carriers without drugs. Our results show that several types of microparticle drug carriers caused hyperproliferation of the tumor when injected IP, as reflected in a reduced survival or an accelerated onset of ascites. Alterations of the product formulation of CaCO3 microparticles could result in less hyperproliferation. The hyperproliferation caused by CaCO3 and PLGA was largely driven by a strong innate immune suppression. A combination with chemotherapy was not able to sufficiently counteract the tumor progression caused by the drug carriers. This research points towards the importance of evaluating a drug carrier before using it in a therapeutic setting, since drug carriers themselves can detrimentally influence tumor progression and immune status of the TME. However, it remains to be determined whether the hyperproliferation in this model will be of relevance in other cancer models or in humans.

Dendritic- cells (DCs) have received considerable attention as potential targets for the development of anticancer vaccines. DC-based anticancer vaccination relies on patient-derived DCs pulsed with a source of tumor-associated antigens (TAAs) in the context of standardized maturation-cocktails, followed by their reinfusion. Extensive evidence has confirmed that DC-based vaccines can generate TAA-specific, cytotoxic T cells. Nonetheless, clinical efficacy of DC-based vaccines remains suboptimal, reflecting the widespread immunosuppression within tumors. Thus, clinical interest is being refocused on DC-based vaccines as combinatorial partners for T cell-targeting immunotherapies. Here, we summarize the most recent preclinical/clinical development of anticancer DC vaccination and discuss future perspectives for DC-based vaccines in immuno-oncology.

The role of the innate immune system in ovarian cancer is gaining importance. The relevance of tumor-associated macrophages (TAM) is insufficiently understood. In this pilot project, comprising the immunofluorescent staining of 30 biopsies taken from 24 patients with ovarian cancer, we evaluated the presence of total TAM (cluster of differentiation (CD) 68 expression), M1 (major histocompatibility complex (MHC) II expression), and M2 (anti-mannose receptor C type 1 (MRC1) expression), and the blood vessel diameter. We observed a high M1/M2 ratio in low-grade ovarian cancer compared to high-grade tumors, more total TAM and M2 in metastatic biopsies, and a further increase in total TAM and M2 at interval debulking, without beneficial effects of bevacizumab. The blood vessel diameter was indicative for M2 tumor infiltration (Spearman correlation coefficient of 0.65). These data mainly reveal an immune beneficial environment in low-grade ovarian cancer in contrast to high-grade serous ovarian cancer, where immune suppression is not altered by neoadjuvant therapy.