BackgroundPatients with rare cancers represent 55% of all gynecological malignancies and have poor survival outcomes due to limited treatment options. Combination immunotherapy with the anti-programmed cell death protein 1 (anti-PD-1) antibody nivolumab and the anti-cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) antibody ipilimumab has demonstrated significant clinical efficacy across a range of common malignancies, justifying evaluation of this combination in rare gynecological cancers.MethodsThis multicenter phase II study enrolled 43 patients with advanced rare gynecological cancers. Patients received induction treatment with nivolumab and ipilimumab at a dose of 3 mg/kg and 1 mg/kg, respectively, every 3 weeks for four doses. Treatment was continued with nivolumab monotherapy at 3 mg/kg every 2 weeks until disease progression or a maximum of 2 years. The primary endpoint was the proportion of patients with disease control at week 12 (complete response, partial response or stable disease (SD) by Response Evaluation Criteria In Solid Tumor V.1.1). Exploratory evaluations correlated clinical outcomes with tumor programmed death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB).ResultsThe objective response rate in the radiologically evaluable population was 36% (12/33 patients) and in the intention-to-treat population was 28% (12/43 patients), with additional 7 patients obtaining SD leading to a disease control rate of 58% and 44%, respectively. Durable responses were seen across a range of tumor histologies. Thirty-one (72%) patients experienced an immune-related adverse event (irAE) with a grade 3/4 irAE observed in seven (16%) patients. Response rate was higher among those patients with baseline PD-L1 expression (≥1% on tumor cells) but was independent of TMB.ConclusionsIpilimumab and nivolumab combination treatment has significant clinical activity with a favorable safety profile across a range of advanced rare gynecological malignancies and warrants further investigation in these tumor types.

Ovarian cancers include several disease subtypes and patients often present with advanced metastatic disease and a poor prognosis. New biomarkers for early diagnosis and targeted therapy are, therefore, urgently required. This study uses antibodies produced locally in tumor-draining lymph nodes (ASC probes) of individual ovarian cancer patients to screen two separate protein microarray platforms and identify cognate tumor antigens. The resulting antigen profiles were unique for each individual cancer patient and were used to generate a 50-antigen custom microarray. Serum from a separate cohort of ovarian cancer patients encompassing four disease subtypes was screened on the custom array and we identified 28.8% of all ovarian cancers, with a higher sensitivity for mucinous (50.0%) and serous (40.0%) subtypes. Combining local and circulating antibodies with high-density protein microarrays can identify novel, patient-specific tumor-associated antigens that may have diagnostic, prognostic or therapeutic uses in ovarian cancer.

The Bennati-Drăgulescu-Yakovenko (BDY) game is an agent-based simple exchange game that models a basic economic system. The BDY game results in the agents’ wealth following a Boltzmann-Gibbs distribution. In other words, the result of the game is many “poor” agents and few “wealthy” agents. In this paper, we apply several tax and redistribution models to study their effect on the population’s wealth distribution by computing the resulting Gini coefficient of the system. We find that income taxes, both flat and progressive, that evenly redistributed taxed monies do little to change the Gini coefficient from the Boltzmann-Gibbs distribution. However, income taxes that are redistributed to the poorest agents can significantly lower the Gini coefficient, resulting in a more evenly distributed wealth distribution. Furthermore, we find that a very small wealth tax can lead to significant decreases in the Gini coefficient.