Preclinical evaluation of cancer immune therapy using patient-derived tumor antigen-specific T cells in a novel xenograft platform.

Objectives: With a rapidly growing list of candidate immune-based cancer therapeutics, there is a critical need to generate highly reliable animal models to preclinically evaluate the efficacy of emerging immune-based therapies, facilitating successful clinical translation. Our aim was to design and validate a novel Methods: Tumor xenografts are established rapidly in the greater omentum of globally immunodeficient NOD- Results: The tumors progress rapidly and disseminate in the mice unless patient-derived tumor-specific T cells are introduced. An initial T cell-mediated tumor arrest is later followed by a tumor escape, which correlates with the upregulation of the checkpoint molecules programmed cell death-1 (PD-1) and lymphocyte-activation gene 3 (LAG3) on T cells. Treatment with immune-based therapies that target these checkpoints, such as anti-PD-1 antibody (nivolumab) or interleukin-12 (IL-12), prevented or delayed the tumor escape. Furthermore, IL-12 treatment suppressed PD-1 and LAG3 upregulation on T cells. Conclusion: Together, these results validate the X-mouse model and establish its potential to preclinically evaluate the therapeutic efficacy of immune-based therapies

Novel phosphatidylserine-binding molecule enhances antitumor T-cell responses by targeting immunosuppressive exosomes in human tumor microenvironments.

BACKGROUND: The human tumor microenvironment (TME) is a complex and dynamic milieu of diverse acellular and cellular components, creating an immunosuppressive environment, which contributes to tumor progression. We have previously shown that phosphatidylserine (PS) expressed on the surface of exosomes isolated from human TMEs is causally linked to T-cell immunosuppression, representing a potential immunotherapeutic target. In this study, we investigated the effect of ExoBlock, a novel PS-binding molecule, on T-cell responses in the TME. METHODS: We designed and synthesized a new compound, (ZnDPA) RESULTS: ExoBlock was able to bind PS with high avidity and was found to consistently and significantly block the immunosuppressive activity of human ovarian tumor and melanoma-associated exosomes in vitro. ExoBlock was also able to significantly enhance T cell-mediated tumor suppression in vivo in both the X-mouse and the OTX model. In the X-mouse model, ExoBlock suppressed tumor recurrence in a T cell-dependent manner. In the OTX model, ExoBlock treatment resulted in an increase in the number as well as function of CD4 and CD8 T cells in the TME, which was associated with a reduction in tumor burden and metastasis, as well as in the number of circulating PS+ exosomes in tumor-bearing mice. CONCLUSION: Our results establish that targeting exosomal PS in TMEs with ExoBlock represents a promising strategy to enhance antitumor T-cell responses

Structuring QoS-Supporting Services with Smart Proxies

While middleware platforms have been established in best-effort environments nowadays, support for QoS-sensitive services is still found lacking. More specifically, due to the high diversity of QoS-requirements, the abstractions provided for QoS-unaware services cannot be maintained and the developer has to face the difficulties of low-level networking in heterogeneous environments again. In this paper, we therefore propose the notion of smart proxies as an effective means for making the use of QoS-sensitive services for the client-application developer as comfortable as the use of QoS-unaware services. This is achieved without imposing restrictions on the internal mechanisms and protocols used by an QoS-sensitive service to guarantee an agreed on level of QoS. Basically, smart proxies encapsulate service-specific code which is downloaded dynamically to the client during binding establishment. The benefits of this model are discussed in general and exemplified in a case study

Construction and Execution of Adaptable Applications Using an Aspect-Oriented and Model Driven Approach

Abstract. Constructing and executing distributed applications that can adapt to their current operating context, in order to maintain or enhance Quality of Ser-vice (QoS) attribute levels, are complex tasks. Managing multiple, interacting QoS features is particularly difficult since these features tend to be distributed across the system and tangled with other features. The crosscutting nature of QoS features can make them difficult to evolve, and it can make it complicated to dynamically optimize with respect to provided QoS during execution. Fur-thermore, it complicates efficient construction of application variants that differ in their QoS characteristics to suit various execution contexts. This paper pre-sents an aspect-oriented and model driven approach for constructing and a QoS-aware middleware for execution of QoS-sensitive applications. Aspect-oriented modeling techniques are used to separate QoS features from primary applica-tion logic, and for efficient specification of alternative application variants. Model driven engineering techniques are used to derive run-time representa-tions of application variants from platform independent models. The developed middleware chooses the best variant according to the current operating context and the available resources.

Flexible and Adaptive Control of Real-Time Distributed Object Computing Middleware

. Next-generation distributed systems have growing demands for real-time quality of service (QoS), flexibility, and control over the often unpredictable environments in which they are deployed. These demands have been hard to achieve simultaneously. For instance, systems have historically either been real-time, which meant that they were highly-tuned, specialpurpose, and fragile, or they were flexible, thereby incurring performance penalties that made it hard to achieve stringent QoS requirements. Achieving both sets of demands simultaneously requires distributed object computing (DOC) middleware that supports dynamic and layered resource management, automated reconfiguration, dynamic scheduling, and application-level interfaces for control and adaptation. This paper provides three contributions to the study of adaptive real-time middleware for distributed and embedded systems. First, it describes advances in Object Request Broker (ORB) technology that can support stringent real-time..

Changes in ovarian tumor cell number, tumor vasculature, and T cell function monitored in vivo using a novel xenograft model.

Despite an initial response to chemotherapy, most patients with ovarian cancer eventually progress and succumb to their disease. Understanding why effector T cells that are known to infiltrate the tumor do not eradicate the disease after cytoreduction is critically important to the development of novel therapeutic strategies to augment tumor immunity and improve patient outcomes. Such studies have been hampered by the lack of a suitable in vivo model. We report here a simple and reliable model system in which ovarian tumor cell aggregates implanted intraperitoneally into severely immunodeficient NSG mice establish tumor microenvironments within the omentum. The rapid establishment of tumor xenografts within this small anatomically well-defined site enables the recovery, characterization, and quantification of tumor and tumor-associated T cells. We validate here the ability of the omental tumor xenograft (OTX) model to quantify changes in tumor cell number in response to therapy, to quantify changes in the tumor vasculature, and to demonstrate and study the immunosuppressive effects of the tumor microenvironment. Using the OTX model, we show that the tumor-associated T cells originally present within the tumor tissues are anergic and that fully functional autologous T cells injected into tumor-bearing mice localize within the tumor xenograft. The transferred T cells remain functional for up to 3 days within the tumor microenvironment but become unresponsive to activation after 7 days. The OTX model provides for the first time the opportunity to study in vivo the cellular and molecular events contributing to the arrest in T cell function in human ovarian tumors. Cancer Immun 2013 May 13; 13:11