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1. Dendrimers for cancer immunotherapy: Avidity‐based drug delivery vehicles for effective anti‐tumor immune response

   https://doi.org/10.1002/wnan.1752  

   Rawding, Piper A. ; Bu, Jiyoon ; Wang, Jianxin ; Kim, Da Won ; Drelich, Adam J. ; Kim, Youngsoo ; Hong, Seungpyo ( August 2021 , WIREs Nanomedicine and Nanobiotechnology)

   Cancer immunotherapy, or the utilization of a patient's own immune system to treat cancer, has shifted the paradigm of cancer treatment. Despite meaningful responses being observed in multiple studies, currently available immunotherapy platforms have only proven effective to a small subset of patients. To address this, nanoparticles have been utilized as a novel carrier for immunotherapeutic drugs, achieving robust anti‐tumor effects with increased adaptive and durable responses. Specifically, dendrimer nanoparticles have attracted a great deal of scientific interest due to their versatility in various therapeutic applications, resulting from their unique physicochemical properties and chemically well‐defined architecture. This review offers a comprehensive overview of dendrimer‐based immunotherapy technologies, including their formulations, biological functionalities, and therapeutic applications. Common formulations include: (1) modulators of cytokine secretion of immune cells (adjuvants); (2) facilitators of the recognition of tumorous antigens (vaccines); (3) stimulators of immune effectors to selectively attack cells expressing specific antigens (antibodies); and (4) inhibitors of immune‐suppressive responses (immune checkpoint inhibitors). On‐going works and prospects of dendrimer‐based immunotherapies are also discussed. Overall, this review provides a critical overview on rapidly growing dendrimer‐based immunotherapy technologies and serves as a guideline for researchers and clinicians who are interested in this field.

   This article is categorized under:

   Nanotechnology Approaches to Biology > Nanoscale Systems in Biology

   Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease

   Therapeutic Approaches and Drug Discovery > Emerging Technologies

    

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2. Targeting cancer metastasis with antibody therapeutics

   https://doi.org/10.1002/wnan.1698  

   Yang, Huilin ; Kuo, Yun‐Huai ; Smith, Zion I. ; Spangler, Jamie ( January 2021 , WIREs Nanomedicine and Nanobiotechnology)

   Cancer metastasis, the spread of disease from a primary to a distal site through the circulatory or lymphatic systems, accounts for over 90% of all cancer related deaths. Despite significant progress in the field of cancer therapy in recent years, mortality rates remain dramatically higher for patients with metastatic disease versus those with local or regional disease. Although there is clearly an urgent need to develop drugs that inhibit cancer spread, the overwhelming majority of anticancer therapies that have been developed to date are designed to inhibit tumor growth but fail to address the key stages of the metastatic process: invasion, intravasation, circulation, extravasation, and colonization. There is growing interest in engineering targeted therapeutics, such as antibody drugs, that inhibit various steps in the metastatic cascade. We present an overview of antibody therapeutic approaches, both in the pipeline and in the clinic, that disrupt the essential mechanisms that underlie cancer metastasis. These therapies include classes of antibodies that indirectly target metastasis, including anti‐integrin, anticadherin, and immune checkpoint blocking antibodies, as well as monoclonal and bispecific antibodies that are specifically designed to interrupt disease dissemination. Although few antimetastatic antibodies have achieved clinical success to date, there are many promising candidates in various stages of development, and novel targets and approaches are constantly emerging. Collectively, these efforts will enrich our understanding of the molecular drivers of metastasis, and the new strategies that arise promise to have a profound impact on the future of cancer therapeutic development.

   This article is categorized under:

   Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease

    

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3. Development of an In Situ Cancer Vaccine via Combinational Radiation and Bacterial‐Membrane‐Coated Nanoparticles

   https://doi.org/10.1002/adma.201902626  

   Patel, Ravi B. ; Ye, Mingzhou ; Carlson, Peter M. ; Jaquish, Abigail ; Zangl, Luke ; Ma, Ben ; Wang, Yuyuan ; Arthur, Ian ; Xie, Ruosen ; Brown, Ryan J. ; et al ( September 2019 , Advanced Materials)

   Neoantigens induced by random mutations and specific to an individual's cancer are the most important tumor antigens recognized by T cells. Among immunologically “cold” tumors, limited recognition of tumor neoantigens results in the absence of a de novo antitumor immune response. These “cold” tumors present a clinical challenge as they are poorly responsive to most immunotherapies, including immune checkpoint inhibitors (ICIs). Radiation therapy (RT) can enhance immune recognition of “cold” tumors, resulting in a more diversified antitumor T‐cell response, yet RT alone rarely results in a systemic antitumor immune response. Therefore, a multifunctional bacterial membrane‐coated nanoparticle (BNP) composed of an immune activating PC7A/CpG polyplex core coated with bacterial membrane and imide groups to enhance antigen retrieval is developed. This BNP can capture cancer neoantigens following RT, enhance their uptake in dendritic cells (DCs), and facilitate their cross presentation to stimulate an antitumor T‐cell response. In mice bearing syngeneic melanoma or neuroblastoma, treatment with BNP+RT results in activation of DCs and effector T cells, marked tumor regression, and tumor‐specific antitumor immune memory. This BNP facilitates in situ immune recognition of a radiated tumor, enabling a novel personalized approach to cancer immunotherapy using off‐the‐shelf therapeutics.

    

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4. Modeling immune cell behavior across scales in cancer

   https://doi.org/10.1002/wsbm.1484  

   Makaryan, Sahak Z. ; Cess, Colin G. ; Finley, Stacey D. ( March 2020 , WIREs Systems Biology and Medicine)

   Detailed, mechanistic models of immune cell behavior across multiple scales in the context of cancer provide clinically relevant insights needed to understand existing immunotherapies and develop more optimal treatment strategies. We highlight mechanistic models of immune cells and their ability to become activated and promote tumor cell killing. These models capture various aspects of immune cells: (a) single‐cell behavior by predicting the dynamics of intracellular signaling networks in individual immune cells, (b) multicellular interactions between tumor and immune cells, and (c) multiscale dynamics across space and different levels of biological organization. Computational modeling is shown to provide detailed quantitative insight into immune cell behavior and immunotherapeutic strategies. However, there are gaps in the literature, and we suggest areas where additional modeling efforts should be focused to more prominently impact our understanding of the complexities of the immune system in the context of cancer.

   This article is categorized under:

   Biological Mechanisms > Cell Signaling

   Models of Systems Properties and Processes > Mechanistic Models

   Models of Systems Properties and Processes > Cellular Models

    

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5. Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma

   https://doi.org/10.1007/s00285-023-02027-y  

   Anderson, Hannah G. ; Takacs, Gregory P. ; Harris, Duane C. ; Kuang, Yang ; Harrison, Jeffrey K. ; Stepien, Tracy L. ( December 2023 , Journal of Mathematical Biology)

   Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the approximate Bayesian computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended fourier amplitude sensitivity test. Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.

    

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