The mutant form of the GTPase KRAS is a key driver of pancreatic cancer but remains a challenging therapeutic target. Exosomes are extracellular vesicles generated by all cells, and are naturally present in the blood. Here we show that enhanced retention of exosomes, compared to liposomes, in the circulation of mice is likely due to CD47-mediated protection of exosomes from phagocytosis by monocytes and macrophages. Exosomes derived from normal fibroblast-like mesenchymal cells were engineered to carry short interfering RNA or short hairpin RNA specific to oncogenic KrasG12D, a common mutation in pancreatic cancer. Compared to liposomes, the engineered exosomes (known as iExosomes) target oncogenic KRAS with an enhanced efficacy that is dependent on CD47, and is facilitated by macropinocytosis. Treatment with iExosomes suppressed cancer in multiple mouse models of pancreatic cancer and significantly increased overall survival. Our results demonstrate an approach for direct and specific targeting of oncogenic KRAS in tumours using iExosomes.

Exosomes facilitate therapeutic targeting of oncogenic KRAS in pancreatic cancer

Immunotherapy is currently the most rapidly advancing area of clinical oncology, and provides the unprecedented opportunity to effectively treat, and even cure, several previously untreatable malignancies. A growing awareness exists of the fact that the success of chemotherapy and radiotherapy, in which the patient's disease can be stabilized well beyond discontinuation of treatment (and occasionally is cured), also relies on the induction of a durable anticancer immune response. Indeed, the local immune infiltrate undergoes dynamic changes that accompany a shift from a pre-existing immune response to a therapy-induced immune response. As a result, the immune contexture, which is determined by the density, composition, functional state and organization of the leukocyte infiltrate of the tumour, can yield information that is relevant to prognosis, prediction of a treatment response and various other pharmacodynamic parameters. Several complementary technologies can be used to explore the immune contexture of tumours, and to derive biomarkers that could enable the adaptation of individual treatment approaches for each patient, as well as monitoring a response to anticancer therapies.

The immune contexture in cancer prognosis and treatment

New insights into cancer immunoediting and its three component phases — elimination, equilibrium and escape

Iterative model-building, structure refinement, and density modification with the PHENIX AutoBuild Wizard Thomas C. Terwilliger a* , Ralf W. Grosse-Kunstleve b , Pavel V. Afonine b , Nigel W. Moriarty b , Peter Zwart b , Li-Wei Hung a , Randy J. Read c , Paul D. Adams b* a b Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA Lawrence Berkeley National Laboratory, One Cyclotron Road, Bldg 64R0121, Berkeley, CA 94720, USA. c Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK. * Email: terwill@lanl.gov or PDAdams@lbl.gov Running title: The PHENIX AutoBuild Wizard Abstract The PHENIX AutoBuild Wizard is a highly automated tool for iterative model- building, structure refinement and density modification using RESOLVE or TEXTAL model- building, RESOLVE statistical density modification, and phenix.refine structure refinement. Recent advances in the AutoBuild Wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model completion algorithms, and automated solvent molecule picking. Model completion algorithms in the AutoBuild Wizard include loop-building, crossovers between chains in different models of a structure, and side-chain optimization. The AutoBuild Wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 A to 3.2 A, resulting in a mean R-factor of 0.24 and a mean free R factor of 0.29. The R-factor of the final model is dependent on the quality of the starting electron density, and relatively independent of resolution. Keywords: Model building; model completion; macromolecular models; Protein Data Bank; structure refinement; PHENIX Introduction Iterative model-building and refinement is a powerful approach to obtaining a complete and accurate macromolecular model. The approach consists of cycles of building an atomic model based on an electron density map for a macromolecular structure, refining the structure, using the refined structure as a basis for improving the map, and building a new model. This type of approach has been carried out in a semi-automated fashion for many years, with manual model-building iterating with automated refinement (Jensen, 1997). More recently, with the development first of ARP/wARP (Perrakis et al., 1999), and later other procedures including RESOLVE iterative model-building and refinement (Terwilliger,

Iterative model-building, structure refinement, and density modification with the PHENIX AutoBuild Wizard

Macrophages are critical mediators of tissue homeostasis, with tumours distorting this proclivity to stimulate proliferation, angiogenesis and metastasis. This had led to an interest in targeting macrophages in cancer, and preclinical studies have demonstrated efficacy across therapeutic modalities and tumour types. Much of the observed efficacy can be traced to the suppressive capacity of macrophages, driven by microenvironmental cues such as hypoxia and fibrosis. As a result, tumour macrophages display an ability to suppress T cell recruitment and function as well as to regulate other aspects of tumour immunity. With the increasing impact of cancer immunotherapy, macrophage targeting is now being evaluated in this context. Here, we discuss the results of clinical trials and the future of combinatorial immunotherapy. In this Review, DeNardo and Ruffell describe how macrophages shape local immune responses in the tumour microenvironment to both suppress and promote immunity to tumours. The authors also discuss the potential of targeting tumour-associated macrophages to enhance antitumour immune responses.

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Macrophages as regulators of tumour immunity and immunotherapy

CD47, a "don't eat me" signal for phagocytic cells, is expressed on the surface of all human solid tumor cells Analysis of patient tumor and matched adjacent normal (nontumor) tissue revealed that CD47 is overexpressed on cancer cells CD47 mRNA expression levels correlated with a decreased probability of survival for multiple types of cancer CD47 is a ligand for SIRPα, a protein expressed on macrophages and dendritic cells In vitro, blockade of CD47 signaling using targeted monoclonal antibodies enabled macrophage phagocytosis of tumor cells that were otherwise protected Administration of anti-CD47 antibodies inhibited tumor growth in orthotopic immunodeficient mouse xenotransplantation models established with patient tumor cells and increased the survival of the mice over time Anti-CD47 antibody therapy initiated on larger tumors inhibited tumor growth and prevented or treated metastasis, but initiation of the therapy on smaller tumors was potentially curative The safety and efficacy of targeting CD47 was further tested and validated in immune competent hosts using an orthotopic mouse breast cancer model These results suggest all human solid tumor cells require CD47 expression to suppress phagocytic innate immune surveillance and elimination These data, taken together with similar findings with other human neoplasms, show that CD47 is a commonly expressed molecule on all cancers, its function to block phagocytosis is known, and blockade of its function leads to tumor cell phagocytosis and elimination CD47 is therefore a validated target for cancer therapies

https://www.pnas.org/content/pnas/109/17/6662.full.pdf

The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors

Cancer immunotherapy has emerged as a promising therapeutic intervention. However, complete and durable responses are only seen in a fraction of patients who have cancer. A key factor that limits therapeutic success is the infiltration of tumors by cells of the myeloid lineage. The inhibitory receptor signal regulatory protein-α (SIRPα) is a myeloid-specific immune checkpoint that engages the “don’t eat me” signal CD47 expressed on tumors and normal tissues. We therefore developed the monoclonal antibody KWAR23, which binds human SIRPα with high affinity and disrupts its binding to CD47. Administered by itself, KWAR23 is inert, but given in combination with tumor-opsonizing monoclonal antibodies, KWAR23 greatly augments myeloid cell-dependent killing of a collection of hematopoietic and nonhematopoietic human tumor-derived cell lines. Following KWAR23 antibody treatment in a human SIRPA knockin mouse model, both neutrophils and macrophages infiltrate a human Burkitt’s lymphoma xenograft and inhibit tumor growth, generating complete responses in the majority of treated animals. We further demonstrate that a bispecific anti-CD70/SIRPα antibody outperforms individually delivered antibodies in specific types of cancers. These studies demonstrate that SIRPα blockade induces potent antitumor activity by targeting multiple myeloid cell subsets that frequently infiltrate tumors. Thus, KWAR23 represents a promising candidate for combination therapy.

https://www.pnas.org/content/pnas/114/49/E10578.full.pdf

Tejaswitha J. Naik

Papers

The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors

Anti-SIRPα antibody immunotherapy enhances neutrophil and macrophage antitumor activity.