Oncolytic Orf virus licenses NK cells via cDC1 to activate innate and adaptive antitumor mechanisms and extends survival in a murine model of late-stage ovarian cancer

Vloten, Jacob P. van; Matuszewska, Kathy; Minow, Mark A A; Minott, Jessica A.; Santry, Lisa A.; Pereira, Madison; Stegelmeier, Ashley A.; McAusland, Thomas M.; Klafuric, Elaine M.; Karimi, Khalil; Colasanti, Joseph; McFadden, Dennis; Petrik, Jim; Bridle, Byram W.; Wootton, Sarah K.

doi:10.1136/jitc-2021-004335

Cited by 18 publications

(18 citation statements)

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“…The advantages of these viruses include their ability to kill tumor cells directly, stimulate intratumoral inflammation, and trigger both the innate and adaptive tumor-targeting immune responses [ 10 , 11 , 12 , 13 ]. One of the OVs that has been explored includes the replication-competent poxvirus Orf virus (OrfV), which can potently kill human and murine cancer cells in vitro and has demonstrated efficacy in vivo, as observed through a reduction in tumor burden, extended survival, and enhanced antitumor immune responses [ 14 , 15 ]. The efficacy of OrfV as an anticancer therapy has been primarily attributed to the potent induction of tumoricidal natural killer (NK) and T-cell responses [ 14 , 16 , 17 ], but the contribution of neutrophils to the overall antitumor response elicited following OrfV therapy remained to be elucidated.…”

Section: Introductionmentioning

confidence: 99%

The Role of Neutrophils in Oncolytic Orf Virus-Mediated Cancer Immunotherapy

Minott

Vloten

Chan

et al. 2022

Cells

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Neutrophils are innate leukocytes with diverse effector functions that allow them to respond to pathogens rapidly. Accumulating evidence has highlighted these cells’ complex roles in the host’s response to viral infections and tumor progression. Oncolytic virotherapy is emerging as a promising treatment modality in the armamentarium of cancer therapeutics. Oncolytic viruses preferentially kill cancer cells and stimulate tumor-associated inflammation, resulting in tumor regression. Assessing the activity of individual effector cell subsets following oncolytic virotherapy is important in identifying their contribution to antitumor immunity. In this study, we investigated the role of neutrophils in oncolytic Orf-virus-mediated immunotherapy in a murine model of pulmonary melanoma metastases. The systemic administration of the Orf virus stimulated a dramatic increase in the number of leukocytes in circulation and within the tumor microenvironment, most of which were neutrophils. Analysis of tumor-burdened lungs shortly after therapy revealed significant numbers of phenotypically immature neutrophils, with the enhanced expression of molecules affiliated with activation, migration, and cytotoxicity. Neutrophils stimulated by Orf virus therapy were directly tumoricidal through tumor necrosis factor-α-mediated effects and were required for optimal antitumor efficacy following Orf virus therapy. Taken together, these data reveal neutrophils as a crucial innate effector to consider when investigating oncolytic virotherapy.

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Section: Introductionmentioning

confidence: 99%

The Role of Neutrophils in Oncolytic Orf Virus-Mediated Cancer Immunotherapy

Minott

Vloten

Chan

et al. 2022

Cells

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“…To test this protocol for detecting tumor-associated antibodies, a C57BL/6 murine model of orthotopic, syngeneic ID8 epithelial ovarian carcinoma was used as previously described ( 30 , 31 ). Sixty days following the implantation of ID8 tumor cells under the ovarian bursa, mice were injected intraperitoneally with an OV known as Orf virus (OrfV) ( 32 ).…”

Section: Resultsmentioning

confidence: 99%

Multiplex flow cytometry-based assay for quantifying tumor- and virus-associated antibodies induced by immunotherapies

et al. 2022

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Novel immunotherapies continue to be developed and tested for application against a plethora of diseases. The clinical translation of immunotherapies requires an understanding of their mechanisms. The contributions of antibodies in driving long-term responses following immunotherapies continue to be revealed given their diverse effector functions. Developing an in-depth understanding of the role of antibodies in treatment efficacy is required to optimize immunotherapies and improve the chance of successfully translating them into the clinic. However, analyses of antibody responses can be challenging in the context of antigen-agnostic immunotherapies, particularly in the context of cancers that lack pre-defined target antigens. As such, robust methods are needed to evaluate the capacity of a given immunotherapy to induce beneficial antibody responses, and to identify any therapy-limiting antibodies. We previously developed a comprehensive method for detecting antibody responses induced by antigen-agnostic immunotherapies for application in pre-clinical models of vaccinology and cancer therapy. Here, we extend this method to a high-throughput, flow cytometry-based assay able to identify and quantify isotype-specific virus- and tumor-associated antibody responses induced by immunotherapies using small sample volumes with rapid speed and high sensitivity. This method provides a valuable and flexible protocol for investigating antibody responses induced by immunotherapies, which researchers can use to expand their analyses and optimize their own treatment regimens.

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“…The tumor microenvironment is a complex ecological environment in which the interactions between tumor cells, immune cells, and non-immune cells determine the tumor progression ( Hornburg et al, 2021 ). Among them, immune cells play an important role and greatly influence the invasive and metastatic ability of tumors ( Giraldo et al, 2019 ; van Vloten et al, 2022 ). Although an increasing number of studies have focused on analyzing the prognostic features of tumors.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of the Diagnostic Characteristic Genes of Ovarian Cancer by Bioinformatics and Machine Learning

Liu

Antwi

et al. 2022

Front. Genet.

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Background: Ovarian cancer (OC) has a high mortality rate and poses a severe threat to women’s health. However, abnormal gene expression underlying the tumorigenesis of OC has not been fully understood. This study aims to identify diagnostic characteristic genes involved in OC by bioinformatics and machine learning.Methods: We utilized five datasets retrieved from the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) database, and the Genotype-Tissue Expression (GTEx) Project database. GSE12470 and GSE18520 were combined as the training set, and GSE27651 was used as the validation set A. Also, we combined the TCGA database and GTEx database as validation set B. First, in the training set, differentially expressed genes (DEGs) between OC and non-ovarian cancer tissues (nOC) were identified. Next, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were performed for functional enrichment analysis of these DEGs. Then, two machine learning algorithms, Least Absolute Shrinkage and Selector Operation (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), were used to get the diagnostic genes. Subsequently, the obtained diagnostic-related DEGs were validated in the validation sets. Then, we used the computational approach (CIBERSORT) to analyze the association between immune cell infiltration and DEGs. Finally, we analyzed the prognostic role of several genes on the KM-plotter website and used the human protein atlas (HPA) online database to analyze the expression of these genes at the protein level.Results: 590 DEGs were identified, including 276 upregulated and 314 downregulated DEGs.The Enrichment analysis results indicated the DEGs were mainly involved in the nuclear division, cell cycle, and IL−17 signaling pathway. Besides, DEGs were also closely related to immune cell infiltration. Finally, we found that BUB1, FOLR1, and PSAT1 have prognostic roles and the protein-level expression of these six genes SFPR1, PSAT1, PDE8B, INAVA and TMEM139 in OC tissue and nOC tissue was consistent with our analysis.Conclusions: We screened nine diagnostic characteristic genes of OC, including SFRP1, PSAT1, BUB1B, FOLR1, ABCB1, PDE8B, INAVA, BUB1, TMEM139. Combining these genes may be useful for OC diagnosis and evaluating immune cell infiltration.

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Oncolytic Orf virus licenses NK cells via cDC1 to activate innate and adaptive antitumor mechanisms and extends survival in a murine model of late-stage ovarian cancer

Cited by 18 publications

References 53 publications

The Role of Neutrophils in Oncolytic Orf Virus-Mediated Cancer Immunotherapy

The Role of Neutrophils in Oncolytic Orf Virus-Mediated Cancer Immunotherapy

Multiplex flow cytometry-based assay for quantifying tumor- and virus-associated antibodies induced by immunotherapies

Identification and Validation of the Diagnostic Characteristic Genes of Ovarian Cancer by Bioinformatics and Machine Learning

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