Next Article in Journal
The Optimization Design of Macrophage Membrane Camouflaging Liposomes for Alleviating Ischemic Stroke Injury through Intranasal Delivery
Next Article in Special Issue
Altered Glycolysis, Mitochondrial Biogenesis, Autophagy and Apoptosis in Peritoneal Endometriosis in Adolescents
Previous Article in Journal
Folate-Targeted Nanocarriers Co-Deliver Ganciclovir and miR-34a-5p for Combined Anti-KSHV Therapy
Previous Article in Special Issue
Proteomic Profiling Identifies Candidate Diagnostic Biomarkers of Hydrosalpinx in Endometrial Fluid: A Pilot Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 25
Issue 5
10.3390/ijms25052925
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Sindbis Virus Vaccine Platform: A Promising Oncolytic Virus-Mediated Approach for Ovarian Cancer Treatment

by
Christine Pampeno
1,
Silvana Opp
2,
Alicia Hurtado
1 and
Daniel Meruelo
1,*
1
Department of Pathology, NYU Grossman School of Medicine, New York University, New York, NY 10016, USA
2
BioNTech, Cambridge, MA 02139, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2024, 25(5), 2925; https://doi.org/10.3390/ijms25052925
Submission received: 13 December 2023 / Revised: 30 January 2024 / Accepted: 28 February 2024 / Published: 2 March 2024
(This article belongs to the Special Issue Molecular Research in Gynecological Diseases)
Browse Figures
Versions Notes

Abstract

:
This review article provides a comprehensive overview of a novel Sindbis virus vaccine platform as potential immunotherapy for ovarian cancer patients. Ovarian cancer is the most lethal of all gynecological malignancies. The majority of high-grade serous ovarian cancer (HGSOC) patients are diagnosed with advanced disease. Current treatment options are very aggressive and limited, resulting in tumor recurrences and 50–60% patient mortality within 5 years. The unique properties of armed oncolytic Sindbis virus vectors (SV) in vivo have garnered significant interest in recent years to potently target and treat ovarian cancer. We discuss the molecular biology of Sindbis virus, its mechanisms of action against ovarian cancer cells, preclinical in vivo studies, and future perspectives. The potential of Sindbis virus-based therapies for ovarian cancer treatment holds great promise and warrants further investigation. Investigations using other oncolytic viruses in preclinical studies and clinical trials are also presented.

1. Introduction

1.1. Ovarian Cancer as a Significant Health Concern

Ovarian cancer is one of the most common and lethal types of gynecological cancers with an overall survival rate of 50 percent that has not changed significantly for several decades [1,2,3]. Although it can occur at any age, it primarily affects women who have gone through menopause. The estimated rate of new cases and death in 2023 are 19,710 and 13,720, respectively [4]. Due to the absence of noticeable symptoms, ovarian cancer often goes undetected in its early stages and hence is referred to as the “silent killer” [5,6,7,8]. As the disease progresses, symptoms include abdominal bloating or swelling, difficulty eating or feeling full quickly, pelvic pain and fatigue. These symptoms can be indicative of other conditions as well, which makes early detection and accurate diagnosis challenging. As a result, patients are frequently diagnosed at an advanced stage when tumors have already spread beyond the ovaries. Thus, metastasis presents the greatest therapeutic challenge, restricting successful treatment of patients and dramatically reducing the overall survival rate [9,10].
There are different types of ovarian cancer, with epithelial ovarian cancer being the most common form, accounting for about 90% of cases [9,11,12,13,14,15]. Highly aggressive high-grade serous ovarian carcinoma (HGSOC) is the most common epithelial subtype with a tendency to develop early chemotherapy resistance. HGSOC presents with various molecular abnormalities, especially TP53 mutations observed in the majority of tumors [16]. Other less common types include germ cell tumors and stromal tumors, which develop in the cells that produce eggs and hormones within the ovary. The exact cause of ovarian cancer is not well understood, but certain factors have been identified that may increase a woman’s risk of developing the disease. These risk factors include a family history of ovarian or breast cancer, certain inherited gene mutations (such as TP53, BRCA1, and BRCA2), increasing age, obesity, and certain hormonal factors [12,13,17,18].

1.2. Current Treatment Challenges and Limitations

Current treatment strategies typically involve a combination of surgery, systemic chemotherapy, and sometimes radiation therapy. Surgery, which is often the first line of treatment, aims to remove as much tumor tissue as possible (referred to as “debulking” [19,20]), which includes removal of one or both ovaries, fallopian tubes, uterus, and other affected tissues such as colon tissue. Adjuvant chemotherapy uses drugs to kill cancer cells that may have spread to other parts of the body [20,21]. These procedures and their limitations are a major burden for patients. Clinical trials and new therapies that explore innovative approaches, including targeted therapies and immunotherapy, are much needed to improve outcomes for women with this disease. Additionally, ongoing efforts to raise awareness about the symptoms and risk factors of ovarian cancer are crucial in promoting early detection and better overall survival rates.

1.3. HGSOC Tumor Microenvironment Presents Obstacles to Treatment

Current immunotherapeutic approaches have not been as promising as for other cancers due to the unique tumor microenvironment (TME) of ovarian cancer that facilitates efficient metastasis and dramatically impairs immune surveillance. Several comprehensive reviews discuss the composition and effects of the ascites TME on ovarian cancer progression and treatment [22,23,24,25,26,27].
HGSOC cells mainly metastasize within the peritoneal cavity [28]. The transition of epithelial ovarian cancer cells (EOCs) to a mesenchymal phenotype (EMT) involves aberrant expression of adhesion molecules [29,30] resulting in the loss of tight junctions and a more invasive behavior [31]. Cells that exfoliate from the primary tumor survive detachment by forming spheroids composed of tumor and non-tumor cells that can adhere to the mesothelium, omentum, and organs within the peritoneal cavity [32].
Peritoneal membrane permeability and angiogenesis, induced by EOC overexpression of vascular endothelial growth factor (VEGF), contributes to the accumulation of ascites fluid [33]. More than 90% of patients with stage III and IV ovarian cancer develop ascites fluid, the components of which constitute the TME [34]. The ascites TME contains diverse cell types including mesothelial, endothelial cells, immune cells, adipocytes, and fibroblasts. Interaction between tumor cells and the TME can occur through direct cell contact, soluble molecules, or exosome vesicles released by cells. The crosstalk among TME components shapes cellular phenotypes ultimately determining tumor progression or suppression.

1.3.1. Anti-Tumor Immune Components in the TME

The migration of immune cells to the EOC tumor is orchestrated by various cytokines and chemokines (reviewed in [35,36,37]). Chemokine CCL5, constitutively expressed by EOC cells, induces the infiltration of CD8 T cells [38]. Interaction with peptides presented by MHC I on tumor cells induces CD8 T cells to produce cytolytic factors, granzyme and perforin, and cytokines IL-12, IL-2 and IFNγ that act to kill tumor cells. This immunogenic cell death along with genome instability [39] releases danger signals (DAMPS) [40] that attract antigen presenting (APC) and innate natural killer (NK) cells. In this environment, tumor-associated antigens (TAAs) can be presented to activate and amplify cytolytic T cell and B cell anti-tumor responses. Prevalent TAAs in HGSOC include NY-ESO-1 [41], MAGE [42], p53 mutation, and WT1 [43,44].
Interferons play an important role in the TME by regulating the gene expression of tumor infiltrating lymphocytes (TILs) [37]. Plasmacytoid dendritic cells, CD8 T cells, NK cells and T cell helper 1 (Th1) CD4 T cells are major sources of IFNγ. Anti-tumor M1 macrophages are induced by IFNγ and lipopolysaccharides [45]. IFNγ induces myeloid cell CXCL9 secretion, which cooperates with CCL5 to enhance lymphocyte recruitment [38]. IFN I induces CXCL13 expression in tumors, which correlates with the generation of tertiary lymphoid structures and infiltration of CD4, CD8 T cells and CD20 B cells [46].
Activated immune cells clearly have the potential to effect immune surveillance and eliminate or inhibit tumor growth. It is the relative resistance to re-programming by pro-tumor elements of the TME that determines the efficacy of the immune response.

1.3.2. Pro-Tumor TME Components

The cellular components of the ascites TME include EOCs and spheroids, T cell subsets, tumor-associated macrophage (TAM), cancer-associated fibroblasts (CAFs), and myeloid-derived suppressor cells (MDSCs). Ascitic fluid facilitates the spread of tumor cells within the peritoneum to form metastatic lesions.
Interactions among cells, leading to altered phenotypes of tumor and immune cells, are mediated by cytokines, chemokines, and other factors, which bind to receptors that activate or inhibit signaling pathways. EOC cells release exosomes containing proteins, miRNA, or cytokines that can further activate tumor cells or reprogram fibroblasts or immune cells [47]. Macrophages can be polarized to an M2 pro-tumor phenotype [48] and CAFs can secrete cytokines that induce the metastasis and EMT of cancer cells [49].
The malignant ascites TME is hypoxic and has low levels of glucose and other nutrients [50,51,52,53]. Tumor hypoxia induces chemokines to recruit myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs) and TAMs that create an immunosuppressive environment [51]. The TME impedes T cell function by inhibiting T-cell mitochondrial biogenesis and decreasing the production of bioenergetic intermediates [52,53]. Compared with peripheral T cells, higher levels of inhibitory co-receptors, such as LAG-3, PD-1, TIM-3, and CTLA-4, are found on T cells within the TME [54].
Major cytokines and chemokines and signaling factors that affect tumor progression and immune cell functions are presented in Table 1 and Table 2. The tumor immune microenvironment of ovarian cancer is considered “cold” compared with “hot” cancers that are characterized by a relatively high preexisting immune cell infiltration such as occurs with melanoma or lung cancers that respond successfully to immunotherapy. The ultimate immunotherapy success to cure many cold cancers, including ovarian cancers, depends on the relative ability to turn cold TME into hot [55,56].

1.4. Oncolytic Viruses as a Potential Therapeutic Strategy

Oncolytic viruses represent an evolving field of research for the treatment of ovarian cancer due to their ability to target and directly kill cancer cells while synergistically stimulating the body’s own anti-tumor immune response that also protects from tumor recurrence. Oncolytic viruses can also carry therapeutic genes to enhance their anti-tumor effects. These vectors are called “armed” oncolytic viruses. The expression of these genes is fully dependent on the replication of the virus [93,94]. Unlike gene therapy and gene editing, which needs to be customized for each patient, oncolytic viruses offer a targeted, yet multifaceted approach that could potentially improve outcomes for patients with this challenging disease.
Different types of oncolytic viruses have been investigated in preclinical and clinical studies for ovarian cancer treatment [95]. These viral vectors can be modified to target and kill ovarian cancer cells while stimulating immune responses. Table 3 lists studies of recent oncolytic virus-mediated therapies. The genomes of oncolytic viruses can consist of double-stranded DNA, single-stranded, negative sense RNA or single-stranded, positive sense RNA. Table 4 shows current clinical trials.

2. Sindbis Virus as a Novel Approach to Ovarian Cancer Treatment

2.1. Sindbis Is a Prototypic Alphavirus

Sindbis virus (SV), an enveloped, single-stranded, positive sense RNA virus, is a member of the alphavirus genus, Togavirus family [116]. In depth reviews of alphavirus structure, expression, infection, replication, and evolution have been published [116,117,118].
Alphaviruses have many attributes that render them advantageous for gene expression vectors: (1) they exhibit a broad host range for mammalian cell infection [119]; (2) RNA genomes, which mimic mRNA, quickly form replication complexes in the cytoplasm of infected cells; (3) the lack of DNA intermediates avoids the risk of insertional chromosome mutagenesis [120,121,122]; (4) approximately 106 copies of viral RNA, coupled with a strong subgenomic promoter, enable very high expression levels of recombinant protein [120,123]; and (5) vectors are easy to manipulate and can accommodate at least 8000 bp of heterologous mRNA [124].

2.2. Alphavirus Vectors as an Oncoviral-Mediated Therapy

The properties of alphaviruses that make them suitable for cancer therapy include: (1) cytopathicity causing infected cells to die by apoptosis [125,126,127]; (2) tumor-associated antigens (TAAs) released from apoptotic bodies induce immune responses via cross-priming [128,129,130]; (3) double-stranded RNA replication intermediates elicit “danger signals”, activating antiviral pathways that stimulate innate immune responses and enhance adaptive immunity [131,132,133,134,135,136,137]; (4) alphaviruses infect lymph nodes [129,138,139] and dendritic cells [140,141]; (5) transmitted via insect bites, alphaviruses are blood-borne allowing recombinant vectors to be systemically delivered in vivo [116]; and (6) repeated administration of vectors remains efficacious [142,143,144].

2.3. Vector Safety

In nature, SV has the safest profile among alphaviruses with mostly asymptomatic infections causing mild fever, rash or arthralgia [145,146,147]. In addition, for added safety SV-derived vectors can be produced in a manner that prevents the amplification of virus particles (Figure 1). The cDNA sequence of the RNA genome is split into two segments and cloned into separate plasmids. A replicon DNA plasmid encodes the non-structural replicase proteins and contains a strong subgenomic promoter to express heterologous “genes of interest”. A helper DNA plasmid, encoding the viral capsid and envelope proteins, lacks a packaging signal so that vector particles only contain the replicase and heterologous genes and can undergo only one round of infection [120,123,148].

2.4. Sindbis Virus Selectively Targets and Replicates within Ovarian Cancer Cells While Sparing Healthy Cells

Immunohistochemical and bioluminescent in vivo imaging studies using SV vectors that express reporter genes indicate the specific targeting of tumor and metastatic cells in both murine xenotropic and syngeneic ovarian cancer models [125,149]. Figure 2 shows that SV vector expressing Firefly luciferase (SV/Fluc) localizes to tumors and metastases in a syngeneic C57BL/6 MOSEC ovarian cancer model [150] while non-tumor bearing control mice show no significant bioluminescent signals. Similar results were observed in a nude mice human ovarian cancer model systemically treated with replication-positive SV [115].
Sindbis virus has been shown to bind with the 67 KDa high affinity laminin receptor (LAMR) protein [151,152]. LAMR has a high affinity for laminin, a major component of cell basement membranes that plays an important role in cellular adhesion, morphology, differentiation, and migration (reviewed in [153]). The presence and conservation of LAMR among many distantly related species is consistent with the broad host range of the Sindbis virus. The overexpression of LAMR by cDNA transfection into Baby hamster kidney (BHK) cells increased the level of SV infection [152] while LAMR antisense RNA [152], silencing siRNA [125] or short hairpin shRNA [154] decreased infection.
Although the exact mechanism of SV infection via LAMR has not been elucidated (reviewed in [155]), it has been determined that the glutamic acid residue at amino acid position 70 of the envelope E2 protein is critical for in vivo tumor targeting [156]. The overexpression of the 67 KDa LAMR occurs on the surface of many human cancer cells [157,158,159,160,161,162] including those of ovarian origin [162,163]. LAMR monoclonal antibody binding studies suggest that tumor cells have varying degrees of unoccupied cell-surface LAMRs that conceivably result from the increased biosynthesis of LAMR or the dissolution of the surrounding basement membrane and extracellular matrix by tumor cells [164,165,166,167]. It is thus plausible that SV uses unoccupied LAMRs as fortuitous binding sites on tumor cells. Other SV receptors have been more recently discovered. The natural resistance-associated macrophage protein (NRAMP), a divalent metal transport protein, has been identified as an SV receptor in Drosophila and the vertebrate homolog, NRAMP2, as an SV receptor in mammalian cells [168]. VLDLR and ApoER2, members of the low-density lipoprotein family, were found to be receptors for certain alphaviruses including SV [169]. Affinity purification followed by mass spectrometry identified the CD147 membrane protein as a receptor for SV and other alphaviruses in human cells [170]. Notably, CD147, which has been found to be overexpressed on many cancer cells and cells within the tumor microenvironment, plays a role in tumor proliferation and the inhibition of apoptosis [171]. The protumor effects of CD147 may potentially be obviated by SV binding, infection, and cell lysis.

3. Mechanisms of Action against Ovarian Cancer Cells

SV vector cancer therapy can involve several processes. SV replication complexes produce abundant RNA molecules with double stranded RNA intermediates triggering “danger signals” [40]. The cytotoxic effects of SV infection result from the inhibition of cellular protein translation, activation of a stress response, and ultimately an apoptotic cascade [126]. The expression of tumor-associated antigens (TAAs) or immunomodulatory agents can augment anti-tumor effects.

3.1. Immunotherapeutic Effects of SV Vectors

The ability of SV vector treatment to stimulate a rapid influx of activated innate natural killer cells (NK) was demonstrated using a xenotropic ES-2 human ovarian cancer [172] model in SCID (severe combined immunodeficiency) mice, which lack T and B cells [133]. Significant inhibition of tumor growth and increased survival were observed. The incorporation of IL-12 into the SV vector enhanced the therapeutic effect by inducing IFNγ secretion from NK cells, which was shown to upregulate the expression of MHC class II on peritoneal macrophages promoting an M1 anti-tumor effect.
The potential of SV vectors to promote an adaptive immune response against tumors was studied in a syngeneic, immunocompetent BALB/c CT26 colon carcinoma tumor model [129]. As CT26 cells are not susceptible to SV infection, this model separated SV oncolytic activity from potential immunogenic effects. A bioluminescent signal was first observed in the mediastinal lymph nodes that drain the peritoneum 3 h after SV/Firefly luciferase i.p. injection. When CT26 TAAs were expressed by SV vectors, an influx of activated CD8 T cells to the peritoneum occurred within one week. Effector and memory CD8 T cells were generated correlating with long-term survival. The cytolytic activity of immune cells released endogenous CT26 TAAs that were shown to be engaged by CD8 T cell specific tetramers revealing that SV vectors can be therapeutic via epitope spreading without oncolytic tumor targeting.

3.2. Combination of IL-12 and OX40 Agonistic Antibody

Although many oncolytic virus vectors have been designed for the local delivery of IL-12 in preclinical trials, only oncolytic Herpes virus (OHSV-IL-12) has progressed clinically [173]. Improved therapeutic outcomes have required a synergistic or additive combined approach [174,175,176,177,178,179]. SV vectors expressing IL-12 cytokine have also been shown to have greater tumor-killing activity but have not been curative [133,180,181,182].
The observation that IL-12 increases the presence of OX40 (CD134) on the surface of CD4 T cells [181,183] prompted the study of a combined anti-tumor capacity. IL-12 activates T cells, stimulates the production of IFNγ and increases the expression of OX40 on effector CD4 T cells [183]. The combination of SV.IL-12 with an agonistic antibody to OX40 exhibits strong therapeutic efficacy in CT26, colon, and MyC-CaP, prostate carcinoma, models [181]. The transcriptome and metabolic reprogramming of T cells drove the development of activated effector T cells with enhanced tumor infiltration and anti-tumor capacity within the TME.
OX40 is a member of the tumor necrosis family that is expressed on activated T cells [184]. OX40 promotes the clonal expansion, differentiation, and survival of CD4 Th1 helper cells, which produce IFNγ and IL-2 cytokines [185,186,187,188,189] that sustain the survival of primed CD8 T cells [184,190]. The co-expression of OX40 with ICOS on follicular T helper cells (Tfh) facilitates the differentiation of antibody-producing B cells and long-lived plasma cells from germinal center B cells [191]. In addition, OX40 signaling represses regulatory T cells (Treg) by downregulating the expression of Foxp3 [192].

3.3. SV.IL12 and Agonistic Anti-OX40 as an Ovarian Cancer Therapy

The collaborative effects of SV.IL12 and anti-OX40 agonistic antibody (⍺OX40) were investigated using the C57BL/6 mouse MOSEC/ID8 model [150]. The MOSEC cells, which are susceptible to SV infection, were modified by cell passaging to achieve a more reproducible tumor engraftment and by transduction with firefly luciferase for in vivo imaging (MOSEC.Fluc.p11) [114]. MOSEC.Fluc.p11 cells (2.5 × 106) were i.p. injected into C57BL/6 albino mice and within 7 days, tumors were observed. Treatment began on day 8 by i.p. injections of SV.IL-12 (107 TU/mL, 0.5 mL), 4 times per week for 4 weeks and ⍺OX40 (250 µg/mouse), 3 times per week for 3 weeks. As observed for other cancer models, combined therapy increased survival [181], however, in the MOSEC model SV.IL-12 was almost as effective.
Treatment with SV.IL-12, ⍺OX40 and SV.IgGOX40 increased the migration of immune T cells into MOSEC.Fluc.p11 tumors within 7 days, as shown by the overlapping of multiplex immunofluorescence staining of CD8 and CD4 T cells with Ki67 and granzyme B markers for proliferating cytotoxic T cells [114]. Significantly more lysis of tumor tissue was observed when ⍺OX40 was delivered by SV.⍺OX40 vector presumably as SV infection of MOSEC cells produce high levels of and ⍺OX40 to stimulate a cytotoxic immune response and SV vector induced apoptosis.
The immune function of T cells require a high metabolic state. The ascites TME, characterized by hypoxia, acidosis, and low nutrient levels, impairs the metabolism and function of T cells (reviewed in [50,193,194,195]). The metabolic profiles of splenic T cells were measured by Agilent Seahorse technology. Only SV.IL-12 combined with ⍺OX40 provided T cells with a spare respiratory capacity and a higher basal energetic state [114].
To examine sustained protection from MOSEC growth, mice were treated with either SV.IL-12 or SV.IgGOX40.IL-12 and at 140 days, surviving mice were rechallenged with MOSEC cells (Figure 3). Naive control mice, inoculated with tumor cells at the same time as the rechallenged mice, succumbed after 35 days while both vectors provided long-term tumor suppression. The ability of SV.IL-12 to stimulate OX40 expression on T cells may account for the efficacy of both SV.IgGOX40.IL-12 and SV.IL-2 in this cancer model [114].
In vivo antibody depletion studies indicated that while both CD4 and CD8 T cells are important for SV.IgGOX40.IL-12 efficacy, CD4 T cells appear to play a more pivotal role [114]. This observation coincides with previous results showing that SV.IL-12 and ⍺OX40 elevate and sustain cytotoxic CD4 T cells [181]. Effector CD4 T cell have been increasingly recognized for anti-tumor activity, independent of their helper function [196,197].
Transcriptome analysis, performed for untreated MOSEC tumors vs. tumors treated with SV empty vector, SV.IL-12, SV.⍺OX40 or SV.IgGOX40.IL-12 showed distinct gene expression profiles for all treatment groups. Empty SV vector showed the lowest number of differentially expressed genes implying that the “armed” vectors were deployed at tumor sites. Pathway and network analysis showed the downregulation of genes involved with DNA replication, transcription, and cell division correlating with the elimination of tumor cells. Upregulated genes were predominantly related to immune response pathways most likely correlating with infiltrated lymphocytes.
The modulation of anti-tumor immune responses is illustrated in Figure 4. The ability of SV.IgGOX40.IL-12 to systemically target metastatic tumors while altering the transcriptome signature and metabolic program of T cells, increasing their capacity to infiltrate the repressive TME, renders these vectors a promising therapy for ovarian and other types of cancers.

4. Summary

The unique TME of HGSOC complicates treatment strategies. More than 90% of stage III/IV patients develop malignant ascites fluid. Crosstalk among the myriad of the components of the ascites TME modulates the phenotypes of tumor and immune response cells. The goals of oncolytic virus-mediated therapies must include tumor targeting and killing, as well as, the skewing of the TME toward a strong immune response. Several recent studies and clinical trials have been presented.
A SV vector platform has been developed combining the expression of IL-12 and an agonistic antibody targeting the co-stimulatory OX40 receptor. The SV.IgGOX40.IL-12 vector decreases the tumor burden in ovarian cancer mouse models, increases survival and provides protection against tumor rechallenge. A notable influx of immune cells into the tumor microenvironment occurs. Treatment efficacy is associated with the transcriptional reprogramming of T cells leading to the expression of immune response genes and metabolic alterations that result in higher energy states.
The lack of clinical trials involving SV vectors, thus far, makes it difficult to evaluate their transition from animal models to human patients. Translation to clinical applications is feasible as SV vectors can be produced and purified under Good Manufacturing Practice (GMP) standards, ensuring high titers (1011 transducing units per milliliter (TU/mL)) to compensate for dilution in the bloodstream or TME. Vectors might be administered directly to patients or after the debulking of tumors and ascites where they may have a greater chance of preventing a suppressive TME. Treatment efficacy may require multiple doses. While alphaviruses are not highly immunogenic, the requirement for many doses could pose challenges and may lead to patient reluctance to undergo treatment. The ease of SV vector modifications, however, will allow continued optimization.

5. Future Perspectives

The lytic activity of oncolytic viruses, which selectively replicate in tumor cells, initiated their role as tools for cancer treatment. Ultimately, lytic effects were observed to reshape “cold” into “hot” tumors that are more responsive to immunotherapies. Table 3 and Table 4 present several families of oncolytic viruses that have been studied in combination with chemotherapy, checkpoint inhibitors, and other immunomodulatory agents for the treatment of ovarian cancer. Several oncolytic viruses have also been genetically modified to express therapeutic cargos.
Future studies should identify and optimize interactions between oncolytic viruses and the immune system within the TME. Epigenetic changes to cancer cells and effects on viral infection and replication should also be considered (reviewed in [198,199]). Epigenetic modifications of the genome, which include DNA methylation and histone acetylation, are often deregulated in tumors leading to cell proliferation. The inhibition of these modifiers have been shown to attenuate cellular anti-viral response, promote cancer cell cycle arrest and apoptosis and potentiate the immune response. The inhibition of histone deacetylase (HDACi) has been shown to augment adenovirus oncolysis in cisplatin-resistant ovarian cancer cells [200].
The considerable heterogeneity within patients with ovarian cancer involving genetic, epigenetic, and immunological systems presents a challenge to therapy. Oncolytic viruses combined with the modulators of the immune system, epigenome, and chemical drugs can provide powerful weapons in the arsenal against ovarian cancer.

Author Contributions

D.M., C.P., A.H. and S.O. conceptualized the review; original papers, all authors; writing, C.P. and S.O.; editing, D.M. and A.H., preparation of figures, A.H., S.O. and C.P.; supervision, project administration, funding acquisition, D.M. All authors have read and agreed to the published version of the manuscript.

Funding

Funding was provided by NIH 5R44CA250627 and through a Research and Licensing Agreement between Cynvec and NYU Langone, which licenses the Sindbis technology to Cynvec. This work was also supported, in part, by The Experimental Pathology Research Laboratory at NYU Langone that is partially supported by the Cancer Center Support Grant P30CA016087. The Vectra3 multispectral imaging system was purchased through Shared Instrumentation Grant S10 OD021747.

Institutional Review Board Statement

All experiments were performed in accordance with the Institutional Animal Care and Use Committee of New York University Health.

Informed Consent Statement

Not applicable.

Data Availability Statement

All sequencing data that support the findings of this study will be. deposited in the National Center for Biotechnology Information Gene Expression Omnibus (GEO) and are accessible through the GEO Series accession number that will be provided and including all other relevant data included in the article, and further inquiries can be directed to the corresponding authors.

Acknowledgments

We wish to thank all the postdoctoral fellows, graduate students and technicians who contributed to the studies described in this review. We appreciate the Funding was provided by NIH 5R44CA250627. We would like to thank the NYU High Throughput Biology Laboratory for Seahorse usage, the NYU Genome Technology Center for RNA sequencing service and the Experimental Pathology Research Laboratory at NYU Langone, which also supported this work, in part, by the Experimental Pathology Research Laboratory at NYU Langone, which is partially supported by the Cancer Center Support Grant P30CA016087. The Vectra3 multispectral imaging system was purchased through Shared Instrumentation Grant S10 OD021747.

Conflicts of Interest

All authors are employed by NYU Langone School of Medicine and have no employment relationship or consultancy agreement with Cynvec, a biotechnology company that supports some studies under a Research and Licensing agreement with NYU. S.O., A.H., C.P., and D.M. are inventors on one or several issued patents and/or patent applications held by NYU that cover the Sindbis treatment of neoplasia and COVID-19. As part of the Research and Licensing agreement, the authors who are inventors on patents are entitled to a portion of the royalties that NYU Langone would receive, should Sindbis vectors be approved by the FDA for therapeutic or vaccination use. Data and materials availability: Correspondence should be addressed to D.M.

References

  1. Bowtell, D.D.; Bohm, S.; Ahmed, A.A.; Aspuria, P.J.; Bast, R.C., Jr.; Beral, V.; Berek, J.S.; Birrer, M.J.; Blagden, S.; Bookman, M.A.; et al. Rethinking ovarian cancer II: Reducing mortality from high-grade serous ovarian cancer. Nat. Rev. Cancer 2015, 15, 668–679. [Google Scholar] [CrossRef] [PubMed]
  2. Cannistra, S.A. Cancer of the ovary. N. Engl. J. Med. 2004, 351, 2519–2529. [Google Scholar] [CrossRef] [PubMed]
  3. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  4. National Cancer Institute. Surveillance, Epidemiology and End Results Program. Available online: https://seer.cancer.gov/ (accessed on 19 September 2022).
  5. Bodurka-Bevers, D.; Sun, C.C.; Gershenson, D.M. Pharmacoeconomic considerations in treating ovarian cancer. Pharmacoeconomics 2000, 17, 133–150. [Google Scholar] [CrossRef]
  6. Feeney, L.; Harley, I.J.; McCluggage, W.G.; Mullan, P.B.; Beirne, J.P. Liquid biopsy in ovarian cancer: Catching the silent killer before it strikes. World J. Clin. Oncol. 2020, 11, 868–889. [Google Scholar] [CrossRef]
  7. Le Page, C.; Provencher, D.; Maugard, C.M.; Ouellet, V.; Mes-Masson, A.M. Signature of a silent killer: Expression profiling in epithelial ovarian cancer. Expert Rev. Mol. Diagn. 2004, 4, 157–167. [Google Scholar] [CrossRef]
  8. Nersesian, S.; Glazebrook, H.; Toulany, J.; Grantham, S.R.; Boudreau, J.E. Naturally Killing the Silent Killer: NK Cell-Based Immunotherapy for Ovarian Cancer. Front. Immunol. 2019, 10, 1782. [Google Scholar] [CrossRef]
  9. Mitra, A.K.; Chiang, C.Y.; Tiwari, P.; Tomar, S.; Watters, K.M.; Peter, M.E.; Lengyel, E. Microenvironment-induced downregulation of miR-193b drives ovarian cancer metastasis. Oncogene 2015, 34, 5923–5932. [Google Scholar] [CrossRef]
  10. Wang, F.Q.; So, J.; Reierstad, S.; Fishman, D.A. Vascular endothelial growth factor-regulated ovarian cancer invasion and migration involves expression and activation of matrix metalloproteinases. Int. J. Cancer 2006, 118, 879–888. [Google Scholar] [CrossRef]
  11. Ledermann, J.; Harter, P.; Gourley, C.; Friedlander, M.; Vergote, I.; Rustin, G.; Scott, C.L.; Meier, W.; Shapira-Frommer, R.; Safra, T.; et al. Olaparib maintenance therapy in patients with platinum-sensitive relapsed serous ovarian cancer: A preplanned retrospective analysis of outcomes by BRCA status in a randomised phase 2 trial. Lancet Oncol. 2014, 15, 852–861. [Google Scholar] [CrossRef]
  12. Reid, B.M.; Permuth, J.B.; Sellers, T.A. Epidemiology of ovarian cancer: A review. Cancer Biol. Med. 2017, 14, 9–32. [Google Scholar] [CrossRef] [PubMed]
  13. Roett, M.A.; Evans, P. Ovarian cancer: An overview. Am. Fam. Physician 2009, 80, 609–616. [Google Scholar] [PubMed]
  14. Torre, L.A.; Trabert, B.; DeSantis, C.E.; Miller, K.D.; Samimi, G.; Runowicz, C.D.; Gaudet, M.M.; Jemal, A.; Siegel, R.L. Ovarian cancer statistics, 2018. CA Cancer J. Clin. 2018, 68, 284–296. [Google Scholar] [CrossRef] [PubMed]
  15. Gavalas, N.G.; Tsiatas, M.; Tsitsilonis, O.; Politi, E.; Ioannou, K.; Ziogas, A.C.; Rodolakis, A.; Vlahos, G.; Thomakos, N.; Haidopoulos, D.; et al. VEGF directly suppresses activation of T cells from ascites secondary to ovarian cancer via VEGF receptor type 2. Br. J. Cancer 2012, 107, 1869–1875. [Google Scholar] [CrossRef] [PubMed]
  16. Ahmed, A.A.; Etemadmoghadam, D.; Temple, J.; Lynch, A.G.; Riad, M.; Sharma, R.; Stewart, C.; Fereday, S.; Caldas, C.; Defazio, A.; et al. Driver mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovary. J. Pathol. 2010, 221, 49–56. [Google Scholar] [CrossRef] [PubMed]
  17. Gayther, S.A.; Pharoah, P.D. The inherited genetics of ovarian and endometrial cancer. Curr. Opin. Genet. Dev. 2010, 20, 231–238. [Google Scholar] [CrossRef] [PubMed]
  18. Parazzini, F.; Negri, E.; La Vecchia, C.; Restelli, C.; Franceschi, S. Family history of reproductive cancers and ovarian cancer risk: An Italian case-control study. Am. J. Epidemiol. 1992, 135, 35–40. [Google Scholar] [CrossRef] [PubMed]
  19. Abbas-Aghababazadeh, F.; Sasamoto, N.; Townsend, M.K.; Huang, T.; Terry, K.L.; Vitonis, A.F.; Elias, K.M.; Poole, E.M.; Hecht, J.L.; Tworoger, S.S.; et al. Predictors of residual disease after debulking surgery in advanced stage ovarian cancer. Front. Oncol. 2023, 13, 1090092. [Google Scholar] [CrossRef]
  20. Schorge, J.O.; McCann, C.; Del Carmen, M.G. Surgical debulking of ovarian cancer: What difference does it make? Rev. Obstet. Gynecol. 2010, 3, 111–117. [Google Scholar]
  21. Alvero, A.B. Recent insights into the role of NF-kappaB in ovarian carcinogenesis. Genome Med. 2010, 2, 56. [Google Scholar] [CrossRef]
  22. Ford, C.E.; Werner, B.; Hacker, N.F.; Warton, K. The untapped potential of ascites in ovarian cancer research and treatment. Br. J. Cancer 2020, 123, 9–16. [Google Scholar] [CrossRef]
  23. Jiang, Y.; Wang, C.; Zhou, S. Targeting tumor microenvironment in ovarian cancer: Premise and promise. Biochim. Biophys. Acta Rev. Cancer 2020, 1873, 188361. [Google Scholar] [CrossRef]
  24. Luo, X.; Xu, J.; Yu, J.; Yi, P. Shaping Immune Responses in the Tumor Microenvironment of Ovarian Cancer. Front. Immunol. 2021, 12, 692360. [Google Scholar] [CrossRef]
  25. Mei, S.; Chen, X.; Wang, K.; Chen, Y. Tumor microenvironment in ovarian cancer peritoneal metastasis. Cancer Cell Int. 2023, 23, 11. [Google Scholar] [CrossRef] [PubMed]
  26. Ritch, S.J.; Telleria, C.M. The Transcoelomic Ecosystem and Epithelial Ovarian Cancer Dissemination. Front. Endocrinol. 2022, 13, 886533. [Google Scholar] [CrossRef] [PubMed]
  27. Yang, Y.; Yang, Y.; Yang, J.; Zhao, X.; Wei, X. Tumor Microenvironment in Ovarian Cancer: Function and Therapeutic Strategy. Front. Cell Dev. Biol. 2020, 8, 758. [Google Scholar] [CrossRef] [PubMed]
  28. Lengyel, E. Ovarian cancer development and metastasis. Am. J. Pathol. 2010, 177, 1053–1064. [Google Scholar] [CrossRef]
  29. Dhaliwal, D.; Shepherd, T.G. Molecular and cellular mechanisms controlling integrin-mediated cell adhesion and tumor progression in ovarian cancer metastasis: A review. Clin. Exp. Metastasis 2022, 39, 291–301. [Google Scholar] [CrossRef] [PubMed]
  30. Sawada, K.; Mitra, A.K.; Radjabi, A.R.; Bhaskar, V.; Kistner, E.O.; Tretiakova, M.; Jagadeeswaran, S.; Montag, A.; Becker, A.; Kenny, H.A.; et al. Loss of E-cadherin promotes ovarian cancer metastasis via alpha 5-integrin, which is a therapeutic target. Cancer Res. 2008, 68, 2329–2339. [Google Scholar] [CrossRef] [PubMed]
  31. Bagnato, A.; Rosano, L. Epithelial-mesenchymal transition in ovarian cancer progression: A crucial role for the endothelin axis. Cells Tissues Organs 2007, 185, 85–94. [Google Scholar] [CrossRef] [PubMed]
  32. Capellero, S.; Erriquez, J.; Battistini, C.; Porporato, R.; Scotto, G.; Borella, F.; Di Renzo, M.F.; Valabrega, G.; Olivero, M. Ovarian Cancer Cells in Ascites Form Aggregates That Display a Hybrid Epithelial-Mesenchymal Phenotype and Allows Survival and Proliferation of Metastasizing Cells. Int. J. Mol. Sci. 2022, 23, 833. [Google Scholar] [CrossRef]
  33. Zebrowski, B.K.; Liu, W.; Ramirez, K.; Akagi, Y.; Mills, G.B.; Ellis, L.M. Markedly elevated levels of vascular endothelial growth factor in malignant ascites. Ann. Surg. Oncol. 1999, 6, 373–378. [Google Scholar] [CrossRef] [PubMed]
  34. Huang, H.; Li, Y.J.; Lan, C.Y.; Huang, Q.D.; Feng, Y.L.; Huang, Y.W.; Liu, J.H. Clinical significance of ascites in epithelial ovarian cancer. Neoplasma 2013, 60, 546–552. [Google Scholar] [CrossRef] [PubMed]
  35. Huang, X.; Hao, J.; Tan, Y.Q.; Zhu, T.; Pandey, V.; Lobie, P.E. CXC Chemokine Signaling in Progression of Epithelial Ovarian Cancer: Theranostic Perspectives. Int. J. Mol. Sci. 2022, 23, 2642. [Google Scholar] [CrossRef] [PubMed]
  36. Kohli, K.; Pillarisetty, V.G.; Kim, T.S. Key chemokines direct migration of immune cells in solid tumors. Cancer Gene Ther. 2022, 29, 10–21. [Google Scholar] [CrossRef] [PubMed]
  37. Liu, T.; Li, Y.; Wang, X.; Yang, X.; Fu, Y.; Zheng, Y.; Gong, H.; He, Z. The role of interferons in ovarian cancer progression: Hinderer or promoter? Front. Immunol. 2022, 13, 1087620. [Google Scholar] [CrossRef]
  38. Dangaj, D.; Bruand, M.; Grimm, A.J.; Ronet, C.; Barras, D.; Duttagupta, P.A.; Lanitis, E.; Duraiswamy, J.; Tanyi, J.L.; Benencia, F.; et al. Cooperation between Constitutive and Inducible Chemokines Enables T Cell Engraftment and Immune Attack in Solid Tumors. Cancer Cell 2019, 35, 885–900.e10. [Google Scholar] [CrossRef]
  39. Morden, C.R.; Farrell, A.C.; Sliwowski, M.; Lichtensztejn, Z.; Altman, A.D.; Nachtigal, M.W.; McManus, K.J. Chromosome instability is prevalent and dynamic in high-grade serous ovarian cancer patient samples. Gynecol. Oncol. 2021, 161, 769–778. [Google Scholar] [CrossRef]
  40. Garg, A.D.; Galluzzi, L.; Apetoh, L.; Baert, T.; Birge, R.B.; Bravo-San Pedro, J.M.; Breckpot, K.; Brough, D.; Chaurio, R.; Cirone, M.; et al. Molecular and Translational Classifications of DAMPs in Immunogenic Cell Death. Front. Immunol. 2015, 6, 588. [Google Scholar] [CrossRef] [PubMed]
  41. Odunsi, K.; Jungbluth, A.A.; Stockert, E.; Qian, F.; Gnjatic, S.; Tammela, J.; Intengan, M.; Beck, A.; Keitz, B.; Santiago, D.; et al. NY-ESO-1 and LAGE-1 cancer-testis antigens are potential targets for immunotherapy in epithelial ovarian cancer. Cancer Res. 2003, 63, 6076–6083. [Google Scholar]
  42. Daudi, S.; Eng, K.H.; Mhawech-Fauceglia, P.; Morrison, C.; Miliotto, A.; Beck, A.; Matsuzaki, J.; Tsuji, T.; Groman, A.; Gnjatic, S.; et al. Expression and immune responses to MAGE antigens predict survival in epithelial ovarian cancer. PLoS ONE 2014, 9, e104099. [Google Scholar] [CrossRef]
  43. Network, C.G.A.R. Integrated genomic analyses of ovarian carcinoma. Nature 2011, 474, 609–615. [Google Scholar] [CrossRef]
  44. Sallum, L.F.; Andrade, L.; Ramalho, S.; Ferracini, A.C.; de Andrade Natal, R.; Brito, A.B.C.; Sarian, L.O.; Derchain, S. WT1, p53 and p16 expression in the diagnosis of low- and high-grade serous ovarian carcinomas and their relation to prognosis. Oncotarget 2018, 9, 15818–15827. [Google Scholar] [CrossRef]
  45. Baci, D.; Bosi, A.; Gallazzi, M.; Rizzi, M.; Noonan, D.M.; Poggi, A.; Bruno, A.; Mortara, L. The Ovarian Cancer Tumor Immune Microenvironment (TIME) as Target for Therapy: A Focus on Innate Immunity Cells as Therapeutic Effectors. Int. J. Mol. Sci. 2020, 21, 3125. [Google Scholar] [CrossRef] [PubMed]
  46. Ukita, M.; Hamanishi, J.; Yoshitomi, H.; Yamanoi, K.; Takamatsu, S.; Ueda, A.; Suzuki, H.; Hosoe, Y.; Furutake, Y.; Taki, M.; et al. CXCL13-producing CD4+ T cells accumulate in the early phase of tertiary lymphoid structures in ovarian cancer. JCI Insight 2022, 7, e157215. [Google Scholar] [CrossRef] [PubMed]
  47. Cheng, L.; Wu, S.; Zhang, K.; Qing, Y.; Xu, T. A comprehensive overview of exosomes in ovarian cancer: Emerging biomarkers and therapeutic strategies. J. Ovarian Res. 2017, 10, 73. [Google Scholar] [CrossRef] [PubMed]
  48. Carroll, M.J.; Kapur, A.; Felder, M.; Patankar, M.S.; Kreeger, P.K. M2 macrophages induce ovarian cancer cell proliferation via a heparin binding epidermal growth factor/matrix metalloproteinase 9 intercellular feedback loop. Oncotarget 2016, 7, 86608–86620. [Google Scholar] [CrossRef] [PubMed]
  49. Zhao, L.; Ji, G.; Le, X.; Luo, Z.; Wang, C.; Feng, M.; Xu, L.; Zhang, Y.; Lau, W.B.; Lau, B.; et al. An integrated analysis identifies STAT4 as a key regulator of ovarian cancer metastasis. Oncogene 2017, 36, 3384–3396. [Google Scholar] [CrossRef] [PubMed]
  50. Chang, C.H.; Qiu, J.; O’Sullivan, D.; Buck, M.D.; Noguchi, T.; Curtis, J.D.; Chen, Q.; Gindin, M.; Gubin, M.M.; van der Windt, G.J.; et al. Metabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression. Cell 2015, 162, 1229–1241. [Google Scholar] [CrossRef] [PubMed]
  51. Facciabene, A.; Peng, X.; Hagemann, I.S.; Balint, K.; Barchetti, A.; Wang, L.P.; Gimotty, P.A.; Gilks, C.B.; Lal, P.; Zhang, L.; et al. Tumour hypoxia promotes tolerance and angiogenesis via CCL28 and T(reg) cells. Nature 2011, 475, 226–230. [Google Scholar] [CrossRef] [PubMed]
  52. Scharping, N.E.; Menk, A.V.; Moreci, R.S.; Whetstone, R.D.; Dadey, R.E.; Watkins, S.C.; Ferris, R.L.; Delgoffe, G.M. The Tumor Microenvironment Represses T Cell Mitochondrial Biogenesis to Drive Intratumoral T Cell Metabolic Insufficiency and Dysfunction. Immunity 2016, 45, 374–388. [Google Scholar] [CrossRef] [PubMed]
  53. Song, M.; Sandoval, T.A.; Chae, C.S.; Chopra, S.; Tan, C.; Rutkowski, M.R.; Raundhal, M.; Chaurio, R.A.; Payne, K.K.; Konrad, C.; et al. IRE1α-XBP1 controls T cell function in ovarian cancer by regulating mitochondrial activity. Nature 2018, 562, 423–428. [Google Scholar] [CrossRef] [PubMed]
  54. Rådestad, E.; Klynning, C.; Stikvoort, A.; Mogensen, O.; Nava, S.; Magalhaes, I.; Uhlin, M. Immune profiling and identification of prognostic immune-related risk factors in human ovarian cancer. Oncoimmunology 2019, 8, e1535730. [Google Scholar] [CrossRef] [PubMed]
  55. Ghisoni, E.; Imbimbo, M.; Zimmermann, S.; Valabrega, G. Ovarian Cancer Immunotherapy: Turning up the Heat. Int. J. Mol. Sci. 2019, 20, 2927. [Google Scholar] [CrossRef] [PubMed]
  56. Too, N.S.H.; Ho, N.C.W.; Adine, C.; Iyer, N.G.; Fong, E.L.S. Hot or cold: Bioengineering immune contextures into in vitro patient-derived tumor models. Adv. Drug Deliv. Rev. 2021, 175, 113791. [Google Scholar] [CrossRef]
  57. Mustea, A.; Pirvulescu, C.; Könsgen, D.; Braicu, E.I.; Yuan, S.; Sun, P.; Lichtenegger, W.; Sehouli, J. Decreased IL-1 RA concentration in ascites is associated with a significant improvement in overall survival in ovarian cancer. Cytokine 2008, 42, 77–84. [Google Scholar] [CrossRef] [PubMed]
  58. Ullah, M.; Azazzen, D.; Kaci, R.; Benabbou, N.; Pujade Lauraine, E.; Pocard, M.; Mirshahi, M. High Expression of HLA-G in Ovarian Carcinomatosis: The Role of Interleukin-1β. Neoplasia 2019, 21, 331–342. [Google Scholar] [CrossRef] [PubMed]
  59. Nishio, H.; Yaguchi, T.; Sugiyama, J.; Sumimoto, H.; Umezawa, K.; Iwata, T.; Susumu, N.; Fujii, T.; Kawamura, N.; Kobayashi, A.; et al. Immunosuppression through constitutively activated NF-κB signalling in human ovarian cancer and its reversal by an NF-κB inhibitor. Br. J. Cancer 2014, 110, 2965–2974. [Google Scholar] [CrossRef]
  60. Wu, L.; Deng, Z.; Peng, Y.; Han, L.; Liu, J.; Wang, L.; Li, B.; Zhao, J.; Jiao, S.; Wei, H. Ascites-derived IL-6 and IL-10 synergistically expand CD14(+)HLA-DR(-/low) myeloid-derived suppressor cells in ovarian cancer patients. Oncotarget 2017, 8, 76843–76856. [Google Scholar] [CrossRef]
  61. Browning, L.; Patel, M.R.; Horvath, E.B.; Tawara, K.; Jorcyk, C.L. IL-6 and ovarian cancer: Inflammatory cytokines in promotion of metastasis. Cancer Manag. Res. 2018, 10, 6685–6693. [Google Scholar] [CrossRef]
  62. Thongchot, S.; Jamjuntra, P.; Therasakvichya, S.; Warnnissorn, M.; Ferraresi, A.; Thuwajit, P.; Isidoro, C.; Thuwajit, C. Interleukin-8 released by cancer-associated fibroblasts attenuates the autophagy and promotes the migration of ovarian cancer cells. Int. J. Oncol. 2021, 58, 14. [Google Scholar] [CrossRef]
  63. Wang, Y.; Xu, R.C.; Zhang, X.L.; Niu, X.L.; Qu, Y.; Li, L.Z.; Meng, X.Y. Interleukin-8 secretion by ovarian cancer cells increases anchorage-independent growth, proliferation, angiogenic potential, adhesion and invasion. Cytokine 2012, 59, 145–155. [Google Scholar] [CrossRef]
  64. Li, L.; Ma, Y.; Xu, Y. Follicular regulatory T cells infiltrated the ovarian carcinoma and resulted in CD8 T cell dysfunction dependent on IL-10 pathway. Int. Immunopharmacol. 2019, 68, 81–87. [Google Scholar] [CrossRef]
  65. Fujisawa, T.; Joshi, B.H.; Puri, R.K. IL-13 regulates cancer invasion and metastasis through IL-13Rα2 via ERK/AP-1 pathway in mouse model of human ovarian cancer. Int. J. Cancer 2012, 131, 344–356. [Google Scholar] [CrossRef] [PubMed]
  66. Ripley, D.; Shoup, B.; Majewski, A.; Chegini, N. Differential expression of interleukins IL-13 and IL-15 in normal ovarian tissue and ovarian carcinomas. Gynecol. Oncol. 2004, 92, 761–768. [Google Scholar] [CrossRef]
  67. Lecker, L.S.M.; Berlato, C.; Maniati, E.; Delaine-Smith, R.; Pearce, O.M.T.; Heath, O.; Nichols, S.J.; Trevisan, C.; Novak, M.; McDermott, J.; et al. TGFBI Production by Macrophages Contributes to an Immunosuppressive Microenvironment in Ovarian Cancer. Cancer Res. 2021, 81, 5706–5719. [Google Scholar] [CrossRef] [PubMed]
  68. Rodriguez, G.C.; Haisley, C.; Hurteau, J.; Moser, T.L.; Whitaker, R.; Bast, R.C., Jr.; Stack, M.S. Regulation of invasion of epithelial ovarian cancer by transforming growth factor-beta. Gynecol Oncol 2001, 80, 245–253. [Google Scholar] [CrossRef] [PubMed]
  69. Fogg, K.C.; Olson, W.R.; Miller, J.N.; Khan, A.; Renner, C.; Hale, I.; Weisman, P.S.; Kreeger, P.K. Alternatively activated macrophage-derived secretome stimulates ovarian cancer spheroid spreading through a JAK2/STAT3 pathway. Cancer Lett. 2019, 458, 92–101. [Google Scholar] [CrossRef]
  70. Landskron, J.; Helland, Ø.; Torgersen, K.M.; Aandahl, E.M.; Gjertsen, B.T.; Bjørge, L.; Taskén, K. Activated regulatory and memory T-cells accumulate in malignant ascites from ovarian carcinoma patients. Cancer Immunol. Immunother. 2015, 64, 337–347. [Google Scholar] [CrossRef]
  71. Song, M.; Yeku, O.O.; Rafiq, S.; Purdon, T.; Dong, X.; Zhu, L.; Zhang, T.; Wang, H.; Yu, Z.; Mai, J.; et al. Tumor derived UBR5 promotes ovarian cancer growth and metastasis through inducing immunosuppressive macrophages. Nat. Commun. 2020, 11, 6298. [Google Scholar] [CrossRef]
  72. Kulbe, H.; Thompson, R.; Wilson, J.L.; Robinson, S.; Hagemann, T.; Fatah, R.; Gould, D.; Ayhan, A.; Balkwill, F. The inflammatory cytokine tumor necrosis factor-alpha generates an autocrine tumor-promoting network in epithelial ovarian cancer cells. Cancer Res. 2007, 67, 585–592. [Google Scholar] [CrossRef]
  73. Taki, M.; Abiko, K.; Baba, T.; Hamanishi, J.; Yamaguchi, K.; Murakami, R.; Yamanoi, K.; Horikawa, N.; Hosoe, Y.; Nakamura, E.; et al. Snail promotes ovarian cancer progression by recruiting myeloid-derived suppressor cells via CXCR2 ligand upregulation. Nat. Commun. 2018, 9, 1685. [Google Scholar] [CrossRef]
  74. Wang, Q.; Tang, Y.; Yu, H.; Yin, Q.; Li, M.; Shi, L.; Zhang, W.; Li, D.; Li, L. CCL18 from tumor-cells promotes epithelial ovarian cancer metastasis via mTOR signaling pathway. Mol. Carcinog. 2016, 55, 1688–1699. [Google Scholar] [CrossRef]
  75. Liu, W.; Wang, W.; Zhang, N.; Di, W. The Role of CCL20-CCR6 Axis in Ovarian Cancer Metastasis. Onco. Targets Ther. 2020, 13, 12739–12750. [Google Scholar] [CrossRef]
  76. Guo, Q.; Gao, B.L.; Zhang, X.J.; Liu, G.C.; Xu, F.; Fan, Q.Y.; Zhang, S.J.; Yang, B.; Wu, X.H. CXCL12-CXCR4 Axis Promotes Proliferation, Migration, Invasion, and Metastasis of Ovarian Cancer. Oncol. Res. 2014, 22, 247–258. [Google Scholar] [CrossRef]
  77. Ignacio, R.M.; Kabir, S.M.; Lee, E.S.; Adunyah, S.E.; Son, D.S. NF-κB-Mediated CCL20 Reigns Dominantly in CXCR2-Driven Ovarian Cancer Progression. PLoS ONE 2016, 11, e0164189. [Google Scholar] [CrossRef] [PubMed]
  78. Herr, D.; Sallmann, A.; Bekes, I.; Konrad, R.; Holzheu, I.; Kreienberg, R.; Wulff, C. VEGF induces ascites in ovarian cancer patients via increasing peritoneal permeability by downregulation of Claudin 5. Gynecol. Oncol. 2012, 127, 210–216. [Google Scholar] [CrossRef] [PubMed]
  79. Bruney, L.; Conley, K.C.; Moss, N.M.; Liu, Y.; Stack, M.S. Membrane-type I matrix metalloproteinase-dependent ectodomain shedding of mucin16/ CA-125 on ovarian cancer cells modulates adhesion and invasion of peritoneal mesothelium. Biol. Chem. 2014, 395, 1221–1231. [Google Scholar] [CrossRef] [PubMed]
  80. Rump, A.; Morikawa, Y.; Tanaka, M.; Minami, S.; Umesaki, N.; Takeuchi, M.; Miyajima, A. Binding of ovarian cancer antigen CA125/MUC16 to mesothelin mediates cell adhesion. J. Biol. Chem. 2004, 279, 9190–9198. [Google Scholar] [CrossRef] [PubMed]
  81. Chen, W.; Liang, X.; Peterson, A.J.; Munn, D.H.; Blazar, B.R. The indoleamine 2,3-dioxygenase pathway is essential for human plasmacytoid dendritic cell-induced adaptive T regulatory cell generation. J. Immunol. 2008, 181, 5396–5404. [Google Scholar] [CrossRef] [PubMed]
  82. Zhang, J.; Han, X.; Hu, X.; Jin, F.; Gao, Z.; Yin, L.; Qin, J.; Yin, F.; Li, C.; Wang, Y. IDO1 impairs NK cell cytotoxicity by decreasing NKG2D/NKG2DLs via promoting miR-18a. Mol. Immunol. 2018, 103, 144–155. [Google Scholar] [CrossRef]
  83. Sharma, S.; Yang, S.C.; Zhu, L.; Reckamp, K.; Gardner, B.; Baratelli, F.; Huang, M.; Batra, R.K.; Dubinett, S.M. Tumor cyclooxygenase-2/prostaglandin E2-dependent promotion of FOXP3 expression and CD4+ CD25+ T regulatory cell activities in lung cancer. Cancer Res. 2005, 65, 5211–5220. [Google Scholar] [CrossRef] [PubMed]
  84. Bronger, H.; Singer, J.; Windmüller, C.; Reuning, U.; Zech, D.; Delbridge, C.; Dorn, J.; Kiechle, M.; Schmalfeldt, B.; Schmitt, M.; et al. CXCL9 and CXCL10 predict survival and are regulated by cyclooxygenase inhibition in advanced serous ovarian cancer. Br. J. Cancer 2016, 115, 553–563. [Google Scholar] [CrossRef]
  85. Abrahams, V.M.; Straszewski, S.L.; Kamsteeg, M.; Hanczaruk, B.; Schwartz, P.E.; Rutherford, T.J.; Mor, G. Epithelial ovarian cancer cells secrete functional Fas ligand. Cancer Res. 2003, 63, 5573–5581. [Google Scholar]
  86. Webb, T.J.; Li, X.; Giuntoli, R.L., 2nd; Lopez, P.H.; Heuser, C.; Schnaar, R.L.; Tsuji, M.; Kurts, C.; Oelke, M.; Schneck, J.P. Molecular identification of GD3 as a suppressor of the innate immune response in ovarian cancer. Cancer Res. 2012, 72, 3744–3752. [Google Scholar] [CrossRef]
  87. Alberti, C.; Pinciroli, P.; Valeri, B.; Ferri, R.; Ditto, A.; Umezawa, K.; Sensi, M.; Canevari, S.; Tomassetti, A. Ligand-dependent EGFR activation induces the co-expression of IL-6 and PAI-1 via the NFkB pathway in advanced-stage epithelial ovarian cancer. Oncogene 2012, 31, 4139–4149. [Google Scholar] [CrossRef]
  88. Saini, U.; Naidu, S.; ElNaggar, A.C.; Bid, H.K.; Wallbillich, J.J.; Bixel, K.; Bolyard, C.; Suarez, A.A.; Kaur, B.; Kuppusamy, P.; et al. Elevated STAT3 expression in ovarian cancer ascites promotes invasion and metastasis: A potential therapeutic target. Oncogene 2017, 36, 168–181. [Google Scholar] [CrossRef] [PubMed]
  89. Chen, M.W.; Yang, S.T.; Chien, M.H.; Hua, K.T.; Wu, C.J.; Hsiao, S.M.; Lin, H.; Hsiao, M.; Su, J.L.; Wei, L.H. The STAT3-miRNA-92-Wnt Signaling Pathway Regulates Spheroid Formation and Malignant Progression in Ovarian Cancer. Cancer Res. 2017, 77, 1955–1967. [Google Scholar] [CrossRef] [PubMed]
  90. Johnson, D.E.; O’Keefe, R.A.; Grandis, J.R. Targeting the IL-6/JAK/STAT3 signalling axis in cancer. Nat. Rev. Clin. Oncol. 2018, 15, 234–248. [Google Scholar] [CrossRef]
  91. Deying, W.; Feng, G.; Shumei, L.; Hui, Z.; Ming, L.; Hongqing, W. CAF-derived HGF promotes cell proliferation and drug resistance by up-regulating the c-Met/PI3K/Akt and GRP78 signalling in ovarian cancer cells. Biosci. Rep. 2017, 37, BSR20160470. [Google Scholar] [CrossRef]
  92. Ozmadenci, D.; Shankara Narayanan, J.S.; Andrew, J.; Ojalill, M.; Barrie, A.M.; Jiang, S.; Iyer, S.; Chen, X.L.; Rose, M.; Estrada, V.; et al. Tumor FAK orchestrates immunosuppression in ovarian cancer via the CD155/TIGIT axis. Proc. Natl. Acad. Sci. USA 2022, 119, e2117065119. [Google Scholar] [CrossRef]
  93. Ehrlich, M.; Bacharach, E. Oncolytic Virotherapy: The Cancer Cell Side. Cancers 2021, 13, 931. [Google Scholar] [CrossRef]
  94. Ma, R.; Li, Z.; Chiocca, E.A.; Caligiuri, M.A.; Yu, J. The emerging field of oncolytic virus-based cancer immunotherapy. Trends Cancer 2023, 9, 122–139. [Google Scholar] [CrossRef] [PubMed]
  95. Lundstrom, K. Viral Vectors in Gene Therapy: Where Do We Stand in 2023? Viruses 2023, 15, 698. [Google Scholar] [CrossRef] [PubMed]
  96. Wang, Q.; Ma, X.; Wu, H.; Zhao, C.; Chen, J.; Li, R.; Yan, S.; Li, Y.; Zhang, Q.; Song, K.; et al. Oncolytic adenovirus with MUC16-BiTE shows enhanced antitumor immune response by reversing the tumor microenvironment in PDX model of ovarian cancer. Oncoimmunology 2022, 11, 2096362. [Google Scholar] [CrossRef] [PubMed]
  97. Shi, G.; Shi, P.; Yu, Y.; Xu, J.; Ma, J.; Zhang, Y.; Dong, Z.; Shen, L.; Dai, L.; Cheng, L.; et al. Oncolytic adenovirus inhibits malignant ascites of advanced ovarian cancer by reprogramming the ascitic immune microenvironment. Mol. Ther. Oncolytics 2021, 23, 488–500. [Google Scholar] [CrossRef]
  98. Alfano, A.; Cafferata, E.G.A.; Gangemi, M.; Nicola Candia, A.; Malnero, C.M.; Bermudez, I.; Lopez, M.V.; Ríos, G.D.; Rotondaro, C.; Cuneo, N.; et al. In Vitro and In Vivo Efficacy of a Stroma-Targeted, Tumor Microenvironment Responsive Oncolytic Adenovirus in Different Preclinical Models of Cancer. Int. J. Mol. Sci. 2023, 24, 9992. [Google Scholar] [CrossRef] [PubMed]
  99. Li, F.; Yuan, Y.; Dai, Y.; Cheng, T.; Cao, H.; Yan, D.; Li, Y.; Sun, Q.; Huang, X.; Gao, Q. M11: A Tropism-Modified Oncolytic Adenovirus Arming with a Tumor-Homing Peptide for Advanced Ovarian Cancer Therapies. Hum. Gene Ther. 2022, 33, 262–274. [Google Scholar] [CrossRef] [PubMed]
  100. Cui, Y.; Li, Y.; Li, S.; Li, W.; Zhu, Y.; Wang, J.; Liu, X.; Yue, Y.; Jin, N.; Li, X. Anti-tumor effect of a dual cancer-specific recombinant adenovirus on ovarian cancer cells. Exp. Cell Res. 2020, 396, 112185. [Google Scholar] [CrossRef] [PubMed]
  101. Santos, J.M.; Heiniö, C.; Cervera-Carrascon, V.; Quixabeira, D.C.A.; Siurala, M.; Havunen, R.; Butzow, R.; Zafar, S.; de Gruijl, T.; Lassus, H.; et al. Oncolytic adenovirus shapes the ovarian tumor microenvironment for potent tumor-infiltrating lymphocyte tumor reactivity. J. Immunother. Cancer 2020, 8, e000188. [Google Scholar] [CrossRef]
  102. Yue, E.; Yang, G.; Yao, Y.; Wang, G.; Mohanty, A.; Fan, F.; Zhao, L.; Zhang, Y.; Mirzapoiazova, T.; Walser, T.C.; et al. Targeting CA-125 Transcription by Development of a Conditionally Replicative Adenovirus for Ovarian Cancer Treatment. Cancers 2021, 13, 4265. [Google Scholar] [CrossRef] [PubMed]
  103. Basnet, S.; Santos, J.M.; Quixabeira, D.C.A.; Clubb, J.H.A.; Grönberg-Vähä-Koskela, S.A.M.; Arias, V.; Pakola, S.; Kudling, T.V.; Heiniö, C.; Havunen, R.; et al. Oncolytic adenovirus coding for bispecific T cell engager against human MUC-1 potentiates T cell response against solid tumors. Mol. Ther. Oncolytics 2023, 28, 59–73. [Google Scholar] [CrossRef] [PubMed]
  104. Tian, L.; Xu, B.; Teng, K.Y.; Song, M.; Zhu, Z.; Chen, Y.; Wang, J.; Zhang, J.; Feng, M.; Kaur, B.; et al. Targeting Fc Receptor-Mediated Effects and the “Don’t Eat Me” Signal with an Oncolytic Virus Expressing an Anti-CD47 Antibody to Treat Metastatic Ovarian Cancer. Clin. Cancer Res. 2022, 28, 201–214. [Google Scholar] [CrossRef] [PubMed]
  105. Huang, S.; Hu, H.; Tang, G.; Liu, K.; Luo, Z.; Zeng, W. An oncolytic herpes simplex virus type 1 strain expressing a single-chain variable region antibody fragment against PD-1 and a PI3K inhibitor synergize to elicit antitumor immunity in ovarian cancer. Arch. Virol. 2023, 168, 128. [Google Scholar] [CrossRef] [PubMed]
  106. Mistarz, A.; Winkler, M.; Battaglia, S.; Liu, S.; Hutson, A.; Rokita, H.; Gambotto, A.; Odunsi, K.O.; Singh, P.K.; McGray, A.J.R.; et al. Reprogramming the tumor microenvironment leverages CD8(+) T cell responses to a shared tumor/self antigen in ovarian cancer. Mol. Ther. Oncolytics 2023, 28, 230–248. [Google Scholar] [CrossRef] [PubMed]
  107. Van Vloten, J.P.; Matuszewska, K.; Minow, M.A.A.; Minott, J.A.; Santry, L.A.; Pereira, M.; Stegelmeier, A.A.; McAusland, T.M.; Klafuric, E.M.; Karimi, K.; et al. 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. J. Immunother. Cancer 2022, 10, e004335. [Google Scholar] [CrossRef] [PubMed]
  108. Gebremeskel, S.; Nelson, A.; Walker, B.; Oliphant, T.; Lobert, L.; Mahoney, D.; Johnston, B. Natural killer T cell immunotherapy combined with oncolytic vesicular stomatitis virus or reovirus treatments differentially increases survival in mouse models of ovarian and breast cancer metastasis. J. Immunother. Cancer 2021, 9, e002096. [Google Scholar] [CrossRef]
  109. Arulanandam, R.; Taha, Z.; Garcia, V.; Selman, M.; Chen, A.; Varette, O.; Jirovec, A.; Sutherland, K.; Macdonald, E.; Tzelepis, F.; et al. The strategic combination of trastuzumab emtansine with oncolytic rhabdoviruses leads to therapeutic synergy. Commun. Biol. 2020, 3, 254. [Google Scholar] [CrossRef]
  110. Muñoz-Alía, M.; Nace, R.A.; Tischer, A.; Zhang, L.; Bah, E.S.; Auton, M.; Russell, S.J. MeV-Stealth: A CD46-specific oncolytic measles virus resistant to neutralization by measles-immune human serum. PLoS Pathog. 2021, 17, e1009283. [Google Scholar] [CrossRef]
  111. McGray, A.J.R.; Huang, R.Y.; Battaglia, S.; Eppolito, C.; Miliotto, A.; Stephenson, K.B.; Lugade, A.A.; Webster, G.; Lichty, B.D.; Seshadri, M.; et al. Oncolytic Maraba virus armed with tumor antigen boosts vaccine priming and reveals diverse therapeutic response patterns when combined with checkpoint blockade in ovarian cancer. J. Immunother. Cancer 2019, 7, 189. [Google Scholar] [CrossRef]
  112. Matuszewska, K.; Santry, L.A.; van Vloten, J.P.; AuYeung, A.W.K.; Major, P.P.; Lawler, J.; Wootton, S.K.; Bridle, B.W.; Petrik, J. Combining Vascular Normalization with an Oncolytic Virus Enhances Immunotherapy in a Preclinical Model of Advanced-Stage Ovarian Cancer. Clin. Cancer Res. 2019, 25, 1624–1638. [Google Scholar] [CrossRef]
  113. Budzik, K.M.; Nace, R.A.; Ikeda, Y.; Russell, S.J. Oncolytic Foamy Virus-generation and properties of a nonpathogenic replicating retroviral vector system that targets chronically proliferating cancer cells. J. Virol. 2021, 95, e00015-21. [Google Scholar] [CrossRef] [PubMed]
  114. Opp, S.; Hurtado, A.; Pampeno, C.; Lin, Z.; Meruelo, D. Potent and Targeted Sindbis Virus Platform for Immunotherapy of Ovarian Cancer. Cells 2022, 12, 77. [Google Scholar] [CrossRef] [PubMed]
  115. Unno, Y.; Shino, Y.; Kondo, F.; Igarashi, N.; Wang, G.; Shimura, R.; Yamaguchi, T.; Asano, T.; Saisho, H.; Sekiya, S.; et al. Oncolytic viral therapy for cervical and ovarian cancer cells by Sindbis virus AR339 strain. Clin. Cancer Res. 2005, 11, 4553–4560. [Google Scholar] [CrossRef] [PubMed]
  116. Strauss, J.H.; Strauss, E.G. The alphaviruses: Gene expression, replication, and evolution. Microbiol. Rev. 1994, 58, 491–562. [Google Scholar] [CrossRef] [PubMed]
  117. Jose, J.; Snyder, J.E.; Kuhn, R.J. A structural and functional perspective of alphavirus replication and assembly. Future Microbiol. 2009, 4, 837–856. [Google Scholar] [CrossRef] [PubMed]
  118. Zimmerman, O.; Holmes, A.C.; Kafai, N.M.; Adams, L.J.; Diamond, M.S. Entry receptors-the gateway to alphavirus infection. J. Clin. Investig. 2023, 133, e165307. [Google Scholar] [CrossRef] [PubMed]
  119. Xiong, C.; Levis, R.; Shen, P.; Schlesinger, S.; Rice, C.M.; Huang, H.V. Sindbis virus: An efficient, broad host range vector for gene expression in animal cells. Science 1989, 243, 1188–1191. [Google Scholar] [CrossRef] [PubMed]
  120. Frolov, I.; Hoffman, T.A.; Prágai, B.M.; Dryga, S.A.; Huang, H.V.; Schlesinger, S.; Rice, C.M. Alphavirus-based expression vectors: Strategies and applications. Proc. Natl. Acad. Sci. USA 1996, 93, 11371–11377. [Google Scholar] [CrossRef]
  121. Froshauer, S.; Kartenbeck, J.; Helenius, A. Alphavirus RNA replicase is located on the cytoplasmic surface of endosomes and lysosomes. J. Cell Biol. 1988, 107, 2075–2086. [Google Scholar] [CrossRef]
  122. Kujala, P.; Ikaheimonen, A.; Ehsani, N.; Vihinen, H.; Auvinen, P.; Kaariainen, L. Biogenesis of the Semliki Forest virus RNA replication complex. J. Virol. 2001, 75, 3873–3884. [Google Scholar] [CrossRef] [PubMed]
  123. Bredenbeek, P.J.; Frolov, I.; Rice, C.M.; Schlesinger, S. Sindbis virus expression vectors: Packaging of RNA replicons by using defective helper RNAs. J. Virol. 1993, 67, 6439–6446. [Google Scholar] [CrossRef] [PubMed]
  124. Scaglione, A.; Opp, S.; Hurtado, A.; Lin, Z.; Pampeno, C.; Noval, M.G.; Thannickal, S.A.; Stapleford, K.A.; Meruelo, D. Combination of a Sindbis-SARS-CoV-2 Spike Vaccine and alphaOX40 Antibody Elicits Protective Immunity Against SARS-CoV-2 Induced Disease and Potentiates Long-Term SARS-CoV-2-Specific Humoral and T-Cell Immunity. Front. Immunol. 2021, 12, 719077. [Google Scholar] [CrossRef] [PubMed]
  125. Tseng, J.C.; Hurtado, A.; Yee, H.; Levin, B.; Boivin, C.; Benet, M.; Blank, S.V.; Pellicer, A.; Meruelo, D. Using sindbis viral vectors for specific detection and suppression of advanced ovarian cancer in animal models. Cancer Res. 2004, 64, 6684–6692. [Google Scholar] [CrossRef] [PubMed]
  126. Venticinque, L.; Meruelo, D. Sindbis viral vector induced apoptosis requires translational inhibition and signaling through Mcl-1 and Bak. Mol. Cancer 2010, 9, 37. [Google Scholar] [CrossRef] [PubMed]
  127. Zhang, J.; Frolov, I.; Russell, S.J. Gene therapy for malignant glioma using Sindbis vectors expressing a fusogenic membrane glycoprotein. J. Gene Med. 2004, 6, 1082–1091. [Google Scholar] [CrossRef]
  128. Chen, Z.; Moyana, T.; Saxena, A.; Warrington, R.; Jia, Z.; Xiang, J. Efficient antitumor immunity derived from maturation of dendritic cells that had phagocytosed apoptotic/necrotic tumor cells. Int. J. Cancer 2001, 93, 539–548. [Google Scholar] [CrossRef]
  129. Granot, T.; Yamanashi, Y.; Meruelo, D. Sindbis viral vectors transiently deliver tumor-associated antigens to lymph nodes and elicit diversified antitumor CD8+ T-cell immunity. Mol. Ther. 2014, 22, 112–122. [Google Scholar] [CrossRef]
  130. Huckriede, A.; Bungener, L.; Holtrop, M.; de Vries, J.; Waarts, B.L.; Daemen, T.; Wilschut, J. Induction of cytotoxic T lymphocyte activity by immunization with recombinant Semliki Forest virus: Indications for cross-priming. Vaccine 2004, 22, 1104–1113. [Google Scholar] [CrossRef]
  131. Alexopoulou, L.; Holt, A.C.; Medzhitov, R.; Flavell, R.A. Recognition of double-stranded RNA and activation of NF-kappaB by Toll-like receptor 3. Nature 2001, 413, 732–738. [Google Scholar] [CrossRef]
  132. Fournier, P.; Zeng, J.; Schirrmacher, V. Two ways to induce innate immune responses in human PBMCs: Paracrine stimulation of IFN-alpha responses by viral protein or dsRNA. Int. J. Oncol. 2003, 23, 673–680. [Google Scholar] [CrossRef]
  133. Granot, T.; Venticinque, L.; Tseng, J.C.; Meruelo, D. Activation of cytotoxic and regulatory functions of NK cells by Sindbis viral vectors. PLoS ONE 2011, 6, e20598. [Google Scholar] [CrossRef]
  134. Leitner, W.W.; Hwang, L.N.; deVeer, M.J.; Zhou, A.; Silverman, R.H.; Williams, B.R.; Dubensky, T.W.; Ying, H.; Restifo, N.P. Alphavirus-based DNA vaccine breaks immunological tolerance by activating innate antiviral pathways. Nat. Med. 2003, 9, 33–39. [Google Scholar] [CrossRef]
  135. Martin-Fontecha, A.; Thomsen, L.L.; Brett, S.; Gerard, C.; Lipp, M.; Lanzavecchia, A.; Sallusto, F. Induced recruitment of NK cells to lymph nodes provides IFN-gamma for T(H)1 priming. Nat. Immunol. 2004, 5, 1260–1265. [Google Scholar] [CrossRef] [PubMed]
  136. Vivier, E.; Tomasello, E.; Baratin, M.; Walzer, T.; Ugolini, S. Functions of natural killer cells. Nat. Immunol. 2008, 9, 503–510. [Google Scholar] [CrossRef] [PubMed]
  137. Wang, L.; Smith, D.; Bot, S.; Dellamary, L.; Bloom, A.; Bot, A. Noncoding RNA danger motifs bridge innate and adaptive immunity and are potent adjuvants for vaccination. J. Clin. Investig. 2002, 110, 1175–1184. [Google Scholar] [CrossRef] [PubMed]
  138. Choi, Y.; Chang, J. Viral vectors for vaccine applications. Clin. Exp. Vaccine Res. 2013, 2, 97–105. [Google Scholar] [CrossRef] [PubMed]
  139. Scherwitzl, I.; Hurtado, A.; Pierce, C.M.; Vogt, S.; Pampeno, C.; Meruelo, D. Systemically Administered Sindbis Virus in Combination with Immune Checkpoint Blockade Induces Curative Anti-tumor Immunity. Mol. Ther. Oncolytics 2018, 9, 51–63. [Google Scholar] [CrossRef] [PubMed]
  140. Gardner, J.P.; Frolov, I.; Perri, S.; Ji, Y.; MacKichan, M.L.; zur Megede, J.; Chen, M.; Belli, B.A.; Driver, D.A.; Sherrill, S.; et al. Infection of human dendritic cells by a sindbis virus replicon vector is determined by a single amino acid substitution in the E2 glycoprotein. J. Virol. 2000, 74, 11849–11857. [Google Scholar] [CrossRef] [PubMed]
  141. MacDonald, G.H.; Johnston, R.E. Role of dendritic cell targeting in Venezuelan equine encephalitis virus pathogenesis. J. Virol. 2000, 74, 914–922. [Google Scholar] [CrossRef] [PubMed]
  142. Osada, T.; Morse, M.A.; Hobeika, A.; Lyerly, H.K. Novel recombinant alphaviral and adenoviral vectors for cancer immunotherapy. Semin. Oncol. 2012, 39, 305–310. [Google Scholar] [CrossRef]
  143. Pushko, P.; Parker, M.; Ludwig, G.V.; Davis, N.L.; Johnston, R.E.; Smith, J.F. Replicon-helper systems from attenuated Venezuelan equine encephalitis virus: Expression of heterologous genes in vitro and immunization against heterologous pathogens in vivo. Virology 1997, 239, 389–401. [Google Scholar] [CrossRef] [PubMed]
  144. Uematsu, Y.; Vajdy, M.; Lian, Y.; Perri, S.; Greer, C.E.; Legg, H.S.; Galli, G.; Saletti, G.; Otten, G.R.; Rappuoli, R.; et al. Lack of interference with immunogenicity of a chimeric alphavirus replicon particle-based influenza vaccine by preexisting antivector immunity. Clin. Vaccine Immunol. 2012, 19, 991–998. [Google Scholar] [CrossRef]
  145. Brummer-Korvenkontio, M.; Vapalahti, O.; Kuusisto, P.; Saikku, P.; Manni, T.; Koskela, P.; Nygren, T.; Brummer-Korvenkontio, H.; Vaheri, A. Epidemiology of Sindbis virus infections in Finland 1981-96: Possible factors explaining a peculiar disease pattern. Epidemiol. Infect. 2002, 129, 335–345. [Google Scholar] [CrossRef] [PubMed]
  146. Hardwick, J.M.; Levine, B. Sindbis virus vector system for functional analysis of apoptosis regulators. Methods Enzymol. 2000, 322, 492–508. [Google Scholar] [CrossRef]
  147. Manni, T.; Kurkela, S.; Vaheri, A.; Vapalahti, O. Diagnostics of Pogosta disease: Antigenic properties and evaluation of Sindbis virus IgM and IgG enzyme immunoassays. Vector Borne Zoonotic Dis. 2008, 8, 303–311. [Google Scholar] [CrossRef]
  148. Pampeno, C.; Hurtado, A.; Opp, S.; Meruelo, D. Channeling the Natural Properties of Sindbis Alphavirus for Targeted Tumor Therapy. Int. J. Mol. Sci. 2023, 24, 14948. [Google Scholar] [CrossRef]
  149. Tseng, J.C.; Levin, B.; Hurtado, A.; Yee, H.; Perez de Castro, I.; Jimenez, M.; Shamamian, P.; Jin, R.; Novick, R.P.; Pellicer, A.; et al. Systemic tumor targeting and killing by Sindbis viral vectors. Nat. Biotechnol. 2004, 22, 70–77. [Google Scholar] [CrossRef] [PubMed]
  150. Roby, K.F.; Taylor, C.C.; Sweetwood, J.P.; Cheng, Y.; Pace, J.L.; Tawfik, O.; Persons, D.L.; Smith, P.G.; Terranova, P.F. Development of a syngeneic mouse model for events related to ovarian cancer. Carcinogenesis 2000, 21, 585–591. [Google Scholar] [CrossRef] [PubMed]
  151. Strauss, J.H.; Wang, K.S.; Schmaljohn, A.L.; Kuhn, R.J.; Strauss, E.G. Host-cell receptors for Sindbis virus. Arch. Virol. Suppl. 1994, 9, 473–484. [Google Scholar] [CrossRef]
  152. Wang, K.S.; Kuhn, R.J.; Strauss, E.G.; Ou, S.; Strauss, J.H. High-affinity laminin receptor is a receptor for Sindbis virus in mammalian cells. J. Virol. 1992, 66, 4992–5001. [Google Scholar] [CrossRef]
  153. Liotta, L.A.; Rao, C.N.; Wewer, U.M. Biochemical interactions of tumor cells with the basement membrane. Annu. Rev. Biochem. 1986, 55, 1037–1057. [Google Scholar] [CrossRef]
  154. Scheiman, J.; Tseng, J.C.; Zheng, Y.; Meruelo, D. Multiple functions of the 37/67-kd laminin receptor make it a suitable target for novel cancer gene therapy. Mol. Ther. 2010, 18, 63–74. [Google Scholar] [CrossRef]
  155. DiGiacomo, V.; Meruelo, D. Looking into laminin receptor: Critical discussion regarding the non-integrin 37/67-kDa laminin receptor/RPSA protein. Biol. Rev. Camb. Philos. Soc. 2016, 91, 288–310. [Google Scholar] [CrossRef]
  156. Hurtado, A.; Tseng, J.C.; Boivin, C.; Levin, B.; Yee, H.; Pampeno, C.; Meruelo, D. Identification of amino acids of Sindbis virus E2 protein involved in targeting tumor metastases in vivo. Mol. Ther. 2005, 12, 813–823. [Google Scholar] [CrossRef]
  157. De Manzoni, G.; Guglielmi, A.; Verlato, G.; Tomezzoli, A.; Pelosi, G.; Schiavon, I.; Cordiano, C. Prognostic significance of 67-kDa laminin receptor expression in advanced gastric cancer. Oncology 1998, 55, 456–460. [Google Scholar] [CrossRef] [PubMed]
  158. Martignone, S.; Menard, S.; Bufalino, R.; Cascinelli, N.; Pellegrini, R.; Tagliabue, E.; Andreola, S.; Rilke, F.; Colnaghi, M.I. Prognostic significance of the 67-kilodalton laminin receptor expression in human breast carcinomas. J. Natl. Cancer Inst. 1993, 85, 398–402. [Google Scholar] [CrossRef] [PubMed]
  159. Ozaki, I.; Yamamoto, K.; Mizuta, T.; Kajihara, S.; Fukushima, N.; Setoguchi, Y.; Morito, F.; Sakai, T. Differential expression of laminin receptors in human hepatocellular carcinoma. Gut 1998, 43, 837–842. [Google Scholar] [CrossRef]
  160. Sanjuan, X.; Fernandez, P.L.; Miquel, R.; Munoz, J.; Castronovo, V.; Menard, S.; Palacin, A.; Cardesa, A.; Campo, E. Overexpression of the 67-kD laminin receptor correlates with tumour progression in human colorectal carcinoma. J. Pathol. 1996, 179, 376–380. [Google Scholar] [CrossRef]
  161. Taraboletti, G.; Belotti, D.; Giavazzi, R.; Sobel, M.E.; Castronovo, V. Enhancement of metastatic potential of murine and human melanoma cells by laminin receptor peptide G: Attachment of cancer cells to subendothelial matrix as a pathway for hematogenous metastasis. J. Natl. Cancer Inst. 1993, 85, 235–240. [Google Scholar] [CrossRef]
  162. Van den Brule, F.A.; Berchuck, A.; Bast, R.C.; Liu, F.T.; Gillet, C.; Sobel, M.E.; Castronovo, V. Differential expression of the 67-kD laminin receptor and 31-kD human laminin-binding protein in human ovarian carcinomas. Eur. J. Cancer 1994, 30, 1096–1099. [Google Scholar] [CrossRef]
  163. Van den Brule, F.A.; Castronovo, V.; Menard, S.; Giavazzi, R.; Marzola, M.; Belotti, D.; Taraboletti, G. Expression of the 67 kD laminin receptor in human ovarian carcinomas as defined by a monoclonal antibody, MLuC5. Eur. J. Cancer 1996, 32, 1598–1602. [Google Scholar] [CrossRef]
  164. Ardini, E.; Sporchia, B.; Pollegioni, L.; Modugno, M.; Ghirelli, C.; Castiglioni, F.; Tagliabue, E.; Ménard, S. Identification of a novel function for 67-kDa laminin receptor: Increase in laminin degradation rate and release of motility fragments. Cancer Res. 2002, 62, 1321–1325. [Google Scholar]
  165. Hand, P.H.; Thor, A.; Schlom, J.; Rao, C.N.; Liotta, L. Expression of laminin receptor in normal and carcinomatous human tissues as defined by a monoclonal antibody. Cancer Res. 1985, 45, 2713–2719. [Google Scholar]
  166. Hayman, E.G.; Engvall, E.; Ruoslahti, E. Concomitant loss of cell surface fibronectin and laminin from transformed rat kidney cells. J. Cell Biol. 1981, 88, 352–357. [Google Scholar] [CrossRef]
  167. Liotta, L.A. Tumor invasion and metastases: Role of the basement membrane. Warner-Lambert Parke-Davis Award lecture. Am. J. Pathol. 1984, 117, 339–348. [Google Scholar]
  168. Rose, P.P.; Hanna, S.L.; Spiridigliozzi, A.; Wannissorn, N.; Beiting, D.P.; Ross, S.R.; Hardy, R.W.; Bambina, S.A.; Heise, M.T.; Cherry, S. Natural resistance-associated macrophage protein is a cellular receptor for sindbis virus in both insect and mammalian hosts. Cell Host Microbe 2011, 10, 97–104. [Google Scholar] [CrossRef]
  169. Clark, L.E.; Clark, S.A.; Lin, C.; Liu, J.; Coscia, A.; Nabel, K.G.; Yang, P.; Neel, D.V.; Lee, H.; Brusic, V.; et al. VLDLR and ApoER2 are receptors for multiple alphaviruses. Nature 2022, 602, 475–480. [Google Scholar] [CrossRef] [PubMed]
  170. De Caluwe, L.; Coppens, S.; Vereecken, K.; Daled, S.; Dhaenens, M.; Van Ostade, X.; Deforce, D.; Arien, K.K.; Bartholomeeusen, K. The CD147 Protein Complex Is Involved in Entry of Chikungunya Virus and Related Alphaviruses in Human Cells. Front. Microbiol. 2021, 12, 615165. [Google Scholar] [CrossRef] [PubMed]
  171. Zhang, J.; Wang, Z.; Zhang, X.; Dai, Z.; Zhi-Peng, W.; Yu, J.; Peng, Y.; Wu, W.; Zhang, N.; Luo, P.; et al. Large-Scale Single-Cell and Bulk Sequencing Analyses Reveal the Prognostic Value and Immune Aspects of CD147 in Pan-Cancer. Front. Immunol. 2022, 13, 810471. [Google Scholar] [CrossRef] [PubMed]
  172. Lau, D.H.; Lewis, A.D.; Ehsan, M.N.; Sikic, B.I. Multifactorial mechanisms associated with broad cross-resistance of ovarian carcinoma cells selected by cyanomorpholino doxorubicin. Cancer Res. 1991, 51, 5181–5187. [Google Scholar]
  173. Nguyen, H.M.; Guz-Montgomery, K.; Saha, D. Oncolytic Virus Encoding a Master Pro-Inflammatory Cytokine Interleukin 12 in Cancer Immunotherapy. Cells 2020, 9, 400. [Google Scholar] [CrossRef]
  174. Bortolanza, S.; Bunuales, M.; Otano, I.; Gonzalez-Aseguinolaza, G.; Ortiz-de-Solorzano, C.; Perez, D.; Prieto, J.; Hernandez-Alcoceba, R. Treatment of pancreatic cancer with an oncolytic adenovirus expressing interleukin-12 in Syrian hamsters. Mol. Ther. 2009, 17, 614–622. [Google Scholar] [CrossRef]
  175. Huang, J.H.; Zhang, S.N.; Choi, K.J.; Choi, I.K.; Kim, J.H.; Lee, M.G.; Lee, M.; Kim, H.; Yun, C.O. Therapeutic and tumor-specific immunity induced by combination of dendritic cells and oncolytic adenovirus expressing IL-12 and 4-1BBL. Mol. Ther. 2010, 18, 264–274. [Google Scholar] [CrossRef]
  176. Kim, W.; Seong, J.; Oh, H.J.; Koom, W.S.; Choi, K.J.; Yun, C.O. A novel combination treatment of armed oncolytic adenovirus expressing IL-12 and GM-CSF with radiotherapy in murine hepatocarcinoma. J. Radiat. Res. 2011, 52, 646–654. [Google Scholar] [CrossRef] [PubMed]
  177. Quetglas, J.I.; Labiano, S.; Aznar, M.A.; Bolanos, E.; Azpilikueta, A.; Rodriguez, I.; Casales, E.; Sanchez-Paulete, A.R.; Segura, V.; Smerdou, C.; et al. Virotherapy with a Semliki Forest Virus-Based Vector Encoding IL12 Synergizes with PD-1/PD-L1 Blockade. Cancer Immunol. Res. 2015, 3, 449–454. [Google Scholar] [CrossRef]
  178. Yang, Z.; Zhang, Q.; Xu, K.; Shan, J.; Shen, J.; Liu, L.; Xu, Y.; Xia, F.; Bie, P.; Zhang, X.; et al. Combined therapy with cytokine-induced killer cells and oncolytic adenovirus expressing IL-12 induce enhanced antitumor activity in liver tumor model. PLoS ONE 2012, 7, e44802. [Google Scholar] [CrossRef] [PubMed]
  179. Zhang, S.N.; Choi, I.K.; Huang, J.H.; Yoo, J.Y.; Choi, K.J.; Yun, C.O. Optimizing DC vaccination by combination with oncolytic adenovirus coexpressing IL-12 and GM-CSF. Mol. Ther. 2011, 19, 1558–1568. [Google Scholar] [CrossRef]
  180. Hurtado, A.; Tseng, J.C.; Meruelo, D. Gene therapy that safely targets and kills tumor cells throughout the body. Rejuvenation Res. 2006, 9, 36–44. [Google Scholar] [CrossRef]
  181. Scherwitzl, I.; Opp, S.; Hurtado, A.M.; Pampeno, C.; Loomis, C.; Kannan, K.; Yu, M.; Meruelo, D. Sindbis Virus with Anti-OX40 Overcomes the Immunosuppressive Tumor Microenvironment of Low-Immunogenic Tumors. Mol. Ther. Oncolytics 2020, 17, 431–447. [Google Scholar] [CrossRef] [PubMed]
  182. Sun, K.; Shi, X.; Li, L.; Nie, X.; Xu, L.; Jia, F.; Xu, F. Oncolytic Viral Therapy for Glioma by Recombinant Sindbis Virus. Cancers 2023, 15, 4738. [Google Scholar] [CrossRef] [PubMed]
  183. Liu, J.; Cao, S.; Kim, S.; Chung, E.Y.; Homma, Y.; Guan, X.; Jimenez, V.; Ma, X. Interleukin-12: An update on its immunological activities, signaling and regulation of gene expression. Curr. Immunol. Rev. 2005, 1, 119–137. [Google Scholar] [CrossRef] [PubMed]
  184. Aspeslagh, S.; Postel-Vinay, S.; Rusakiewicz, S.; Soria, J.C.; Zitvogel, L.; Marabelle, A. Rationale for anti-OX40 cancer immunotherapy. Eur. J. Cancer 2016, 52, 50–66. [Google Scholar] [CrossRef] [PubMed]
  185. Bansal-Pakala, P.; Halteman, B.S.; Cheng, M.H.; Croft, M. Costimulation of CD8 T cell responses by OX40. J. Immunol. 2004, 172, 4821–4825. [Google Scholar] [CrossRef] [PubMed]
  186. Gramaglia, I.; Weinberg, A.D.; Lemon, M.; Croft, M. Ox-40 ligand: A potent costimulatory molecule for sustaining primary CD4 T cell responses. J. Immunol. 1998, 161, 6510–6517. [Google Scholar] [CrossRef]
  187. Paterson, D.J.; Jefferies, W.A.; Green, J.R.; Brandon, M.R.; Corthesy, P.; Puklavec, M.; Williams, A.F. Antigens of activated rat T lymphocytes including a molecule of 50,000 Mr detected only on CD4 positive T blasts. Mol. Immunol. 1987, 24, 1281–1290. [Google Scholar] [CrossRef]
  188. Wang, Q.; Shi, B.M.; Xie, F.; Fu, Z.Y.; Chen, Y.J.; An, J.N.; Ma, Y.; Liu, C.P.; Zhang, X.K.; Zhang, X.G. Enhancement of CD4(+) T cell response and survival via coexpressed OX40/OX40L in Graves’ disease. Mol. Cell Endocrinol. 2016, 430, 115–124. [Google Scholar] [CrossRef]
  189. Zander, R.A.; Obeng-Adjei, N.; Guthmiller, J.J.; Kulu, D.I.; Li, J.; Ongoiba, A.; Traore, B.; Crompton, P.D.; Butler, N.S. PD-1 Co-inhibitory and OX40 Co-stimulatory Crosstalk Regulates Helper T Cell Differentiation and Anti-Plasmodium Humoral Immunity. Cell Host Microbe 2015, 17, 628–641. [Google Scholar] [CrossRef]
  190. Song, A.; Tang, X.; Harms, K.M.; Croft, M. OX40 and Bcl-xL promote the persistence of CD8 T cells to recall tumor-associated antigen. J. Immunol. 2005, 175, 3534–3541. [Google Scholar] [CrossRef] [PubMed]
  191. Tahiliani, V.; Hutchinson, T.E.; Abboud, G.; Croft, M.; Salek-Ardakani, S. OX40 Cooperates with ICOS To Amplify Follicular Th Cell Development and Germinal Center Reactions during Infection. J. Immunol. 2017, 198, 218–228. [Google Scholar] [CrossRef] [PubMed]
  192. Zhang, X.; Xiao, X.; Lan, P.; Li, J.; Dou, Y.; Chen, W.; Ishii, N.; Chen, S.; Xia, B.; Chen, K.; et al. OX40 Costimulation Inhibits Foxp3 Expression and Treg Induction via BATF3-Dependent and Independent Mechanisms. Cell Rep. 2018, 24, 607–618. [Google Scholar] [CrossRef]
  193. Delgoffe, G.M. Filling the Tank: Keeping Antitumor T Cells Metabolically Fit for the Long Haul. Cancer Immunol. Res. 2016, 4, 1001–1006. [Google Scholar] [CrossRef] [PubMed]
  194. Siska, P.J.; Rathmell, J.C. T cell metabolic fitness in antitumor immunity. Trends Immunol. 2015, 36, 257–264. [Google Scholar] [CrossRef] [PubMed]
  195. Russell, S.; Wojtkowiak, J.; Neilson, A.; Gillies, R.J. Metabolic Profiling of healthy and cancerous tissues in 2D and 3D. Sci. Rep. 2017, 7, 15285. [Google Scholar] [CrossRef] [PubMed]
  196. Kruse, B.; Buzzai, A.C.; Shridhar, N.; Braun, A.D.; Gellert, S.; Knauth, K.; Pozniak, J.; Peters, J.; Dittmann, P.; Mengoni, M.; et al. CD4(+) T cell-induced inflammatory cell death controls immune-evasive tumours. Nature 2023, 618, 1033–1044. [Google Scholar] [CrossRef] [PubMed]
  197. Speiser, D.E.; Chijioke, O.; Schaeuble, K.; Münz, C. CD4(+) T cells in cancer. Nat. Cancer 2023, 4, 317–329. [Google Scholar] [CrossRef] [PubMed]
  198. Chianese, A.; Santella, B.; Ambrosino, A.; Stelitano, D.; Rinaldi, L.; Galdiero, M.; Zannella, C.; Franci, G. Oncolytic Viruses in Combination Therapeutic Approaches with Epigenetic Modulators: Past, Present and Future Perspecties. Cancers 2021, 13, 2761. [Google Scholar] [CrossRef] [PubMed]
  199. Murphy, S.A.; Mapes, N.J., Jr.; Dua, D.; Kaur, B. Histone Modifiers at the Crossroads of Oncolytic and Oncogenic Viruses. Mol. Ther. 2022, 30, 2153–2162. [Google Scholar] [CrossRef]
  200. Hulin-Curtis, S.L.; Davies, J.A.; Jones, R.; Hudson, E.; Hanna, L.; Chester, J.D.; Parker, A.L. Histone Deacetylase Inhibitor Tricostatin A Sensitizes Cisplatin-Resistant Ovarian Cancer Cells to Oncolytic Adenovirus. Oncotarget 2018, 9, 26328–26341. [Google Scholar] [CrossRef]
Ijms 25 02925 g001
Figure 1. Preparation of SV vector. Plasmids are linearized, transcribed by T7 polymerase and capped in vitro. Transcripts are electroporated into BHK cells and viral vectors harvested from media [148]. T7, transcription promoter; Psg, Sindbis subgenomic promoter; GOI, gene of interest; AAA poly A tail; BHK, baby hamster kidney cells. Created with Biorender.
Figure 1. Preparation of SV vector. Plasmids are linearized, transcribed by T7 polymerase and capped in vitro. Transcripts are electroporated into BHK cells and viral vectors harvested from media [148]. T7, transcription promoter; Psg, Sindbis subgenomic promoter; GOI, gene of interest; AAA poly A tail; BHK, baby hamster kidney cells. Created with Biorender.
Ijms 25 02925 g001
Ijms 25 02925 g002
Figure 2. SV/Fluc vectors detect syngeneic MOSEC metastases in the peritoneum of immunocompetent C57BL/6 mice. Left panel: Four weeks after intraperitoneal injection (i.p.) of 1 × 107 MOSEC cells, mice were treated with a single i.p. injection of SV/Fluc vectors (~107 transducing units) and IVIS imaged the next day. Tumor free control mice were injected with SV/Fluc and imaged in parallel (Right panel) [125].
Figure 2. SV/Fluc vectors detect syngeneic MOSEC metastases in the peritoneum of immunocompetent C57BL/6 mice. Left panel: Four weeks after intraperitoneal injection (i.p.) of 1 × 107 MOSEC cells, mice were treated with a single i.p. injection of SV/Fluc vectors (~107 transducing units) and IVIS imaged the next day. Tumor free control mice were injected with SV/Fluc and imaged in parallel (Right panel) [125].
Ijms 25 02925 g002
Ijms 25 02925 g003
Figure 3. Mice treated with either SV.IL-12 or SV.IgGOX40.IL-12 at day 140 were rechallenged with MOSEC cells. The survivor mice were protected from recurrence after rechallenge [114,148].
Figure 3. Mice treated with either SV.IL-12 or SV.IgGOX40.IL-12 at day 140 were rechallenged with MOSEC cells. The survivor mice were protected from recurrence after rechallenge [114,148].
Ijms 25 02925 g003
Ijms 25 02925 g004
Figure 4. Summary of synergistic immune stimulating anti-tumor mechanism of armed SVs via (1) direct tumor oncolysis and (2) tumor influx of activated immune cells that enhance the anti-tumor response in the tumor microenvironment (TME) [114].
Figure 4. Summary of synergistic immune stimulating anti-tumor mechanism of armed SVs via (1) direct tumor oncolysis and (2) tumor influx of activated immune cells that enhance the anti-tumor response in the tumor microenvironment (TME) [114].
Ijms 25 02925 g004
Table 1. Pro-tumor cytokines and chemokines.
Table 1. Pro-tumor cytokines and chemokines.
CytokineOriginEffectsRefs.
IL-1βEOC↑ tumor aggressiveness; T regs; ↓ NK and mT cells[57,58]
IL-6EOC, CAFs, TAMs, adipocytes↓ DC maturation; immunosuppression; ↑ MDSCs activates cell signaling pathways [59,60]
that ↑ cell proliferation; ↑ EMT[59,60,61]
IL-8EOC, CAFs↑ angiogenesis, ↑ cancer cell migration[62,63]
IL-10EOC, T regs, TAMs↑ MDSCs; ↓ CD8 T cell function; ↑ M2 polarization[64]
IL-13EOC, CD4 Th2↑ EOC invasion and metastasis[65,66]
TGFβMDSCs, CAFs, TAMs↑ EMT; activates JAK/STAT-3; ↑ MMPs;
↑ Tregs; ↑ metastasis; ↑ VEGF		[67,68,69,70]
CSF-1EOCrecruit and activate M2 TAMs[45,71]
TNF⍺EOC↑ metastasis; ↑ VEGF[72]
ChemokineOriginEffectsRefs.
CCL1EOC, CAFs, TAMsdrives MDSCs to tumor[73]
CCL2EOCrecruit and activate M2 TAMs[71]
CCL18EOC↑ EOC invasion and metastasis[74]
CCL20EOC↑ metastasis[75]
CXCL12EOC, stromal cells↑ EOC invasion and metastasis[76,77]
EOCs, epithelial ovarian cancer cells; Tregs, regulatory T cells; NK, natural killer cells; mT cells, memory T cells; CAFs, cancer associated fibroblasts: TAMs, tumor associated macrophage; DC, dendritic cell; MDSCs; myeloid derived suppressor cells; EMT, epithelial to mesenchymal transition; M2, pro-tumor macrophage; JAK/STAT-3, Janus kinases/signal transducer and activator of transcription; MMPs, matrix metalloproteinases; VEGF, vascular endothelial growth factor. ↑, increased; ↓, decreased.
Table 2. Pro-Tumor signaling factors and pathways.
Table 2. Pro-Tumor signaling factors and pathways.
ComponentsOriginEffectsRefs.
VEGFEOC, mesothelial cells↑ peritoneal, vascular permeability; ↑ MMP[10,15,78]
CA-125(MUC16)EOCEOC adhesion to mesothelial cells; ↑ invasiveness[79,80]
IDOMDSCs,↑ T regs; ↓ NK function[81,82]
COX2/PGE2EOC↑ MDSCs; ↓ TIL recruitment; ↑ Tregs[83,84]
CD95L (Fas)EOC exosomeskills immune cells expressing CD95R[85]
GD3 gangliocideEOCsuppresses the innate immune response[86]
PathwaysOriginEffectsRefs.
NFkBEOC, macrophage↑ growth; ↑ invasiveness; ↑ angiogenesis; immunosuppression[21,87]
STAT3EOC, CAFskey role in tumor progression
↑ angiogenesis ↓ apoptosis;
↑ M2 polarization ↑ EMT in spheroids ↑ T regs; ↑ MDSCs; ↑ proliferation and metastasis[88,89,90]
PI3K/AKTEOC, CAFs↑ EMT, OC cell growth[91]
FAKEOC↓ TILs[92]
CA-125(MUC16), cancer antigen, mucin; IDO, indolamine 2,3-dioxygenase; COX-2, cyclooxygenase-2; PGE2, prostaglandin E2; TIL, tumor infiltrating lymphocyte; NFκB, nuclear factor κB; PIK, phosphinositide 3-kinase; AKT, protein kinase B; FAK, focal adhesion kinase. ↑, increased; ↓, decreased
Table 3. Studies of Oncolytic Virus-mediated Treatment of Ovarian Cancer.
Table 3. Studies of Oncolytic Virus-mediated Treatment of Ovarian Cancer.
Virus TypeFamilyDesignationVirus Modification/Combined TreatmentRefs.
dsDNAAdenoviridaeOAd-MUC16-BiTEexpresses bispecific Ab to MUC16 and CD3[96]
Ad5 ΔE1b, E3combination with anti-PD-1, CSF-R1 inhibitor[97]
AR2011(h404)expresses hCD40 and h41BBL combined with cisplatin[98]
M11capsid contains tumor targeting peptide TMTP1 expresses truncated BID (mitochondrial apoptotic protein) combined with cisplatin[99]
Ad-VThTERT tumor specific promoter, expresses apoptin[100]
TILT-123expresses hTNF ⍺ and hIL-2[101]
CRAdMUC16 promoter transactivation region targets cells with high CA-125 expression[102]
TILT-321expresses bispecific MUC1 and CD3[103]
HerpesviridaeOV-αCD47-G1binds to Fc-receptors on NK and macrophage combined with PD-L1 antibody[104]
NG34ScFvPD-1expresses single chain PD-1 antibody combined with PI3K inhibitor (LY294002)[105]
PoxviridaeOV-CXCR4-A (Vaccinia)CXCR4 antagonist in the context of the Fc portion of murine IgG2a[106]
OrfVmonotherapy; stimulates NK cells[107]
ss(−)RNARhabdovirusVSVΔM51attenuated VSV combined with α-galactosylceramide-loaded DCs[108]
VSVΔM51attenuated VSV combined with T-DM1 (Kadcyla®)[109]
MeV-StealthMeV pseudotyped with CDV envelope modified to target CD46[110]
oMRBexpresses OVA as a TAA[111]
ParamyxovirusNDV(F3aa)-GFPexpresses thrombospondin peptide (3TSR) combined with MIS416Vax adjuvant for vascular normalization[112]
ss(+)RNARetroviridaeoFVinfects slow dividing cancer cells latent in quiescent cells, replicates upon cell division[113]
AlphaviridaeSV.IgGOX40.IL-12expresses IL-12 and agonistic antibody to OX40[114]
SIN AR339replication competent Sindbis virus[115]
VSV, vesticular stomatitis; MeV, measles virus; oMRB, Maraba virus; NDV, Newcastle disease virus; oFV foamy virus; SV Sindbis virus; dsDNA, double-stranded DNA; ss(−)RNA, single-stranded, negative sense RNA; ss(+)RNA, single-stranded, positive sense RNA.
Table 4. Clinical trials of oncolytic virus mediated treatment of ovarian cancer.
Table 4. Clinical trials of oncolytic virus mediated treatment of ovarian cancer.
NameTypeNCT IDPhaseInvestigations
MV-CEA or NISmeaslesNCT00408590Isafety and toxicity of MeV expressing different TAAs
MV-NISmeaslesNCT02068794I/IIi.p. administration for infection of mesenchymal stem cells
MV-NISmeaslesNCT02364713IIi.p. administration combined with chemotherapy of choice
TILT-123adenovirusNCT05271318Iencodes TNF⍺ and IL-2 combined with Pembrolizumab
R130herpesNCT05801783Isafety/efficacy of recombinant HSV I for relapsed/refractory OC
GL-ONCvacciniaNCT02759588I/IIi.p. infusion +/− chemotherapy
Olvi-VecvacciniaNCT05281471IIIsafety and efficacy of adding Olvi-Vec to platinum and bevacizumab treatment
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Pampeno, C.; Opp, S.; Hurtado, A.; Meruelo, D. Sindbis Virus Vaccine Platform: A Promising Oncolytic Virus-Mediated Approach for Ovarian Cancer Treatment. Int. J. Mol. Sci. 2024, 25, 2925. https://doi.org/10.3390/ijms25052925

AMA Style

Pampeno C, Opp S, Hurtado A, Meruelo D. Sindbis Virus Vaccine Platform: A Promising Oncolytic Virus-Mediated Approach for Ovarian Cancer Treatment. International Journal of Molecular Sciences. 2024; 25(5):2925. https://doi.org/10.3390/ijms25052925

Chicago/Turabian Style

Pampeno, Christine, Silvana Opp, Alicia Hurtado, and Daniel Meruelo. 2024. "Sindbis Virus Vaccine Platform: A Promising Oncolytic Virus-Mediated Approach for Ovarian Cancer Treatment" International Journal of Molecular Sciences 25, no. 5: 2925. https://doi.org/10.3390/ijms25052925

APA Style

Pampeno, C., Opp, S., Hurtado, A., & Meruelo, D. (2024). Sindbis Virus Vaccine Platform: A Promising Oncolytic Virus-Mediated Approach for Ovarian Cancer Treatment. International Journal of Molecular Sciences, 25(5), 2925. https://doi.org/10.3390/ijms25052925

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop