Abstract
Background:
Oncolytic viruses (OVs) have the ability to efficiently enter, replicate within, and destroy cancer cells. This capacity to selectively target cancer cells while inducing long-term anti-tumor immune responses, makes OVs a promising tool for next-generation cancer therapy. Immunogenic cell death (ICD) induced by OVs initiates the cancer-immunity cycle (CIC) and plays a critical role in activating and reshaping anti-cancer immunity. Genetic engineering, including arming OVs with cancer cell-specific binders and immunostimulatory molecules, further enhances immune responses at various stages of the CIC, improving the specificity and safety of virotherapy.
The aim of this study is to update current knowledge in immunotherapy using OVs and to highlight the remarkable plasticity of viruses in shaping the tumor immune microenvironment, which may facilitate anti-cancer treatment through various approaches.
Methodology:
Research articles, meta-analyses, and systematic reviews were retrieved from PubMed, using the search terms (‘Oncolytics’ OR ‘Immunotherapy’ OR ‘Virotherapy’ OR ‘Viral vector’) AND ‘gene therapy’, without language restrictions.
Results:
In this review, we discuss current strategies aimed at increasing the tumor specificity of OVs and improving their safety. We summarize and functionally categorize different biochemical approaches, with a focus on virus engineering and advancements in immunotherapy. Transduction targeting methods (e.g., xenotype switching, pseudotyping, cell receptor targeting) and non-transduction modifications (e.g., miRNA, optogenetics, transcriptional targeting) are critically reviewed. We also examine the mechanisms of ICD and viral modifications that contribute to efficient cancer cell death and modulation of cancer-specific immunity. Finally, we provide an outlook on promising future oncolytics and approaches with potential therapeutic benefit for the next generation of cancer immunotherapy.
Conclusion:
Immunogenic cell death induced by oncolytic viruses is a key mediator of potent anti-cancer immunity. The genetic integration of immunostimulatory molecules as regulatory elements into OV genomes significantly enhances their therapeutic potential, safety, and stability. Additionally, therapeutic potency can be further increased by deleting viral genes that inhibit apoptosis, thereby enhancing ICD. However, the synergistic effects of these modifications may vary significantly depending on the cancer type.
1 Introduction
Translational cancer research is among the fastest-growing fields in next-generation medicine, focusing on the development and application of innovative therapeutic strategies to target malignant cells. Despite recent advances in cancer treatment, several types of malignant tumors continue to exhibit resistance to conventional chemotherapy and radiotherapy (). Coupled with aggressive phenotypes and, in some cases, inaccessibility for surgical removal, cancer remains a leading cause of mortality, accounting for nearly 10 million deaths annually worldwide. The incidence of cancer varies widely depending on cancer type, gender, and, in some instances, racial disparities. According to the American Cancer Society, the cancer mortality rate in the United States has continued to decline, with a 2% annual decrease from 2016 to 2020, largely attributable to advancements in modern cancer therapies and diagnostics. Nevertheless, the overall incidence of cancer continues to rise. In 2022, over 19.9 million new cases were diagnosed globally, with the highest incidence rates observed in lung, female breast, colorectal, prostate, and stomach cancers. Projections estimate that by 2040, there will be more than 28.4 million new cancer cases worldwide. This alarming trend underscores the urgent need for the development of novel, cancer-specific, safe, and highly effective therapeutics (, ).
Immunotherapeutic approaches have significantly enhanced our understanding of the role of the tumor microenvironment in cancer progression and therapeutic resistance. It is now well established that activating or stimulating the patient’s immune system through external interventions is crucial for effectively eliminating cancer cells and preventing their dissemination (, ).
Oncolytic viruses (OVs) are a cutting-edge form of immunotherapy. They are based on attenuated or recombinant human or animal viruses that selectively infect cancer cells due to the impaired antiviral defenses often found in tumors, leaving normal cells largely unharmed. OVs have key features that clearly articulate their mode of action ().
Direct oncolysis of cancer cells (e.g. Adenoviruses (Ads) and Herpes simplex viruses (HSVs) and releasing tumor-associated antigens (TAAs) — a process that is critical for initiating immunogenic cell death (ICD) ().
Release of DAMPs (Damage-Associated Molecular Patterns): DAMPs such as ATP, HMGB1, and calreticulin are vital for ICD. These molecules act as signals that enhance dendritic cell (DC) maturation and antigen presentation, leading to a stronger antitumor immune response (). Oncolytic viruses like reoviruses and Newcastle disease virus (NDV) have been engineered to enhance the release of these DAMPs, thereby amplifying ICD. Recent studies have shown that modifications to increase the release of DAMPs or enhance their signaling can significantly improve the efficacy of oncolytic viruses ().
ICD enhancement: promoting the secretion of proinflammatory cytokines such as IL-12 and GM-CSF (granulocyte-macrophage colony-stimulating factor). These modifications help to shift the tumor microenvironment from an immunosuppressive (“cold”) state to an immunostimulatory (“hot”) state, thus facilitating a more effective immune response ().
ICD modulation by synergy with immune checkpoint inhibitors (ICIs): combining ICIs (e.g. anti-PD-1 or anti-CTLA-4), with oncolytic viruses would enhance immune checkpoint development. While ICIs aid in overcoming immune resistance sometimes observed with monotherapy, oncolytic viruses cause direct oncolysis and the release of DAMPs (). Current clinical trials have shown that this combination approach can result in better patient outcomes and more antitumor responses (, ).
Furthermore, OVs can effectively regulate the expression of immune checkpoint molecules, effectively rendering tumor cells susceptible to cytotoxic anti-cancer therapy (). In addition, due to the relatively simple and modular structure of their genomes, viruses are frequently used in gene therapy to transport effector molecules to cells and tissues. Combinatorial strategies involving oncolytic viruses, immune checkpoint inhibitors (e.g., PD-1, CTLA-4, LAG-3), immunostimulatory molecules (e.g., interferons such as IFN-γ and IFN-β), TAAS, or tumor-specific antigens (TSA) (e.g., MAGE-3, claudin 18.2, mesothelin, E6, E7), as well as chemotherapy agents like the kinase inhibitor Sorafenib, aim to enhance anti-cancer efficacy and overcome the limitations associated with monotherapy (, ). While immune checkpoint inhibitors and CAR T-cell therapies have shown promise, they are also associated with certain limitations and adverse effects. In contrast, oncolytic viruses represent a promising therapeutic modality that combines the benefits of both approaches. They have the potential to induce immunogenic cell death (ICD) and activate tumor-specific immune responses with minimal severe toxic effects (, ).
In this review, we describe strategies proposed in translational cancer research to enhance the anti-cancer activity of oncolytic viruses, improve tumor specificity, regulate gene expression, and increase safety. We summarize the mechanisms of action of oncolytic viruses and reveal the complex relationship between OVs and the tumor microenvironment. We broke down and clustered the major approaches that have been used for oncolytics in preclinical and clinical settings. Research articles, meta-analyses, and systematic reviews were retrieved from PubMed, using the search terms (‘Oncolytics’ OR ‘Immunotherapy’ OR ‘Virotherapy’ OR ‘Viral vector’) AND ‘gene therapy’, without language restrictions. The retrieved research was categorized according to the mechanism of action, with particular emphasis on immune response modulation. The main targeting approaches are critically discussed, and the potential of oncolytic virotherapy as a strategy for cancer immunotherapy is summarized.
2 Oncolytic viruses induce immunogenic cancer cell death rewiring anti-cancer immunity
ICD is a unique form of regulated cell death that arises due to pathological changes in the intracellular or extracellular environment. As a result, dying cells release DAMPs or alarmins into the extracellular space or display them on their surface. ICD activation requires reactive oxygen species (ROS) and endoplasmic reticulum stress (). Dudek et al. categorized ICD inducers into two types based on their effects on the endoplasmic reticulum (ER). Type I inducers target processes not directly related to the ER, whereas type II inducers lead to cell death by directly inducing endoplasmic stress. Oncolytic viruses are categorized as type II inducers, particularly because they can induce ER stress through excessive viral protein synthesis ().
Importantly, in addition to its antitumor role, the immune system can stimulate tumor growth through signaling with certain cytokines (IL-1β, IL-23, IL-11, IL-6, TNF, and GM-CSF). Thus, understanding how ICD inducers can bypass this signaling is crucial (–).
In addition to DAMPs, TAA, and TSA, pathogen-associated molecular patterns (PAMPs) stimulate the immune system during OV-induced ICD. In 2013, Chen and Mellman () introduced the concept of Cancer-Immunity Cycle (CIC), describing the principle of immune system activation in response to cancer cell death and demonstrated how its action can be enhanced at each stage of the cycle. Figure 1 illustrates its interpretation in the context of oncolytic virus action on tumors.
Figure 1
3 Tumor immune microenvironment
The relationship between OVs, tumor, and immune system cannot be fully understood without considering the tumor microenvironment, which mediates the interaction between tumor and healthy tissues. The tumor microenvironment is composed of cellular components (such as immune cells, fibroblasts, and blood vessel endothelial cells), extracellular matrix, and various signaling molecules (cytokines and chemokines) (
Table 1
| Cell type | Mechanism | Activation | Suppression | Reference |
|---|---|---|---|---|
| CD8+ T cells (CTLs) | - Killing cancer cells by granule exocytosis and apoptosis stimulated by death ligands in the cells such as TRAIL-FasL - Induction of cytotoxicity through the release of IFN-γ and TNFα - IFN-γ production induces M1 polarity of macrophages and release of chemokines to attract CD4+ T cells. - Release of TNFα promotes anti-M2 polarization of macrophages | -Cross-presentation of MHC class I antigens by DCs to CD8+ T-cells induces the generation of CTLs. -Ligand interactions on DCs CD70 and CD80-CD86) and receptors on CD8+ T cells (CD27 and CD28) play a key role in priming CD8 + T cells.-Leaded by cytokines (CXCL9 and CXCL10) secreted by DCs CTLs migrate into the tumor. -IFN-γ stimulates the production of CTLs -Promotion by CD4+ T-cells -Stimulatory checkpoints (CD40L, etc.) | - Tregs, MDSCs and cancer cells -Adenosine released by cancer cells stimulates Tregs and MDSCs mediated suppression -By the action of immunosuppressive mediators (IDO1, PD-L1, COX-2, STAT3) released by cancer cells - By the action of TNF-α, TGF-β, IL-6. -Inhibitory checkpoints (CTLA-4, PD-1, etc.) | ( |
| CD4+ T helper cells | - Interaction with MHC class II antigens and activation of CD8+ T cells - Optimization of the quality and magnitude of CTLs responses by priming through DCs. - Induction of IL-12 and IL-15 production by DCs, responsible for clonal expansion and differentiation of CTLs - Facilitate shaping of CD8+ T cells into memory CTLs | - Differentiation into antigen-specific effector T cells is activated by DCs - Blockade of CTLA-4 and PD-1 can potentiate the activity of CD4+ T cells | - TGF-β suppresses proliferation | ( |
| Tregs | - Weakening the translocation of CTLs to the tumor nucleus - TGF-β release and suppression of CTLs activity - Expression of CD73 on the surface contributes to Treg-mediated inhibition of CTLs immunosuppressive activity - CTLA-4-mediated suppression of antigen-presenting cells - Consumption of IL-2 - Release of anti-inflammatory cytokines (IL-10, TGFβ) | - IL-6 - Gradients of the chemokines CCR4-CCL17/22, CCR8-CCL1, CCR10-CCL28, and CXCR3-CCL9/10/11 are recruited to the TME -TGFβ for the development, function, and survival of Tregs | - The PI3K-AKT-mTOR signaling pathway blocks the generation of Foxp3 + Tregs | ( |
| DCs | - Activation of CTLs through antigen cross-presentation - Transmission of costimulatory signals from CD4+ T cells to CTLs - Interaction with NK and B cells - Infiltration of DCs attracts immune effector cells | - CD4+ T cells can promote the activation and maturation of DCs - GM-CSF for recruitment, maturation and survival | - Activated by CCL2, CXCL1, and CXCL5 and VEGF released by cancer cells - Tumors can paralyze DCs through the induction of PD-1 expression - CTLA-4 is able to competently bind to CD80 and CD86 on DCs, preventing the activation of CD8+ T cells by DCs | ( |
| NK cells | -Immunosurveillance of tumor -Immature NK cells have antitumor activities -Differentiated NK cells with PD‐1 receptor exhibit protumor activities -Destruction of cancer cells exhibiting MHC-I expressive profile -Release of perforin and granzymes that induce cancer cell apoptosis -Secretion of pro-inflammatory cytokines and chemokines (GM-CSF, CCL5, TNF, IFN-γ, IL-6) | - IL-2 promotes tumor-led engagement of chemokines secreted by DCs (IL-12, etc.) - IL-2 promotes proliferation | - Reduction of NK cell infiltration by TGF-β and other immunosuppressive agents released by cancer cells - Limitation of function through inhibitory checkpoints | ( |
| M1-polarized macrophages | - Antitumor action - Production of pro-inflammatory cytokines, reactive oxygen and nitrogen species | -IFN-γ, bacterial lipopolysaccharide (LPS), TNFα | - Blocking Notch signaling leads to M2 polarization | ( |
| M2-polarized macrophages | - Production of anti-inflammatory cytokines - Suppression of immunosurveillance against tumor cells - Promote angiogenesis and matrix remodeling, inducing tumor progression - Tumor-associated macrophages are considered a major source of MDSCs | -IL4, IL13, IL10 | - SOCS3 (a downstream molecule of Notch signaling) promotes M1-polarization of macrophages | ( |
| Neutrophils | - Like macrophages, they have N1 and N2 polarization and contribute to anti-tumor and pro-tumor action, respectively - N1 neutrophils release granules with cytotoxic compounds to destroy cancer cells, secrete cytokines and chemokines. - N2 neutrophils are similar to polymorphonuclear MDSCs | - IL8 promotes neutrophil recruitment through binding to CXCR1 and CXCR2 receptors - DAMPs (HMGB, S100) overexpressed in tumors enhance neutrophil chemotaxis - GM-CSF, G-CSF and IFNg block neutrophil apoptosis | - TGFβ prevents the infiltration of N1-neutrophils into the tumor and promotes the accumulation of N2-neutrophils in the tumor | ( |
| MDSCs | - Enhancement of angiogenesis through the production of MMP9, prokineticin 2 and VEGF - Induction of cancer cell migration to endothelial cells, metastasis - Inhibition of T-cell function through production of arginase, inducible nitric oxide synthase, TGF-β and IL-10 - Production of indole amine 2,3 dioxygenase (IDO), which suppresses immune response and induces Treg production | - GM-CSF, SCF-1, PGE2, COX-2, VEGEF, M-CSF, and IL-6 induce the expansion of MDSCs | - IDO inhibitors (1-methyl-L-tryptophan or STAT3 antagonist JSI-124) block MDSC immunosuppressive activity | ( |
| B cells | - Production of cytokines that activate CTLs - Act as antigen-presenting cells - Production of cytokines that recruit MDSCs and enhance angiogenesis - Suppression of T-cells through IL-10 production | - Recognition of antigens via B cell receptors (BCRs) - Costimulatory molecules (CD80/86) - GTF-β can become immunosuppressive under the influence of TGF-β | - Polymorphonuclear MDSCs are able to suppress B-cell proliferation | ( |
Immune cells in TIME.
Tumor cells and tumor microenvironment use various strategies for immune evasion: disruption of antigen expression or presentation, accumulation of metabolites suppressing the functioning of effector T cells, modulation of cellular extracellular matrix to impede immune cell penetration and motility, the exposure of inhibitory immune checkpoints, secretion of immunosuppressive cytokines and production of chemokines recruiting pro-tumor stromal cells (
Depending on the composition of immune infiltrates and the nature of the inflammatory response, the TIME can be subdivided into three main classes: infiltrated-excluded (I-E), infiltrated-inflamed (I-I), and deserted TIME (
4 Reinforcement of cell death with OVs
Oncolytic viruses can induce immunogenic cell death (ICD) in tumor cells, but their efficacy can be enhanced through genetic modification and their combination with other therapies. These strategies can potentiate their immunostimulatory effects at different stages of the cancer-immunity cycle. Here, we describe the main types of genetic modifications that stimulate ICD and enhance the immune response.
4.1 OVs engineering for ICD modulation
Different oncolytic viruses (OVs) possess unique proteins that modulate cell death; however, there are common patterns in their mechanisms of action, which depend on the type of cell death induced and the associated effector signaling pathways. Several strategies have been used to modify OVs for the promotion of ICD, including the deletion or knockout of genes, the insertion of genes that modulate cell death, and the arming of OVs with immunostimulatory molecules, such as TAAs, DAMPs, co-stimulatory ligands, cytokines, and chemokines. Numerous reviews have discussed the various types of cell death and their modulation by viruses (
Table 2
| ICD type | Virus | Modification | Results | Ref. |
|---|---|---|---|---|
| Apoptosis | Adenovirus (AdΔE1B19K) | Deletion of E1B19K gene | Enhancement of gemcitabine-induced apoptosis in the pancreatic carcinoma cells PT45 and Suit2 and in PT45 xenografts | ( |
| Herpesvirus (vBSΔ27) | Deletion of ICP27 gene | Induction of apoptosis in human cells | ( | |
| Vesicular stomatitis virus (VSV-ΔM51) | Deletion of methionine at amino acid position 51 of the M protein | Induction and enhancement of apoptosis through type II extrinsic pathway in pancreatic ductal adenocarcinoma cell lines | ( | |
| Vaccinia Virus (VG9-IL-24) | Disruption of the viral thymidine kinase gene region, IL-24 expression | Induction of apoptosis in breast cancer cell lines through PI3K/β-catenin signaling pathway. Delayed tumor growth and improved survival in MDA-MB-231 tumor model | ( | |
| Newcastle disease virus (rAF-IL12) | IL12 expression | Induction apoptosis of CT26 colon cancer cells, cell cycle arrest at G1 phase. CT26 tumor growth inhibition in Balb/c mice, increasing the level of CD4 + , CD8 + , IL-2, IL-12, and IFN-γ. | ( | |
| Measles Virus (rMV-BNiP3) | BNiP3, human pro-apoptotic gene, insertion | Induction of apoptosis in breast cancer cells (MDA-MB-231, MCF-7) | ( | |
| Autophagy | Adenovirus (Ad-hTERT-E1a-apoptin; Ad-VT) | E1A gene is driven by the cancer-specific promoter hTERT, apoptin expression | Regulation of autophagy through the AMPK-mTOR-eIF4F signaling axis. Reduction of drug resistance of MCF-7/ADR adriamycin resistant human breast cancer cell line). Decreased tumor volume in BALB/c with SGC7901 cell line (human gastric cancer), increased survival of mice | ( |
| Measles Virus (rMV-Hu191) | Attenuated measles vaccine strain | Promotion of caspase-dependent apoptosis and complete autophagy through PI3K/AKT pathway in human colorectal cancer cells | ( | |
| Necroptosis | Adenovirus (ZD55-IFN-β) | IFN-β expression | Initiation of caspase-dependent apoptosis and necroptosis in human hepatoma cells SMMC-7721 | ( |
| Adenovirus (dl922-947) | E1A CR2 deletion | Induction of necrosis in cancer cell lines | ( | |
| Ferroptosis | Newcastle disease virus | Wild type | Induction of ferroptosis through p53-SLC7A11-GPX4 pathway in U251 cells | ( |
Types of ICD induced by oncolytic viruses.
4.2 TAAs and DAMPs
Classical apoptosis and autophagy are generally considered as non-immunogenic cell death; hence no DAMP, PAMP, TAAs and TSAa are released. OVs induced ICD of cancer cells stimulate the release of immunogenic molecules that are recognized by APCs, which subsequently activate cytotoxic T-lymphocyte (CTL) response. To stimulate a specific immune response, OVs are used in situ as vectors of TAAs. For example, adenovirus expressing human dopachrome tautomerase (hDCT) leads to a potent CTL response in a mouse model of melanoma (
DAMPs similarly to TAAs trigger an immune response in tumor microenvironment through recognition by APCs, which allows them to be used to reinforce OVs to boost antitumor immunity. For example, Measles virus (MV) encoding Helicobacter pylori heat shock protein A (HspA) has been shown to have enhanced replicative activity and exhibit a pronounced antitumor effect in in vitro and in vivo models of ovarian cancer (
4.3 Cytokines and chemokines
Cytokines, including chemokines, play a critical role in the cancer immunity cycle, in which they act as signal transmitters between cellular components of TIME and contribute to both induction and suppression of immunity (Table 2). Cytokines have been widely utilized in tumor virotherapy and are being actively studied (
4.4 Co-stimulatory ligands
Another method to enhance the antitumor immune response is to activate immune cells through the expression of co-stimulatory ligands by OVs (e.g., CD40L, 4-1BB, CD80, ICOS ligand) or, conversely, inhibitors or antagonists of co-inhibitory molecules (e.g., antibodies against “don’t eat me” signals (CD24 and CD47) used by the tumor for immune evasion) (
4.5 Combination with other therapies
The tumor’s significant defense system against OVs, including restricted viral spread, resistance to oncogenic signaling pathway targeting, and immunosuppressive tumor microenvironment, often limits the effectiveness of OV monotherapy (
One of the major challenges in virotherapy is the induction of immune responses directed primarily against viral antigens rather than tumor antigens, which can limit the antitumor effect. A potential solution is the “prime-boost” strategy, in which an initial dose of virus encoding a tumor antigen primes the immune system, and subsequent doses further amplify, or boost, the antitumor immune response (
5 Targeting technologies for arming oncolytic viruses
There is no doubt that viruses are able to bind both normal “healthy” and malignant cells. However, oncolytic viruses productively replicate specifically in cancer cells while their productive infection is hampered in normal cells. Virus tropism is determined by cell receptors and/or co-receptors that viruses use to initiate cell attachment followed by cell entry. For example, the measles virus has a natural tropism for the human CD46 molecule, which facilitates virus binding to the cell (
Available approaches for OV modifications in research and development are broadly divided into two categories: genetic and biochemical targeting (Figure 2). Genetic modifications are more challenging to design and implement but, unlike biochemical modifications, they ensure that the desired features are reproduced in the viral progeny. Genetic modifications are further classified into transduction-targeting and non-transduction targeting approaches (Figure 3). These changes are intended to preserve the virus’s oncolytic efficacy while preventing it from harming healthy cells. On the other hand, the virus can be modified to show very little tropism for the target cell type. This approach reduces the virus’s toxicity to healthy cells, but it requires a deep understanding of the host mechanism that restricts the spread of the virus and the availability of accessible targets in order to overcome these restrictions.
Figure 2

Types of approaches for OVs modifications for next-generation cancer therapy. Genetic and biochemical modifications are two major categories that grouped the available approaches. Based on the mechanism of action, the approaches could be clustered in transductional targeting and non-transduction targeting groups. Combinatorial approaches using various modifications of OV occupy a central place in current oncolytic therapy.
Figure 3

Modifications of OVs by genetic and biochemical methods. Genetic modifications can be divided into two groups: transduction targeting (A) and non-transductional targeting (B). Transduction targeting may use xenotype switching, cell receptor targeting and virus pseudotyping. Non-transduction targeting approaches focus on transcriptional retargeting, RNA interference (miRNA) or control of gene expression using optogenetic technologies. Variety of biomedical modifications (C) have been applied to increase OVs specificity (e.g. ligand conjugation, bispecific antibodies) to cancer cells and increase its potency (PEG, biotin-avidin bridges).
5.1 Transduction targeting
Transductional targeting has been studied since the 2000s and involves various methods for modifying oncolytic viruses to maximize their transduction of tumor cells. The key goal for transduction targeting is to minimize OVs’ replication in non-cancerous cells. Therefore, thorough screening of viral interactions with healthy cells is essential. The genetic approach includes modifying viral capsid proteins to specifically target tumor cells while reducing entry into non-tumor cells. This is accomplished by genetically altering existing viral proteins and inserting new genes that encode interaction proteins, which enhance the OVs ability to bind to the surface of cancer cells. In the following sections, we provide summarized transduction targeting approaches proposed for OV therapy.
5.1.1 Genetic targeting of OV on tumor cell receptors
One branch of transduction targeting involves interactions with tumor surface markers, such as the avβ6 integrin, which is expressed in a number of aggressively transformed epithelial cancers but remains undetectable in healthy tissues (
5.1.2 Transduction targeting by chimeric and pseudotyped OVs
A significant number of studies have focused on the construction of viral chimeras (hybrids) - the combination of viral particles and proteins of different viruses to improve the properties of oncolytic viruses (OVs) (
One of the most popular trends is the creation of adenovirus hybrid fibers. Adenoviruses attach to the target cell via the knob domain of the trimeric capsid protein fiber. This domain is structurally conserved across different Ads serotypes but utilizes several different receptors. The interaction of Ads with the receptor depends on both fiber length and flexibility (
5.1.3 Biochemical retargeting of OVs
Another approach to achieving virus specificity is biochemical retargeting, which involves conjugation with cell-targeting ligands. This includes, for example, the use of bispecific antibodies, biotin-avidin molecular bridges, and pegylation. This approach stands out because it does not lead to complications associated with genetic modifications and allows targeting the virus to several cell receptors simultaneously. The main disadvantage of the method is that the modification is limited to one generation of the virus and is not transmitted to the offspring after replication (
5.2 Non-transduction targeting
Non-transduction targeting is the modification of the virus genome to enable replication exclusively in cancer cells. The strategy includes approaches, such as transcriptional targeting, targeting matrix metalloproteinases (MMP) and targeting miRNAs.
5.2.1 Transcriptional targeting
Transcriptional targeting is most often achieved by placing critical parts of the viral genome under the control of tumor-specific promoters, which are active in tumors but inactive in most normal tissues. Cancer-specific promoters are primarily applicable to engineer DNA-genome OVs (e.g. herpesviruses, adenoviruses). For example, the human epidermal growth factor receptor 2 (HER-2) promoter is often used to regulate the replication of herpes simplex virus (HSV) in glioma cells (
The cell mass of solid tumors develops predominantly in a hypoxic environment, therefore, a number of studies (as shown in Table 3) have focused on regulating the expression of the toxic adenovirus E1A protein through regulatory elements responsive to hypoxia. The E1A gene was placed under the control of various tissue-specific tumor promoters for controlled cytotoxic effects (Table 3). One of such promoters is the human telomerase promoter (human telomerase reverse transcriptase hTERT, see Table 3), as telomerase activity is often higher in cancer cells than in normal cells (
Table 3
| Promoter | Target tumor | Reference |
|---|---|---|
| MUC1 | Breast cancer | ( |
| Promoters responding to hypoxia and estrogen | Breast cancer | ( |
| Prostate-specific antigen (PSA) | Prostate cancer | ( |
| Probasin | Prostate cancer | ( |
| α-feto-protein | Liver cancer | ( |
| Regulatory sequence PPT (PSA enhancer, a PSMA enhancer and a T-cell receptor γ-chain) | Prostate cancer | ( |
| Survivin | Malignant gliomas | ( |
| β-catenin-responsive promoters | Colorectal cancers Liver cancers | ( |
| Cyclooxygenase-2 (Cox-2) | Colorectal cancer Pancreatic cancer | ( |
| Human telomerase (hTERT) | Gastrointestinal cancer | ( |
| PEG-3gene (PEG-Prom) | Primary and distant pancreatic tumors | ( |
Promoters for cancer-specific adenovirus replication and E1A expression.
5.2.2 Targeting matrix metalloproteinases
Host cell proteases are determinants for the replication and pathogenicity of enveloped viruses (
5.2.3 MicroRNA targeting
MicroRNAs (miRNAs) are a class of short (∼22 nucleotides) non-coding RNA molecules that play a crucial role in epigenetic regulation (
Another example of miRNA targeting is the oncolytic vesicular stomatitis virus, which is highly tumor-specific due to its susceptibility to the interferon response in normal tissues. However, VSV is highly neurotoxic not only in rodents but also in non-human primates (
Table 4
| OV | miRNA | Reference |
|---|---|---|
| Adenoviruses | miRNA-122 | ( |
| Herpes Simplex Virus 1 | miRNA-143 miRNA-145 | ( |
| Influenza A virus | miRNA-93 | ( |
| VSV | miRNA let-7, miRNA 9, miRNA-26, miRNA-29, miRNA-125 | ( |
| Picornavirus | miRNA-124, 125, miRNA-142 | ( |
| CVB3 | miRNA-216, miRNA-375, miRNA-34, miRNA-1, miRNA-133 | ( |
| CVA21 | miRNA-142, miRNA-133, miRNA-206 | ( |
| Semliki Forest virus | miRNA-214 | ( |
| AAV | miRNA-1d, miRNA-206, miRNA-122 | ( |
| Measles virus (MV) | miRNA-122, miRNA-7, miRNA-148a | ( |
| Mengovirus, vMC24 | miRNA-124, miRNA-133, miRNA-208 | ( |
| Lentiviral vectors | miRNA-155, miRNA-223 | ( |
| Poliovirus | miRNA-124 | ( |
MicroRNA (miRNA) for detargeting OVs from nonmalignant cells.
5.2.4 OVs modifications by optogenetic modules
A relatively recent non-transduction targeting method has been found in the application of recombination of oncolytic viruses. The method is based on the regulation of gene expression by exposure of transduced cells to light waves of a certain spectrum. The genetic construct responsible for the mechanism for implementing this method is called the optogenetic module (OM). Optogenetic modules incorporated into recombinant oncolytic viruses can help improve tumor selectivity, reduce toxicity, and regulate the expression of immunomodulators, tumor suppressor genes, tumor-associated antigens, and microRNAs. Controlling expression with specific wavelengths of light may, in the future open up new, safe options for treating recurrent cancers with oncolytic viruses. Viral vectors have previously integrated various types of OM. In the study by Hagihara and colleagues, they developed a tumor-specific replication-competent adenovirus in which the expression of adenovirus early region genes 1A (E1A) and 1B (E1B), essential for viral replication, is driven by the human telomerase reverse transcriptase (hTERT) promoter element (
Another group of researchers developed an alternative Opt/Cas-Ad system designed to regulate and enhance a tumor suppressor gene (
However, the prevalence of endogenous antibodies against adenoviruses makes their systemic administration difficult for cancer treatment (
Prescribing oncolytic viruses (OVs) to patients might still be challenging due to delivery issues. Most OVs require direct injection into tumors (intratumoral delivery) to maximize effectiveness and minimize off-target effects. This method is feasible for accessible tumors like melanoma but is difficult for deep-seated or hard-to-reach tumors, requiring specialized skills and equipment. Intravenous delivery is being explored but faces issues, such as rapid clearance by the immune system and unpredictable dosing at the tumor site.
Pre-existing immunity is another hurdle that may limit OVs’ applications. Some patients may have pre-existing immunity to the virus being used, which can neutralize the OV before it reaches the tumor, reducing therapeutic efficacy.
6 Discussion
The improvement and development of novel, potent, and safe anti-tumor drugs remain a top priority in translational cancer research. Despite the availability of effective cancer therapies, certain tumors exhibit poor responsiveness to existing treatments and are associated with low rates of positive outcomes among patients (
Given the mechanisms of action of OVs, combining virotherapy with other cytotoxic anti-cancer approaches is considered a promising direction for future cancer treatment. Notably, the combination of OVs with immune checkpoint inhibitors, such as PD-1 or CTLA-4 inhibitors — or with CAR-T and CAR-NK cell therapies has demonstrated synergistic effects, enhancing the immune system’s capacity to recognize and attack tumors. Clinical trials have shown that these combinations can be both safe and effective, with some studies reporting improved objective response rates and durable anti-tumor responses compared to monotherapies (
Another key feature of OVs is their modular structure, which enables the de novo design of viral carriers to deliver effector molecules specifically to cancer cells. These molecules can be encoded genetically within the viral genome or attached via biochemical interactions, allowing OVs to introduce novel therapeutic modalities into the tumor microenvironment and stimulate local immune responses against cancer-specific antigens or malignant cells. Importantly, OVs generally do not interfere with other anti-cancer treatments, making them well-suited for combinatorial strategies that may yield synergistic effects and potentially increase the proportion of patients who respond positively to therapy. By shaping the anti-cancer immune response, OVs can also be used in “prime-boost” regimens in conjunction with chemotherapy.
However, it is important to note that OVs are not yet a sufficient alternative to currently approved therapies. OV-induced inflammation and anti-viral immunity can limit their distribution and long-term application. Recent advances in computational modeling and simulation have facilitated the prediction and optimization of OV design. For example, phenomenological models have been developed to study viral spread within tumors and normal tissues, taking into account the varying capacities of different cell types to support viral proliferation. These tools are instrumental in guiding the development of more potent and selective oncolytic viruses for clinical use (
The approaches described above not only enhance the activity of OVs but also improve their safety. One promising strategy to mitigate health risks involves incorporating genetic circuits into the OVs’ backbone. These circuits enable precise regulation of the timing and magnitude of the virulence genes expression, as well as controlled delivery of therapeutic payloads, thereby balancing efficacy with biosafety (
The approaches described above not only enhance the activity of OVs but also improve their safety. One promising strategy to mitigate health risks involves incorporating genetic circuits into the OVs’ backbone. These circuits enable precise regulation of the timing and magnitude of the virulence genes expression, as well as controlled delivery of therapeutic payloads, thereby balancing efficacy with biosafety. However, studies have shown that pre-existing antiviral immunity to viruses, such as NDV and adenovirus can actually enhance the antitumor immune response by retargeting antibody-virus complexes and activating tumor-directed CD8+ T cells (
Pre-existing antiviral immunity and severe immunodeficiency may worsen the adverse effects of OV therapy. Usually adverse effects of virotherapy are generally mild to moderate, but can vary depending on the virus used, route of administration, and patient factors. The most commonly reported side effects include flu-like symptoms, fatigue, and nausea (
In oncolytic virotherapy trials for advanced melanoma, the most common adverse effects were fatigue, chills, nausea, diarrhoea, headache, myalgia, gastrointestinal, musculoskeletal and connective tissue disorders (
Other types of therapies, such as chemotherapy, radiotherapy and immunotherapy also present adverse effects. The most common adverse events in chemotherapy were nausea, vomiting, dry mouth, hair loss, fatigue, numbness in fingers or toes, confusion, depression, loss of appetite, chest pain, diarrhea, dyspnoea, and rash (
According to the clinical trials data, most adverse effects from using OVs are manageable and tend to resolve with supportive care. Severe complications are rare but highlight the need for careful patient selection, monitoring, and adherence to safety protocols during OV therapy.
Despite the initiation of more than 200 clinical trials investigating various OVs, the regulatory framework governing their administration remains underdeveloped. Key challenges include the lack of standardized clinical endpoints, validated biomarkers, and appropriate control arms in clinical trials, which complicate regulatory approval and integration of OVs into standard cancer care. Regulatory agencies, such as the FDA and EMA have issued guidance documents specific to gene therapy and oncolytic virus products, but the unique biology of OVs, such as their delivery methods, pharmacokinetics, and immunologic effects poses additional hurdles for clinical trial design and product standardization (
Another significant challenge associated with resistance to oncolytic virotherapy involves tumor cell-dependent IFN signaling. IFN-mediated antiviral pathways inhibit viral spread and replication, thereby limiting the efficacy of oncolytic viruses. This mechanism of resistance has been well documented for many OVs, particularly RNA viruses (
Taking together, advances in genetic engineering allow OVs to be modified for enhanced tumor specificity, improved immune activation, and delivery of therapeutic genes directly to cancer cells. Strategies include engineering viruses to express immunostimulatory molecules (such as chemokines and cytokines), modifying viral capsids for targeted delivery, and using nanomaterials as carriers to improve delivery and efficacy (205). Ongoing research aims to expand the range of cancers treatable with OVs and to refine combination regimens for maximum efficacy and safety.
7 Conclusions
Cancer is a heterogeneous and progressive disease that requires personalized treatment. Traditional therapies often lose effectiveness as tumors develop resistance, making the search for new combination therapies a significant challenge. Updated knowledge of virotherapy using oncolytic OVs, as summarized in this review, strongly suggests that shaping and modulating the tumor immune microenvironment may be a prerequisite for successful anti-cancer treatment. We anticipate that oncolytic viruses targeting or modulating the TIME may have beneficial therapeutic effects, particularly when used in combination with ICIs.
OVs have a dual effect on tumors: they destroy cancer cells and stimulate an antitumor immune response by inducing immune checkpoint inhibition and converting the TIME to an immunologically ‘hot’ state. However, OVs can also replicate in healthy cells, so targeting them specifically to cancer cells is essential. In this context, OVs carrying regulatory sequences (e.g., miRNA or tissue-specific promoters) help minimize the risk of uncontrolled viral spread, which is particularly important in immunocompromised cancer patients.
To improve ICD, immunostimulatory molecules are commonly integrated into OV genomes. Additionally, ICD induction can be enhanced by deleting viral genes that inhibit apoptosis. However, the synergistic effects of these modifications may vary significantly depending on the cancer type.
Light-activated oncolytic viruses could become indispensable and safe tools for translational studies, potentially accelerating the clinical development of novel anti-cancer therapies. Nevertheless, several intrinsic properties of optogenetic tools–such as background leakage, stability, biodistribution, and potential toxicity–remain significant barriers to future clinical application.
To summarize recent advances in virotherapeutic approaches, the main focus of translational research is on retargeting oncolytic viruses to bind specifically to cancer cells (using genetic or biochemical methods), enhancing the ability of viruses to induce ICD by altering the tumor microenvironment, and minimizing the risk of uncontrolled viral replication at off-target sites.
Despite the versatility of OV treatments, combined approaches involving chemotherapy, radiotherapy, and immunotherapy are likely to be the most effective and clinically applicable, while novel oncolytic-based therapeutics continue to undergo clinical trials.
Statements
Author contributions
IA: Visualization, Writing – original draft. AT: Writing – original draft, Project administration, Resources. EI: Resources, Writing – original draft, Data curation, Methodology. SV: Methodology, Resources, Validation, Visualization, Writing – original draft. NP: Investigation, Writing – original draft. EB: Resources, Writing – original draft. AM: Conceptualization, Data curation, Formal analysis, Supervision, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. The Molecular virology laboratory is supported by the Academic leadership program Priority 2030 by the Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov, First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University).
Acknowledgments
Figures were created using BioRender.com (2025) templates with our modifications.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
Publisher’s note
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Summary
Keywords
oncolytics, cell targeting, immunotherapy, virus engineering, pseudotyping, retargeting, ICD, TIME
Citation
Isaeva AS, Trujillo Yeriomenko AD, Idota E, Volodina SI, Porozova NO, Bezsonov EE and Malogolovkin AS (2025) Shaping viral immunotherapy towards cancer-targeted immunological cell death. Front. Oncol. 15:1540397. doi: 10.3389/fonc.2025.1540397
Received
05 December 2024
Accepted
06 June 2025
Published
08 July 2025
Volume
15 - 2025
Edited by
Jose Correa Basurto, Escuela Superior de Medicina (IPN), Mexico
Reviewed by
Jozsef Dudas, Innsbruck Medical University, Austria
Cindy Bandala, Escuela Superior de Medicina (IPN), Mexico
Rolando Alberto Rodriguez-Fonseca, Escuela Superior de Medicina (IPN), Mexico
Karina Spunde, Latvian Biomedical Research and Study Centre (BMC), Latvia
Jazmín García-Machorro, Escuela Superior de Medicina (IPN), Mexico
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© 2025 Isaeva, Trujillo Yeriomenko, Idota, Volodina, Porozova, Bezsonov and Malogolovkin.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alexander S. Malogolovkin, Malogolovkin_a_s@staff.sechenov.ru
‡These authors have contributed equally to this work
†Present address: Alexander S. Malogolovkin, Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore, Singapore
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