Oncolytic Viruses in Cancer Immunotherapy: From Molecular Engineering to Clinical Translation
Highlights
- Oncolytic viruses exert antitumor activity through direct tumor lysis and induction of systemic antitumor immunity.
- Advanced viral engineering strategies enhance tumor selectivity, immune activation, and therapeutic efficacy.
- Rational combination therapies are critical to overcome antiviral immunity and tumor resistance.
- The findings guide the development of next-generation oncolytic virus platforms and clinical trial design.
Abstract
1. Introduction
2. Mechanisms of Action: Direct Oncolysis and Immune Stimulation
3. Enhancing OV Efficacy: Engineering and Combination Strategies
3.1. Genetic Engineering for Tumor Selectivity and Potency
3.1.1. Attenuation/Deletion
3.1.2. Tumor-Specific Promoters
- Promoter leakiness and off-target expression: Tumor-specific promoters often retain residual activity in some normal or regenerating tissues. For instance, the hTERT promoter, although largely silent in quiescent cells, can be transiently activated in normal stem cells, endothelial cells, and inflamed tissues, raising potential safety concerns [47]. Similarly, the survivin promoter may exhibit basal activity in proliferating hematopoietic progenitors or during wound healing. Such leakiness can lead to unintended viral replication or off-target transgene expression, particularly problematic when expressing potent cytokines such as IL-12.
- Tumor heterogeneity and dynamic regulation: Promoter activity is rarely uniform across a tumor mass. Intratumoral variation in telomerase or survivin levels can result in patchy replication and incomplete oncolysis. Moreover, hypoxia-responsive or inflammation-inducible promoters fluctuate with microenvironmental cues, leading to inconsistent viral gene expression. For example, an in vivo study reported that HIF-driven OVs may lose replication potential if tumors reoxygenate following therapy or vascular remodeling, reducing efficacy [48].
- Epigenetic silencing and context dependence: Exogenous promoter sequences introduced into viral genomes can undergo epigenetic suppression through DNA methylation or histone modification, leading to transcriptional shutdown during extended viral replication. This phenomenon has been observed with CMV and hTERT promoters in long-term passaging studies [49]. Moreover, promoter strength is often context-dependent—affected by viral backbone, insertion site, and host transcription factor availability—making preclinical predictability difficult.
- Reduced viral fitness and replication kinetics: Restricting essential viral genes to tumor-specific promoters can impair viral replication rate compared with constitutive expression. For instance, under hypoxic conditions, both in vitro and in vivo models showed that hTERT-driven adenoviruses often replicate more slowly than wild-type or E1A-driven counterparts, potentially limiting spread and cytolytic potency. Strategies combining promoter regulation with compensatory mutations or dual-control systems are under development but remain experimentally complex [50].
- Manufacturing and regulatory challenges: Incorporation of large or synthetic promoters increases viral genome size and genetic instability during production. Maintaining promoter integrity and activity across manufacturing batches is technically demanding.
- Payload-specific safety considerations: Even when tumor-specific promoters restrict transgene expression, cytokine payloads such as IL-12, TNF-α, or IFN-β can still diffuse beyond the tumor, potentially inducing systemic inflammation or vascular leak syndromes. Clinical experience with IL-12-armed OVs underscores the need for tightly regulated or inducible promoter systems to mitigate toxicity [51].
3.1.3. MicroRNA (miRNA) Targeting
- Tumor heterogeneity and dynamic miRNA expression: The expression of many regulatory miRNAs varies not only between patients but also across tumor regions and during disease progression. For instance, miR-122 or miR-34a levels can fluctuate in response to inflammation, hypoxia, or therapy-induced stress. Consequently, viral replication control based solely on presumed “tumor-absent” miRNAs may be unreliable, risking incomplete viral replication or off-target expression in normal tissues where miRNA levels transiently drop [56].
- Incomplete repression and saturation effects: Even with multiple tandem target sites, miRNA-mediated repression is rarely absolute. Residual low-level expression of essential viral genes may still permit limited replication in protected tissues, particularly at high viral doses. Conversely, excessive insertion of target repeats can destabilize viral transcripts or overwhelm host miRNA machinery, potentially leading to unpredictable off-target effects or miRNA sequestration (“sponging”), which might dysregulate host gene networks [57].
- Evolutionary escape and genetic instability: During serial replication, OVs may undergo mutational loss or deletion of inserted miRNA target sequences, leading to escape variants that replicate indiscriminately. RNA viruses such as VSV or measles, which possess high mutation rates, are particularly prone to such deletions. Maintaining sequence integrity requires careful vector design and stringent manufacturing controls [58,59].
- Context dependence and cross-reactivity: Some miRNAs exhibit overlapping seed sequences or are co-expressed in unexpected tissues, resulting in unanticipated repression in off-target organs. For example, miR-199a and related family members share sequence similarity that can extend viral repression beyond the intended cardiac tissue, potentially diminishing oncolytic potency. This underscores the importance of comprehensive miRNA profiling during vector design.
- Translational and regulatory hurdles: Implementing miRNA-detargeted OVs in clinical trials demands detailed mapping of miRNA distribution in human tissues and across tumor subtypes, which remains incomplete for many cancers. Furthermore, regulators require robust preclinical toxicology data to confirm that miRNA-mediated repression remains stable under inflammatory, hypoxic, or regenerative conditions—contexts that can alter miRNA levels dramatically.
3.1.4. Retargeting
- Tumor receptor heterogeneity remains one of the foremost obstacles. Expression of target molecules such as CD46, EGFR, HER2, ICAM-1, and integrins often varies among tumor regions and evolves under therapy. For example, Ad5/3 adenoviruses efficiently infect DSG2-high ovarian tumors but fail in DSG2-poor lesions, and HER2-retargeted HSVs show uneven replication in breast cancers with heterogeneous HER2 expression. In glioblastoma, subsets of cells lacking CD46 or nectin-1 escape infection even with optimized adenoviral or HSV vectors. This was demonstrated using in vitro models [66].
- Expression in normal tissues. Most tumor-associated receptors are not truly cancer-specific. Low-level expression of HER2 in cardiomyocytes and epithelial cells, or of EGFR in skin and respiratory mucosa, can cause off-target toxicity. EGFR-targeted measles viruses have induced pulmonary inflammation in preclinical models, while CD46-tropic vectors (e.g., Ad5/35) may infect immune or endothelial cells, complicating systemic delivery safety [67].
- Receptor accessibility. From a structural standpoint, modifying viral surface proteins often compromises assembly and infectivity. In adenoviruses, large peptide insertions into the fiber knob can disrupt trimerization and reduce viral yield; RGD-modified Ad5 particles show improved tumor entry but decreased stability. In HSV, engineering gD to recognize HER2 instead of nectin-1 or HVEM can impair fusion efficiency and lower replication rates. Similarly, measles virus H-protein retargeting to CD20 or CEA can destabilize the H–F complex, reducing fusion potency [67].
- Immune-mediated neutralization. Immune neutralization also poses a major translational barrier. Retargeted vectors derived from common serotypes (Ad5, HSV-1, measles) remain susceptible to pre-existing antibodies and complement attack. Ad5/3-D24-GM-CSF and ONCOS-102—though potent in situ—require intratumoral administration because systemic delivery leads to rapid neutralization. Even novel surface ligands can inadvertently expose neo-epitopes, heightening immunogenicity [67].
- Dynamic receptor regulation. Receptor expression is also dynamic and context-dependent. Tumor cells may downregulate or shed receptors after initial viral binding, an antiviral escape observed with integrin- and DSG2-targeted adenoviruses. Cytokine-driven or IFN-mediated responses can alter receptor glycosylation, further diminishing secondary infection cycles [68].
- Tumor architecture. In addition, biophysical barriers within the TME—dense extracellular matrix, stromal fibroblasts, and high interstitial pressure—limit viral diffusion. For instance, an in vivo study showed that RGD-modified adenoviruses and HER2-targeted HSVs typically show peripheral infection with minimal spread into the hypoxic tumor core. Combining retargeting with matrix-degrading enzymes (e.g., hyaluronidase or relaxin) or stromal-modulating agents is being explored to overcome this limitation [69].
3.2. Payload Incorporation
3.2.1. Cytokines/Chemokines
3.2.2. Immune Checkpoint Modulators
3.2.3. BiTEs (Bispecific T-Cell Engagers)
- (1)
- Risk of cytokine release syndrome and systemic immune activation. The potent, antigen-independent activation of T cells mediated by BiTEs carries a risk of cytokine-release syndrome (CRS) even when expression is restricted to TME. Locally produced BiTEs can diffuse beyond the infection site, especially in highly vascularized or necrotic tumors, resulting in systemic spillover of IL-6, TNF-α, and IFN-γ. In preclinical models using adenovirus-encoded CD3 × EpCAM BiTEs, elevated cytokine levels and transient weight loss were observed despite the intended confinement of expression [97]. While oncolytic viruses are generally better tolerated than many systemic immunotherapies, CRS and irAEs remain clinically relevant concerns, particularly in combination regimens involving immune checkpoint inhibitors, cytokine-armed viruses, or BiTE-expressing platforms. These toxicities reflect the intended immune activation but may influence dose intensity, scheduling, and patient eligibility. Importantly, available clinical data indicate that most OV-associated CRS cases and irAEs are low to moderate in severity and clinically manageable using established interventions such as corticosteroids, IL-6 blockade, or temporary treatment interruption. However, the risk increases in settings involving potent immunostimulatory payloads or systemic viral delivery, underscoring that toxicity represents a context-dependent translational constraint rather than a prohibitive barrier. Accordingly, multiple mitigation strategies are being pursued, including localized intratumoral delivery, tumor-restricted or inducible transgene expression, attenuated viral backbones, and careful treatment sequencing to align OV administration with immune recovery, supporting continued clinical development with appropriate safety oversight [97].
- (2)
- Antigen heterogeneity and immune escape. Another important limitation arises from antigen heterogeneity and immune escape. Many solid tumors exhibit spatially and temporally variable expression of TAAs such as MUC16, EpCAM, or EGFR. OVs encoding single-target BiTEs may effectively eliminate antigen-positive subclones but leave antigen-negative variants intact, promoting rapid selection for escape mutants [98].
- (3)
- Limited control over BiTE expression levels and stoichiometry. From a mechanistic perspective, BiTE expression levels and stoichiometry within the TME are difficult to control. Excessive local BiTE concentrations may trigger T cell “over-activation” and local tissue necrosis, while insufficient expression fails to achieve durable synapse formation or sustained cytotoxicity. Moreover, the short half-life and rapid turnover of BiTEs in protease-rich, hypoxic tumor microenvironments can further reduce their bioavailability.
- (4)
- Dependence on viral replication kinetics and antiviral immunity. OVs that replicate quickly, such as vaccinia or VSV, may produce a burst of BiTEs but are rapidly cleared by antiviral immunity, limiting the duration of immune engagement.
- (5)
- Tumor microenvironment-imposed barriers to immune engagement. The immunological contexture of the TME also dictates BiTE efficacy. Dense fibrotic stroma, abnormal vasculature, and myeloid-derived suppressor cells can physically and metabolically hinder T cell infiltration and activation. In “cold” tumors characterized by low T cell density or defective antigen presentation, BiTEs may have little substrate for engagement [99].
- (6)
- Manufacturing, regulatory, and quality control challenges. Translationally, the manufacturing and regulatory landscape for OV-encoded BiTEs remains complex. These are dual-entity biologics whose potency depends on both viral replication and functional bispecific expression. Batch-to-batch consistency must be verified for infectious titer, BiTE concentration, binding affinity, and in vitro cytotoxicity—parameters not yet standardized for gene-encoded antibody fragments [100].
- (7)
- Residual safety concerns despite localized expression. Finally, safety concerns persist despite localized expression. Viral shedding or leakage of BiTE proteins into systemic circulation can lead to unintended immune activation or off-target effects. In particular, hepatotoxicity and pulmonary inflammation have been reported in murine models where BiTEs targeted antigens with low basal expression in normal tissues [101].
3.2.4. Other Therapeutics
3.3. Combination Therapies
3.3.1. Immune Checkpoint Inhibitors (ICIs)
3.3.2. Adoptive Cell Therapies (ACTs)
3.3.3. Targeted Therapies, Epigenetic Therapies and Chromatin Reprogramming Strategies
3.3.4. Chemotherapy/Radiotherapy
3.3.5. Neo-Adjuvant/Adjuvant Use
4. Translational Integration and Clinical Realities in OV-Based Combination Strategies: Lessons from Clinical Experience
4.1. Lesson 1: Immune Activation Is Necessary but Insufficient
4.2. Lesson 2: Preclinical Models Overestimate Viral Persistence and Immune Engagement
4.3. Lesson 3: Tumor Heterogeneity Dictates Clinical Responsiveness
4.4. Lesson 4: Conventional Clinical Endpoints Underestimate OV Benefit
4.5. Lesson 5: Manufacturing and Regulatory Complexity Limits Scalability
4.6. Lesson 6: Empirical Combination Strategies Are Insufficient
4.7. Outlook: From Optimism to Precision Implementation
5. Clinical Applications and Key Trials
5.1. Talimogene Laherparepvec (T-VEC; HSV-1/GM-CSF)
5.2. Teserpaturev/G47Δ (Third-Generation HSV-1; “Delytact”)
5.3. H101 (Oncorine; Adenovirus)
5.4. Other Clinically Advanced Exemplary
6. Challenges, Limitations and Future Directions
6.1. Challenges and Limitations
6.1.1. Delivery and Biodistribution
- Physical Methods: Ultrasound-mediated cavitation, convection-enhanced delivery (CED) for brain tumors.
- Chemical/Physical Modifications: PEGylation or coating with polymers to reduce immunogenicity and increase circulation time; conjugation to cell-penetrating peptides or targeting ligands.
- Biological Carriers: Encapsulation in cells (e.g., mesenchymal stem cells, carrier cells), liposomes, or nanoparticles. Cell carriers can potentially home to tumors and protect the virus from immune clearance. Nanovesicles are an emerging platform.
- Overcoming NAbs: Albumin-binding viruses or encapsulation techniques, use of less prevalent serotypes or engineering viruses to avoid common neutralizing epitopes, and chemical shielding.
- Routes of Administration: Exploring different routes like intravenous, intraperitoneal, or intravesicular delivery for tumor-specific applications.
6.1.2. Tumor Heterogeneity and Resistance
6.1.3. Patient Selection and Biomarkers
6.1.4. Balancing Antiviral and Antitumor Immune Responses
6.1.5. Safety and Toxicity
6.1.6. Manufacturing and Regulatory Hurdles
6.2. Future Directions
- Biomarkers: Development predictive biomarkers (viral receptors, immune status, microbiome composition) to identify patients most likely to benefit from specific OV treatments.
- Personalized OV Therapy: Tailoring OVs based on tumor molecular profiling and patient-specific features such as specific receptor expression and immune status.
- Advanced Engineering: Creating “smart” viruses with enhanced tumor targeting, controlled replication (e.g., using miRNA targets for tissue specificity), and sophisticated payload release mechanisms (e.g., inducible promoters). Expanding the range of payloads, including gene editing tools like CRISPR, is also an area of interest. Synthetic virology approaches are emerging.
- Improved Combination Strategies: Identifying optimal combinations and sequencing of OVs with ICIs, ACTs, targeted therapies, and conventional therapies. Understanding biomarkers predictive of response to specific combinations is crucial.
- Novel Delivery Systems: Continued innovation in delivery methods, including image-guided delivery and responsive nanocarriers. Exploring routes like inhalation for lung cancers or intraperitoneal delivery for peritoneal carcinomatosis is also important.
- Integration with Microbiome Research: Investigating the interactions between OVs, the tumor microbiome, and the host’s gut microbiome, and how these interactions influence treatment efficacy.
- Virus Cocktails: Using combinations of different OVs to potentially overcome resistance and target multiple pathways.
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| ACT | Adoptive Cell Therapy |
| ADCC | Antibody-Dependent Cellular Cytotoxicity |
| ADCP | Antibody-Dependent Cellular Phagocytosis |
| AKT | Protein Kinase B |
| APC | Antigen-Presenting Cell |
| ATM | Ataxia Telangiectasia Mutated |
| ATP | Adenosine Triphosphate |
| ATR | Ataxia Telangiectasia and Rad3-Related |
| BRAF | v-Raf Murine Sarcoma Viral Oncogene Homolog B |
| CAR | Chimeric Antigen Receptor |
| CEA | Carcinoembryonic Antigen |
| CED | Convection-Enhanced Delivery |
| CMV | Cytomegalovirus |
| CRISPR | Clustered Regularly Interspaced Short Palindromic Repeats |
| CRS | Cytokine Release Syndrome |
| CRT | Calreticulin |
| CSF | Colony-Stimulating Factor |
| CTL | Cytotoxic T Lymphocyte |
| CTLA-4 | Cytotoxic T-Lymphocyte-Associated Protein 4 |
| DAMP | Damage-Associated Molecular Pattern |
| DC | Dendritic Cell |
| DNA | Deoxyribonucleic Acid |
| DNMT | DNA Methyltransferase |
| DNX-2401 | Delta-24-RGD Oncolytic Adenovirus |
| ECM | Extracellular Matrix |
| EGFR | Epidermal Growth Factor Receptor |
| ERK | Extracellular Signal-Regulated Kinase |
| ERV | Endogenous Retrovirus |
| FDA | Food and Drug Administration |
| GBM | Glioblastoma Multiforme |
| GM-CSF | Granulocyte-Macrophage Colony-Stimulating Factor |
| HDAC | Histone Deacetylase |
| HIF | Hypoxia-Inducible Factor |
| HSV | Herpes Simplex Virus |
| ICD | Immunogenic Cell Death |
| IDO | Indoleamine 2,3-Dioxygenase |
| IFN | Interferon |
| IL | Interleukin |
| IRF | Interferon Regulatory Factor |
| JAK | Janus Kinase |
| LAG-3 | Lymphocyte-Activation Gene 3 |
| MDSC | Myeloid-Derived Suppressor Cell |
| MHC | Major Histocompatibility Complex |
| miRNA | MicroRNA |
| NF-κB | Nuclear Factor Kappa B |
| NK | Natural Killer Cell |
| NDV | Newcastle Disease Virus |
| OV | Oncolytic Virus |
| PD-1 | Programmed Cell Death Protein 1 |
| PD-L1 | Programmed Death-Ligand 1 |
| PRR | Pattern Recognition Receptor |
| RECIST | Response Evaluation Criteria in Solid Tumors |
| RNA | Ribonucleic Acid |
| scFv | Single-Chain Variable Fragment |
| STING | Stimulator of Interferon Genes |
| TAA | Tumor-Associated Antigen |
| TAM | Tumor-Associated Macrophage |
| TCR | T-Cell Receptor |
| TIGIT | T Cell Immunoreceptor with Ig and ITIM Domains |
| TLS | Tertiary Lymphoid Structure |
| TME | Tumor Microenvironment |
| TNF | Tumor Necrosis Factor |
| TriTE | Trispecific T-Cell Engager |
| VISTA | V-Domain Ig Suppressor of T-Cell Activation |
| VSV | Vesicular Stomatitis Virus |
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| Virus Family | Representative OV Platforms | Key Engineering Strategies | Cancer Targets (Examples) | Clinical Status | Primary Barrier to Clinical Efficacy |
|---|---|---|---|---|---|
| A. Clinically Advanced Oncolytic Virus Platforms (Human Testing) | |||||
| Herpesviridae | T-VEC; G47Δ; HF10; NV1020; RP1/RP2/RP3; oHSV-IL12 | ICP34.5/ICP47 deletions; GM-CSF or IL-12 arming; antibody/minibody payloads; tumor-specific promoters | Melanoma; GBM; liver metastases; pancreatic and other solid tumors | FDA approval (T-VEC); Japan approval (G47Δ); phase I–III trials | Limited intratumoral spread; pre-existing HSV immunity; local toxicity |
| Adenoviridae | H101; ONYX-015; DNX-2401; OBP-301; Enadenotucirev; LOAd703 | E1A/E1B deletions; hTERT promoters; RGD retargeting; CD40L/4-1BBL and cytokine arming | HNSCC; GBM; ovarian; pancreatic; colorectal; liver tumors | H101 approved in China; global phase I–II trials | Pre-existing adenoviral immunity; inflammatory toxicity |
| Poxviridae (Vaccinia/MVA) | Pexa-Vec; Olvi-Vec; TG6002; JX-963 | TK deletion; GM-CSF/IFN payloads; suicide genes; systemic replication | HCC; melanoma; colorectal liver metastases | Phase I–III trials | Neutralizing antibodies; safety in immunocompromised hosts |
| Reoviridae | Pelareorep (Reolysin) | Natural Ras-pathway tropism; ICD induction; combination with ICIs | Breast; GI cancers; melanoma; lymphoma | FDA Fast Track; phase II–III trials | Modest single-agent efficacy; reliance on combinations |
| Picornaviridae | PVSRIPO; CAVATAK (CVA-21); SVV-001 | Receptor tropism (CD155, ICAM-1); IRES rewiring | GBM; melanoma; SCLC | Phase I–II trials | Neurotoxicity risk; narrow tumor tropism |
| Paramyxoviridae | MV-NIS; MV-CEA; NDV-PV701 | Receptor retargeting; cytokine arming; strong innate activation | Myeloma; ovarian; lung; PDAC; bladder | Phase I–II trials | Antiviral immunity; limited persistence |
| Rhabdoviridae | VSV-IFNβ; MG1 (Maraba) | IFN-β safety switch; NIS imaging; in situ vaccination | Melanoma; AML; TNBC | Early clinical trials | Rapid antiviral clearance; neurotoxicity concerns |
| Parvoviridae | H-1PV (ParvOryx) | Natural oncotropism; NS1-mediated apoptosis | GBM; PDAC | Phase I–II trials | Limited replication efficiency |
| B. Emerging and Preclinical Oncolytic Virus Platforms | |||||
| Retroviridae | RRV-CD; RRV-TK; MLV-based vectors | Pro-drug converting enzymes; stable integration | Glioma; liver metastases | Phase I–II | Insertional mutagenesis risk; slow kinetics |
| Orthomyxoviridae | NS1-deleted influenza OVs | Enhanced IFN induction; respiratory targeting | Lung; ovarian; colon | Preclinical–early clinical | Safety concerns; host immunity |
| Bornaviridae | Recombinant BDV OVs | Low-cytolytic persistent infection | CNS tumors | Preclinical | Risk of viral persistence |
| Baculoviridae | Baculo-GM-CSF; Baculo-STING | Large payload capacity; non-replicating in mammals | Hepatobiliary; PDAC | Preclinical | Lack of replication limits efficacy |
| Alphaviridae | SFV; Sindbis; VEE OVs | High-level expression; strong innate immunity | Breast; ovarian; glioma | Preclinical–early-phase I | Systemic toxicity; rapid clearance |
| Coronaviridae | Engineered MHV-1 | Synthetic chassis; innate immune activation | Experimental tumor models | Preclinical | Biosafety and regulatory constraints |
| Flaviviridae | Zika-based OVs | Neural progenitor tropism; IFN-sensitive attenuation | GBM; pediatric brain tumors | Preclinical | Neurotoxicity risk |
| Togaviridae | Ross River virus OVs | Rapid replication; antigen expression | Solid tumors | Preclinical | Limited translational experience |
| Bunyavirales | Attenuated RVFV OVs | Strong RIG-I/MDA5 activation | Liver cancers | Preclinical | Hepatotoxicity and safety concerns |
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Fayyad-Kazan, M.; Al-Tameemi, S.; Ouhtit, A. Oncolytic Viruses in Cancer Immunotherapy: From Molecular Engineering to Clinical Translation. Cells 2026, 15, 393. https://doi.org/10.3390/cells15050393
Fayyad-Kazan M, Al-Tameemi S, Ouhtit A. Oncolytic Viruses in Cancer Immunotherapy: From Molecular Engineering to Clinical Translation. Cells. 2026; 15(5):393. https://doi.org/10.3390/cells15050393
Chicago/Turabian StyleFayyad-Kazan, Mohammad, Sarah Al-Tameemi, and Allal Ouhtit. 2026. "Oncolytic Viruses in Cancer Immunotherapy: From Molecular Engineering to Clinical Translation" Cells 15, no. 5: 393. https://doi.org/10.3390/cells15050393
APA StyleFayyad-Kazan, M., Al-Tameemi, S., & Ouhtit, A. (2026). Oncolytic Viruses in Cancer Immunotherapy: From Molecular Engineering to Clinical Translation. Cells, 15(5), 393. https://doi.org/10.3390/cells15050393

