Cancer terminator viruses (CTVs) are next‑generation conditionally replicating oncolytic adenoviruses that integrate precise tumor targeting, direct oncolysis, and potent cytokine‑mediated immunotherapy into a single platform. In CTVs, viral replication is driven by cancer‑selective promoters such as the progression elevated gene‑3 (PEG‑3) promoter, restricting E1A expression and adenoviral replication to tumor cells while sparing normal tissues. These vectors are "armed" with broad‑acting immunomodulatory cytokines, most notably melanoma differentiation-associated gene‑7/interleukin‑24 (mda‑7/IL‑24) or interferon‑gamma, which can induce cancer‑selective apoptosis, toxic autophagy, anti‑angiogenesis, and robust innate and adaptive immune responses, including "bystander killing" of distant, noninfected tumor cells. Chimeric fiber‑modified backbones such as Ad.5/3 enhance infection of Coxsackie-adenovirus receptor-deficient tumors, broadening applicability to refractory epithelial, prostate, brain, and pancreatic cancers. Preclinical studies demonstrate that CTVs eradicate primary and metastatic lesions in multiple xenograft models and synergize with chemotherapy, radiotherapy, and immune checkpoint inhibitors, especially when combined with advanced delivery technologies such as ultrasound‑targeted microbubble destruction and focused ultrasound double-microbubble platforms for systemic, site‑directed release. Ongoing efforts to incorporate IL‑24 "Superkine," fusion cytokines and fusion Superkines, and rational combinations with immunotherapies position CTVs as a versatile and clinically translatable viro-immunotherapeutic strategy for advanced solid tumors. Progress in these efforts will pave the way for applying these virotherapies for improved cancer treatments in the clinic.
While there are many choices among gene transfer vectors for basic or applied research, non-replicating adenoviruses are among the most studied. The virus is well suited for in vivo gene therapy since the vector can be produced with relatively high titers, is an efficient platform for in vivo modification of a variety of target cells and is relatively safe considering that the viral genome remains episomal. The production of adenoviral vectors is scalable and, once virus particles have been recovered, does not depend on the transfection of plasmids, a costly and laborious process to perform on large scale and with pharmaceutical quality. These vectors can be extensively modified to provide targeting at the level of transduction and transgene expression. The use of a non-replicating vector implies that it will not express viral proteins but instead can be modified to carry coding or non-coding sequences, including those that may be prejudicial to the life cycle of replicating viruses. Admittedly, immunogenicity of adenoviral vectors is an issue that requires careful consideration but may be leveraged to act as an adjuvant for vaccines or to overcome the immunosuppressive tumor microenvironment. Modifications also allow adenoviral vectors to act as important allies for achieving long-term expression. If viral replication is desired, non-replicating vectors can be paired with conditionally replicating adenovirus, thus providing the best of both approaches. To date, three cancer gene therapy products, Gendicine, Adstiladrin, and Papzimeos, that are based on non-replicating adenovirus have been approved for commercialization. As we will explore here, non-replicating adenoviral vectors continue to be developed for cancer gene therapy.
Reoviruses have emerged as promising oncolytic agents, exploiting their natural tropism for transformed cells with aberrant Ras signaling to enable selective replication and tumor cell lysis. The most clinically advanced candidate, Mammalian orthoreovirus Pelareorep (Reolysin), has demonstrated efficacy across multiple malignancies, including breast cancer, glioma, and pancreatic adenocarcinoma, with generally manageable safety profiles. Beyond Pelareorep, novel orthoreoviruses such as Avian orthoreovirus and Pteropine orthoreovirus have shown potent oncolytic activity and favorable tolerability in preclinical models, broadening the therapeutic landscape. Reovirus-based virotherapy exerts dual anti-tumor effects by inducing direct oncolysis and activating innate and adaptive immune responses, thereby enhancing outcomes when combined with chemotherapy or immune checkpoint inhibitors. Despite these advances, several barriers remain. Tumor heterogeneity and variable receptor expression affect viral infectivity and dissemination, while host immune responses, though critical for anti-tumor immunity, can also limit viral persistence and efficacy. Key mechanistic gaps persist in understanding reovirus-host interactions, particularly in immune modulation and cell death pathways. Furthermore, the optimal integration of reoviruses into combination regimens and clinical protocols requires further validation. Future efforts should emphasize biomarker-driven patient stratification, rational immunotherapeutic combinations to overcome tumor immunosuppression, and engineering of reovirus vectors to improve specificity and safety. Exploration of emerging orthoreoviruses with distinct biological properties also presents new opportunities for therapeutic innovation. Collectively, reoviruses represent a compelling platform at the forefront of precision oncolytic virotherapy, with translational potential hinging on the resolution of critical mechanistic and clinical challenges.
Viruses are extraordinary products of evolution that can be harnessed as versatile platforms for cancer therapy. They replicate in tumor cells, induce lysis, and stimulate antitumor immunity. Among viral platforms, oncolytic adenoviruses (OAds) have emerged as leading candidates. They are well-characterized, amenable to genetic modification, capable of accommodating large payloads, and can be produced at high titers. Nonetheless, natural adenoviruses require precise engineering to maximize therapeutic benefit. Clinical translation has also been constrained by several barriers, including the absence of murine models permissive for adenovirus replication, immune neutralization during systemic delivery, and insufficient tumor penetration. This chapter explores strategies to overcome these challenges, beginning with an overview of the adenovirus replication cycle and its interaction with host cells and systemic factors. We discuss the intrinsic properties of the adenoviral life cycle that make these vectors effective oncolytic agents, as well as genetic modifications designed to further enhance antitumor efficacy. These include receptor retargeting, replication control, insertion of therapeutic payloads, and capsid protein engineering to ablate unwanted interactions with host factors. We also highlight clinically advanced OAds to illustrate which modifications have successfully moved beyond laboratory development into clinical application. In addition, the potential of alternative adenovirus types with distinct seroprevalence, replication machinery, and blood interactions is reviewed. Finally, we discuss advances in preclinical modeling, emphasizing the limitations of murine models and highlighting the development of immunocompetent hamster and porcine models that better reproduce adenovirus-host interactions and provide critical insights for clinical translation of OAds.
Viruses have been developed as oncolytic immunotherapy agents due to their ability to target and kill cancer cells while sparing normal cells. Additionally, engineered oncolytic viruses (OVs) can alter the immunosuppressive tumor microenvironment, making other cancer therapies more favorable. Many candidate OVs are currently in clinical trials as monotherapy or in combination with other cancer therapeutics. Oncolytic myxoma virus (MYXV), a member of the Poxviridae family that infects only leporids in nature and causes no infection to humans or other animals, has been developed as an oncolytic immunotherapy agent. MYXV selectively infects cancer cells due to the accumulation of mutations and the absence of functional antiviral responses within these cells. The large dsDNA genome of MYXV is amenable to the deletion of non-essential immunomodulatory genes and to the insertion of multiple immunostimulatory transgenes with antitumor properties. The systemic and local administration of engineered MYXV promotes changes within the tumor microenvironment that reverse immunosuppression and improve immune activation and infiltration. These cancer tropism and immune activation properties, combined with the absence of preexisting antibodies, led to the testing of MYXV in various types of preclinical cancer models, including pancreatic cancer, glioblastoma, ovarian cancer, melanoma, small cell lung cancer, and hematological malignancies. This review highlights the current progress with the development of MYXV as an immunotherapeutic agent.
Vesicular stomatitis virus (VSV), an enveloped RNA virus that naturally infects livestock, has emerged as a highly versatile and potent platform for research purposes and, especially, for oncolytic virotherapy. The unique advantages of VSV as an oncolytic platform, including its rapid replication kinetics, strong cytolytic activity, its easily manipulated genome and ability to express foreign transgenes, and the ability to manufacture VSV at high concentrations, make this virus particularly well-suited as an oncolytic virus vector. This chapter provides a comprehensive overview of the biological and therapeutic foundations underlying the development of oncolytic VSV. It begins with the basic virology of VSV, including its genome organization, host range, and its inherent tumor specificity due to its sensitivity to type I interferons, allowing for preferential replication in cells that harbor impairments in antiviral responses, which is a hallmark of cancer. The principles of oncolytic virotherapy are outlined, emphasizing the multiple mechanisms of action, including direct tumor cell lysis and induction of local and systemic antitumor immunity. Examples of genetic engineering strategies to enhance efficacy and improve the translational potential are outlined. Finally, the current state of clinical development, highlighting completed and ongoing clinical trials evaluating recombinant oncolytic VSV vectors in various malignancies is summarized. Together, these basic principles, the extensive preclinical development spanning over 2 decades, and recent clinical advances underscore the promise of VSV as a next-generation oncolytic platform with substantial potential to transform cancer therapy through virus engineering and combinatorial immuno-oncology strategies.
Current cancer therapies, including cytotoxic agents, molecularly targeted drugs, and immune-based treatments, are often constrained by therapeutic resistance, systemic toxicity, and inconsistent clinical efficacy. The adeno-associated virus (AAV) vector-based therapy emerges as a promising strategy to address these limitations, owing to its favorable safety profile and high degree of engineerability. AAV-based gene therapy development is expanding beyond the treatment of rare monogenic disorders to encompass chronic diseases and cancer conditions associated with a high disease burden, driven not only by advances in vector technology but also by strategic considerations such as development costs, clinical needs, and commercial viability. Although challenges such as pre-existing host immunity and limited transgene packaging capacity remain, recent advances in biotechnology are actively mitigating these barriers. This review highlights recent progress in AAV-based gene therapy for cancer challenges and discusses future directions for the implementation of AAV vectors as a next-generation therapeutic modality in oncology.
Oncolytic viruses (OVs) are a rapidly expanding class of anti-neoplastic management options that utilize the innate infectivity of either native or modified viruses to preferentially lyse malignant cells while sparing healthy ones. Some OVs naturally target antigens within a tumor micro-environment, while others are re-oriented to identify specific targets via deletion of or addition to their existing genetic makeup. This chapter focuses on OVs in cutaneous oncology, providing an overview of their molecular mechanisms, clinical applications across a variety of disease states, and future directions for the field.
Glioblastoma (GBM) is a common, aggressive, primary brain tumor. New therapies are needed to improve outcomes in patients with this disease. One such approach which has shown preclinical promise is the use of genetically engineered Zika virus for oncolytic virotherapy. Zika virus is an enveloped, positive-sense, single-stranded RNA virus and is spread by mosquitoes of the Aedes genus. Most infections with Zika virus in adults are asymptomatic. However, primary infection with Zika virus early during pregnancy can cause fetal congenital defects. This phenomenon, termed congenital Zika syndrome, is thought to be the result of infection of fetal neural stem cells. The development of Zika virus as an oncolytic for GBM arose from the discovery that Zika virus infects and kills GBM stem cells. GBM stem cells have similarities to fetal neural stem cells and are a subpopulation of cells within the tumor that are refractory to treatment and likely drive tumor persistence and re-occurrence. In preclinical models of GBM, infection with Zika virus triggers immune-mediated clearance of orthotopically transplanted tumors and leads to development of immunological memory. The propensity of Zika virus to infect GBM stem cells along with limited systemic toxicities and transmissibility make Zika virus an ideal candidate for development as an oncolytic therapy.
Cancer biomarkers significantly advance precision oncology by giving physicians guidance about treatment options based on the molecular characteristics of a person's tumor, allowing for personalized cancer care. When used collectively, the identification of these cancer biomarkers will lead to better selection of appropriate therapies, facilitate monitoring of response to treatment, and provide rapid evaluation of treatment efficacy. Genetic mutations that are frequently used as cancer biomarkers include mutant forms of particular oncogenes like EGFR (epidermal growth factor receptor), BRAF (B-Raf proto-oncogene), and NTRK (neurotrophic receptor kinase). Targeted therapies that have been successfully developed to treat EGFR mutations in lung cancer and V600E BRAF mutations in melanoma have been proven to be effective. The use of drug therapies such as imlunestrant that specifically target ESR1 mutations in advanced breast cancer cases reflects the incorporation of genetic biomarkers into routine clinical decision making. Non-invasive liquid biopsy technologies, such as the MI Cancer Seek assay, permit the identification of the driver mutations (e.g., PIK3CA, EGFR, BRAF), the presence of microsatellite instability (MSI), and the mutational burden of a tumor tissue sample, providing predictive markers for both targeted and immunotherapeutic treatment options. The further development of HRD and the viral onco-genes have widened the options available for a biomarker-based therapy. This chapter will provide an in-depth explanation of an Introduction to Cancer Biomarkers and new research developments.
Biomarkers are molecules, for example, DNA, RNA, proteins, as well as metabolites, present in biofluids or tissues, whose levels are altered in response to disease. They are very important for healthcare settings as they provide significant insights to identify various biological processes, including progression and treatment response. In cancer therapy, these biomarkers assist in early identification, monitoring disease development as well as progression, and guiding personalized medicine. Cancer biomarkers are clinically categorised into three types: Diagnostic, Prognostic, and Predictive. Diagnostic biomarkers provide information about the disease and whether the patient has a particular kind of cancer. They also give information about the subtypes of that disease. Prognostic biomarkers assist for the prediction of the effects of the cancer in a patient, without considering the type of treatment. In addition, it also shows how aggressive the cancer is and how fast it may progress. Predictive biomarkers, in contrast, predict the patient's response to a particular treatment and which treatment strategy will be the most beneficial for the patient, which minimizes the time and expenditure of the treatment, and also avoids any adverse effects of the treatment. Recent advancements in highly efficient techniques such as genomics, proteomics, metabolomics, and advanced imaging have improved the detection of cancer biomarkers, which are more sensitive, specific, and accurate. These advances have led to the rise of targeted therapies, immunotherapy, and personalized medicine. Despite all these breakthroughs, challenges remain in the biomarker standardization, clinical validation, and accessibility of biomarker-based approaches. This chapter highlights the different types of biomarkers available for cancer detection and diagnosis, clinical applications, recent perspectives, and future prospects in cancer therapeutics.
The identification and detection of clinically meaningful cancer biomarkers are at the core of precision oncology development, with the potential to revolutionize cancer screening, diagnosis, prognosis, and targeted therapeutic approaches. The shifting paradigm of cancer biomarker discovery, including both new opportunities and old challenges preventing clinical translation, will be the subject of this chapter. Biomarkers such as genetic mutation, epigenetic alteration, protein expression profiling, and metabolomic fingerprints play a central role in stratifying cancer patients, predicting treatment efficacy, and monitoring disease progression. Advances in technologies at breakneck pace NGS, single-cell omics, proteomics, and artificial intelligence (AI)-driven analytics have significantly boosted the capacity to decode tumor heterogeneity, clonal evolution, and microenvironment interactions. Of particular interest, liquid biopsy platforms that focus on circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, and microRNAs are transforming non-invasive diagnostics with the potential for early detection and real-time monitoring of disease. Bringing candidate biomarkers to fully validated clinical tests, however, is an elusive goal. The current chapter critically assesses barriers like biological heterogeneity, lack of adequate assay standardization, sparse longitudinal validation, and variability in data interpretation across different platforms and populations. Tumor plasticity and pressure from therapy-induced dynamic alterations further cloud biomarker dependability, necessitating adaptive and integrative solutions. Consistently, there is a growing shift away from single-marker solutions toward composite biomarker panels guided by multi-omics integration and AI-guided predictive modeling. The chapter will also address current clinical applications of established biomarkers such as HER2 in breast cancer, EGFR in lung cancer, and PD-L1 expression and tumor mutational burden (TMB) in cancer immunotherapy and the limitations these biomarkers have in heterogeneous populations. Further, the ethical and regulatory considerations of biomarker development including data privacy issues in AI-based applications, equitable access to advanced diagnostics in low-resource settings, and cost-effectiveness for roll-out at scale will be addressed. Directions of the future will include developing standardized validation pipelines, interdisciplinarity, and biomarker platforms available globally that can be dynamically calibrated based on patient-specific profiles. Finally, this chapter hopes to set an all-encompassing road map toward closing the gap between the discovery of molecular biomarkers and clinical application in the hope of fashioning a better more accurate, individualized, and equitable future in cancer treatment.
The advent of biomarker-driven strategies has focused research on early detection, accurate diagnosis, prognosis assessment, and personalized treatment, thus revolutionizing the landscape of cancer care. The current chapter gives an extensive review of the latest advances in predictive, prognostic, and diagnostic biomarker detection methods in solid tumors using advanced technologies such as liquid biopsy, circulating tumor DNA (ctDNA), microRNAs, exosomal profiling, and multi-omics platforms that have high specificity and sensitivity in the identification of biomarkers. Additionally, the application of artificial intelligence and machine learning in biomarker analysis has showcased its ability to facilitate improved clinical decision-making. In addition, the chapter explores the clinical usefulness of these biomarkers in different solid cancers like breast, lung, colorectal, and prostate cancers. Despite the well-paced development in these fields, issues like tumor heterogeneity, cross-validation in different populations, and translating emerging biomarkers into everyday clinical practice still persist. The chapter concludes by describing future horizons and the imperative of strong standardization, interdisciplinarity, and ethics in applying biomarker-based approaches in oncology. As precision oncology advancements are on the rise, the integration of real-time biomarker monitoring and minimally invasive techniques holds promise for dynamic disease management. Emerging technologies like single-cell sequencing and spatial transcriptomics further enhance our understanding of tumor biology, paving the way for more individualized and adaptive therapeutic interventions in solid cancer treatment. Collaborative efforts between academia, industry, and clinical settings are essential to accelerate biomarker validation and regulatory approval, ensuring equitable access to advanced diagnostic tools across diverse patient populations worldwide.
The introduction of molecular diagnostics has completely changed oncology, moving the classification based on histology to biomarker-driven precision medicine. Through the use of biomarkers genomic, transcriptomic, proteomic, metabolomic, and epigenetic changes the cancer field is able to gain much needed insights for detection at an early stage, prognosis that is accurate, and treatment selection that is personalized. The current paper looks at the high-tech molecular processes that make the discovery and use of biomarkers possible, including next-generation sequencing, mass spectrometry, and PCR-based techniques, which are capable of very sensitive detection of everything from single-nucleotide variants to complete proteomic profiles. The talk points out the successful clinical translations like EGFR inhibitors in lung cancer and PARP inhibitors in BRCA-mutant cancers, at the same time acknowledging the biggest hurdles in biomarker validation such as standardization, ethical issues, and making sure no one is left out in access to the benefits. Some of the most promising new technologies like single-cell sequencing, CRISPR-based diagnostics, and artificial intelligence are expected to bring about further revolution in the area by unraveling the complexities of tumor heterogeneity, facilitating super-sensitive detection, and assimilating data from multiple omics. The future of cancer biomarker analysis is in the application of diverse molecular layers to evolve dynamic and comprehensive profiles of individual tumors. This will enable real-time monitoring through liquid biopsy and point-of-care devices. Ultimately, the constant improvement and the interdisciplinary partnership in biomarker science are of utmost importance to the full realization of the personalized oncology's promise and the enhancement of the survival rate of all cancer patients.
Over the past few years, targeted therapy has become the backbone of precision oncology, with personalized treatment plans shaped by the individual tumor's molecular and genetic profile. Underpinning this treatment approach, biomarkers enable identification of patient subgroups in whom specific agents are likely to be most beneficial, assist with monitoring response to treatment, and enable anticipation or prevention of drug resistance. This chapter gives an in-depth overview of biomarkers in targeted therapy and their central role in treatment decision-making across different types of cancer. It outlines established biomarkers including EGFR mutations in non-small cell lung cancer, HER2 amplification in breast cancer, BRAF mutations in melanoma, ALK rearrangement, and PD-L1 expression as integral in the direction of immunotherapy. This chapter also takes into account the growing impact of liquid biopsy techniques, such as circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), exosomes, and microRNAs, as minimally invasive approaches to dynamic monitoring, early diagnosis and therapeutic direction. It also discusses tumor mutational burden (TMB), microsatellite instability (MSI), and gene expression signatures as more general indicators of responsiveness to treatment. The integration of multi-omics approaches, artificial intelligence, and machine learning is also enabling new horizons in biomarker discovery and validation. However, there are obstacles to clinical translation, such as tumor heterogeneity, adaptive resistance mechanisms, and regulatory and ethical considerations for biomarker-directed therapies. By integrating current advances and clinical applications, this chapter emphasizes the central role of biomarkers in optimizing treatment approaches, reducing adverse effects, and ultimately enhancing patient outcomes. The discussion emphasizes the potential capabilities of precision medicine to revolutionize cancer care, where biomarker-directed treatment decisions are predictive, prognostic, and dynamically responsive to tumor evolution.
The term biomarkers defines a wide collection of biological indicators responsible for diagnosis, prognosis, and treatment outcome for an individual. In cancer, biomarkers are precise and valuable tool in diagnosis of early onset of neoplasm, diversity in oncologic conditions, heterogeneity in tumor and its micro-environment. As cancer treatment has shifted from high dosage and multiple therapy to precise and precision medicine, the role of biomarkers have been exponentially captured the therapeutic market. The cancer biomarkers ranges from diagnostic, prognostic, predictive, pharmacodynamic and monitoring to companion diagnostic biomarkers. The use of these biomarkers are very precise and strategically designed for the high efficacy and less toxic for the patient.
In oncology, biomarkers have various probable applications. They are crucial in cancer detection and are vital in diagnosis, predicting outcomes, and determining the prognosis of various types of cancer. Biomarkers are critical in enhancing treatment outcomes and reducing healthcare costs. Numerous biomolecules can be used as diagnostic, predictive, and prognostic cancer biomarkers. These biomolecules include genetic, epigenetic, transcriptomic, metabolomic, proteomic, cellular, physiological, or imaging-based biomarkers. Cancer cells or surrounding non-cancerous cells produce cancer biomarkers in response to the presence of tumors. It offers a critical insight into molecular and cellular changes associated with malignancy. Once a biomarker is identified, it helps elucidate the molecular pathways linked to the onset and progression of cancer and is used to formulate treatment. Many cancer biomarkers are already in therapeutic practice. One major challenge is the development of early-stage detection and prognostic biomarkers, as most early-stage cancers are often asymptomatic and therefore difficult to detect. This chapter will cover the broad spectrum of the role of cancer biomarkers and their application in the context of cancer detection, diagnosis, and treatment.
Abstract Background Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality. Moreover, the clinical utility of conventional chemotherapies is limited by systemic toxicity and poor tumor selectivity. Receptor-targeted small extracellular vesicles (sEVs) represent a promising nanotechnology-based strategy for precision drug delivery; however, rational receptor selection remains insufficiently explored. Results We performed a comparative evaluation of epidermal growth factor receptor (EGFR)-targeted (GE11-sEVs) and NTSR1-targeted (RKPDIL-sEVs) sEVs for doxorubicin delivery in HCC models. GE11-sEVs exhibited efficient uptake in EGFR-overexpressing SK-Hep1 cells, triggered apoptosis through activation of p53 and cleaved PARP1, and significantly suppressed tumor growth in xenograft models. In contrast, RKPDIL-sEVs exhibited higher cellular uptake than control EVs (Ct-sEVs) in cells with high NTSR1 expression; however, it did not result in a significant increase in apoptotic responses. Furthermore, in vivo biodistribution analyses revealed that sustained tumor accumulation and therapeutic efficacy were achieved only with GE11-sEVs. Importantly, both formulations exhibited minimal systemic toxicity. Conclusions Receptor expression alone is insufficient for effective sEV-mediated drug delivery. Instead, receptor-specific uptake efficiency and in vivo retention critically are critical determinants of therapeutic outcomes. This study highlights the importance of rational receptor selection and comparative validation—including informative negative results—in the design of targeted sEV-based nanomedicines for HCC.
Oral squamous cell carcinoma (OSCC) is known to inadequate therapies outcomes due to low efficacy and inflammatory toxicity of conventional chemotherapy. Herein, this study was developed cisplatin-loaded cerium oxide nanozymes (Cis@CeO₂ NZs) as a multi-functional platform to improve the anticancer properties by modulating redox and regulating anti-inflammatory responses. Cerium oxide nanozymes were successfully synthesized using controlled precipitation method and it showed high efficiency in Cis loading (encapsulation efficiency 68–75
