The development of cancer causes disruption of anti-tumor immunity required for surveillance and elimination of tumor cells. Immunotherapeutic strategies aim for the restoration or establishment of these anti-tumor immune responses. Cancer immunotherapies include immune checkpoint inhibitors (ICIs), adoptive cellular therapy (ACT), cancer vaccines, and oncolytic virotherapy (OVT). The clinical success of some of these immunotherapeutic modalities, including herpes simplex virus type-1 derived OVT, resulted in Food and Drug Administration (FDA) approval for use in treatment of human cancers. However, a significant proportion of patients do not respond or benefit equally from these immunotherapies. The creation of an immunosuppressive tumor microenvironment (TME) represents an important barrier preventing success of many immunotherapeutic approaches. Mechanisms of immunosuppression in the TME are a major area of current research. In this review, we discuss how oncolytic HSV affects the tumor microenvironment to promote anti-tumor immune responses. Where possible we focus on oncolytic HSV strains for which clinical data is available, and discuss how these viruses alter the vasculature, extracellular matrix and immune responses in the tumor microenvironment.

Current oncolytic virotherapies possess limited response rates. However, when certain patient selection criteria are used, oncolytic virotherapy response rates have been shown to increase.

Detecting cancers at early stages can dramatically reduce mortality rates. Therefore, practical cancer screening at the population level is needed. To develop a comprehensive detection system to classify multiple cancer types, we integrated an artificial intelligence deep learning neural network and noncoding RNA biomarkers selected from massive data. Our system can accurately detect cancer vs. healthy objects with 96.3% of AUC of ROC (Area Under Curve of a Receiver Operating Characteristic curve), and it surprisingly reaches 78.77% of AUC when validated by real-world raw data from a completely independent data set. Even validating with raw exosome data from blood, our system can reach 72% of AUC. Moreover, our system significantly outperforms conventional machine learning models, such as random forest. Intriguingly, with no more than six biomarkers, our approach can easily discriminate any individual cancer type vs. normal with 99% to 100% AUC. Furthermore, a comprehensive marker panel can simultaneously multi-classify common cancers with a stable 82.15% accuracy rate for heterogeneous cancerous tissues and conditions. This detection system provides a promising practical framework for automatic cancer screening at population level. Key points: (1) We developed a practical cancer screening system, which is simple, accurate, affordable, and easy to operate. (2) Our system binarily classify cancers vs. normal with >96% AUC. (3) In total, 26 individual cancer types can be easily detected by our system with 99 to 100% AUC. (4) The system can detect multiple cancer types simultaneously with >82% accuracy.

Current approaches to cancer immunotherapy include immune checkpoint inhibitors, cancer vaccines, and adoptive cellular therapy. These therapies have produced significant clinical success for specific cancers, but their efficacy has been limited. Oncolytic virotherapy (OVT) has emerged as a promising immunotherapy for a variety of cancers. Furthermore, the unique characteristics of OVs make them a good choice for delivering tumor peptides/antigens to induce enhanced tumor-specific immune responses. The first oncolytic virus (OV) approved for human use is the attenuated herpes simplex virus type 1 (HSV-1), Talimogene laherparepvec (T-VEC) which has been FDA approved for the treatment of melanoma in humans. In this study, we engineered the recombinant oncolytic HSV-1 (oHSV) VC2-OVA expressing a fragment of ovalbumin (OVA) as a fusion protein with VP26 virion capsid protein. We tested the ability of VC2-OVA to act as a vector capable of stimulating strong, specific antitumor immunity in a syngeneic murine melanoma model. Therapeutic vaccination with VC2-OVA led to a significant reduction in colonization of tumor cells in the lungs of mice intravenously challenged B16cOVA cells. In addition, VC2-OVA induced a potent prophylactic antitumor response and extended survival of mice that were intradermally engrafted with B16cOVA tumors compared with mice immunized with control virus.

Here, we present the construction of an attenuated herpes simplex virus type-1 (HSV-1)-vectored vaccine, expressing three liver-stage (LS) malaria parasite exported proteins (EXP1, UIS3 and TMP21) as fusion proteins with the VP26 viral capsid protein. Intramuscular and subcutaneous immunizations of mice with a pooled vaccine, composed of the three attenuated virus strains expressing each LS antigen, induced sterile protection against the intravenous challenge of Plasmodium yoelii 17X-NL salivary gland sporozoites. Our data suggest that this malaria vaccine may be effective in preventing malaria parasite infection using practical routes of immunization in humans.