Multiple myeloma (MM) is an incurable hematological malignancy. Chimeric antigen receptor (CAR)-expressing T cells have been demonstrated successful in the clinic to treat B-lymphoid malignancies. However, the potential utility of antigen-specific CAR-engineered natural killer (NK) cells to treat MM has not been explored. In this study, we determined whether CS1, a surface protein that is highly expressed on MM cells, can be targeted by CAR NK cells to treat MM. We successfully generated a viral construct of a CS1-specific CAR and expressed it in human NK cells. In vitro, CS1-CAR NK cells displayed enhanced MM cytolysis and IFN-γ production, and showed a specific CS1-dependent recognition of MM cells. Ex vivo, CS1-CAR NK cells also showed similarly enhanced activities when responding to primary MM tumor cells. More importantly, in an aggressive orthotopic MM xenograft mouse model, adoptive transfer of NK-92 cells expressing CS1-CAR efficiently suppressed the growth of human IM9 MM cells and also significantly prolonged mouse survival. Thus, CS1 represents a viable target for CAR-expressing immune cells, and autologous or allogeneic transplantation of CS1-specific CAR NK cells may be a promising strategy to treat MM.

Computed tomography (CT) is widely used in screening, diagnosis, and image-guided therapy for both clinical and research purposes. Since CT involves ionizing radiation, an overarching thrust of related technical research is development of novel methods enabling ultrahigh quality imaging with fine structural details while reducing the X-ray radiation. In this paper, we present a semi-supervised deep learning approach to accurately recover high-resolution (HR) CT images from lowresolution (LR) counterparts. Specifically, with the generative adversarial network (GAN) as the building block, we enforce the cycle-consistency in terms of the Wasserstein distance to establish a nonlinear end-to-end mapping from noisy LR input images to denoised and deblurred HR outputs. We also include the joint constraints in the loss function to facilitate structural preservation. In this deep imaging process, we incorporate deep convolutional neural network (CNN), residual learning, and network in network techniques for feature extraction and restoration. In contrast to the current trend of increasing network depth and complexity to boost the CT imaging performance, which limit its real-world applications by imposing considerable computational and memory overheads, we apply a parallel 1 × 1 1 × 1 1 × 1 CNN to compress the output of the hidden layer and optimize the number of layers and the number of filters for each convolutional layer. Quantitative and qualitative evaluations demonstrate that our proposed model is accurate, efficient and robust for superresolution (SR) image restoration from noisy LR input images. In particular, we validate our composite SR networks on three largescale CT datasets, and obtain promising results as compared to the other state-of-the-art methods.

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Replication-selective oncolytic herpes simplex virus (HSV) has shown considerable promise as an antitumor agent. Although the current oncolytic HSVs were exclusively constructed from HSV-1, HSV-2 has several unique features that could be exploited to convert the virus to an oncolytic agent. The N-terminus of the HSV-2 ICP10 gene product contains a well-defined serine/threonine protein kinase (PK) domain, which can activate the Ras/MEK/MAPK mitogenic pathway and thus facilitate efficient HSV-2 replication. Because the Ras signaling pathway is a key regulator of normal cell growth and malignant transformation, it is aberrantly activated in many human tumors. Here we report that a mutant HSV-2 (FusOn-H2), constructed by replacing the PK domain of ICP10 with the gene encoding the green fluorescent protein, can selectively replicate in and thus lyse tumor cells. Moreover, infection of FusOn-H2 led to syncytia formation in tumor cells, providing an additional tumor-destroying mechanism. A single moderate-dose injection of FusOn-H2 into established breast cancer xenografts completely eradicated the tumors in more than 80% of the animals, leading to their long-term survival. We conclude that this HSV-2 mutant is a safe and potent oncolytic agent useful for the treatment of malignant solid tumors such as breast cancer.

Oncolytic viruses have shown considerable promise in the treatment of solid tumors, but their potency must be improved if their full clinical potential is to be realized. We inserted the gene encoding a truncated form of the gibbon ape leukemia virus envelope fusogenic membrane glycoprotein (GALV.fus) into an oncolytic herpes simplex virus, using an enforced ligation procedure. Subsequent in vitro and in vivo studies showed that expression of GALV.fus in the context of an oncolytic virus significantly enhances the antitumor effect of the virus. Furthermore, by controlling GALV.fus expression through a strict late viral promoter, whose activity depends on the initiation of viral DNA replication, we were able to express this glycoprotein in tumor cells but not in normal nondividing cells. It will be of interest to confirm whether functional expression of a strong fusogenic gene by an oncolytic herpes simplex virus enhances viral antitumor activity without increasing its toxicity.

The receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2s pike (S) protein playsacentral role in mediating the first step of virus infection to cause disease:v irus binding to angiotensin-converting enzyme 2( ACE2) receptors on human host cells.T herefore, S/RBD is an ideal target for blocking and neutralization therapies to prevent and treat coronavirus disease 2019 (COVID-19). Using at arget-based selection approach, we developed oligonucleotide aptamers containing ac onserved sequence motif that specifically targets S/RBD.S ynthetic aptamers had high binding affinity for S/RBD-coated virus mimics (K D % 7nM) and also blocked interaction of S/RBD with ACE2 receptors (IC 50 % 5nM). Importantly,a ptamers were able to neutralizeSprotein-expressing viral particles and prevent host cell infection, suggesting apromising COVID-19 therapys trategy.

A simple and sensitive method to quantitatively measure the cytolytic effect of tumor-specific T killer cells is highly desirable for basic and clinical studies. Chromium (51Cr) release assay has been the “gold standard” for quantifying cytolytic activities of cytotoxic T lymphocytes (CTLs) against target cells and this method is still being used in many laboratories. However, a major drawback of this method is the use of radioactive materials, which is inconvenient to handle because of environmental safety concerns and expensive due to the short half-life of the isotope. Consequently, several nonradioactive methods have been reported recently. Here we report a new method that we recently developed for quantifying antigen-specific cytolytic activity of CTLs. This method fully exploits the high sensitivity and the relative simplicity of luciferase quantitative assay. We initially expected the released luciferase in the supernatant to be the adequate source for monitoring cell death. However, to our total surprise, incubation of these killer T cells with the tumor cell targets did not result in significant release of luciferase in the culture medium. Instead, we found that the remaining luciferase inside the cells could accurately reflect the overall cell viability.

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