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T cell-engaging therapies involving bispecific T cell engager (BiTE) and chimeric antigen receptor T (CAR-T) cells have achieved great success in the treatment of hematological tumors. However, the paucity of ideal cell surface molecules that can be targeted on glioblastoma (GBM) partially reduces the immunotherapeutic efficacy. Recently, high expression of Fn14 has been reported in several solid tumors, so the strategy of exploiting this specific antigen for GBM immunotherapy is worth studying. Consequently, we constructed Fn14× CD3 BiTE and Fn14-specific CAR-T cells and investigated their cytotoxic activity against GBM in vitro and in vivo. First, expression of Fn14 was confirmed in glioma tissues and GBM cells. Then, we designed Fn14-specific BiTE and CAR-T cells and tested their cytotoxicity in GBM cell cultures and mouse models of GBM. Fn14 was highly expressed in GBM tissues and cell lines, while it was undetectable in normal brain samples. Fn14× CD3 BiTE, Fn14 CAR-T cells and Fn14 CAR-T/IL-15 cells were antigen-specific and highly cytotoxic, showing good antitumor activity in vitro and causing significant regression of established solid tumors in xenograft models. However, the xenografts treated with Fn14 CAR-T cells regrew, whereas xenografts treated with Fn14 CAR-T/IL-15 cells did not. IL-15 engineering augmented the antitumor activity of Fn14 CAR-T cells and resulted in significant antitumor effects similar to those of Fn14× CD3 BiTE. Our results suggest that Fn14 is an appropriate target for GBM. Anti-Fn14 BiTE and Fn14-specific CAR-T/IL-15 cells may be exciting immunotherapeutic options for malignant brain cancer.

Objective We conducted a first‐in‐human study to evaluate the bioactivity and safety of B7‐H3‐targeted chimeric antigen receptor (CAR) autologous T cells for treating recurrent anaplastic meningioma. Methods Tumor tissues from a patient with recurrent anaplastic meningioma were evaluated for B7‐H3 expression. B7‐H3‐targeted CAR‐T cells were delivered into the intracranial tumor resection cavity using an Ommaya device at a maximum dose of 1.5 × 107 cells. Magnetic resonance imaging (MRI) screening and multiple serum indexes were regularly monitored. The patient received surgical intervention after three‐cycle infusions, allowing analysis for CAR‐T‐cell infiltration and target antigen expression in post‐CAR‐T therapy tumor tissues. Results Immunochemical analysis demonstrated high and homogeneous B7‐H3 expression in tumor samples. MRI results indicated that the tumor near the delivery device was relatively stable compared with the rapid progression of tumors distant from the device. We found CAR‐T‐cell trafficking to regions of B7‐H3+ tumor tissues near the device, but not to tumor tissues distant from the device. Decreased B7‐H3 expression was observed near the region of CAR‐T‐cell infiltration after therapy. The intracavitary delivery of B7‐H3‐targeted CAR‐T cells was well‐tolerated and not associated with any toxic effects of grade 3 or higher. Conclusion Our results suggested that although intracavitary administration of B7‐H3‐targeted CAR‐T cells was safe and resulted in local bioactivity, addressing antigen loss and CAR‐T‐cell trafficking may further enhance the applications of B7‐H3‐targeted CAR‐T‐cell therapy., We present a first‐in‐human B7‐H3 (CD276)‐targeted CAR‐T‐cell pilot study for the treatment of recurrent anaplastic meningioma and evaluated the bioactivity and safety of this approach. We provide the evidence of safety and anti‐tumor response of local administration autologous B7‐H3‐targeted CAR‐T cells and have established the foundation for further development of B7‐H3‐targeted CAR‐T‐cell therapy.

With the growing number of automobiles, it brings both the problem of difficult parking and the increasing traffic accidents in parking process. As one of the important issue in the parking assist system, the detection method of nearest point from the obstacle to automobile body is studied. On the basis of analyzing and comparing several methods of automobile distance detection, a nearest point detection scheme of obstacle is proposed based on machine vision technology. The feature point analysis and matching algorithms of the vision images of the obstacle is analyzed emphatically. The improved Harris algorithm is used to detect the image corners. The basic matrix is used to establish epipolar constraint, and the region matching and parallax principle are used to realize corner matching. The nearest distance detection strategy between the automobile body and obstacle is put forward by polygon fitting for the automobile tail. The experiment results show that this method can effectively measure the nearest point and nearest distance between the automobile body and obstacle, which can provide effective information for the parking assist system and improve the driving safety.

In order to provide auxiliary information for car parking, a strategy of detecting the nearest distance between obstacle and vehicle tail was studied based on the binocular vision system and a parking assist system was designed. The captured images processed and analyzed by using binocular vision system, the image distortion was improved by using the histogram correction method, and the influence of noise in space was eliminated by using GAUSS FILTER. Harris algorithm was used to detect the characteristic points accurately, and the feature points were matched. A kind of strategy about detecting the recent distance between obstacles and the rear of vehicle was put forward. When fitting the curve, the curve of car tail was instead by polygon approximation. The detection of closest distance between obstacles and the rear of the vehicle was accomplished by using the binocular vision principle. The distance could be used to provide useful parking information to drivers.