Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment.

BACKGROUND: The perineural invasion (PNI)-mediated inflammation of the tumor microenvironment (TME) varies among gastric cancer (GC) patients and exhibits a close relationship with prognosis and immunotherapy. Assessing the neuroinflammation of TME is important in predicting the response to immunotherapy in GC patients. METHODS: Fifteen independent cohorts were enrolled in this study. An inflammatory score was developed and validated in GC. Based on PNI-related prognostic inflammatory signatures, patients were divided into Clusters A and B using unsupervised clustering. The characteristics of clusters and the potential regulatory mechanism of key genes were verified by RT-PCR, western-blot, immunohistochemistry and immunofluorescence in cell and tumor tissue samples.The neuroinflammation infiltration (NII) scoring system was developed based on principal component analysis (PCA) and visualized in a nomogram together with other clinical characteristics. RESULTS: Inflammatory scores were higher in GC patients with PNI compared with those without PNI (P < 0.001). NII.clusterB patients with PNI had abundant immune cell infiltration in the TME but worse prognosis compared with patients in the NII.clusterA patients with PNI and non-PNI subgroups. Higher immune checkpoint expression was noted in NII.clusterB-PNI. VCAM1 is a specific signature of NII.clusterB-PNI, which regulates PD-L1 expression by affecting the phosphorylation of STAT3 in GC cells. Patients with PNI and high NII scores may benefit from immunotherapy. Patients with low nomogram scores had a better prognosis than those with high nomogram scores. CONCLUSIONS: Inflammation mediated by PNI is one of the results of tumor-nerve crosstalk, but its impact on the tumor immune microenvironment is complex. Assessing the inflammation features of PNI is a potential method in predicting the response of immunotherapy effectively.

Experimental study on FBG sensing technology-based stress monitoring at the corners of reinforced soil retaining walls.

As a unique type of flexible slope fill-retaining structure, reinforced soil-retaining walls have the advantages of convenient construction, broad application conditions, good seismic performance, and high economic benefits. In general, reinforced soil-retaining walls appear at corners due to the restriction in topographic conditions during engineering construction. However, their special structures and stress conditions are usually ignored, thus triggering panel bulging, cracking, and collapse. In this study, an experimental method based on fiber Bragg grating (FBG) sensing technology was proposed for a physical model of reinforced soil-retaining walls. Then, a uniformly distributed load experiment was performed on this model by combining the measurement advantages of intelligent wire-type soil pressure sensors and the flexible characteristics of geotechnical reinforcement materials. The deformation development of this reinforced soil-retaining wall was monitored. Results revealed that before and after the loading of the reinforced soil-retaining wall, the deformation was mainly concentrated above the retaining wall, and the deformation scale at the corners was larger than that in the bilateral linear parts. After loading, the largest force deformation area on the retaining wall was transferred from the corners to the load area. The maximum strain was right beneath the load above the retaining wall, and the peak value at the other layers gradually approached the retaining wall. The experimental results prove that FBG sensing technology is feasible and effective for the whole-process monitoring of reinforced soil-retaining walls and is thus worthy of popularization and application.