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The latest research confirms that cytotoxic lymphocytes rely on pyroptosis to kill tumor cells, suggesting that pyroptosis plays a vital role in immune response. However, the influence of pyroptosis on tumor microenvironment (TME) remodeling and immunotherapy is still unclear. We analyzed the variations in the expression of 28 pyroptosis-related molecules in pan-cancer tissues and normal tissues and the influence of genome changes. We investigated 2,214 bladder cancer samples and determined that there are three pyroptosis phenotypes in bladder cancer, and there are significant differences in cell infiltration characteristics in different pyroptosis phenotypes. Phenotypes with high expression of pyroptosis-related molecules are “hot tumors” with better immune function. We used a principal component analysis to measure the level of pyroptosis in patients with PyroScore, and confirmed that the PyroScore can predict the prognosis of bladder cancer patients, the sensitivity of the immune phenotype to chemotherapy, and the response to immunotherapy. Patients with a high PyroScore are more sensitive to chemotherapeutics such as cisplatin and gemcitabine, and have a better prognosis (HR = 0.7; 95%CI = 0.51–0.97, P = 0.041). Our study suggests a significant correlation between the expression imbalance of pyroptosis-related molecules and genome variation in various cancers and suggests pyroptosis plays an important role in modeling the TME. Evaluating pyroptosis modification patterns contributes to enhancing our understanding of TME infiltration and can guide more effective immunotherapy strategies.

Immune-checkpoint blockade (ICB) has been routinely implemented to treat bladder cancer; however, most patients have little or no clinical benefit. In this study, 348 pretreated metastatic urothelial cancer samples from the IMvigor210 cohort were used to identify important genes significantly associated with CD8+ T effector and immune checkpoint signatures. The immune checkpoint inhibitor score (IMS) scoring system was constructed to predict the immunotherapy responsiveness. Transcriptome analysis confirmed that the high IMS score group had significant immune activation with better prognosis and higher immunotherapy responsiveness, which was a powerful biomarker for predicting the prognosis and responsiveness of ICB. Tumor immune dysfunction and exclusion (TIDE) scores were calculated using 2031 external bladder cancer samples for further validation. We selected the important Hub genes as potential therapeutic targets, and validated the genes using genomic, transcriptomic, immunomic, and other multi-omics methods. In addition, we construct a risk prediction model which could stratify patients with bladder cancer and predict patient prognosis and ICB treatment responsiveness. In conclusion, this study identified effective biomarkers for the prediction of immune checkpoint inhibitor treatment responsiveness in bladder cancer patients and provided new immunotherapeutic targets.

According to the difference in temperature, thermotherapy can be divided into thermal ablation and mild hyperthermia. The main advantage of thermal ablation is that it can efficiently target tumors in situ, while mild hyperthermia has a good inhibitory effect on distant metastasis. There are some similarities and differences between the two therapies with respect to inducing anti-tumor immune responses, but neither of them results in sustained systemic immunity. Malignant tumors (such as breast cancer, pancreatic cancer, nasopharyngeal carcinoma, and brain cancer) are recurrent, highly metastatic, and highly invasive even after treatment, hence a single therapy rarely resolves the clinical issues. A more effective and comprehensive treatment strategy using a combination of hyperthermia and immune checkpoint inhibitor (ICI) therapies has gained attention. This paper summarizes the relevant preclinical and clinical studies on hyperthermia combined with ICI therapies and compares the efficacy of two types of hyperthermia combined with ICIs, in order to provide a better treatment for the recurrence and metastasis of clinically malignant tumors.

BackgroundOvarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).ResultsWe identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.ConclusionsIn this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.

Objective Hypoxia, which can considerably affect the tumor microenvironment, hinders the use of immunotherapy in bladder cancer (BLCA). Therefore, we aimed to identify reliable hypoxia‐related biomarkers to guide clinical immunotherapy in BLCA. Methods Using data downloaded from TCGA‐BLCA cohort, we determined BLCA subtypes which divide 408 samples into different subtypes. Tumor immune infiltration levels of two clusters were quantified using ssGSEA, MCPcounter, EPIC, ESTIMATE, and TIMER algorithms. Next, we constructed a hypoxia score based on the expression of hypoxia‐related genes. The IMvigor210 cohort and SubMap analysis were used to predict immunotherapeutic responses in patients with different hypoxia scores. Hub genes were screened using cytoscape, immunohistochemistry (IHC), and multispectral immunofluorescence were used to detect the spatial distribution of immune markers. Results Patients with BLCA were categorized into cluster1 (n = 227) and Cluster2 (n = 181). Immune infiltration and expression of immune markers were higher in Cluster1. Immune infiltration was also more obvious in the high‐hypoxia score group which related to a better predicted response to immunotherapy. IHC, and multispectral immunofluorescence confirmed the importance of TLR8 in immune infiltration and immune phenotype. Conclusions BLCA subtype can evaluate the infiltration of immune cells in the tumor microenvironment of different patients. Hypoxia score in this study could effectively predict immunotherapeutic responses in patients with BLCA. TLR8 may be a potential target for clinical immunotherapy.

Immune-checkpoint blockade (ICB) has been routinely implemented to treat bladder cancer; however, most patients have little or no clinical benefit. In this study, 348 pretreated metastatic urothelial cancer samples from the IMvigor210 cohort were used to identify important genes significantly associated with CD8+ T effector and immune checkpoint signatures. The immune checkpoint inhibitor score (IMS) scoring system was constructed to predict the immunotherapy responsiveness. Transcriptome analysis confirmed that the high IMS score group had significant immune activation with better prognosis and higher immunotherapy responsiveness, which was a powerful biomarker for predicting the prognosis and responsiveness of ICB. Tumor immune dysfunction and exclusion (TIDE) scores were calculated using 2031 external bladder cancer samples for further validation. We selected the important Hub genes as potential therapeutic targets, and validated the genes using genomic, transcriptomic, immunomic, and other multi-omics methods. In addition, we construct a risk prediction model which could stratify patients with bladder cancer and predict patient prognosis and ICB treatment responsiveness. In conclusion, this study identified effective biomarkers for the prediction of immune checkpoint inhibitor treatment responsiveness in bladder cancer patients and provided new immunotherapeutic targets.

Background: Nasopharyngeal carcinoma (NPC), a neoplasm of the head and neck, has high incidence and mortality rates in East and Southeast Asia. Evodia rutaecarpa is a tree that is native to Korea and China, and its fruit (hereafter referred to as Evodia) exhibits remarkable antitumor properties. However, little is known about its mechanism of action in NPC. In this study, we employed network pharmacology to identify targets of active Evodia compounds in nasopharyngeal carcinoma and generate an interaction network. Methods: The active ingredients of Evodia and targets in NPC were obtained from multiple databases, and an interaction network was constructed via the Cytoscape and STRING databases. The key biological processes and signaling pathways were predicted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Molecular docking technology was used to identify the affinity and activity of target genes, and The Cancer Genome Atlas and Human Protein Atlas databases were used to analyze differential expression. Cell Counting Kit (CCK)-8 and Annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) dual-fluorescence staining were used for experimental verification. Results: Active Evodia compounds included quercetin, isorhamnetin, and evodiamine, and important NPC targets included MAPK14, AKT1, RELA, MAPK1, JUN, and p53, which were enriched in lipid and atherosclerosis signaling pathways. Additionally, we verified the high affinity and activity of the active compounds through molecular docking, and the target proteins were verified using immunohistochemistry and differential expression analyses. Furthermore, CCK-8 assays and Annexin V-FITC/PI dual-fluorescence staining showed that isorhamnetin inhibited the proliferation of NPC cells and induced apoptosis. Conclusion: Our results identified the molecular mechanisms of Evodia and demonstrated its ability to alter the proliferation and apoptosis of NPC cells through multiple targets and pathways, thereby providing evidence for clinical application of Evodia.

In the field of firms’ technological innovation, a large body of research has emphasized the roles of interlocking directors and the associated board networks in which they are embedded. By integrating the process perspective of absorptive capacity theory with stakeholder network theory, this study investigates the influence of board networks on firms’ technological innovation output, with particular attention given to the moderating effects of shareholder networks and CEO networks. The theoretical hypotheses suggest that degree centrality within board networks positively influences firms’ technological innovation output, and that this positive effect is weakened by degree centrality within both shareholder networks and CEO networks. While board networks facilitate information acquisition for technological innovation, shareholder networks and CEO networks may serve as substitutes. Furthermore, they may shape the motivations of shareholders and CEOs, potentially hindering the exploitation of information acquired through board networks. Using longitudinal data on Chinese A-share listed companies from 2005 to 2023, we construct three distinct types of interorganizational networks and annually measure firms’ degree centralities within each network type. Employing fixed-effects panel models, this study empirically verifies the proposed hypotheses. Practically, the findings offer important implications for firms seeking to align interorganizational networks with their technological innovation management strategies. We recommend that future research further explore the roles of diverse stakeholder networks in interorganizational contexts to enhance the understanding of how interactions across multilayer networks affect firms’ technological innovation output.

Abstract ObjectiveThe aim of this study was to investigate the different ictal onset stereoelectroencephalography patterns (IOPs) in patients with drug-resistant temporal lobe epilepsy (TLE). We examined whether the IOPs relate to different TLE subtypes, MRI findings, and underlying pathologies, and we evaluated their prognostic value for predicting the surgical outcome.MethodsWe retrospectively analyzed data from patients with TLE who underwent stereoelectroencephalography (SEEG) monitoring followed by surgical resection between January 2018 and January 2020. The SEEG recordings were independently analyzed by two epileptologists.ResultsForty-five patients were included in the study, and 61seizures were analyzed. Five IOPs were identified: low voltage fast activity (LVFA; 44.3%), spike-and-wave activity (16.4%), low frequency high-amplitude periodic spikes (LFPS; 18%), a burst of high-amplitude polyspikes (8.2%), and rhythmic sharp activity at ≤ 13 Hz (13.1%). Thirty-two patients were found to have a single IOP, while the other 13 patients had two or more IOPs. All five IOPs were found to occur in the medial temporal lobe epilepsy (MTLE), while four IOPs occurred in the lateral temporal lobe epilepsy (LTLE). The LFPS was a common IOP that could distinguish MTLE from LTLE (x2 = 7.046, p = 0.011). Among the MTLE patients, the LFPS was exclusively seen in cases of hippocampal sclerosis (x2 = 5.058, p = 0.038), while the LVFA was associated with nonspecific histology (x2 = 6.077, p = 0.023). The IOPs were not found to differ according to whether the MRI scans were positive or negative. After surgery, patients achieved the higher seizure-free rate at 81.8% and 77.8%, respectively, if the LFPS and LVFA were the predominant patterns. Multiple IOPs or a negative MRI did not indicate a poor prognosis.ConclusionsFive distinct IOPs were identified in the patients with TLE. The differences found have important clinical implications and could provide complementary information for surgical decision-making, especially in MRI-negative patients.

Channel pruning can reduce the number of neural network parameters and computational cost by eliminating redundant channels, its main purpose is to adapt to resource constrained devices. Evaluation-based global pruning and network search-based pruning are two common methods of channel pruning. However, the network architecture pruned by the global mask is often not optimal, while the method that directly searches for the optimal architecture will introduce a large number of hyperparameters, which greatly increases the training cost. In this paper, we propose a novel Two-dimensional information Entropy based Channel Pruning method (TECP). The pruning process consists of two steps. First, a global mask pruning scheme is employed to obtained a pre-pruning model. Then, the two-dimensional information entropy is calculated by using feature maps of dense network to adjust the pre-pruning model adaptively to get a compact network. Moreover, the entropy values are used to determine the minimum number of reserved channels per layer based on to avoid the imbalance of network architecture and the layer collapse caused by global pruning. Extensive experiments with a variety of networks on several datasets clearly demonstrate the effectiveness of our proposed TECP method. For example, results show that on CIFAR-10, the compressed model achieves comparable accuracy to the original model, but with a significantly lower number of parameters (44.29% for ResNet-20 and 46.79% for VGG-16). This is beneficial for industrial deployment. And experimental results also show that TECP method obtain the better performance compared with state-of-the-art method.