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Abstract Purpose Dexmedetomidine (Dexmed) is a highly selective alpha 2 adrenoceptor (α2-AR) agonist with excellent sedation and analgesic effects and is frequently used in breast cancer surgery. However, the exact impact of Dexmed on breast cancer prognosis is still unclear. The primary objective of this pilot study was to explore study feasibility (recruitment and dropout rates) for future large-scale randomized controlled trial (RCT) to test the hypothesis that intraoperative Dexmed reduced recurrence-free survival (RFS) and overall survival (OS) in patients after breast cancer surgery. Methods Interviews with patients were performed during the anesthetic preoperative visit for informed consent. Adult females scheduled for a mastectomy due to primary breast cancer were 1:1 randomised to saline (Group Control) or Dexmed (Group Dexmed) treatment groups. The primary outcomes were descriptions of study feasibility (recruitment and dropout rates). We also performed a preliminary analysis of RFS (time from surgery to the earliest date of recurrence/metastasis) and OS (time from surgery to the date of all-cause death) and collected data on percentages/numbers of circulating immune cells at pre- and 24 h post-operation. Results A total of 964 patients were screened; 40% (385/964) met the inclusion criteria, among which 39% (150/385) were enrolled and randomly assigned to either Group Control (n = 75) or Group Dexmed (n = 75). The median follow-up duration was 49 months (interquartile range (IQR): 34–58 months) for Group Control and 48 months (IQR: 33–60 months) for Group Dexmed. Five percent (5%, 8/150) patients were lost to follow-up and 1% (2/150) died. There was no significant difference in RFS and OS. The percentage/number of natural killer (NK), B and T-cell subsets and the CD4+/CD8+ ratio were similar between groups at 24 h post-operation. Conclusion The pilot study was feasible to deliver. In a future definitive trial, the lower recruitment rate may be improved by increasing the number of anesthesiologists involved in the study. The study about the effects of Dexmed on long-term prognoses of breast cancer patients that is planned to follow this pilot study is a large-scaled randomized control study with the aim of providing evidence-based guidelines for rational use of Dexmed in patients undergoing breast cancer surgery. Trial registration Registered at ClinicalTrials.gov on October 20, 2016 (ID: NCT03109990). Graphical Abstract

Abstract Background μ‐opioid receptor agonists (MORAs) are indispensable for analgesia in bladder cancer (BC) patients, both during surgery and for chronic pain treatment. Whether MORAs affect BC progression and metastasis remains largely unknown. This study focused on the effects of MORAs on the formation of circulating tumor cells (CTCs) in BC and aimed to provide potential therapeutic targets, which would retain the pain‐relieving effects of MORAs in BC patients without sacrificing their long‐term prognosis. Methods Different preclinical models were used to identify the effects of MORAs on the progression of BC. A novel immunocapture microfluidic chip was utilized to analyze whether MORAs affected the number of CTCs in mouse models and clinical BC patients. Bioinformatic analyses, total transcriptome sequencing, and molecular biology methods were then used to investigate the underlying mechanisms in these models and in BC cell lines. Results Mouse models of hematogenous metastasis and in situ BC demonstrated that tumor metastasis was significantly increased after MORA treatment. A significant increase in the number of mesenchymal and/or epithelial CTCs was detected after MORA treatment in both the mouse models and clinical trial patients. Mechanistically, MORAs facilitated the formation of CTCs by activating the MOR/PI3K/AKT/Slug signaling pathway, hereby promoting the epithelial‐mesenchymal transition (EMT) of BC cells, as knockdown of MOR, Slug or blockade of PI3K inhibited the EMT process and CTC formation. Conclusion MORAs promoted BC metastasis by facilitating CTC formation. The EMT‐CTC axis could be targeted for preventive measures during MORA treatment to inhibit the associated tumor metastasis or recurrence in BC patients.

Opioids are commonly used in patients with breast cancer (BC), both for perioperative analgesia and for the relief of chronic cancer pain. Studies have suggested a potential association of opioid receptors (ORs) with the prognosis of BC patients. However, the exact roles of different ORs remain poorly understood. In this study, we found that κ opioid receptor (KOR) was the only OR (among the four types of ORs) that was significantly decreased in BC tumor tissues compared with peritumoral normal tissues. In addition, decreased expression of KOR correlated with poor clinical outcomes in patients with estrogen receptor (ER)-positive BC. In vitro studies confirmed the anti-tumor effects of KOR agonists in ER-positive MCF-7 and T47D cells by showing that activation of KOR significantly inhibited cellular proliferation and promoted apoptosis. Using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction network (PPI) analysis, we found that KOR-ER-XBP1 was the potential downstream signaling pathway mediating the anti-tumor effects of KOR agonist. Finally, the role of XBP1 was confirmed as KOR activation-induced increase in the proliferative and monoclonal formation abilities of ER-positive BC cells were both significantly abolished after silencing of XBP1. These findings provide us a better understanding of the roles of different ORs in BC, identifying KOR agonists as better opioids than traditional μ opioid receptor (MOR) agonists for providing analgesia in ER-positive BC patients owing to their association with better prognosis.

IntroductionBlood–brain barrier (BBB) breakdown is closely associated with cognitive dysfunction. This study aimed to categorize and summarize research topics on the correlation between BBB breakdown and its effects on cognitive function.MethodsBibliometric analysis methods were used to quantitatively and qualitatively assess research progress and predict future research hotspots. Relevant publications from the Web of the Science Core Collection were extracted on November 5, 2022 and analyzed to predict trends and hotspots in the field.ResultsWe identified 5518 articles published from 2000 to 2021 about the BBB and cognition. The number of manuscripts on this topic increased steadily during this time period, especially after 2013. We found that the number of articles published in China increased gradually and is in second place behind the United States of America (USA). In the research field of BBB breakdown and cognitive function, the USA is still far ahead. Keyword burst detection suggested that cognitive impairment, neurodegeneration disease and neuroinflammation are emerging research hotspots.DiscussionThe mechanisms of BBB integrity breakdown and its effects on the deterioration of cognitive function are complex, and clinical treatment of the affected diseases has been a hot topic in the field over the past 22 years. Looking forward, this body of research is aimed at improving or maintaining patients’ cognitive abilities, by finding preventive measures and to provide a basis for finding new treatments of cognitive disorders.

BackgroundHepatocellular carcinoma (HCC), one of the most common cancers worldwide, exhibits high immune heterogeneity and mortality. Emerging studies suggest that copper (Cu) plays a key role in cell survival. However, the relationship between Cu and tumor development remains unclear.MethodsWe investigated the effects of Cu and cuproptosis-related genes (CRGs) in patients with HCC in the TCGA-LIHC (The Cancer Genome Atlas-Liver cancer, n = 347) and ICGC-LIRI-JP (International Cancer Genome Consortium-Liver Cancer-Riken-Japan, n = 203) datasets. Prognostic genes were identified by survival analysis, and a least absolute shrinkage and selection operator (Lasso) regression model was constructed using the prognostic genes in the two datasets. Additionally, we analyzed differentially expressed genes and signal pathway enrichment. We also evaluated the effects of CRGs on tumor immune cell infiltration and their co-expression with immune checkpoint genes (ICGs) and performed validation in different tumor immune microenvironments (TIMs). Finally, we performed validation using clinical samples and predicted the prognosis of patients with HCC using a nomogram.ResultsA total of 59 CRGs were included for analysis, and 15 genes that significantly influenced the survival of patients in the two datasets were identified. Patients were grouped by risk scores, and pathway enrichment analysis suggested that immune-related pathways were substantially enriched in both datasets. Tumor immune cell infiltration analysis and clinical validation revealed that PRNP (Prion protein), SNCA (Synuclein alpha), and COX17 (Cytochrome c oxidase copper chaperone COX17) may be closely correlated with immune cell infiltration and ICG expression. A nomogram was constructed to predict the prognosis of patients with HCC using patients’ characteristics and risk scores.ConclusionCRGs may regulate the development of HCC by targeting the TIM and ICGs. CRGs such as PRNP, SNCA, and COX17 could be promising targets for HCC immune therapy in the future.

BackgroundAlthough dexmedetomidine (DEX) is widely used during the perioperative period in patients with hepatocellular carcinoma (HCC), its clinical effects on liver function and postoperative inflammation are unclear. This study aimed to explore effects of DEX on postoperative liver function and inflammation in patients with HCC after hepatectomy.MethodsA retrospective cohort study with propensity score matching was performed. A total of 494 patients who underwent hepatectomy from June 2019 to July 2020 and fulfilled the eligibility criteria were included in this study. Baseline data, liver function indexes and inflammation-related biomarkers were collected and compared between the two groups. Survival analysis was conducted to investigate the effects of DEX on the overall survival (OS) of patients. Propensity score matching (PSM) was used to minimize bias between the two groups.ResultsThe study cohort comprised 189 patients in the DEX-free group and 305 patients in the DEX group. Patients in the DEX group had lower levels of alanine transaminase (ALT, P = 0.018) and lactate dehydrogenase (LDH, P = 0.046) and higher level of serum albumin (ALB, P < 0.001) than patients in the DEX-free group before discharge. A total of 107 pairs of patients were successfully matched by PSM. Results consistently suggested that ALT and LDH levels were significantly lower (P = 0.044 and P = 0.046, respectively) and ALB levels were significantly higher (P = 0.002) in the DEX group than in the DEX-free group in the early postoperative period. No significant differences of inflammation-related biomarkers were observed between two groups after PSM. Neither the Kaplan–Meier survival analysis nor the multiple Cox regression survival analysis identified DEX as a contributing factor that would affect the OS of patients after PSM.ConclusionDEX exerts protective effects on liver function while has little effects on inflammation-related biomarkers in the early postoperative period in patients undergoing hepatectomy due to HCC.

Zeroing neural network (ZNN) is an effective method to calculate time-varying problems. However, the ZNN and its extensions separately addressed the robustness and the convergence. To simultaneously promote the robustness and finite-time convergence, a nonlinearly activated integration-enhanced ZNN (NIEZNN) model based on a coalescent activation function (C-AF) has been designed for solving the time-varying Sylvester equation in various noise situations. The C-AF with an optimized structure is convenient for simulations and calculations, which promotes NIEZNN accelerates convergence speed without remarkable efficiency loss. The robustness and the finite-time convergence of the NIEZNN model have been proved in theoretical analyses. Furthermore, the upper bounds of convergence time of the NIEZNN model and the noise-attached NIEZNN model have been deduced in theory. At last, numerical comparative results and the application to mobile manipulator have validated the efficiency and superiority of the NIEZNN model based on the designed coalescent activation function.

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with high morbidity and mortality, which accounts for the fourth most common cause of cancer-related deaths. Reports suggest that the neurotransmitter receptor-related genes (NRGs) may influence the tumor microenvironment and the prognosis of patients with HCC.Methods: The clinical information and RNA-seq data of patients with HCC were acquired from the ICGC-LIRI-JP dataset and the TCGA-LIHC dataset. Effects of 115 NRGs on the prognosis of HCC patients were analyzed in the ICGC-LIRI-JP dataset. The least absolute shrinkage and selection operator (LASSO) regression model was utilized to generate a risk score formula based on the critical NRGs. Next, the risk score effectiveness was validated both in the TCGA-LIHC dataset and in our clinical HCC samples. Based on the risk scores, patients with HCC were divided into two groups. Moreover, differentially expressed genes (DEGs) were screened. The gene ontology (GO) was used to analyze the functional enrichments of DEGs and to identify potential signaling pathways. To test the diagnostic effectiveness of our model, the receiver operator characteristic curve (ROC) analysis and nomogram were used. Finally, potential targeted drug prediction was performed based on DEGs of nine clinical HCC samples.Results: Nine NRGs were correlated significantly with the prognosis of patients with HCC, and eight NRGs were successfully included in the LASSO regression model. The Kaplan-Meier analysis of overall survival (OS) suggested that patients in the high-risk score group had worse prognosis; on the other hand, ROC analysis revealed a high prognostic value of the risk score in HCC. Several critical signaling pathways, such as lipid metabolism, organic acid metabolism, cell migration, cell adhesion, and immune response, were enriched both in public datasets and clinical samples. Nomogram results also suggested that the risk scores correlated well with the patients’ prognosis. Potential targeted drugs prediction revealed that tubulin inhibitors might be the promising drugs for patients with HCC who have high risk scores based on the NRGs.Conclusion: We established a prognostic model based on critical NRGs. NRGs show a promising prognostic prediction value in HCC and are potential therapeutic targets for the disease treatment.

BackgroundBibliometric analysis is used to gain a systematic understanding of developments in the correlation between neurotransmitters and tumor progression in research hotspots over the past 20 years.MethodsRelevant publications from the Web of Science Core Collection (WoSCC) were downloaded on August 1, 2021. Acquired data were then analyzed using the Online Analysis Platform of Literature Metrology (http://biblimetric.com) and the CiteSpace software to analyze and predict trends and hot spots in this field.ResultsA total of 1310 publications on neurotransmitters and tumor progression were identified, and 1285 qualified records were included in the final analysis. The country leading the research was the United States of America. The University of Buenos Aires featured the highest number of publications among all institutions. Co-citation cluster labels revealed the characteristics of 10 main clusters: beta-adrenergic receptors (β-AR), glutamate, neurotransmitters, serotonin, drd2, histamine, glycine, interleukin-2, neurokinin receptor-1, and nicotinic acetylcholine receptors (AchRs). Keywords and references burst detection indicated that apart from β-AR, dopamine receptor and cancer types like gastric cancer and glioblastoma are the newly emerging research hotspots.ConclusionsThis study analyzed 1285 publications and 39677 references covering the topic of neurotransmitters and tumor progression and showed that while β-AR has always been a hot topic in this field, dopamine receptor is an emerging target for this research field, and gastric cancer and glioblastoma are the top two tumors that have garnered increasing attention and have become the focal point of recent studies.

BackgroundWhether anesthesia methods affect malignant biological behavior of cancer remains unresolved. In this study, we aim to compare the effects of general anesthesia (GA) and local anesthesia (LA) on serum collected from primary hepatocellular carcinoma (HCC) patients presenting for radiofrequency ablation (RFA).MethodsFrom August 2020 to December 2020, a prospective, randomized, and controlled study was conducted at Renji Hospital, which is affiliated with Shanghai Jiaotong University School of Medicine. 25 qualified patients from 18 to 65 years of age undergoing RFA were enrolled in the study and randomly assigned into two groups: the GA group (n = 14) and the LA group (n = 11). Venous blood was drawn from all patients preoperatively and 1 hour postoperatively. The serum collected was then used for the culturing of HepG2 cells. The malignant biological behaviors of HepG2 cells, including invasion, migration and proliferation, were observed after 24 hours of exposure to patients’ serum. ELISA was used to compare expression levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) and lymphokines (IFN-γ, IL-2) in patients’ serum from both groups.ResultsHepG2 cells cultured with postoperative serum obtained from patients who received GA, but not LA, were associated with significantly increased cell invasion, migration and proliferation, compared to preoperative serum from the same patient group. Expression levels of pro-inflammatory cytokines were significantly higher, and lymphokines significantly lower in postoperative serum from GA patients compared to the corresponding preoperative serum.ConclusionGA affects the serum milieu of patients with HCC, promoting the malignant biological behavior of a human HCC cell line.

BackgroundBibliometric analysis is used to gain a systematic understanding of developments in the field of the influence of anesthesia on tumor prognosis and changes in research hot spots over the past 20 years.MethodsRelevant publications from the Web of Science Core Collection (WoSCC) were downloaded on May 5, 2021. Acquired data were then analyzed using the Online Analysis Platform of Literature Metrology (http://biblimetric.com) and the CiteSpace software was used to analyze and predict trends and hot spots in this field.Results1,521 publications on the influence of anesthesia on tumor prognosis were identified and 1494 qualifying records were included in the final analysis. The leading country in this field was the United States of America (USA). The University of Texas MD Anderson Cancer Center (Houston, TX, USA) and Pennsylvania State University (State College, PA, USA) featured the highest number of publications among all institutions. Co-citation cluster labels revealed characteristics of ten main clusters: total intravenous anesthesia, opioid growth factor receptor, gastric cancer cell, opioid receptor, murine model, natural killer cell activity, health-related quality, glioma cell, opioid switching and mu-type opioid receptor. Keyword burst detection indicated that randomized controlled trials (RCTs), volatile anesthetics, and ropivacaine were the newly emerging research hot spots.ConclusionsThis study compiled 1494 publications covering anesthesia and tumor prognosis research and showed that the direction of these studies is likely in transition from opioids and their receptors to other anesthetics, and from retrospective studies to prospective randomized controlled trials. It provides guidance for further research and clinical applications on choosing anesthetic methods and drugs.

Abstract Background Thrombospondin type 1 domain containing 7A (THSD7A) was recently identified target autoantigen in membranous nephropathy (MN). However, patients with positive THSD7A expression were prone to have malignancies. THSD7A was found to be expressed in a variety of malignant tumors. In this study, we investigated the histologic expression of THSD7A in colorectal or breast cancers, as well as the relationship between THSD7A expression and proteinuria in the patients with cancers. Method A total of 101 patients were enrolled in the study, 81 of them had colorectal cancer and 20 had breast cancer. THSD7A expression was detected by immunohistochemical staining in tumor tissues. The clinical and laboratory parameters of these patients before their tumor resection were collected. Results Positive expression rates of THSD7A in the two types of tumor tissues were very high, 97.5% in colorectal cancer, and 100% in breast cancer. THSD7A expression was also detected in lymph nodes of two patients with lymph node metastasis. Total 11 patients (10.9%) had proteinuria before surgery. Among the 4 patients who had proteinuria and were followed up, the proteinuria of 3 patients disappeared after surgery. Conclusions The positive rate of THSD7A expression was very high in human colorectal cancer or breast cancer. It might be an important link between malignant tumors and kidney diseases.