Emodin nanocapsules inhibit acute pancreatitis by regulating lipid metabolic reprogramming in macrophage polarization.

BACKGROUND: Emodin is a chemical compound found in traditional Chinese herbs. It possesses anti-inflammatory and many other pharmacological effects. Our previous study showed that emodin significantly alleviates the inflammation effect of severe acute pancreatitis (SAP). However, its poor solubility, high toxicity and limited pancreas retention time hinder its clinical application. PURPOSE: We aimed to prepare emodin nanocapsules with improved bioavailability to achieve the controlled release of emodin by targeting macrophages. Further, the mechanism of mannose-conjugated chitosan-coated lipid nanocapsules loaded with emodin (M-CS-E-LNC) in the treatment of SAP was explored. METHODS: M-CS-E-LNC were prepared by the phase inversion method with slight modification. The expression of inflammation mediators and the anti-inflammation efficacy of M-CS-E-LNC were examined by ELISA, IHC and IF in macrophage cells and LPS-induced SAP mice. IVIS spectrum imaging and HPLC were applied to explore the controlled release of M-CS-E-LNC in the pancreas. LC-MS/MS was performed for lipidomics analysis of macrophages. Moreover, a vector-based short hairpin RNA (shRNA) method was used to silence CTP1 gene expression in macrophage cells. RESULTS: The levels of inflammatory mediators in macrophages were markedly decreased after treatment with M-CS-E-LNC. The same anti-inflammation effects were detected in SAP mouse through the analysis of serum levels of amylase, TNF-α and IL-6. Importantly, M-CS-E-LNC allowed the emodin to selectively accumulate at pancreas and gastrointestinal tissues, thus exhibiting a targeted release. Mechanistically, the M-CS-E-LNC treatment group showed up-regulated expression of the carnitine palmitoyltransferase 1 (CPT1) protein which promoted intracellular long-chain fatty acid transport, thereby promoting the M2 phenotype polarization of macrophages. CONCLUSION: M-CS-E-LNC exhibited significantly improved bioavailability and water solubility, which translated to greater therapeutic effects on macrophage polarization. Our findings also demonstrate, for the first time, that CPT1 may be a new therapeutic target for SAP treatment.

Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer.

Endoplasmic reticulum stress (ERS) is caused by the accumulation of intracellular misfolded or unfolded proteins and is associated with cancer development. In this study, pan-cancer analysis revealed complex genetic variations, including copy number variation, methylation, and somatic mutations for ERS-related genes (ERGs) in 33 kinds of cancer. Consensus clustering divided pancreatic cancer (PC) patients from TCGA and GEO databases into two ERS-related subtypes: ERGcluster A and B. Compared with ERGcluster A, ERGcluster B had a more active ERS state and worse prognosis. Subsequently, the ERS-related prognostic model was established to quantify the ERS score for a single sample. The patient with a low ERS score had remarkably longer survival times. ssGSEA and CIBERSORT algorithms revealed that activated B cells and CD8+ T cells had higher infiltration in the low ERS score group, but higher infiltration of activated CD4+ T cells, activated dendritic cells, macrophages, and neutrophils in the high ERS score group. Drug sensitivity analysis indicated the low ERS score group had a better response to gemcitabine, paclitaxel, 5-fluorouracil, oxaliplatin, and irinotecan. RT-qPCR validated that MET, MUC16, and KRT7 in the model had higher expression levels in pancreatic tumour tissues. Single-cell analysis further revealed that MET, MUC16, and KRT7 were mainly expressed in cancer cells in PC tumour microenvironment. In all, we first constructed the ERS-related molecular subtypes and prognostic model in PC. Our research highlighted the vital role of ERS in PC and contributed to further research on molecular mechanisms and novel therapeutic strategies for PC in the future.

Integrated multi-omics identified the novel intratumor microbiome-derived subtypes and signature to predict the outcome, tumor microenvironment heterogeneity, and immunotherapy response for pancreatic cancer patients.

Background: The extremely malignant tumour known as pancreatic cancer (PC) lacks efficient prognostic markers and treatment strategies. The microbiome is crucial to how cancer develops and responds to treatment. Our study was conducted in order to better understand how PC patients' microbiomes influence their outcome, tumour microenvironment, and responsiveness to immunotherapy. Methods: We integrated transcriptome and microbiome data of PC and used univariable Cox regression and Kaplan-Meier method for screening the prognostic microbes. Then intratumor microbiome-derived subtypes were identified using consensus clustering. We utilized LASSO and Cox regression to build the microbe-related model for predicting the prognosis of PC, and utilized eight algorithms to assess the immune microenvironment feature. The OncoPredict package was utilized to predict drug treatment response. We utilized qRT-PCR to verify gene expression and single-cell analysis to reveal the composition of PC tumour microenvironment. Results: We obtained a total of 26 prognostic genera in PC. And PC samples were divided into two microbiome-related subtypes: Mcluster A and B. Compared with Mcluster A, patients in Mcluster B had a worse prognosis and higher TNM stage and pathological grade. Immune analysis revealed that neutrophils, regulatory T cell, CD8+ T cell, macrophages M1 and M2, cancer associated fibroblasts, myeloid dendritic cell, and activated mast cell had remarkably higher infiltrated levels within the tumour microenvironment of Mcluster B. Patients in Mcluster A were more likely to benefit from CTLA-4 blockers and were highly sensitive to 5-fluorouracil, cisplatin, gemcitabine, irinotecan, oxaliplatin, and epirubicin. Moreover, we built a microbe-derived model to assess the outcome. The ROC curves showed that the microbe-related model has good predictive performance. The expression of LAMA3 and LIPH was markedly increased within pancreatic tumour tissues and was linked to advanced stage and poor prognosis. Single-cell analysis indicated that besides cancer cells, the tumour microenvironment of PC was also rich in monocytes/macrophages, endothelial cells, and fibroblasts. LIPH and LAMA3 exhibited relatively higher expression in cancer cells and neutrophils. Conclusion: The intratumor microbiome-derived subtypes and signature in PC were first established, and our study provided novel perspectives on PC prognostic indicators and treatment options.

A prospective prognostic signature for pancreatic adenocarcinoma based on ubiquitination-related mRNA-lncRNA with experimental validation in vitro and vivo.

Ubiquitination-related genes (URGs) exerted a crucial part in a variety of human disease disorders; however, their association with pancreatic adenocarcinoma (PAAD) had yet to be clearly described. We aimed to comprehensively characterize the contributions of URGs in PAAD through in silico analysis and experimental validation, and then identified a robust mRNA-lncRNA-based molecular prognostic panel for patients with PAAD using bulk RNA-sequencing and single-cell RNA-sequencing data. Initially, we collected the multi-omics data from TCGA platform to depict a comprehensive landscape of URGs in pan-cancer. Furthermore, we were accurate to PAAD for in-depth analysis. Significant differences of the activation of ubiquitination pathways and the expression of URGs were detected between normal and malignant cells. Unsupervised hierarchical clustering determined two PAAD subtypes with distinct clinical outcomes, ubiquitination pathway activities, immune microenvironment, and functional annotation characteristics. The expression profiles of ubiquitination-associated mRNAs and lncRNAs in the training and validation datasets were utilized to develop and verify a novel ubiquitination-related mRNA-lncRNA prognostic panel, which had a satisfied prediction efficiency. Our ubiquitination-associated model could function as an effective prognostic index and outperformed four other recognized panels in evaluating PAAD patients' survival status. Tumor immune microenvironment, mutation burden, and chemotherapy response were intensively explored to demonstrate the underlying mechanism of prognostic difference according to our panel. Our findings also revealed that FTI-277, a farnesyltransferase inhibitor, had a better curative effect in high-risk patients, while MK-2206, an Akt allosteric inhibitor, had a superior therapeutic effect in low-risk patients. The real-time PCR results uncovered the RNA expression of AC005062.1 in all the three PAAD cell lines was elevated several thousandfold. In conclusion, our URGs-based classification panel could be triumphantly served as a prediction tool for survival evaluation in patients with PAAD, and the genes in this panel could be developed as a potential target in PAAD therapy.

The Retention-Rate Improvement of Stromal Vascular Fraction Gel in Prefrontal Filling With Botulinum Toxin-A Injection: A Retrospective Analysis.

BACKGROUND: As a derivative of adipose tissues, stromal vascular fraction gel has been widely utilized in facial soft tissue filling, but it still does not achieve the expected effect in forehead filling. The reason may be related to the corrugator muscles movements. OBJECTIVES: The authors aimed to evaluate the effect of botulinum toxin-A (BTX-A) on the retention rate of stromal vascular fraction gel by limiting the corrugator muscles movements and to provide a theoretical basis that short-term inhibition of movement in the affected area could improve the effects of the fat graft. METHODS: From January 2019 to June 2021, patients with stromal vascular fraction gel facial filling (including frontal and temporal parts) were selected. According to whether or not BTX-A treatment was received, patients were divided into injected and the noninjected groups. A questionnaire and the Global Aesthetic Improvement Scale (GAIS) were administered to evaluate 2-dimensional photos. The retention rate and curvature were calculated with 3-dimensional images utilizing Artec Studio 13 Professional and MATLAB software. RESULTS: The graft retention, forehead curvature, and GAIS scores were all higher in the injected group than the noninjected group (P < .01). On the questionnaire, the injected group also showed more satisfaction with the treatment effect and were more willing to recommend the treatment to their friends. CONCLUSIONS: BTX-A injection can improve the retention rate of prefrontal stromal vascular fraction gel filling, with higher patient satisfaction and better postoperative effects.

Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma.

Background: Despite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel. Methods: Single cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel. Results: The malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel. Conclusions: Overall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.

Comprehensive characterization of extracellular matrix-related genes in PAAD identified a novel prognostic panel related to clinical outcomes and immune microenvironment: A silico analysis with in vivo and vitro validation.

The extracellular matrix (ECM) is a vital component of the tumor microenvironment, which interplays with stromal and tumor cells to stimulate the capacity of cancer cells to proliferate, migrate, invade, and undergo angiogenesis. Nevertheless, the crucial functions of ECM-related genes (ECMGs) in pancreatic adenocarcinoma (PAAD) have not been systematically evaluated. Hence, a comprehensive evaluation of the ECMGs is required in pan-cancer, especially in PAAD. First, a pan-cancer overview of ECMGs was explored through the integration of expression profiles, prognostic values, mutation information, methylation levels, and pathway-regulation relationships. Seven ECMGs (i.e. LAMB3, LAMA3, ITGB6, ITGB4, ITGA2, LAMC2, and COL11A1) were identified to be hub genes of PAAD, which were obviously up-regulated in PAAD and considerably linked to tumor stage as well as prognosis. Subsequently, patients with PAAD were divided into 3 clusters premised on ECMG expression and ECM scores. Cluster 2 was the subtype with the best prognosis accompanied by the lowest ECM scores, further verifying ECM's significant contribution to the pathophysiological processes of PAAD. Significant differences were observed for oncogene and tumor suppressor gene expression, immune microenvironment, and chemotherapy sensitivity across three ECM subtypes. After applying a variety of bioinformatics methods, a novel and robust ECM-associated mRNA-lncRNA-based prognostic panel (ECM-APP) was developed and validated for accurately predicting clinical outcomes of patients with PAAD. Patients with PAAD were randomly categorized into the train, internal validation, and external validation cohorts; meanwhile, each patient was allocated into high-risk (unfavorable prognosis) and low-risk (favorable prognosis) populations premised on the expression traits of ECM-related mRNAs and lncRNAs. The discrepancy in the tumor mutation burden and immune microenvironment might be responsible for the difference in prognoses across the high-risk and low-risk populations. Overall, our findings identified and validated seven ECMGs remarkably linked to the onset and progression of PAAD. ECM-based molecular classification and prognostic panel aid in the prognostic assessment and personalized intervention of patients with PAAD.

Characterization of neuroendocrine regulation- and metabolism-associated molecular features and prognostic indicators with aid to clinical chemotherapy and immunotherapy of patients with pancreatic cancer.

The worldwide prevalence of pancreatic cancer has been rising in recent decades, and its prognosis has not improved much. The imbalance of substance and energy metabolism in tumour cells is among the primary causes of tumour formation and occurrence, which is often controlled by the neuroendocrine system. We applied Cox and LASSO regression analysis to develop a neuroendocrine regulation- and metabolism-related prognostic risk score model with three genes (GSK3B, IL18 and VEGFA) for pancreatic cancer. TCGA dataset served as the training and internal validation sets, and GSE28735, GSE62452 and GSE57495 were designated as external validation sets. Patients classified as the low-risk population (category, group) exhibited considerably improved survival duration in contrast with those classified as the high-risk population, as determined by the Kaplan-Meier curve. Then, we combined all the samples, and divided them into three clusters using unsupervised clustering analysis. Unsupervised clustering, t-distributed stochastic neighbor embedding (t-SNE), and principal component analysis (PCA) were further utilized to demonstrate the reliability of the prognostic model. Moreover, the risk score was shown to independently function as a predictor of pancreatic cancer in both univariate and multivariate Cox regression analyses. The results of gene set enrichment analysis (GSEA) illustrated that the low-risk population was predominantly enriched in immune-associated pathways. "ESTIMATE" algorithm, single-sample GSEA (ssGSEA) and the Tumor Immune Estimation Resource (TIMER) database showed immune infiltration ratings were enhanced in the low-risk category in contrast with the high-risk group. Tumour immune dysfunction and exclusion (TIDE) database predicted that immunotherapy for pancreatic cancer may be more successful in the high-risk than in the low-risk population. Mutation analysis illustrated a positive link between the tumour mutation burden and risk score. Drug sensitivity analysis identified 44 sensitive drugs in the high- and low-risk population. GSK3B expression was negatively correlated with Oxaliplatin, and IL18 expression was negatively correlated with Paclitaxel. Lastly, we analyzed and verified gene expression at RNA and protein levels based on GENPIA platform, HPA database and quantitative real-time PCR. In short, we developed a neuroendocrine regulation- and metabolism-associated prognostic model for pancreatic cancer that takes into account the immunological microenvironment and drug sensitivity.

Bioinformatics study on different gene expression profiles of fibroblasts and vascular endothelial cells in keloids.

ABSTRACT: Keloid is a benign fibroproliferative skin tumor. The respective functions of fibroblasts and vascular endothelial cells in keloid have not been fully studied. The purpose of this study is to identify the respective roles and key genes of fibroblasts and vascular endothelial cells in keloids, which can be used as new targets for diagnosis or treatment.The microarray datasets of keloid fibroblasts and vascular endothelial cells were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for functional enrichment analysis. The search tool for retrieval of interacting genes and Cytoscape were used to construct protein-protein interaction (PPI) networks and analyze gene modules. The hub genes were screened out, and the relevant interaction networks and biological process analysis were carried out.In fibroblasts, the DEGs were significantly enriched in collagen fibril organization, extracellular matrix organization and ECM-receptor interaction. The PPI network was constructed, and the most significant module was selected, which is mainly enriched in ECM-receptor interaction. In vascular endothelial cells, the DEGs were significantly enriched in cytokine activity, growth factor activity and transforming growth factor-ß (TGF-ß) signaling pathway. Module analysis was mainly enriched in TGF-ß signaling pathway. Hub genes were screened out separately.In summary, the DEGs and hub genes discovered in this study may help us understand the molecular mechanisms of keloid, and provide potential targets for diagnosis and treatment.

Identification of the Real Hub Gene and Construction of a Novel Prognostic Signature for Pancreatic Adenocarcinoma Based on the Weighted Gene Co-expression Network Analysis and Least Absolute Shrinkage and Selection Operator Algorithms.

Background: Pancreatic adenocarcinoma (PAAD) has a considerably bad prognosis, and its pathophysiologic mechanism remains unclear. Thus, we aimed to identify real hub genes to better explore the pathophysiology of PAAD and construct a prognostic panel to better predict the prognosis of PAAD using the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithms. Methods: WGCNA identified the modules most closely related to the PAAD stage and grade based on the Gene Expression Omnibus. The module genes significantly associated with PAAD progression and prognosis were considered as the real hub genes. Eligible genes in the most significant module were selected for construction and validation of a multigene prognostic signature based on the LASSO-Cox regression analysis in The Cancer Genome Atlas and the International Cancer Genome Consortium databases, respectively. Results: The brown module identified by WGCNA was most closely associated with the clinical characteristics of PAAD. Scaffold attachment factor B (SAFB) was significantly associated with PAAD progression and prognosis, and was identified as the real hub gene of PAAD. Moreover, both transcriptional and translational levels of SAFB were significantly lower in PAAD tissues compared with normal pancreatic tissues. In addition, a novel multigene-independent prognostic signature consisting of SAFB, SP1, and SERTAD3 was identified and verified. The predictive accuracy of our signature was superior to that of previous studies, especially for predicting 3- and 5-year survival probabilities. Furthermore, a prognostic nomogram based on independent prognostic variables was developed and validated using calibration curves. The predictive ability of this nomogram was also superior to the well-established AJCC stage and histological grade. The potential mechanisms of different prognoses between the high- and low-risk subgroups were also investigated using functional enrichment analysis, GSEA, ssGSEA, immune checkpoint analysis, and mutation profile analysis. Conclusion: SAFB was identified as the real hub gene of PAAD. A novel multigene-independent prognostic signature was successfully identified and validated to better predict PAAD prognosis. An accurate nomogram was also developed and verified to aid in the accurate treatment of tumors, as well as in early intervention.

Anatomic Characteristics and Treatment of the Midcheek Groove by Deep Filling.

BACKGROUND: Because the anatomic mechanisms underlying the formation of the midcheek groove are unclear, treatments to date have resulted in unsatisfactory outcomes. OBJECTIVE: This study investigated the anatomical foundation of the midcheek groove and evaluated appropriate treatment methods. MATERIALS AND METHODS: Six cadaver hemifacial specimens were subjected to gross anatomic dissection and 6 to P45 sheet plastination. Based on the anatomic results, the area under the orbicularis oculi muscle (OOM) was selected for deep filling. Patients were evaluated by measuring 3D depth, regrading, and self-assessment. RESULTS: The medial band was observed to be an important structure of the OOM, with the facial projection overlapping the midcheek groove trace. Two of the 6 P45 specimens were found to have compact fibroelastic bundles (CFBs) between the medial band and the dermis. Deep filling of the area under the OOM significantly reduced the depth of each section in all 34 patients (p < .001). Grades 3 and 4 midcheek grooves were downgraded distinctively. Most subjects expressed satisfaction with outcomes. CONCLUSION: Formation of the midcheek groove is associated with the passage of CFBs. Deep filling of the area under the OOM effectively improves the midcheek grooves.

5-Hydroxymethylcytosine as a potential epigenetic biomarker in papillary thyroid carcinoma.

DNA methylation at the 5 position of cytosine (5-mC) is an epigenetic hallmark that is critical in various biological and pathological processes such as DNA methylation regulation, and initiation and development of cancers. 5-mC can be oxidized to 5-hydroxymethylcytosine (5-hmC) by the ten-eleven translocation family of DNA hydroxylases. Accumulating evidence has reported that loss of 5-hmC is associated with cancer development. However, its level in papillary thyroid carcinoma (PTC) remains unclear. The present study reports that the loss of 5-hmC is an epigenetic mark of PTCs, associated with their malignant biological behavior, providing diagnostic and predictive advantages over DNA hypomethylation (5-mC), an acknowledged epigenetic alteration in cancer. In addition, the 5-hmC staining levels were decreased in cases of micro-carcinoma with lymph node metastasis, which suggests that 5-hmC expression levels could be used as valuable biomarkers for predicting malignant potential and assist in the selection of therapeutic strategies in PTC; therefore, 5-hmC has the potential to provide a more precise direction for PTC therapy.

Transforming growth factor-ß in pancreatic diseases: Mechanisms and therapeutic potential.

Pancreatic diseases, such as acute pancreatitis, chronic pancreatitis, and pancreatic cancer, are common gastrointestinal diseases resulting in the development of local and systemic complications with a high risk of death. Numerous studies have examined pancreatic diseases over the past few decades; however, the pathogenesis remains unclear, and there is a lack of effective treatment options. Recently, emerging evidence has suggested that transforming growth factor beta (TGF-ß) exerts controversial functions in apoptosis, inflammatory responses, and carcinogenesis, indicating its complex role in the pathogenesis of pancreas-associated disease. Therefore, a further understanding of relevant TGF-ß signalling will provide new ideas and potential therapeutic targets for preventing disease progression. This is the first systematic review of recent data from animal and human clinical studies focusing on TGF-ß signalling in pancreas damage and diseases. This information may aid in the development of therapeutic agents for regulating TGF-ß in this pathology to prevent or treat pancreatic diseases.