Endoscopic ultrasonography-based intratumoral and peritumoral machine learning radiomics analyses for distinguishing insulinomas from non-functional pancreatic neuroendocrine tumors.

Objectives: To develop and validate radiomics models utilizing endoscopic ultrasonography (EUS) images to distinguish insulinomas from non-functional pancreatic neuroendocrine tumors (NF-PNETs). Methods: A total of 106 patients, comprising 61 with insulinomas and 45 with NF-PNETs, were included in this study. The patients were randomly assigned to either the training or test cohort. Radiomics features were extracted from both the intratumoral and peritumoral regions, respectively. Six machine learning algorithms were utilized to train intratumoral prediction models, using only the nonzero coefficient features. The researchers identified the most effective intratumoral radiomics model and subsequently employed it to develop peritumoral and combined radiomics models. Finally, a predictive nomogram for insulinomas was constructed and assessed. Results: A total of 107 radiomics features were extracted based on EUS, and only features with nonzero coefficients were retained. Among the six intratumoral radiomics models, the light gradient boosting machine (LightGBM) model demonstrated superior performance. Furthermore, a peritumoral radiomics model was established and evaluated. The combined model, integrating both the intratumoral and peritumoral radiomics features, exhibited a comparable performance in the training cohort (AUC=0.876) and achieved the highest accuracy in predicting outcomes in the test cohorts (AUC=0.835). The Delong test, calibration curves, and decision curve analysis (DCA) were employed to validate these findings. Insulinomas exhibited a significantly smaller diameter compared to NF-PNETs. Finally, the nomogram, incorporating diameter and radiomics signature, was constructed and assessed, which owned superior performance in both the training (AUC=0.929) and test (AUC=0.913) cohorts. Conclusion: A novel and impactful radiomics model and nomogram were developed and validated for the accurate differentiation of NF-PNETs and insulinomas utilizing EUS images.

A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification.

Objective: This study aimed to construct a machine learning model using clinical variables and ultrasound radiomics features for the prediction of the benign or malignant nature of pancreatic tumors. Methods: 242 pancreatic tumor patients who were hospitalized at the First Affiliated Hospital of Guangxi Medical University between January 2020 and June 2023 were included in this retrospective study. The patients were randomly divided into a training cohort (n=169) and a test cohort (n=73). We collected 28 clinical features from the patients. Concurrently, 306 radiomics features were extracted from the ultrasound images of the patients' tumors. Initially, a clinical model was constructed using the logistic regression algorithm. Subsequently, radiomics models were built using SVM, random forest, XGBoost, and KNN algorithms. Finally, we combined clinical features with a new feature RAD prob calculated by applying radiomics model to construct a fusion model, and developed a nomogram based on the fusion model. Results: The performance of the fusion model surpassed that of both the clinical and radiomics models. In the training cohort, the fusion model achieved an AUC of 0.978 (95% CI: 0.96-0.99) during 5-fold cross-validation and an AUC of 0.925 (95% CI: 0.86-0.98) in the test cohort. Calibration curve and decision curve analyses demonstrated that the nomogram constructed from the fusion model has high accuracy and clinical utility. Conclusion: The fusion model containing clinical and ultrasound radiomics features showed excellent performance in predicting the benign or malignant nature of pancreatic tumors.

Construction and validation of an endoscopic ultrasonography-based ultrasomics nomogram for differentiating pancreatic neuroendocrine tumors from pancreatic cancer.

Objectives: To develop and validate various ultrasomics models based on endoscopic ultrasonography (EUS) for retrospective differentiating pancreatic neuroendocrine tumors (PNET) from pancreatic cancer. Methods: A total of 231 patients, comprising 127 with pancreatic cancer and 104 with PNET, were retrospectively enrolled. These patients were randomly divided into either a training or test cohort at a ratio of 7:3. Ultrasomics features were extracted from conventional EUS images, focusing on delineating the region of interest (ROI) for pancreatic lesions. Subsequently, dimensionality reduction of the ultrasomics features was performed by applying the Mann-Whitney test and least absolute shrinkage and selection operator (LASSO) algorithm. Eight machine learning algorithms, namely logistic regression (LR), light gradient boosting machine (LightGBM), multilayer perceptron (MLP), random forest (RF), extra trees, k nearest neighbors (KNN), support vector machine (SVM), and extreme gradient boosting (XGBoost), were employed to train prediction models using nonzero coefficient features. The optimal ultrasomics model was determined using a ROC curve and utilized for subsequent analysis. Clinical-ultrasonic features were assessed using both univariate and multivariate logistic regression. An ultrasomics nomogram model, integrating both ultrasomics and clinical-ultrasonic features, was developed. Results: A total of 107 EUS-based ultrasomics features were extracted, and 6 features with nonzero coefficients were ultimately retained. Among the eight ultrasomics models based on machine learning algorithms, the RF model exhibited superior performance with an AUC= 0.999 (95% CI 0.9977 - 1.0000) in the training cohort and an AUC= 0.649 (95% CI 0.5215 - 0.7760) in the test cohort. A clinical-ultrasonic model was established and evaluated, yielding an AUC of 0.999 (95% CI 0.9961 - 1.0000) in the training cohort and 0.847 (95% CI 0.7543 - 0.9391) in the test cohort. Subsequently, the ultrasomics nomogram demonstrated a significant improvement in prediction accuracy in the test cohort, as evidenced by an AUC of 0.884 (95% CI 0.8047 - 0.9635) and confirmed by the Delong test. The calibration curve and decision curve analysis (DCA) depicted this ultrasomics nomogram demonstrated superior accuracy. They also yielded the highest net benefit for clinical decision-making compared to alternative models. Conclusions: A novel ultrasomics nomogram was proposed and validated, that integrated clinical-ultrasonic and ultrasomics features obtained through EUS, aiming to accurately and efficiently identify pancreatic cancer and PNET.

Identification of common genes and pathways between type 2 diabetes and COVID-19.

Background: Numerous studies have reported a high incidence and risk of severe illness due to coronavirus disease 2019 (COVID-19) in patients with type 2 diabetes (T2DM). COVID-19 patients may experience elevated or decreased blood sugar levels and may even develop diabetes. However, the molecular mechanisms linking these two diseases remain unclear. This study aimed to identify the common genes and pathways between T2DM and COVID-19. Methods: Two public datasets from the Gene Expression Omnibus (GEO) database (GSE95849 and GSE164805) were analyzed to identify differentially expressed genes (DEGs) in blood between people with and without T2DM and COVID-19. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the common DEGs. A protein-protein interaction (PPI) network was constructed to identify common genes, and their diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis. Validation was performed on the GSE213313 and GSE15932 datasets. A gene co-expression network was constructed using the GeneMANIA database to explore interactions among core DEGs and their co-expressed genes. Finally, a microRNA (miRNA)-transcription factor (TF)-messenger RNA (mRNA) regulatory network was constructed based on the common feature genes. Results: In the GSE95849 and GSE164805 datasets, 81 upregulated genes and 140 downregulated genes were identified. GO and KEGG enrichment analyses revealed that these DEGs were closely related to the negative regulation of phosphate metabolic processes, the positive regulation of mitotic nuclear division, T-cell co-stimulation, and lymphocyte co-stimulation. Four upregulated common genes (DHX15, USP14, COPS3, TYK2) and one downregulated common feature gene (RIOK2) were identified and showed good diagnostic accuracy for T2DM and COVID-19. The AUC values of DHX15, USP14, COPS3, TYK2, and RIOK2 in T2DM diagnosis were 0.931, 0.917, 0.986, 0.903, and 0.917, respectively. In COVID-19 diagnosis, the AUC values were 0.960, 0.860, 1.0, 0.9, and 0.90, respectively. Validation in the GSE213313 and GSE15932 datasets confirmed these results. The miRNA-TF-mRNA regulatory network showed that TYH2 was targeted by PITX1, PITX2, CRX, NFYA, SREBF1, RELB, NR1L2, and CEBP, whereas miR-124-3p regulates THK2, RIOK2, and USP14. Conclusion: We identified five common feature genes (DHX15, USP14, COPS3, TYK2, and RIOK2) and their co-regulatory pathways between T2DM and COVID-19, which may provide new insights for further molecular mechanism studies.

Comparison of EUS-FNA and EUS-FNB for diagnosis of solid pancreatic mass lesions: a meta-analysis of prospective studies.

Objective: To quantitatively compare the diagnostic value of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) and endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) in solid pancreatic mass lesions using a systematic evaluation method.Methods: A systematic literature search was conducted on public databases to include studies comparing the diagnostic value of EUS-FNA and EUS-FNB in solid pancreatic mass lesions. The combined effect size was estimated using mean difference (MD) and risk difference (RD) respectively, and the corresponding 95% confidence interval (CI) was calculated.Results: The 12 articles (7 RCTs and 5 cohort studies) met the inclusion criteria of this study. The meta-analysis showed that compared with EUS-FNB, EUS-FNA had lower diagnostic accuracy (RD: -0.08, 95% CI: -0.15, -0.01) and specimen adequacy (RD: -0.08, 95% CI: -0.15, -0.02), while higher required number of needle passes (MD: 0.42, 95% CI: 0.12, 0.73). However, EUS-FNB and EUS-FNA presented similar overall complications (RD: 0.00, 95% CI: -0.01, 0.02) and technical failures (RD: -0.01, 95% CI: -0.02, 0.00), without statistically significant differences.Conclusions: Compared with EUS-FNA, EUS-FNB seems to be a better choice for diagnosing suspected pancreatic lesions.

Higher serum chromium level may be associated with the presentation of depression in patients with metabolic dysfunction-associated fatty liver disease: evidence from NHANES survey.

Background: Depressive symptoms are frequently observed in patients with Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD), a prevalent metabolic disorder that affects many individuals. It is not yet clear whether there is an association between serum chromium levels and depression. Objective: The purpose of this research was to explore the association between serum chromium level and the manifestation of depression among patients with MAFLD. Methods: The selection of 1837 patients diagnosed with MAFLD was based on data obtained from the 2017-2018 National Health and Nutrition Examination Survey (NHANES) database in this research. The Patient Health Questionnaire-9 (PHQ-9) was employed to evaluate the severity of depression. The researchers utilized logistic regression models that were weighted for multiple variables to investigate the association between depression and serum chromium levels. Results: In our study, we found that 8.98% of US adults with MAFLD were suffering from depression at the time of evaluation. In the logistic regression model, serum chromium levels showed an inverse association with depression (OR=0.82, 95%CI: 0.69-0.96; p=0.016), this relationship remained after adjusting for fully confounding factors (OR=0.83, 95%CI: 0.71-0.97; p=0.021), subgroup analyses showed that the association between serum chromium levels and depression existed in relatively high-prevalence of depression groups. Conclusion: Patients diagnosed with MAFLD have a greater likelihood of experiencing depression, whereas individuals with higher levels of serum chromium are less likely to suffer from depression, and this association persists even after adjusting for other factors. These findings indicate supplementing chromium may be a viable treatment for their depressive symptoms.

EGR1 mediates MDR1 transcriptional activity regulating gemcitabine resistance in pancreatic cancer.

BACKGROUND: Gemcitabine is a cornerstone drug for the treatment of all stages of pancreatic cancer and can prolong the survival of patients with pancreatic cancer, but resistance to gemcitabine in pancreatic cancer patients hinders its efficacy. The overexpression of Early growth response 1(EGR1) in pancreatic ductal adenocarcinoma as a mechanism of gemcitabine chemoresistance in pancreatic cancer has not been explored. The major mechanisms of gemcitabine chemoresistance are related to drug uptake, metabolism, and action. One of the common causes of tumor multidrug resistance (MDR) to chemotherapy in cancer cells is that transporter proteins increase intracellular drug efflux and decrease drug concentrations by inducing anti-apoptotic mechanisms. It has been reported that gemcitabine binds to MDR1 with high affinity. The purpose of this research was to investigate the potential mechanisms by which EGR1 associates with MDR1 to regulate gemcitabine resistance in pancreatic cancer cells. METHODS: The following in vitro and in vivo techniques were used in this research to explore the potential mechanisms by which EGR1 binds to MDR1 to regulate gemcitabine resistance in pancreatic cancer cells. Cell culture; in vitro and in vivo study of EGR1 function by loss of function analysis. Binding of EGR1 to the MDR1 promoter was detected using the ChIP assay. qRT-PCR, Western blot assays to detect protein and mRNA expression; use of Annexin V apoptosis detection assay to test apoptosis; CCK8, Edu assay to test cell proliferation viability. The animal model of pancreatic cancer subcutaneous allograft was constructed and the tumours were stained with hematoxylin eosin and Ki-67 expression was detected using immunohistochemistry. FINDINGS: We revealed that EGR1 expression was increased in different pancreatic cancer cell lines compared to normal pancreatic ductal epithelial cells. Moreover, gemcitabine treatment induced upregulation of EGR1 expression in a dose- and time-dependent manner. EGR1 is significantly enriched in the MDR1 promoter sequence.Upon knockdown of EGR1, cell proliferation was impaired in CFPAC-1 and PANC-1 cell lines, apoptosis was enhanced and MDR1 expression was decreased, thereby partially reversing gemcitabine chemoresistance. In animal experiments, knockdown of EGR1 enhanced the inhibitory effect of gemcitabine on tumor growth compared with the sh-NC group. CONCLUSIONS: Our study suggests that EGR1 may be involved in the regulation of MDR1 to enhance gemcitabine resistance in pancreatic cancer cells. EGR1 could be a novel therapeutic target to overcome gemcitabine resistance in pancreatic cancer.

Artesunate Inhibits the Growth of Insulinoma Cells via SLC7A11/ GPX4-mediated Ferroptosis.

BACKGROUND: Artesunate (ART) has been recognized to induce ferroptosis in various tumor phenotypes, including neuroendocrine tumors. We aimed to investigate the effects of ART on insulinoma and the underlying mechanisms by focusing on the process of ferroptosis. METHODS: The CCK8 and colony formation assays were conducted to assess the effectiveness of ART. Lipid peroxidation, glutathione, and intracellular iron content were determined to validate the process of ferroptosis, while ferrostatin-1 (Fer-1) was employed as the inhibitor of ferroptosis. Subcutaneous tumor models were established and treated with ART. The ferroptosis-associated proteins were determined by western blot and immunohistochemistry assays. Pathological structures of the liver were examined by hematoxylin-eosin staining. RESULTS: ART suppressed the growth of insulinoma both in vitro and in vivo. Insulinoma cells treated by ART revealed signs of ferroptosis, including increased lipid peroxidation, diminished glutathione levels, and ascending intracellular iron. Notably, ART-treated insulinoma cells exhibited a decline in the expressions of catalytic component solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4). These alterations were negated by Fer-1. Moreover, no hepatotoxicity was observed upon the therapeutic dose of ART. CONCLUSION: Artesunate might regulate ferroptosis of insulinoma cells through the SLC7A11/GPX4 pathway.

Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a common complication in patients with cirrhosis. The diagnosis of SBP is still mostly based on ascites cultures and absolute ascites polymorphonuclear (PMN) cell count, which restricts the widely application in clinical settings. This study aimed to identify reliable and easy-to-use biomarkers for both diagnosis and prognosis of cirrhotic patients with SBP. METHODS: We conducted a retrospective study including 413 cirrhotic patients from March 2013 to July 2022 in the First Affiliated Hospital of Guangxi Medical University. Patients' clinical characteristics and laboratory indices were collected and analyzed. Two machine learning methods (Xgboost and LASSO algorithms) and a logistic regression analysis were adopted to screen and validate the indices associated with the risk of SBP. A predictive model was constructed and validated using the estimated area under curve (AUC). The indices related to the survival of cirrhotic patients were also analyzed. RESULTS: A total of 413 cirrhotic patients were enrolled in the study, of whom 329 were decompensated and 84 were compensated. 52 patients complicated and patients with SBP had a poorer Child-Pugh score (P < 0.05). Patients with SBP had a greater proportion of malignancies than those without SBP(P < 0.05). The majority of laboratory test indicators differed significantly between patients with and without SBP (P < 0.05). Albumin, neutrophil-to-lymphocyte ratio (NLR), and ferritin-to-neutrophil ratio (FNR) were found to be independently associated with SBP in decompensated cirrhotic patients using LASSO algorithms, and logistic regression analysis. The model established by the three indices showed a high predictive value with an AUC of 0.808. Furthermore, increased neutrophils, ALP, and C-reactive protein-to-albumin ratio (CAR) were associated with the shorter survival time of patients with decompensated cirrhosis, and the combination of these indices showed a greater predictive value for cirrhotic patients. CONCLUSIONS: The present study identified FNR as a novel index in the diagnosis of SBP in decompensated patients with cirrhosis. A model based on neutrophils, ALP and CAR showed high performance in predicting the prognosis of patients with decompensated cirrhosis.

LncRNA-Gm9866 promotes liver fibrosis by activating TGFß/Smad signaling via targeting Fam98b.

OBJECTIVE: The exact mechanism and target molecules of liver fibrosis have remained largely elusive. Here, we investigated the role of long noncoding RNA Gm9866(lncRNA-Gm9866) on liver fibrosis. METHODS: The transcription of lncRNA-Gm9866 in activated cells and mouse fibrotic livers was determined by quantitative polymerase chain reaction (qRT-PCR). The effects of lentivirus-mediated knockdown or overexpression of lncRNA-Gm9866 in liver fibrosis were examined in vitro and in vivo. Furthermore, bioinformatics analysis, cell samples validation, fluorescence in situ hybridization (FISH) co-localization, RNA binding protein immunoprecipitation (RIP), actinomycin D test and Western blot (WB) were carried out to explore the potential mechanism of lncRNA-Gm9866. RESULTS: The expression of α-smooth muscle actin (α-SMA), Collagen I (COL-1) and lncRNA-Gm9866 were significantly increased in tissues and cells. Overexpressing lncRNA-Gm9866 promoted the activation of hepatic stellate cells (HSCs). Silencing lncRNA-Gm9866 inhibited the activation of HSCs and transforming growth factor-ß1 (TGFß1) induced fibrosis. Overexpressing lncRNA-Gm9866 promoted hepatocytes (HCs) apoptosis and the expression of pro-fibrogenic genes, inhibited the proliferation and migration of HCs. Knockdown of lncRNA-Gm9866 inhibited the apoptosis of HCs, the expression of pro-fibrogenic genes, TGFß1 induced fibrosis and the occurrence of carbon tetrachloride (CCl4)-induced liver fibrosis, and promoted the proliferation and migration of HCs. Mechanistically, lncRNA-Gm9866 may directly bine with Fam98b. Silencing Fam98b in stably overexpressing lncRNA-Gm9866 cell lines reversed the increase of pro-fibrogenic genes and pro-apoptotic genes, fibrosis related pathway protein TGFß1, Smad2/3, p-Smad2/3 and Notch3 induced by overexpressing lncRNA-Gm9866. CONCLUSIONS: LncRNA-Gm9866 may regulate TGFß/Smad and Notch pathways by targeting Fam98b to regulate liver fibrosis. LncRNA-Gm9866 may be a new target for diagnosis and treatment of liver fibrosis.

Alterations in intra- and inter-network connectivity associated with cognition impairment in insulinoma patients.

Objective: Cognitive dysfunction is common in insulinoma patients, but the underlying neural mechanisms are less well understood. This study aimed to explore the alterations of intra- and inter-network connectivity patterns associated with patients with insulinoma. Methods: Resting-state fMRI were acquired from 13 insulinoma patients and 13 matched healthy controls (HCs). Group Independent component analysis (ICA) was employed to capture the resting-state networks (RSNs), then the intra- and inter-network connectivity patterns, were calculated and compared. Montreal Cognitive Assessment (MoCA) was used to assess the cognitive function. The relationship between connectivity patterns and MoCA scores was also examined. Results: Insulinoma patients performed significantly worse on MoCA compared to HCs. The intra-network connectivity analysis revealed that patients with insulinoma showed decreased connectivity in the left medial superior frontal gyrus within anterior default mode network (aDMN), and decreased connectivity in right lingual gyrus within the visual network (VN). The intra-network connectivity analysis showed that patients with insulinoma had an increased connectivity between the inferior-posterior default mode network (ipDMN) and right frontoparietal network (rFPN) and decreased connectivity between the ipDMN and auditory network (AUN). There was a significant negative correlation between the ipDMN-rFPN connectivity and MoCA score. Conclusion: This study demonstrated significant abnormalities in the intra- and inter-network connectivity in patients with insulinoma, which may represent the neural mechanisms underlying the cognitive impairment in insulinoma patients.

Identifying target ion channel-related genes to construct a diagnosis model for insulinoma.

Background: Insulinoma is the most common functional pancreatic neuroendocrine tumor (PNET) with abnormal insulin hypersecretion. The etiopathogenesis of insulinoma remains indefinable. Based on multiple bioinformatics methods and machine learning algorithms, this study proposed exploring the molecular mechanism from ion channel-related genes to establish a genetic diagnosis model for insulinoma. Methods: The mRNA expression profile dataset of GSE73338 was applied to the analysis, which contains 17 insulinoma samples, 63 nonfunctional PNET (NFPNET) samples, and four normal islet samples. Differently expressed ion channel-related genes (DEICRGs) enrichment analyses were performed. We utilized the protein-protein interaction (PPI) analysis and machine learning of LASSO and support vector machine-recursive feature elimination (SVM-RFE) to identify the target genes. Based on these target genes, a nomogram diagnostic model was constructed and verified by a receiver operating characteristic (ROC) curve. Moreover, immune infiltration analysis, single-gene gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were executed. Finally, a drug-gene interaction network was constructed. Results: We identified 29 DEICRGs, and enrichment analyses indicated they were primarily enriched in ion transport, cellular ion homeostasis, pancreatic secretion, and lysosome. Moreover, the PPI network and machine learning recognized three target genes (MCOLN1, ATP6V0E1, and ATP4A). Based on these target genes, we constructed an efficiently predictable diagnosis model for identifying insulinomas with a nomogram and validated it with the ROC curve (AUC = 0.801, 95% CI 0.674-0.898). Then, single-gene GSEA analysis revealed that these target genes had a significantly positive correlation with insulin secretion and lysosome. In contrast, the TGF-beta signaling pathway was negatively associated with them. Furthermore, statistically significant discrepancies in immune infiltration were revealed. Conclusion: We identified three ion channel-related genes and constructed an efficiently predictable diagnosis model to offer a novel approach for diagnosing insulinoma.

GDF-15 (a biomarker for metformin) and the risk of COVID-19: A two-sample Mendelian randomization study.

BACKGROUND: Regarding the impact of metformin on COVID-19, there are currently varying opinions from multiple studies. Growth differentiation factor 15 (GDF-15) is a biomarker of metformin use and dosage, and we used two-sample Mendelian randomization (MR) to assess the causal effect of GDF-15 (metformin) on COVID-19 susceptibility, hospitalization, and severe COVID-19, thereby guiding the selection of glucose-lowering agents for diabetic patients during the COVID-19 pandemic. METHODS: Two sets of genetic tools were utilized for MR analysis, derived from publicly available genetic data. The first set was GDF-15 genome-wide association study (GWAS) data from a study with 5440 participants, while the second set was COVID-19 GWAS data from the Host Genetics Initiative (HGI) GWAS meta-analysis. The primary method used to assess causal effects was random effects inverse variance weighted estimation. Complementary methods included weighted median and MR-Egger analyses. Sensitivity analysis was performed using Cochran Q tests, MR-Egger intercept tests, MR-PRESSO, leave-one-out analyses, and funnel plots. RESULTS: GDF-15 increased the risk of severe COVID-19 in patients (OR = 1.10, 95% CI 1.03-1.19; P = .006); there was no causal effect of GDF-15 on hospitalization for COVID-19 (OR = 1.02, 95% CI 0.96-1.07; P = .47) or susceptibility to COVID-19 in the general population (OR = 1.010, 95% CI 0.988-1.034; P = .354). CONCLUSIONS: Our study supports the notion that GDF-15 increases the risk of severe COVID-19 in patients. However, there is no causal relationship between GDF-15 and hospitalization or susceptibility to COVID-19.

Local Sustained Chemotherapy of Pancreatic Cancer Using Endoscopic Ultrasound-Guided Injection of Biodegradable Thermo-Sensitive Hydrogel.

Purpose: Endoscopic ultrasound-guided fine-needle injection (EUS-FNI) offers a promising minimally invasive approach for locally targeted management of advanced pancreatic cancer. However, the efficacy is limited due to the rapid plasma clearance of chemotherapeutic agents. Injectable hydrogels can form drug release depots, which provide a feasible solution for optimizing targeted chemotherapy through EUS-FNI. Methods: A drug delivery system was developed, consisting of gemcitabine (GEM) and thermo-sensitive hydrogel (PLGA-PEG-PLGA, PPP). The injectability, gel formation ability, biocompatibility and sustained drug delivery properties of PPP hydrogel were verified in vitro and in vivo. The effects of GEM/PPP hydrogel on cell proliferation, invasion, metastasis, and apoptosis were explored through co-culturing with PANC-1 cells. The therapeutic effects of GEM/PPP hydrogel on xenograft mice were compared with those of GEM, ethanol and polidocanol using the precisely targeted EUS-FNI technology. Tumor sections were examined by H&E, Ki-67, and TUNEL staining. Results: GEM/PPP hydrogel exhibited excellent injectability, biocompatibility, and the capability of sustained drug delivery for up to 7 days by forming a gel triggered by body temperature. It demonstrated the best therapeutic effects, significantly reducing proliferation, invasion and migration of PANC-1 cells while promoting apoptosis. After precise injection using EUS-FNI technology, GEM/PPP hydrogel resulted in a reduction of tumor weight by up to 75.96% and extending the survival period by 14.4 days with negligible adverse effects. Pathological examination revealed no systemic toxicity and significant apoptosis and minimal proliferation as well. Conclusion: The combination of GEM/PPP hydrogel and EUS-FNI technology provides an optimal approach of precise chemotherapy for pancreatic cancer, builds a bridge for clinical translation of basic research, and brings great hope for innovation of minimally invasive treatment modalities. The first-hand EUS image data obtained in this study also serves as a crucial reference for future clinical trials.

A retrospective cohort study on the efficacy and safety for combination therapy of immunotherapy, targeted agent, and chemotherapy versus immunochemotherapy or chemotherapy alone in the first-line treatment of advanced biliary tract carcinoma.

Background: A paucity of effective treatment for biliary tract carcinoma (BTC) has necessitated the investigation into new therapies. As combinations of targeted therapy with immunotherapy are well-established in hepatocellular carcinoma, the GEMOX chemotherapy (gemcitabine and oxaliplatin) is the standard treatment for BTC. This study aimed to evaluate the efficacy and safety of immunotherapy in combination with targeted agent and chemotherapy in advanced BTC. Methods: Patients who were pathologically identified advanced BTC and had received gemcitabine-based chemotherapy alone or in combination with anlotinib, and/or anti-programmed cell death protein-1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors such as camrelizumab as first-line treatment were retrospectively screened from The First Affiliated Hospital of Guangxi Medical University from February 2018 to August 2021. The outcomes included objective response rate (ORR), median overall survival (OS), and median progressive-free survival (PFS). Adverse events (AEs) were assessed according to the NCI-CTCAE v. 4.03. Patients were followed up weekly. Results: A total of 35 patients were enrolled in this study: 11 patients treated with PD-1/PD-L1 inhibitor plus anlotinib and gemcitabine (arm A), 12 patients with the GEMOX combined with PD-1/PD-L1 inhibitor (arm B), and 12 patients with GEMOX (arm C). With a median follow-up time of 31.9 months (range, 23.8-39.7 months), the median OS was 16.8 months [95% confidence interval (CI): 7.0-not reached], 11.8 months (95% CI: 7.2-31.7 months), and 11.6 months (95% CI: 7.3-18.0 months) in arms A, B, and C, respectively (P=0.298). The median PFS was 16.8 months (95% CI: 7.0-NR), 6.0 months (95% CI: 5.1-8.7 months), and 6.3 months (95% CI: 4.6-7.0 months) in arms A, B, and C, respectively. The ORR were 63.6% in arm A, 33.3% in arm B, and 25.0% in arm C. AEs of all grades occurred in 33 (94.3%) patients. Grade 3-4 AEs in all patients included neutrophil count decrease (14.3%), aspartate aminotransferase increase (8.6%), alanine aminotransferase increase (8.6%), fatigue (5.7%), and blood bilirubin increase (5.7%). Conclusions: Anti-PD-1/PD-L1 immunotherapy in combination with anlotinib and gemcitabine showed promising efficacy and an acceptable safety profile for the BTC patients included in this study.

Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis.

Background: Atherosclerosis (AS) is one of the leading causes of the cardio-cerebral vascular incident. The constantly emerging evidence indicates a close association between nonalcoholic fatty liver disease (NAFLD) and AS. However, the exact molecular mechanisms underlying the correlation between these two diseases remain unclear. This study proposed exploring the common signature genes, pathways, and immune cells among AS and NAFLD. Methods: The common differentially expressed genes (co-DEGs) with a consistent trend were identified via bioinformatic analyses of the Gene Expression Omnibus (GEO) datasets GSE28829 and GSE49541, respectively. Further, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. We utilized machine learning algorithms of lasso and random forest (RF) to identify the common signature genes. Then the diagnostic nomogram models and receiver operator characteristic curve (ROC) analyses were constructed and validated with external verification datasets. The gene interaction network was established via the GeneMANIA database. Additionally, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to explore the co-regulated pathways and immune cells. Results: A total of 11 co-DEGs were identified. GO and KEGG analyses revealed that co-DEGs were mainly enriched in lipid catabolic process, calcium ion transport, and regulation of cytokine. Moreover, three common signature genes (PLCXD3, CCL19, and PKD2) were defined. Based on these genes, we constructed the efficiently predictable diagnostic models for advanced AS and NAFLD with the nomograms, evaluated with the ROC curves (AUC = 0.995 for advanced AS, 95% CI 0.971-1.0; AUC = 0.973 for advanced NAFLD, 95% CI 0.938-0.998). In addition, the AUC of the verification datasets had a similar trend. The NOD-like receptors (NLRs) signaling pathway might be the most crucial co-regulated pathway, and activated CD4 T cells and central memory CD4 T cells were significantly excessive infiltration in advanced NAFLD and AS. Conclusion: We identified three common signature genes (PLCXD3, CCL19, and PKD2), co-regulated pathways, and shared immune features of NAFLD and AS, which might provide novel insights into the molecular mechanism of NAFLD complicated with AS.

Identification of ZBTB4 as an immunological biomarker that can inhibit the proliferation and invasion of pancreatic cancer.

BACKGROUND: Zinc finger and BTB domain-containing protein 4 (ZBTB4) belongs to the zinc finger protein family, which has a role in regulating epigenetic inheritance and is associated with cell differentiation and proliferation. Previous studies have identified aberrant ZBTB4 expression in cancer and its ability to modulate disease progression, but studies on the immune microenvironment, immunotherapy and its role in cancer are still lacking. METHODS: Human pan-cancer and normal tissue transcriptome data were obtained from The Cancer Genome Atlas. The pan-cancer genomic alteration landscape of ZBTB4 was investigated with the online tool. The Kaplan-Meier method was used to evaluate the prognostic significance of ZBTB4 in pancreatic cancer. In parallel, ZBTB4 interacting molecules and potential functions were analyzed by co-expression and the correlation between ZBTB4 and immune cell infiltration, immune modulatory cells and efficacy of immune checkpoint therapy was explored. Next, we retrieved the Gene Expression Omnibus database expression datasets of ZBTB4 and investigated ZBTB4 expression and clinical significance in pancreatic cancer by immunohistochemical staining experiments. Finally, cell experiments were performed to investigate changes in pancreatic cancer cell proliferation, migration and invasion following overexpression and knockdown of ZBTB4. FINDINGS: ZBTB4 showed loss of expression in the majority of tumors and possessed the ability to predict cancer prognosis. ZBTB4 was closely related to the tumor immune microenvironment, immune cell infiltration and immunotherapy efficacy. ZBTB4 had good diagnostic performance for pancreatic cancer in the clinic, and ZBTB4 protein expression was lost in pancreatic cancer tumor tissues. Cell experiments revealed that overexpression of ZBTB4 inhibited the proliferation, migration and invasion of pancreatic cancer cells, while silencing ZBTB4 showed the opposite effect. CONCLUSIONS: According to our results, ZBTB4 is present in pancreatic cancer with aberrant expression and is associated with an altered immune microenvironment. We show that ZBTB4 is a promising marker for cancer immunotherapy and cancer prognosis and has the potential to influence pancreatic cancer progression.

Identification of Timm13 protein translocase of the mitochondrial inner membrane as a potential mediator of liver fibrosis based on bioinformatics and experimental verification.

OBJECTIVE: To explore the association between translocase of the inner mitochondrial membrane 13 (Timm13) and liver fibrosis. METHODS: Gene expression profiles of GSE167033 were collected from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between liver disease and normal samples were analyzed using GEO2R. Gene Ontology and Enrichment function were performed, a protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the hub genes of the PPI network were calculated by MCODE plug-in in Cytoscape. We validated the transcriptional and post-transcriptional expression levels of the top correlated genes using fibrotic animal and cell models. A cell transfection experiment was conducted to silence Timm13 and detect the expression of fibrosis genes and apoptosis genes. RESULTS: 21,722 genes were analyzed and 178 DEGs were identified by GEO2R analysis. The top 200 DEGs were selected and analyzed in STRING for PPI network analysis. Timm13 was one of the hub genes via the PPI network. We found that the mRNA levels of Timm13 in fibrotic liver tissue decreased (P < 0.05), and the mRNA and protein levels of Timm13 also decreased when hepatocytes were stimulated with transforming growth factor-ß1. Silencing Timm13 significantly reduced the expression of profibrogenic genes and apoptosis related genes. CONCLUSIONS: The results showed that Timm13 is closely related to liver fibrosis and silencing Timm13 significantly reduced the expression of profibrogenic genes and apoptosis related genes, which will provide novel ideas and targets for the clinical diagnosis and treatment of liver fibrosis.

Esophageal foreign body removal under holmium laser-assisted gastroscope: A case report.

As a common clinical emergence, esophageal foreign body can lead to esophageal perforation followed by severe complications including aortic injury, mediastinal abscess and airway obstruction, leading to a high rate of mortality. Therefore, fast and effective diagnosis and treatment are of great necessity. In this case, holmium laser-assisted gastroscopy was adopted to remove the foreign body incarcerated in the esophagus, allowing patients to avoid traumatic and costly surgeries. It is a supplement to traditional methods of foreign body removal. The new combination tried in this report can bring development and innovation inspiration to the development of endoscopic technology.

The Long Noncoding RNA Gm9866/Nuclear Factor-κB Axis Promotes Macrophage Polarization.

Macrophages are a type of immune cells with high levels of plasticity and heterogeneity. They can polarize into M1 or M2 functional phenotypes. These two phenotypes exhibit a dynamic balance during polarization-related diseases and play opposing roles. Long noncoding RNAs (lncRNAs) play an important role in biological processes such as cell proliferation, death, and differentiation; however, how long noncoding RNAs affect the cellular functionality of macrophages remains to be studied. Long noncoding RNA Gm9866 was found to be closely related to macrophage polarization through bioinformatics analysis. In this study, by conducting real-time polymerase chain reaction analysis, it was observed that long noncoding RNA Gm9866 expression significantly increased after treatment with interleukin-4 but significantly decreased after treatment with lipopolysaccharide. Fluorescence in situ hybridization revealed that long noncoding RNA Gm9866 was expressed mainly in the nucleus. Real-time polymerase chain reaction analysis showed that overexpression of long noncoding RNA Gm9866 in RAW264.7 cells further promoted the expression of M2 markers MRC1 (macrophage mannose receptor 1) and MRC2 (macrophage mannose receptor 2). Western blotting analysis demonstrated inhibition of nuclear factor-κB (NF-κB) expression. EdU (5-ethynyl-2'-deoxyuridine) and TUNEL (TdT-mediated dUTP nick-end labeling) staining assays revealed that overexpression of long noncoding RNA Gm9866 promoted cell proliferation and inhibited apoptosis. These findings thus indicated that long noncoding RNA Gm9866 promoted macrophage polarization and inhibited the nuclear factor-κB signaling pathway. Thus, long noncoding RNA Gm9866 may serve as a potential diagnostic and therapeutic target for polarization-related diseases such as infectious diseases, inflammatory diseases, liver fibrosis, and tumors.