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Acute pancreatitis remains a serious public health problem, and the burden of acute pancreatitis is increasing. With significant morbidity and serious complications, appropriate and effective therapies are critical. Great progress has been made in understanding the pathophysiology of acute pancreatitis over the past two decades. However, specific drugs targeting key molecules and pathways involved in acute pancreatitis still require further study. Natural compounds extracted from plants have a variety of biological activities and can inhibit inflammation and oxidative stress in acute pancreatitis by blocking several signaling pathways, such as the nuclear factor kappa-B and mitogen-activated protein kinase pathways. In this article, we review the therapeutic effects of various types of phytochemicals on acute pancreatitis and discuss the mechanism of action of these natural compounds in acute pancreatitis, aiming to provide clearer insights into the treatment of acute pancreatitis. [ABSTRACT FROM AUTHOR]

The diverse bacterial populations within the symbiotic microbiota play a pivotal role in both health and disease. Microbiota modulates critical aspects of tumor biology including cell proliferation, invasion, and metastasis. This regulation occurs through mechanisms like enhancing genomic damage, hindering gene repair, activating aberrant cell signaling pathways, influencing tumor cell metabolism, promoting revascularization, and remodeling the tumor immune microenvironment. These microbiota‐mediated effects significantly impact overall survival and the recurrence of tumors after surgery by affecting the efficacy of chemoradiotherapy. Moreover, leveraging the microbiota for the development of biovectors, probiotics, prebiotics, and synbiotics, in addition to utilizing antibiotics, dietary adjustments, defensins, oncolytic virotherapy, and fecal microbiota transplantation, offers promising alternatives for cancer treatment. Nonetheless, due to the extensive and diverse nature of the microbiota, along with tumor heterogeneity, the molecular mechanisms underlying the role of microbiota in cancer remain a subject of intense debate. In this context, we refocus on various cancers, delving into the molecular signaling pathways associated with the microbiota and its derivatives, the reshaping of the tumor microenvironmental matrix, and the impact on tolerance to tumor treatments such as chemotherapy and radiotherapy. This exploration aims to shed light on novel perspectives and potential applications in the field. [ABSTRACT FROM AUTHOR]

Biliary tract cancer, encompassing intrahepatic and extrahepatic cholangiocarcinoma as well as gallbladder carcinoma, stands as a prevalent malignancy characterized by escalating incidence rates and unfavorable prognoses. The onset of cholangiocarcinoma involves a multitude of risk factors and could potentially be influenced by microbial exposure. The human microbiome, encompassing the entirety of human microbial genetic information, assumes a pivotal role in regulating key aspects such as host digestion, absorption, immune responses, and metabolism. The widespread application of next-generation sequencing technology has notably propelled investigations into the intricate relationship between the microbiome and diseases. An accumulating body of evidence strongly suggests a profound interconnection between biliary tract cancer and the human microbiome. This article critically appraises the existing evidence pertaining to the microbiome milieu within patients afflicted by biliary tract cancer. Furthermore, it delves into potential mechanisms through which dysregulation of the human microbiome could contribute to the advancement of biliary tract cancer. Additionally, the article expounds on its role in the context of chemotherapy and immunotherapy for biliary tract cancer. [ABSTRACT FROM AUTHOR]

Plakophilin 3 (PKP3) affects cell signal transduction and cell adhesion and performs a crucial function in tumorigenesis. The current investigation evaluated the predictive significance and underlying processes of PKP3 within pancreatic cancer (PC) tissues. The assessment of differences in PKP3 expression was conducted through an analysis of RNA-seq data acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Additionally, clinical samples were collected to validate the findings. The predictive significance of PKP3 was investigated by analyzing survival data derived from TCGA and clinical specimens. PKP3′s biological function was assessed via phenotypic experiments after the suppression of PKP3 expression within PC cells. Functional enrichment analysis, encompassing KEGG, GO, and GSEA, was employed to assess the underlying mechanism of PKP3. Immune infiltration analysis was conducted in the present investigation to determine the association between PKP3 and tumor-infiltrating immune cells (TICs). In PC tissues, PKP3 expression was abnormally upregulated and correlated with a negative prognosis in individuals with PC. PKP3 can promote the progression, migration, and invasive capacity of PC cells and is relevant to the regulation of the PI3K–Akt and MAPK signaling pathways. Immune infiltration analysis demonstrated that PKP3 impeded CD8+ T-cell infiltration and immune cytokine expression within the tumor microenvironment. The PKP3 protein was identified as a prospective independent predictive indicator and represents a viable approach for immunotherapy in the context of PC. PKP3 may impact prognosis by broadly inhibiting immune cell infiltration and promoting the activation of tumor-associated signaling pathways. [ABSTRACT FROM AUTHOR]

Tumor-associated macrophages M2 (TAM2), which are highly prevalent infiltrating immune cells in the stroma of pancreatic cancer (PC), have been found to induce an immunosuppressive tumor microenvironment, thus enhancing tumor initiation and progression. However, the immune therapy response and prognostic significance of regulatory genes associated with TAM2 in PC are currently unknown. Based on TCGA transcriptomic data and single-cell sequencing data from the GEO database, we identified TAM2-driven genes using the WGCNA algorithm. Molecular subtypes based on TAM2-driven genes were clustered using the ConsensusClusterPlus algorithm. The study constructed a prognostic model based on TAM2-driven genes through Lasso-COX regression analysis. A total of 178 samples obtained by accessing TCGA were accurately categorized into two molecular subtypes, including the high-TAM2 infiltration (HMI) cluster and the low-TAM2 infiltration (LMI) cluster. The HMI cluster exhibits a poor prognosis, a malignant tumor phenotype, immune-suppressive immune cell infiltration, resistance to immunotherapy, and a high number of genetic mutations, while the LMI cluster is the opposite. The prognostic model composed of six hub genes from TAM2-driven genes exhibits a high degree of accuracy in predicting the prognosis of patients with PC and serves as an independent risk factor. The induction of TAM2 was employed as a means of verifying these six gene expressions, revealing the significant up-regulation of BCAT1, BST2, and MERTK in TAM2 cells. In summary, the immunophenotype and prognostic model based on TAM2-driven genes offers a foundation for the clinical management of PC. The core TAM2-driven genes, including BCAT1, BST2, and MERTK, are involved in regulating tumor progression and TAM2 polarization, which are potential targets for PC therapy. [ABSTRACT FROM AUTHOR]

Ena-VASP-like (EVL), a member of the Enabled/vasodilator stimulated phosphoprotein family, is functionally expressed in various cancers. This study explored the prognostic value and potential mechanism of EVL in pancreatic cancer (PC). RNA-seq obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to evaluate EVL expression differences, and clinical samples were collected for validation. The prognostic value of EVL was evaluated by survival data obtained from TCGA and clinical samples. The biological pathways involved in EVL were evaluated by functional enrichment analysis such as GO, KEGG, and GSEA. We used immune infiltration analysis to estimate the correlation between EVL and tumor-infiltrating immune cells (TICs). The expression of EVL is down-regulated in PC tissues, which is an independent factor affecting survival time. Survival analysis suggested EVL-high expression was associated with good prognosis in PC patients. The results of the enrichment analysis suggested that the biological function of EVL was closely related to the immune mechanism. Tumor immune infiltration analysis showed that high expression of EVL was accompanied by high levels of immune infiltration. Furthermore, EVL was strongly correlated with the content of immune cells such as CD8+ T cells, B cells, regulatory T cells, CD4+ Tem cells, and follicular Th cells. EVL is a potential independent prognostic marker and immunotherapy target for PC. Mechanistically, EVL may affect the prognosis by extensively promoting immune cell infiltration, including strengthening the anti-tumor immune response of CD8+ T cells. [ABSTRACT FROM AUTHOR]

The liver is the most prevalent location of distant metastasis for pancreatic cancer (PC), which is highly aggressive. Pancreatic cancer with liver metastases (PCLM) patients have a poor prognosis. Furthermore, there is a lack of effective predictive tools for anticipating the diagnostic and prognostic techniques that are needed for the PCLM patients in current clinical work. Therefore, we aimed to construct two nomogram predictive models incorporating common clinical indicators to anticipate the risk factors and prognosis for PCLM patients. Clinicopathological information on pancreatic cancer that referred to patients who had been diagnosed between the years of 2004 and 2015 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses and a Cox regression analysis were utilized to recognize the independent risk variables and independent predictive factors for the PCLM patients, respectively. Using the independent risk as well as prognostic factors derived from the multivariate regression analysis, we constructed two novel nomogram models for predicting the risk and prognosis of PCLM patients. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, the consistency index (C-index), and the calibration curve were then utilized to establish the accuracy of the nomograms' predictions and their discriminability between groups. Using a decision curve analysis (DCA), the clinical values of the two predictors were examined. Finally, we utilized Kaplan–Meier curves to examine the effects of different factors on the prognostic overall survival (OS). As many as 1898 PCLM patients were screened. The patient's sex, primary site, histopathological type, grade, T stage, N stage, bone metastases, lung metastases, tumor size, surgical resection, radiotherapy, and chemotherapy were all found to be independent risks variables for PCLM in a multivariate logistic regression analysis. Using a multivariate Cox regression analysis, we discovered that age, histopathological type, grade, bone metastasis, lung metastasis, tumor size, and surgery were all independent prognostic variables for PCLM. According to these factors, two nomogram models were developed to anticipate the prognostic OS as well as the risk variables for the progression of PCLM in PCLM patients, and a web-based version of the prediction model was constructed. The diagnostic nomogram model had a C-index of 0.884 (95% CI: 0.876–0.892); the prognostic model had a C-index of 0.686 (95% CI: 0.648–0.722) in the training cohort and a C-index of 0.705 (95% CI: 0.647–0.758) in the validation cohort. Subsequent AUC, calibration curve, and DCA analyses revealed that the risk and predictive model of PCLM had high accuracy as well as efficacy for clinical application. The nomograms constructed can effectively predict risk and prognosis factors in PCLM patients, which facilitates personalized clinical decision-making for patients. [ABSTRACT FROM AUTHOR]

Background. Pancreatic cancer (PAAD) is a malignant tumor with a poor prognosis and lacks sensitive biomarkers for diagnosis and targeted therapy. Cuproptosis, a recently proposed form of cell death based on cellular copper ion concentration, plays a key role in cancer biology. This study is aimed at constructing a risk model for predicting the prognosis of PAAD patients based on cuproptosis-related genes. Methods. Pancreatic-related data from UCSC-TCGA and UCSC-GTEx databases were extracted for analysis, and TCGA-PAAD samples were randomly divided into the training and validation groups. Pearson correlation analysis was used to obtain cuproptosis-related genes coexpressed with 19 copper death genes. Univariate Cox and Lasso regression analyses were used to obtain cuproptosis-related prognostic genes. Multivariate Cox regression analysis was used to construct the final prognostic risk model. The risk score curve, Kaplan-Meier survival curves, and ROC curve were used to evaluate the predictive ability of the Cox risk model. Finally, the functional annotation of the risk model was obtained through enrichment analysis. Results. The Cox risk model has an eight prognostic cuproptosis-related gene signature. Kaplan-Meier survival curves demonstrated that the high-risk group had a shorter survival time. The ROC curve of the risk score was well created to predict one-, three-, and five-year survival rates, and AUC of the risk score was higher than other clinical characteristics. Cox regression analysis revealed that the risk score has an independent prognostic value for PAAD. GSEA reveals specific tumor pathways associated with the risk model (Myc targets v1, mTORC1 signaling, and E2F targets). Conclusions. We constructed a prognostic model containing eight cuproptosis-related genes (AKR1B10, KLHL29, PROM2, PIP5K1C, KIF18B, AMIGO2, MRPL3, and PI4KB) that can accurately predict the prognosis of PAAD patients. The results will provide new perspectives for individualized outcome prediction and new therapy development for PAAD patients. [ABSTRACT FROM AUTHOR]

Cordycepin is a nucleoside molecule found in Cordyceps sinensis and can be obtained through chemical synthesis and biotransformation. Cordycepin has been extensively studied and has been shown to have antitumour activity. This activity includes effects on the autophagy process and inhibition of the MAPK/ERK and Hedgehog pathways. Ultimately, the inhibitory effect of cordycepin on tumour cells is due to the interplay of these effects. Cordycepin was shown to enhance the therapeutic effects of radiotherapy. There is increasing evidence indicating that cordycepin plays an anticancer role in the treatment of various cancers. The present review aims to provide a clear understanding of the antitumour mechanisms of cordycepin and discuss its present application in the treatment of tumours. This information can be an important theoretical basis and provide clinical guidance for the further development of cordycepin as an antitumour drug. [ABSTRACT FROM AUTHOR]

The signal transducer and activator of transcription (STAT) is a family of intracellular cytoplasmic transcription factors involved in many biological functions in mammalian signal transduction. Among them, STAT3 is involved in cell proliferation, differentiation, apoptosis, and inflammatory responses. Despite the advances in the treatment of pancreatic cancer in the past decade, the prognosis for patients with pancreatic cancer remains poor. STAT3 has been shown to play a pro-cancer role in a variety of cancers, and inhibitors of STAT3 are used in pre-clinical and clinical studies. We reviewed the relationship between STAT3 and pancreatic cancer and the latest results on the use of STAT3 inhibitors in pancreatic cancer, with the aim of providing insights and ideas around STAT3 inhibitors for a new generation of chemotherapeutic modalities for pancreatic cancer. [ABSTRACT FROM AUTHOR]

This study aimed to assess the surgical outcomes of robotic compared to laparoscopic hepatectomy, with a special focus on the meta-analysis method. Original studies were collected from three Chinese databases, PubMed, EMBASE, and Cochrane Library databases. Our systematic review was conducted on 682 patients with robotic liver resection, and 1101 patients were operated by laparoscopic platform. Robotic surgery has a long surgical duration (MD = 43.99, 95% CI: 23.45–64.53, p = 0.0001), while there is no significant difference in length of hospital stay (MD = 0.10, 95% CI: −0.38–0.58, p = 0.69), blood loss (MD = −20, 95% CI: −64.90–23.34, p = 0.36), the incidence of conversion (OR = 0.84, 95% CI: 0.41–1.69, p = 0.62), and tumor size (MD = 0.30, 95% CI: −0–0.60, p = 0.05); the subgroup analysis of major and minor hepatectomy on operation time is (MD = −7.08, 95% CI: −15.22–0.07, p = 0.09) and (MD = 39.87, 95% CI: −1.70–81.44, p = 0.06), respectively. However, despite the deficiencies of robotic hepatectomy in terms of extended operation time compared to laparoscopic hepatectomy, robotic hepatectomy is still effective and equivalent to laparoscopic hepatectomy in outcomes. Scientific evaluation and research on one portion of the liver may produce more efficacity and more precise results. Therefore, more clinical trials are needed to evaluate the clinical outcomes of robotic compared to laparoscopic hepatectomy. [ABSTRACT FROM AUTHOR]