Long non-coding RNA MIR4435-2HG promotes pancreatic cancer progression by regulating ABHD17C through sponging miR-128-3p.

Background: The recently identified carcinogenic long non-coding RNA (lncRNA) MIR4435-2HG has been validated to contribute to the initiation and progression of several malignancies. Nonetheless, its specific mechanistic function in pancreatic cancer (PC) is yet to be determined. This study aims to investigate the expression and functional role of MIR4435-2HG in PC and to elucidate its potential mechanism. Methods: This study employed The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx)-Pancreas datasets for the analysis of MIR4435-2HG expression in PC and normal pancreatic tissues and its relations with prognosis in PC. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was employed for analyzing MIR4435-2HG, miR-128-3p, and ABHD17C expressions within cells and tissues. Cell proliferation and apoptosis were detected in vitro through Cell Counting Kit 8 (CCK-8) assay and flow cytometry while utilizing transwell and wound healing assays to assess cell migration and invasion. Predicting miR-128-3p binding sites with MIR4435-2HG or ABHD17C was conducted via the online tool starBase and validated through a dual-luciferase reporter (DLR), RNA pull-down and RNA binding protein immunoprecipitation (RIP) assays. Herein, we deployed Western blot to assess protein expression levels. The in vivo role of MIR4435-2HG was studied using tumor xenografts. Results: MIR4435-2HG overexpression exhibited a correlation with poor prognosis in PC. Knocking down MIR4435-2HG significantly hindered the proliferative, invading, and migrating PC cell abilities, accompanied by apoptosis induction, counteracted via a miR-128-3p inhibitor. Moreover, MIR4435-2HG could directly bind to miR-128-3p. Additionally, miR-128-3p directly targeted ABHD17C. Furthermore, in vitro as well as in vivo experiment results elucidated that knocking down MIR4435-2HG hindered PC progression by suppressing ABHD17C expression via miR-128-3p upregulation. Conclusions: MIR4435-2HG can serve as a dependable target for PC diagnosis and treatment by modulating the miR-128-3p/ABHD17C axis to promote its progression.

KRT19 is regulated by miR-642a-5p and promotes pancreatic cancer progression through the Wnt/ß-catenin pathway.

Pancreatic cancer (PC) has a really poor prognosis, and we urgently need to delve deeper into its molecular mechanisms. In this study, we found that KRT19 expression was significantly increased in PC tissues and cell lines and it was linked to unfavorable outcomes for patients. Overexpression of KRT19 boosted the proliferation, migration, and invasion of PC cells. Additionally, miR-374b-5p targets KRT19, inhibiting the activation of the Wnt/ß-catenin pathway (WBC), which in turn suppresses epithelial-to-mesenchymal transition (EMT) and the progression of PC. Further experiments showed that under hypoxic conditions, HIF1α was positively correlated with KRT19, promoting its expression. The loss of miR-642a-5p and the upregulation of KRT19 induced by hypoxia can significantly favor PC progression. Plus, the increased expression of KRT19 might act as a predictive marker and potential target for PC treatment.

Ciprofol suppresses proliferation, invasion and migration of human pancreatic cancer cells.

Pancreatic cancer (PC) is heterogeneous cancer having a high death rate and poor prognosis. The perioperative variables, such as anesthetics, may affect the cancer progression. Ciprofol is an intravenous anesthetic widely used recently. We aimed to explore the influence of ciprofol on PC and investigate its possible pathway. The proliferation, migration and invasion roles and apoptosis of ciprofol in human PC cells were examined using methylthiazolyldiphenyl-tetrazolium bromide, trans well and flow cytometery analysis. Then the putative targeted genes were examined using RNA-sequencing (RNA-seq) analysis. When differentially expressed genes (DEGs) were found, a protein-protein interaction network and pathway analyses were made. Moreover, MMP1 gene expression was confirmed in PC cells using quantitative real-time PCR. PANC-1 cells of PC were significantly suppressed with ciprofol in a dose-dependent and time-dependent way, and 20µg/mL ciprofol significantly suppressed tumor cell aggressiveness. Additionally, the RNA-seq analysis demonstrated that ciprofol controls the expression of 929 DEGs. 5 of 20 hub genes with increased connection were selected. Survival analysis demonstrated that MMP1 may be involved in the carcinogenesis and establishment of PC, reflecting the possible roles associated with ciprofol. Moreover, one target miRNA (hsa-miR-330-5p) of MMP1 was identified.

Interplay between the Human Microbiome and Biliary Tract Cancer: Implications for Pathogenesis and Therapy.

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.

Nomograms for Predicting the Risk and Prognosis of Liver Metastases in Pancreatic Cancer: A Population-Based Analysis.

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.

Immunocyte Infiltration Analysis and Immunohistochemistry Identify EVL as a Potential Prognostic Biomarker for Pancreatic Cancer.

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.

Hypoxic microenvironment in cancer: molecular mechanisms and therapeutic interventions.

Having a hypoxic microenvironment is a common and salient feature of most solid tumors. Hypoxia has a profound effect on the biological behavior and malignant phenotype of cancer cells, mediates the effects of cancer chemotherapy, radiotherapy, and immunotherapy through complex mechanisms, and is closely associated with poor prognosis in various cancer patients. Accumulating studies have demonstrated that through normalization of the tumor vasculature, nanoparticle carriers and biocarriers can effectively increase the oxygen concentration in the tumor microenvironment, improve drug delivery and the efficacy of radiotherapy. They also increase infiltration of innate and adaptive anti-tumor immune cells to enhance the efficacy of immunotherapy. Furthermore, drugs targeting key genes associated with hypoxia, including hypoxia tracers, hypoxia-activated prodrugs, and drugs targeting hypoxia-inducible factors and downstream targets, can be used for visualization and quantitative analysis of tumor hypoxia and antitumor activity. However, the relationship between hypoxia and cancer is an area of research that requires further exploration. Here, we investigated the potential factors in the development of hypoxia in cancer, changes in signaling pathways that occur in cancer cells to adapt to hypoxic environments, the mechanisms of hypoxia-induced cancer immune tolerance, chemotherapeutic tolerance, and enhanced radiation tolerance, as well as the insights and applications of hypoxia in cancer therapy.

Glucose metabolism and tumour microenvironment in pancreatic cancer: A key link in cancer progression.

Early and accurate diagnosis and treatment of pancreatic cancer (PC) remain challenging endeavors globally. Late diagnosis lag, high invasiveness, chemical resistance, and poor prognosis are unresolved issues of PC. The concept of metabolic reprogramming is a hallmark of cancer cells. Increasing evidence shows that PC cells alter metabolic processes such as glucose, amino acids, and lipids metabolism and require continuous nutrition for survival, proliferation, and invasion. Glucose metabolism, in particular, regulates the tumour microenvironment (TME). Furthermore, the link between glucose metabolism and TME also plays an important role in the targeted therapy, chemoresistance, radiotherapy ineffectiveness, and immunosuppression of PC. Altered metabolism with the TME has emerged as a key mechanism regulating PC progression. This review shed light on the relationship between TME, glucose metabolism, and various aspects of PC. The findings of this study provide a new direction in the development of PC therapy targeting the metabolism of cancer cells.

The microbiota and aging microenvironment in pancreatic cancer: Cell origin and fate.

Cellular senescence is a state of growth arrest where nonproliferative cells accumulate over time in the aging microenvironment under multiple external factors. Senescent cells exert a double-edged sword effect in an autocrine or paracrine manner: physiologically, they contribute to tissue development, prevent the multiplication of damaged cells and contribute to tissue repair and tumor suppression while favoring the onset of age-related diseases, including tumors. The microbiota in human tissues is intricately linked to cellular senescence and is reportedly present in the tissues of various tumors (including pancreatic tumors), closely associated with tumorigenesis and progression. The microbiota can induce cells to undergo senescence, and their long-term effects can assist senescent cells in transforming and successfully escaping senescence, contributing to tumorigenesis and progression. Here, we focus on the correlation between the microbiota, cellular senescence, and pancreatic cancer to provide novel ideas for the study and therapy of pancreatic cancer.

A nomogram for predicting survival in patients with advanced (stage III/IV) pancreatic body tail cancer: a SEER-based study.

OBJECTIVE: Pancreatic body tail carcinoma (PBTC) is a relatively few pancreatic cancer in clinical practice, and its specific clinicopathological features and prognosis have not been fully described. In this study, we aimed to create a nomogram to predict the overall survival (OS) of patients with advanced PBTC. METHODS: We extracted clinical and related prognostic data of advanced PBTC patients from 2000 to 2018 from the Surveillance, Epidemiology, and End Results database. Independent prognostic factors were selected using univariate and multivariate Cox analyses, and a nomogram was constructed using R software. The C-index, area under the curve (AUC) of receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA) were used to assess the clinical utility of the nomogram. Finally, OS was assessed using the Kaplan-Meier method. RESULTS: A total of 1256 patients with advanced PBTC were eventually included in this study. Age, grade, N stage, M stage, surgery, and chemotherapy were identified as independent risk factors using univariate and multivariate Cox regression analyses (p < 0.05). In the training cohort, the calibration index of the nomogram was 0.709, while the AUC values of the nomogram, age, grade, N stage, M stage, surgery, and chemotherapy were 0.777, 0.562, 0.621, 0.5, 0.576, 0.632, and 0.323, respectively. Meanwhile, in the validation cohort, the AUC values of the nomogram, age, grade, N stage, M stage, surgery, and chemotherapy were 0.772, 0.551, 0.629, 0.534, 0.577, 0.606, and 0.639, respectively. Good agreement of the model in the training and validation cohorts was demonstrated in the calibration and DCA curves. Univariate survival analysis showed a statistically significant effect of age, grade, M stage, and surgery on prognosis (p < 0.05). CONCLUSION: Age, grade, M stage, and surgery were independently associated with OS, and the established nomogram was a visual tool to effectively predict OS in advanced PBTC patients.

Integrated bioinformatics analysis of potential biomarkers for pancreatic cancer.

BACKGROUND: Pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDA), is an aggressive malignancy associated with a low 5-year survival rate. Poor outcomes associated with PDA are attributable to late detection and inoperability. Most patients with PDA are diagnosed with locally advanced and metastatic disease. Such cases are primarily treated with chemotherapy and radiotherapy. Because of the lack of effective molecular targets, early diagnosis and successful therapies are limited. The purpose of this study was to screen key candidate genes for PDA using a bioinformatic approach and to research their potential functional, pathway mechanisms associated with PDA progression. It may help to understand the role of associated genes in the development and progression of PDA and identify relevant molecular markers with value for early diagnosis and targeted therapy. MATERIALS AND METHODS: To identify novel genes associated with carcinogenesis and progression of PDA, we analyzed the microarray datasets GSE62165, GSE125158, and GSE71989 from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and the Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A protein-protein interaction (PPI) network was constructed using STRING, and module analysis was performed using Cytoscape. Gene Expression Profiling Interactive Analysis (GEPIA) was used to evaluate the differential expression of hub genes in patients with PDA. In addition, we verified the expression of these genes in PDA cell lines and normal pancreatic epithelial cells. RESULTS: A total of 202 DEGs were identified and these were found to be enriched for various functions and pathways, including cell adhesion, leukocyte migration, extracellular matrix organization, extracellular region, collagen trimer, membrane raft, fibronectin-binding, integrin binding, protein digestion, and absorption, and focal adhesion. Among these DEGs, 12 hub genes with high degrees of connectivity were selected. Survival analysis showed that the hub genes (HMMR, CEP55, CDK1, UHRF1, ASPM, RAD51AP1, DLGAP5, KIF11, SHCBP1, PBK, and HMGB2) may be involved in the tumorigenesis and development of PDA, highlighting their potential as diagnostic and therapeutic factors in PDA. CONCLUSIONS: In summary, the DEGs and hub genes identified in the present study not only contribute to a better understanding of the molecular mechanisms underlying the carcinogenesis and progression of PDA but may also serve as potential new biomarkers and targets for PDA.

Identification of Transcription Factor/Gene Axis in Colon Cancer Using a Methylome Approach.

Colon cancer is one of the most commonly diagnosed cancers worldwide. Both environmental and molecular characters can influence its development. DNA methylation has been heralded as a promising marker for use in cancer prevention, diagnosis, and treatment. It has been shown to facilitate cancer progression through multiple mechanisms. Changes in DNA methylation can inhibit or promote the binding of transcription factors (TFs) and further disturb gene regulation. Detection of DNA methylation-mediated regulatory events in colon cancer are critical for mining novel biomarkers. Here, we explore the influence of CpG sites located at promoter regions of differentially expressed genes and identify methylation-gene relationships using expression-methylation quantitative trait loci. We find that promoter methylation sites mainly negatively regulate the corresponding genes. We also identify candidate TFs that can bind to these sites in a sequence-dependent manner. By integrating transcriptome and methylome profiles, we construct a TF-CpG-gene regulatory network for colon cancer, which is used to determine the roles of TFs and methylation in the transcription process. Finally, based on TF-CpG-gene relationships, we design a framework to evaluate patient prognosis, which shows that one TF-CpG-gene triplet is significantly associated with patient survival rate and represents a potential novel biomarker for use in colon cancer prognosis and treatment.