Pancreatic ductal adenocarcinoma (PDAC) manifests diverse molecular subtypes, including the classical/progenitor and basal-like/squamous subtypes, with the latter known for its aggressiveness. We employed integrative transcriptome and metabolome analyses to identify potential genes contributing to the molecular subtype differentiation and its metabolic features. Our comprehensive analysis revealed that adrenoceptor alpha 2A (ADRA2A) was downregulated in the basal-like/squamous subtype, suggesting its potential role as a candidate suppressor of this subtype. Reduced ADRA2A expression was significantly associated with a high frequency of lymph node metastasis, higher pathological grade, advanced disease stage, and decreased survival among PDAC patients. In vitro experiments demonstrated that ADRA2A transgene expression and ADRA2A agonist inhibited PDAC cell invasion. Additionally, ADRA2A-high condition downregulated the basal-like/squamous gene expression signature, while upregulating the classical/progenitor gene expression signature in our PDAC patient cohort and PDAC cell lines. Metabolome analysis conducted on the PDAC cohort and cell lines revealed that elevated ADRA2A levels were associated with suppressed amino acid and carnitine/acylcarnitine metabolism, which are characteristic metabolic profiles of the classical/progenitor subtype. Collectively, our findings suggest that heightened ADRA2A expression induces transcriptome and metabolome characteristics indicative of classical/progenitor subtype with decreased disease aggressiveness in PDAC patients. These observations introduce ADRA2A as a candidate for diagnostic and therapeutic targeting in PDAC.

UNASSIGNED: Pancreatic ductal adenocarcinoma (PDAC) is 3rd most lethal cancer in the USA leading to a median survival of six months and less than 5% 5-year overall survival (OS). As the only potentially curative treatment, surgical resection is not suitable for up to 90% of the patients with PDAC due to late diagnosis. Highly fibrotic PDAC with an immunosuppressive tumor microenvironment restricts cytotoxic T lymphocyte (CTL) infiltration and functions causing limited success with systemic therapies like dendritic cell (DC)-based immunotherapy. In this study, we investigated the potential benefits of irreversible electroporation (IRE) ablation therapy in combination with DC vaccine therapy against PDAC.
UNASSIGNED: We performed a literature search to identify studies focused on DC vaccine therapy and IRE ablation to boost therapeutic response against PDAC indexed in PubMed, Web of Science, and Scopus until February 20th, 2023.
UNASSIGNED: IRE ablation destructs tumor structure while preserving extracellular matrix and blood vessels facilitating local inflammation. The studies demonstrated IRE ablation reduces tumor fibrosis and promotes CTL tumor infiltration to PDAC tumors in addition to boosting immune response in rodent models. The administration of the DC vaccine following IRE ablation synergistically enhances therapeutic response and extends OS rates compared to the use of DC vaccination or IRE alone. Moreover, the implementation of data-driven approaches further allows dynamic and longitudinal monitoring of therapeutic response and OS following IRE plus DC vaccine immunoablation.
UNASSIGNED: The combination of IRE ablation and DC vaccine immunotherapy is a potent strategy to enhance the therapeutic outcomes in patients with PDAC.

UNASSIGNED: Assessing the perioperative outcomes of pancreaticoduodenectomy (PD) based solely on individual complications is not comprehensive, and the association between perioperative outcomes and the long-term prognosis of individuals diagnosed with pancreatic ductal adenocarcinoma (PDAC) remains uncertain. Our study is designed to evaluate the impact of a novel composite indicator, textbook outcomes (TO), on the long-term prognosis of patients undergoing PD for PDAC.
UNASSIGNED: This study conducted a retrospective analysis of 139 patients who underwent PD for pathologically confirmed PDAC at our hospital between January 2018 and December 2021. After applying exclusion criteria, a total of 111 patients were included in the subsequent analysis. These patients were categorized into two groups: the non-TO group (n=42) and the TO group (n=69). The Kaplan-Meier survival curve was employed to describe the relationship between TO and disease-free survival (DFS) and overall survival (OS). Cox regression was employed to assess the impact of achieving TO on long-term survival. Logistic regression was employed to investigate the risk factors affecting the achievement of TO.
UNASSIGNED: Out of the 111 PDAC patients, 69 (62.2%) achieved TO following PD. The achievement of TO significantly improved the OS of PDAC patients [P=0.03; hazard ratio (HR) =0.60; 95% confidence interval (CI): 0.37-0.83]. Cox regression analysis indicated that achieving TO was a protective factor for OS (P=0.04; HR =4.08; 95% CI: 1.07-15.61). Logistic regression analysis indicated that high amylase in drainage fluid on the third day after surgery (>1,300 U/L) was detrimental to achieve TO [odds ratio (OR) =0.10; 95% CI: 0.02-0.58; P=0.01], longer surgery durations (≥6.25 hours) was detrimental to achieve TO (OR =0.19; 95% CI: 0.06-0.54; P=0.002), and soft pancreatic texture was detrimental to achieve TO (OR =0.31; 95% CI: 0.10-0.93, P=0.04).
UNASSIGNED: Achievement of TO significantly improves the OS of PDAC patients and has the potential to serve as a robust prognostic indicator. Looking ahead, it is highly necessary for TO to become a standard surgical quality control measure in hospitals.

The gut microbiome plays a significant role in the pathogenesis of pancreatic ductal adenocarcinoma (PDAC), influencing oncogenesis, immune responses, and treatment outcomes. Studies have identified microbial species like Porphyromonas gingivalis and Fusobacterium nucleatum, that promote PDAC progression through various mechanisms. Additionally, the gut microbiome affects immune cell activation and response to immunotherapy, including immune checkpoint inhibitors and CAR-T therapy. Specific microbes and their metabolites play a significant role in the effectiveness of immune checkpoint inhibitors (ICIs). Alterations in the gut microbiome can either enhance or diminish responses to PD-1/PD-L1 and CTLA-4 blockade therapy. Additionally, bacterial metabolites like trimethylamine N-oxide (TMAO) and lipopolysaccharide (LPS) impact antitumor immunity, offering potential targets to augment immunotherapy responses. Modulating the microbiome through fecal microbiota transplantation, probiotics, prebiotics, dietary changes, and antibiotics shows promise in PDAC treatment, although outcomes are highly variable. Dietary modifications, particularly high-fiber diets and specific fat consumption, influence microbiome composition and impact cancer risk. Combining microbiome-based therapies with existing treatments holds potential for improving PDAC therapy outcomes, but further research is needed to optimize their effectiveness.

Pancreatic ductal adenocarcinoma (PDAC) is reported to be amongst the cancers with the lowest survival rate at 5 years. In the present study we aimed to validate a targeted next-generation sequencing (tNGS) panel to use in clinical routine, investigating genes important for PDAC diagnostic, prognostic and potential theragnostic aspect. In this NGS panel we also designed target regions to inquire about loss of heterozygosity (LOH) of chromosome 18 that has been described to be possibly linked to a worse disease progression. Copy number alteration has also been explored for a subset of genes. The last two methods are not commonly used for routine diagnostic with tNGS panels and we investigated their possible contribution to better characterize PDAC. A series of 140 formalin-fixed paraffin-embedded (FFPE) PDAC samples from 140 patients was characterized using this panel. Ninety-two % of patients showed alterations in at least one of the investigated genes (most frequent KRAS, TP53, SMAD4, CDKN2A and RNF43). Regarding LOH evaluation, we were able to detect chr18 LOH starting at 20% cell tumor percentage. The presence of LOH on chr18 is associated with a worse disease- and metastasis-free survival, in uni- and multivariate analyses. The present study validates the use of a tNGS panel for PDAC characterization, also evaluating chr18 LOH status for prognostic stratification.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer characterized by late diagnosis, rapid progression, and a high mortality rate. Its complex biology, characterized by a dense, stromal tumor environment with an immunosuppressive milieu, contributes to resistance against standard treatments like chemotherapy and radiation. This comprehensive review explores the dynamic role of the microbiome in modulating chemotherapy efficacy and outcomes in PDAC. It delves into the microbiome\'s impact on drug metabolism and resistance, and the interaction between microbial elements, drugs, and human biology. We also highlight the significance of specific bacterial species and microbial enzymes in influencing drug action and the immune response in the tumor microenvironment. Cutting-edge methodologies, including artificial intelligence, low-biomass microbiome analysis and patient-derived organoid models, are discussed, offering insights into the nuanced interactions between microbes and cancer cells. The potential of microbiome-based interventions as adjuncts to conventional PDAC treatments are discussed, paving the way for personalized therapy approaches. This review synthesizes recent research to provide an in-depth understanding of how the microbiome affects chemotherapy efficacy. It focuses on elucidating key mechanisms and identifying existing knowledge gaps. Addressing these gaps is crucial for enhancing personalized medicine and refining cancer treatment strategies, ultimately improving patient outcomes.

UNASSIGNED: There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete regional LN dissection can lead to postoperative recurrence, while blind expansion of the scope of regional LN dissection significantly increases the perioperative risk without significantly prolonging overall survival. We aimed to establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) to predict the probability of regional LN metastasis in patients with PDAC.
UNASSIGNED: A total of 163 regional LNs were reviewed and divided into a metastatic cohort (n=58 LNs) and nonmetastatic cohort (n=105 LNs). The DLCT quantitative parameters and the nodal ratio of the longest axis to the shortest axis (L/S) of the regional LNs were compared between the two cohorts. The DLCT quantitative parameters included the iodine concentration in the arterial phase (APIC), normalized iodine concentration in the arterial phase (APNIC), effective atomic number in the arterial phase (APZeff), normalized effective atomic number in the arterial phase (APNZeff), slope of the spectral attenuation curves in the arterial phase (APλHU), iodine concentration in the portal venous phase (PVPIC), normalized iodine concentration in the portal venous phase (PVPNIC), effective atomic number in the portal venous phase (PVPZeff), normalized effective atomic number in the portal venous phase (PVPNZeff), and slope of the spectral attenuation curves in the portal venous phase (PVPλHU). Logistic regression analysis based on area under the curve (AUC) was used to analyze the diagnostic performance of significant DLCT quantitative parameters, L/S, and the models combining significant DLCT quantitative parameters and L/S. A nomogram based on the models with highest diagnostic performance was developed as a predictor. The goodness of fit and clinical applicability of the nomogram were assessed through calibration curve and decision curve analysis (DCA).
UNASSIGNED: The combined model of APNIC + L/S (APNIC + L/S) had the highest diagnostic performance among all models, yielding an AUC, sensitivity, and specificity of 0.878 [95% confidence interval (CI): 0.825-0.931], 0.707, and 0.886, respectively. The calibration curve indicated that the APNIC-L/S nomogram had good agreement between the predicted probability and the actual probability. Meanwhile, the decision curve indicated that the APNIC-L/S nomogram could produce a greater net benefit than could the all- or-no-intervention strategy, with threshold probabilities ranging from 0.0 to 0.75.
UNASSIGNED: As a valid and visual noninvasive prediction tool, the APNIC-L/S nomogram demonstrated favorable predictive efficacy for identifying metastatic LNs in patients with PDAC.

UNASSIGNED: Due to a lack of early diagnosis methods and effective drugs, pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis. DNA methylation, transcriptome expression and gene copy number variation (CNV) have critical relationships with development and progression of various diseases. The purpose of the study was to screen reliable early diagnostic biomarkers and potential drugs based on integrative multiomics analysis.
UNASSIGNED: We used methylation, transcriptome and CNV profiles to build a diagnostic model for PDAC. The protein expression of three model-related genes were externally validated using PDAC samples. Then, potential therapeutic drugs for PDAC were identified by interaction information related to existing drugs and genes.
UNASSIGNED: Four significant differentially methylated regions (DMRs) were selected from 589 common DMRs to build a high-performance diagnostic model for PDAC. Then, four hub genes, PHF12, FXYD3, PRKCB and ZNF582, were obtained. The external validation results showed that PHF12, FXYD3 and PRKCB protein expression levels were all upregulated in tumor tissues compared with adjacent normal tissues (P<0.05). Promising candidate drugs with activity against PDAC were screened and repurposed through gene expression analysis of online datasets. The five drugs, including topotecan, PD-0325901, panobinostat, paclitaxel and 17-AAG, with the highest activity among 27 PDAC cell lines were filtered.
UNASSIGNED: Overall, the diagnostic model built based on four significant DMRs could accurately distinguish tumor and normal tissues. The five drug candidates might be repurposed as promising therapeutics for particular PDAC patients.

UNASSIGNED: Pancreatic ductal adenocarcinoma (PDAC), which accounts for the vast majority of pancreatic cancer (PC), is a highly aggressive malignancy with a dismal prognosis. Age is shown to be an independent factor affecting survival outcomes in patients with PDAC. Our study aimed to identify prognostic factors and construct a nomogram to predict survival in PDAC patients aged ≥60 years.
UNASSIGNED: Data of PDAC patients aged ≥60 years were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate Cox regression analysis was used to determined prognostic factors of overall survival (OS) and cancer-specific survival (CSS), and two nomograms were constructed and validated by calibration plots, concordance index (C-index) and decision curve analysis (DCA). Additionally, 432 patients from the First Affiliated Hospital of Wenzhou Medical University were included as an external cohort. Kaplan-Meier curves were applied to further verify the clinical validity of the nomograms.
UNASSIGNED: Ten independent prognostic factors were identified to establish the nomograms. The C-indexes of the training and validation groups based on the OS nomogram were 0.759 and 0.760, higher than those of the tumor-node-metastasis (TNM) staging system (0.638 and 0.636, respectively). Calibration curves showed high consistency between predictions and observations. Better area under the receiver operator characteristic (ROC) curve (AUC) values and DCA were also obtained compared to the TNM system. The risk stratification based on the nomogram could distinguish patients with different survival risks.
UNASSIGNED: We constructed and externally validated a population-based survival-predicting nomogram for PDAC patients aged ≥60 years. The new model could help clinicians personalize survival prediction and risk assessment.

This review comprehensively investigates the intricate interplay between small non-coding RNAs (sncRNAs) and pancreatic ductal adenocarcinoma (PDAC), a devastating malignancy with limited therapeutic options. Our analysis reveals the pivotal roles of sncRNAs in various facets of PDAC biology, spanning diagnosis, pathogenesis, drug resistance, and therapeutic strategies. sncRNAs have emerged as promising biomarkers for PDAC, demonstrating distinct expression profiles in diseased tissues. sncRNA differential expression patterns, often detectable in bodily fluids, hold potential for early and minimally invasive diagnostic approaches. Furthermore, sncRNAs exhibit intricate involvement in PDAC pathogenesis, regulating critical cellular processes such as proliferation, apoptosis, and metastasis. Additionally, mechanistic insights into sncRNA-mediated pathogenic pathways illuminate novel therapeutic targets and interventions. A significant focus of this review is dedicated to unraveling sncRNA mechanisms underlying drug resistance in PDAC. Understanding these mechanisms at the molecular level is imperative for devising strategies to overcome drug resistance. Exploring the therapeutic landscape, we discuss the potential of sncRNAs as therapeutic agents themselves as their ability to modulate gene expression with high specificity renders them attractive candidates for targeted therapy. In summary, this review integrates current knowledge on sncRNAs in PDAC, offering a holistic perspective on their diagnostic, pathogenic, and therapeutic relevance. By elucidating the roles of sncRNAs in PDAC biology, this review provides valuable insights for the development of novel diagnostic tools and targeted therapeutic approaches, crucial for improving the prognosis of PDAC patients.