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 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.

UNASSIGNED: Advancements in surgical techniques have improved outcomes in patients undergoing pancreatic surgery. To date there have been no meta-analyses comparing robotic and laparoscopic approaches for distal pancreatectomies (DP) in patients with pancreatic adenocarcinoma (PDAC). This systematic review and network meta-analysis aims to explore the oncological outcomes of laparoscopic distal pancreatectomy (LDP), robotic distal pancreatectomy (RDP) and open distal pancreatectomy (ODP).
UNASSIGNED: A systematic search was conducted for studies reporting laparoscopic, robotic or open surgery for DP. Frequentist network meta-analysis of oncological outcomes (overall survival, resection margins, tumor recurrence, examined lymph nodes, administration of adjuvant therapy) were performed.
UNASSIGNED: Fifteen studies totalling 9,301 patients were included in the network meta-analysis. 1,946, 605 and 6,750 patients underwent LDP, RDP and ODP respectively. LDP (HR: 0.761, 95% CI: 0.642-0.901, p = 0.002) and RDP (HR: 0.757, 95% CI: 0.617-0.928, p = 0.008) were associated with overall survival (OS) benefit when compared to ODP. LDP (HR: 1.00, 95% CI: 0.793-1.27, p = 0.968) was not associated with OS benefit when compared to RDP. There were no significant differences between LDP, RDP and ODP for resection margins, tumor recurrence, examined lymph nodes and administration of adjuvant therapy.
UNASSIGNED: This study highlights the longer OS in both LDP and RDP when compared to ODP for patients with PDAC.
UNASSIGNED: https://www.crd.york.ac.uk/, PROSPERO (CRD42022336417).

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its challenging early diagnosis, high malignancy, and resistance to chemotherapy drugs, the treatment of pancreatic cancer has long been exceedingly difficult in the realm of oncology. γ-Glutamyl cyclotransferase (GGCT), a vital enzyme in glutathione metabolism, has been implicated in the proliferation and progression of several tumor types, while the biological function of GGCT in pancreatic ductal adenocarcinoma remains unknown.
METHODS: The expression profile of GGCT was validated through western blotting, immunohistochemistry, and RT-qPCR in both pancreatic cancer tissue samples and cell lines. Functional enrichment analyses including GSVA, ssGSEA, GO, and KEGG were conducted to explore the biological role of GGCT. Additionally, CCK8, Edu, colony formation, migration, and invasion assays were employed to evaluate the impact of GGCT on the proliferation and migration abilities of pancreatic cancer cells. Furthermore, the LASSO machine learning algorithm was utilized to develop a prognostic model associated with GGCT.
RESULTS: Our study revealed heightened expression of GGCT in pancreatic cancer tissues and cells, suggesting an association with poorer patient prognosis. Additionally, we explored the immunomodulatory effects of GGCT in both pan-cancer and pancreatic cancer contexts, found that GGCT may be associated with immunosuppressive regulation in various types of tumors. Specifically, in patients with high expression of GGCT in pancreatic cancer, there is a reduction in the infiltration of various immune cells, leading to poorer responsiveness to immunotherapy and worse survival rates. In vivo and in vitro assays indicate that downregulation of GGCT markedly suppresses the proliferation and metastasis of pancreatic cancer cells. Moreover, this inhibitory effect appears to be linked to the regulation of GGCT on c-Myc. A prognostic model was constructed based on genes derived from GGCT, demonstrating robust predictive ability for favorable survival prognosis and response to immunotherapy.

Macropinocytosis is a cellular process that enables cells to engulf extracellular material, such as nutrients, growth factors, and even whole cells. It is involved in several physiological functions as well as pathological conditions. In cancer cells, macropinocytosis plays a crucial role in promoting tumor growth and survival under nutrient-limited conditions. In particular KRAS mutations have been identified as main drivers of macropinocytosis in pancreatic, breast, and non-small cell lung cancers. We performed a high-content screening to identify inhibitors of macropinocytosis in pancreatic ductal adenocarcinoma (PDAC)-derived cells, aiming to prevent nutrient scavenging of PDAC tumors. The screening campaign was conducted in a well-known pancreatic KRAS-mutated cell line (MIAPaCa-2) cultured under nutrient deprivation and using FITC-dextran to precisely quantify macropinocytosis. We assembled a collection of 3584 small molecules, including drugs approved by the Food and Drug Administration (FDA), drug-like molecules against molecular targets, kinase-targeted compounds, and molecules designed to hamper protein-protein interactions. We identified 28 molecules that inhibited macropinocytosis, with potency ranging from 0.4 to 29.9 μM (EC50). A few of them interfered with other endocytic pathways, while 11 compounds did not and were therefore considered specific \"bona fide\" macropinocytosis inhibitors and further characterized. Four compounds (Ivermectin, Tyrphostin A9, LY2090314, and Pyrvinium Pamoate) selectively hampered nutrient scavenging in KRAS-mutated cancer cells. Their ability to impair albumin-dependent proliferation was replicated both in different 2D cell culture systems and 3D organotypic models. These findings provide a new set of compounds specifically targeting macropinocytosis, which could have therapeutic applications in cancer and infectious diseases.