[Construction and Evaluation of a Prognostic Risk Prediction Model of Pancreatic Ductal Adenocarcinoma Based on Immune-Related Genes].

Objective To construct a risk prediction model by integrating the molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) and immune-related genes.Methods With GSE71729 data set (n=145) as the training set,the differentially expressed genes and differential immune-related genes between the squamous and non-squamous subtypes of PDAC were integrated to construct a regulatory network,on the basis of which five immune marker genes regulating the squamous subtype were screened out.An integrated immune score (IIS) model was constructed based on patient survival information and immune marker genes to predict the clinical prognosis of PDAC patients,and its predictive performance was tested with 5 validation sets (n=758).Results PDAC patients were assigned into high risk and low risk groups according to the IIS.In both training and validation sets,the overall survival of patients in the high risk group was shorter than that in the low risk group (both P<0.001).The multivariable Cox regression showed that IIS was an independent prognostic factor for PDAC (HR=2.16,95%CI=1.50-3.10,P<0.001).Conclusion IIS can be used for risk stratification of PDAC patients and may become a potential prognostic marker for PDAC.

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.

Andrographolide induces protective autophagy and targeting DJ-1 triggers reactive oxygen species-induced cell death in pancreatic cancer.

Background: Andrographolide (Andro), an extract of Andrographis paniculate (Burm.f.) Wall. ex Nees (Acanthaceae), possesses diverse biologically active properties. However, the precise mechanisms and effects of Andro on pancreatic cancer (PC) remain unclear. Methods: The cytotoxic potential of Andro and underlying mechanism towards PC cells was investigated through in vitro experiments and a xenograft mouse model. PC cells were first subjected to varying concentrations of Andro. The reactive oxygen species (ROS) was assessed using flow cytometry and DCFH-DA staining. The apoptosis rate was detected by flow cytometry. Additionally, western blot was applied to evaluate the expression levels of cleaved-caspase-3, DJ-1, LC3-I, LC3-II, and p62. To further elucidate the involvement of ROS accumulation and autophagy, we employed N-acetylcysteine as a scavenger of ROS and 3-Methyladenine as an inhibitor of autophagy. Results: Andro demonstrated potent anti-proliferative effects on PC cells and induced apoptosis, both in vitro and in vivo. The cytotoxicity of Andro on PC cells was counteracted by DJ-1 overexpression. The reduction in DJ-1 expression caused by Andro led to ROS accumulation, subsequently inhibiting the growth of PC cells. Furthermore, Andro stimulated cytoprotective autophagy, thus weakening the antitumor effect. Pharmacological blockade of autophagy further enhanced the antitumor efficacy of Andro. Conclusion: Our study indicated that ROS accumulation induced by the DJ-1 reduction played a key role in Andro-mediated PC cell inhibition. Furthermore, the protective autophagy induced by the Andro in PC cells is a mechanism that needs to be addressed in future studies.

Close relationship between mediators of inflammation and pancreatic cancer: Our experience.

In this editorial, we focus specifically on the mechanisms by which pancreatic inflammation affects pancreatic cancer. Cancer of the pancreas remains one of the deadliest cancer types. The highest incidence and mortality rates of pancreatic cancer are found in developed countries. Trends of pancreatic cancer incidence and mortality vary considerably worldwide. A better understanding of the etiology and identification of the risk factors is essential for the primary prevention of this disease. Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche. In this editorial, we highlight the foundational studies that have driven our understanding of these processes. In our experimental center, we have carefully studied the mechanisms of that link pancreatic inflammation and pancreatic cancer. We focused on the role of mast cells (MCs). MCs contain pro-angiogenic factors, including tryptase, that are associated with increased angiogenesis in various tumors. In this editorial, we address the role of MCs in angiogenesis in both pancreatic ductal adenocarcinoma tissue and adjacent normal tissue. The assessment includes the density of c-Kit receptor-positive MCs, the density of tryptase-positive MCs, the area of tryptase-positive MCs, and angiogenesis in terms of microvascularization density.

Sequential therapy of refractory metastatic pancreatic cancer with 5-FU/LV/irinotecan (FOLFIRI) vs. 5-FU/LV/oxaliplatin (OFF). The PANTHEON trial (AIO PAK 0116).

PURPOSE: In patients with metastatic pancreatic cancer, after failure of gemcitabine/nab-paclitaxel, this trial compares the efficacy of second-line therapy with FOLFIRI vs. OFF (1:1 randomisation) with cross-over to the vice-versa regimen as third-line therapy. PATIENTS AND METHODS: The primary endpoint was PFS (progression-free survival: time from randomization until progression or death) of second-line therapy. The trial aimed to demonstrate non-inferiority of FOLFIRI vs OFF (non-inferiority margin of a hazard ratio (HR) of 1.5, power of 80% and a significance level of 5%, 196 events needed). Secondary endpoints included overall survival (OS), progression-free survival of third-line therapy and safety. The trial is registered with EudraCT Nr. 2016-004640-11. RESULTS: The trial was terminated with 60 evaluable (37 with FOLFIRI, 23 with OFF) patients due to insufficient recruitment. PFS of second-line therapy was 2.4 (95% CI 2.3-2.6) months with FOLFIRI vs 2.4 (95% CI 2.2-2.7) months with OFF (HR: 0.80, 95% CI 0.45-1.42, P = 0.43). OS was comparable between the arms (HR: 0.95, 95% CI 0.54-1.66), P = 0.84). Only 4 out of 28 (14%) patients receiving third-line therapy achieved a disease control (partial remission or stable disease). Both second-line regimens were well tolerated without new or unexpected safety signals being observed. CONCLUSION: The exploratory analysis of this early terminated trial suggests that FOLFIRI and OFF have similar efficacy ant toxicity as second-line therapy of PDAC after failure of gemcitabine/nab-paclitaxel. Third-line therapy regardless of regimen does not provide satisfactory efficacy in this sequential treatment algorithm.

Combining single-cell and bulk RNA sequencing, NK cell marker genes reveal a prognostic and immune status in pancreatic ductal adenocarcinoma.

The NK cell is an important component of the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC), also plays a significant role in PDAC development. This study aimed to explore the relationship between NK cell marker genes and prognosis, immune response of PDAC patients. By scRNA-seq data, we found the proportion of NK cells were significantly downregulated in PDAC and 373 NK cell marker genes were screened out. By TCGA database, we enrolled 7 NK cell marker genes to construct the signature for predicting prognosis in PDAC patients. Cox analysis identified the signature as an independent factor for pancreatic cancer. Subsequently, the predictive power of signature was validated by 6 GEO datasets and had an excellent evaluation. Our analysis of relationship between the signature and patients' immune status revealed that the signature has a strong correlation with immunocyte infiltration, inflammatory reaction, immune checkpoint inhibitors (ICIs) response. The NK cell marker genes are closely related to the prognosis and immune capacity of PDAC patients, and they have potential value as a therapeutic target.

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.

Malignancy and mass-forming phenotypes of IgG4-related disease: a challenging diagnosis.

Mass-forming phenotypes of IgG4-related disease (IgG4-RD) mimic malignancy and histological confirmation can be challenging. A woman in her 70s with HIV infection presented with painless obstructive jaundice and weight loss. Magnetic resonance imaging was suggestive of unresectable cholangiocarcinoma. Tumour markers and serum IgG4 were normal. Percutaneous liver biopsy was consistent with IgG4-RD inflammatory pseudotumour, with complete response to glucocorticoid therapy. Two years later, a new episode of obstructive jaundice occurred, with CT showing a solid lesion in the head of the pancreas with double duct sign and encasement of the portal vein. Re-induction therapy was tried without response. Fine-needle biopsy was consistent with pancreatic cancer. Supportive care was offered and the patient died 8 months later, with no signs of disease progression on subsequent imaging. We discuss the challenges of IgG4-RD diagnosis and treatment and the differential diagnosis between mass-forming phenotypes and malignancy, highlighting the difficulties in managing such patients.

A prognostic model for anoikis-related genes in pancreatic cancer.

Anoikis, a distinct form of programmed cell death, is crucial for both organismal development and maintaining tissue equilibrium. Its role extends to the proliferation and progression of cancer cells. This study aimed to establish an anoikis-related prognostic model to predict the prognosis of pancreatic cancer (PC) patients. Gene expression data and patient clinical profiles were sourced from The Cancer Genome Atlas (TCGA-PAAD: Pancreatic Adenocarcinoma) and the International Cancer Genome Consortium (ICGC-PACA: Pancreatic Ductal Adenocarcinoma). Non-cancerous pancreatic tissue gene expression data were obtained from the Genotype-Tissue Expression (GTEx) project. The R package was used to construct anoikis-related PC prognostic models, which were later validated with the ICGC-PACA database. Survival analyses demonstrated a poorer prognosis for patients in the high-risk group, consistent across both TCGA-PAAD and ICGC-PACA datasets. A nomogram was designed as a predictive tool to estimate patient mortality. The study also analyzed tumor mutations and immune infiltration across various risk groups, uncovering notable differences in tumor mutation patterns and immune landscapes between high- and low-risk groups. In conclusion, this research successfully developed a prognostic model centered on anoikis-related genes, offering a novel tool for predicting the clinical trajectory of PC patients.

Alterations of the bile microbiome is associated with progression-free survival in pancreatic ductal adenocarcinoma patients.

BACKGROUND: Patients with pancreatic ductal adenocarcinoma (PDAC) display an altered oral, gastrointestinal, and intra-pancreatic microbiome compared to healthy individuals. However, knowledge regarding the bile microbiome and its potential impact on progression-free survival in PDACs remains limited. METHODS: Patients with PDAC (n = 45), including 20 matched pairs before and after surgery, and benign controls (n = 16) were included prospectively. The characteristics of the microbiomes of the total 81 bile were revealed by 16  S-rRNA gene sequencing. PDAC patients were divided into distinct groups based on tumor marker levels, disease staging, before and after surgery, as well as progression free survival (PFS) for further analysis. Disease diagnostic model was formulated utilizing the random forest algorithm. RESULTS: PDAC patients harbor a unique and diverse bile microbiome (PCoA, weighted Unifrac, p = 0.038), and the increasing microbial diversity is correlated with dysbiosis according to key microbes and microbial functions. Aliihoeflea emerged as the genus displaying the most significant alteration among two groups (p < 0.01). Significant differences were found in beta diversity of the bile microbiome between long-term PFS and short-term PFS groups (PCoA, weighted Unifrac, p = 0.005). Bacillota and Actinomycetota were identified as altered phylum between two groups associated with progression-free survival in all PDAC patients. Additionally, we identified three biomarkers as the most suitable set for the random forest model, which indicated a significantly elevated likelihood of disease occurrence in the PDAC group (p < 0.0001). The area under the receiver operating characteristic (ROC) curve reached 80.8% with a 95% confidence interval ranging from 55.0 to 100%. Due to the scarcity of bile samples, we were unable to conduct further external verification. CONCLUSION: PDAC is characterized by an altered microbiome of bile ducts. Biliary dysbiosis is linked with progression-free survival in all PDACs. This study revealed the alteration of the bile microbiome in PDACs and successfully developed a diagnostic model for PDAC.

Temporally resolved proteomics identifies nidogen-2 as a cotarget in pancreatic cancer that modulates fibrosis and therapy response.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by increasing fibrosis, which can enhance tumor progression and spread. Here, we undertook an unbiased temporal assessment of the matrisome of the highly metastatic KPC (Pdx1-Cre, LSL-KrasG12D/+, LSL-Trp53R172H/+) and poorly metastatic KPflC (Pdx1-Cre, LSL-KrasG12D/+, Trp53fl/+) genetically engineered mouse models of pancreatic cancer using mass spectrometry proteomics. Our assessment at early-, mid-, and late-stage disease reveals an increased abundance of nidogen-2 (NID2) in the KPC model compared to KPflC, with further validation showing that NID2 is primarily expressed by cancer-associated fibroblasts (CAFs). Using biomechanical assessments, second harmonic generation imaging, and birefringence analysis, we show that NID2 reduction by CRISPR interference (CRISPRi) in CAFs reduces stiffness and matrix remodeling in three-dimensional models, leading to impaired cancer cell invasion. Intravital imaging revealed improved vascular patency in live NID2-depleted tumors, with enhanced response to gemcitabine/Abraxane. In orthotopic models, NID2 CRISPRi tumors had less liver metastasis and increased survival, highlighting NID2 as a potential PDAC cotarget.

Bifocal solid pseudopapillary tumour of the pancreas.

Solid pseudopapillary neoplasm of the pancreas (SPNP) is a rare entity. In this study, we present a woman in her 20's who presented for evaluation of two separate pancreatic masses. On imaging and biopsy, the tail lesion was thought to be a neuroendocrine tumour and the body lesion was thought to be a metastatic lymph node. The patient was brought to the operating room and underwent a distal pancreatectomy and splenectomy. The patient had an uneventful postoperative course and was discharged home on postoperative day 4. Pathology confirmed both masses were consistent with the diagnosis of well-differentiated SPNP with no signs of malignancy including lymphovascular or perineural invasion, or lymph node involvement.

Establishment and characterization of a novel multidrug-resistant pancreatic ductal adenocarcinoma cell line, PDAC-X1.

Drug resistance remains a significant challenge in the treatment of pancreatic cancer. The development of drug-resistant cell lines is crucial to understanding the underlying mechanisms of resistance and developing novel drugs to improve clinical outcomes. Here, a novel pancreatic cancer cell line, PDAC-X1, derived from Chinese patients has been established. PDAC-X1 was characterized by the immune phenotype, biology, genetics, molecular characteristics, and tumorigenicity. In vitro analysis revealed that PDAC-X1 cells exhibited epithelial morphology and cell markers (CK7 and CK19), expressed cancer-associated markers (E-cadherin, Vimentin, Ki-67, CEA, CA19-9), and produced pancreatic cancer-like organs in suspension culture. In vivo analysis showed that PDAC-X1 cells maintained tumorigenicity with a 100% tumor formation rate. This cell line exhibited a complex karyotype, dominated by subtriploid karyotypes. In addition, PDAC-X1 cells exhibited intrinsic multidrug resistance to multiple drugs, including gemcitabine, paclitaxel, 5-fluorouracil, and oxaliplatin. In conclusion, the PDAC-X1 cell line has been established and characterized, representing a useful and valuable preclinical model to study the underlying mechanisms of drug resistance and develop novel drug therapeutics to improve patient outcomes.

Targeted delivery of CEBPA-saRNA for the treatment of pancreatic ductal adenocarcinoma by transferrin receptor aptamer decorated tetrahedral framework nucleic acid.

Pancreatic cancer, predominantly pancreatic ductal adenocarcinoma (PDAC), remains a highly lethal malignancy with limited therapeutic options and a dismal prognosis. By targeting the underlying molecular abnormalities responsible for PDAC development and progression, gene therapy offers a promising strategy to overcome the challenges posed by conventional radiotherapy and chemotherapy. This study sought to explore the therapeutic potential of small activating RNAs (saRNAs) specifically targeting the CCAAT/enhancer-binding protein alpha (CEBPA) gene in PDAC. To overcome the challenges associated with saRNA delivery, tetrahedral framework nucleic acids (tFNAs) were rationally engineered as nanocarriers. These tFNAs were further functionalized with a truncated transferrin receptor aptamer (tTR14) to enhance targeting specificity for PDAC cells. The constructed tFNA-based saRNA formulation demonstrated exceptional stability, efficient saRNA release ability, substantial cellular uptake, biocompatibility, and nontoxicity. In vitro experiments revealed successful intracellular delivery of CEBPA-saRNA utilizing tTR14-decorated tFNA nanocarriers, resulting in significant activation of tumor suppressor genes, namely, CEBPA and its downstream effector P21, leading to notable inhibition of PDAC cell proliferation. Moreover, in a mouse model of PDAC, the tTR14-decorated tFNA-mediated delivery of CEBPA-saRNA effectively upregulated the expression of the CEBPA and P21 genes, consequently suppressing tumor growth. These compelling findings highlight the potential utility of saRNA delivered via a designed tFNA nanocarrier to induce the activation of tumor suppressor genes as an innovative therapeutic approach for PDAC.

Development of human pancreatic cancer avatars as a model for dynamic immune landscape profiling and personalized therapy.

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, a disease with dismal overall survival. Advances in treatment are hindered by a lack of preclinical models. Here, we show how a personalized organotypic "avatar" created from resected tissue allows spatial and temporal reporting on a complete in situ tumor microenvironment and mirrors clinical responses. Our perfusion culture method extends tumor slice viability, maintaining stable tumor content, metabolism, stromal composition, and immune cell populations for 12 days. Using multiplexed immunofluorescence and spatial transcriptomics, we identify immune neighborhoods and potential for immunotherapy. We used avatars to assess the impact of a preclinically validated metabolic therapy and show recovery of stromal and immune phenotypes and tumor redifferentiation. To determine clinical relevance, we monitored avatar response to gemcitabine treatment and identify a patient avatar-predictable response from clinical follow-up. Thus, avatars provide valuable information for syngeneic testing of therapeutics and a truly personalized therapeutic assessment platform for patients.

Identification of immune- and oxidative stress-related signature genes as potential targets for mRNA vaccines for pancreatic cancer patients.

Adenocarcinoma of the pancreas (PAAD) is one of the deadliest malignant tumors, and messenger ribonucleic acid vaccines, which constitute the latest generation of vaccine technology, are expected to lead to new ideas for the treatment of pancreatic cancer. The Cancer Genome Atlas-PAAD and Genotype-Tissue Expression data were merged and analyzed. Weighted gene coexpression network analysis was used to identify gene modules associated with tumor mutational burden among the genes related to both immunity and oxidative stress. Differentially expressed immune-related oxidative stress genes were screened via univariate Cox regression analysis, and these genes were analyzed via nonnegative matrix factorization. After immune infiltration analysis, least absolute shrinkage and selection operator regression combined with Cox regression was used to construct the model, and the usefulness of the model was predicted based on the receiver operating characteristic curve and decision curve analysis curves after model construction. Finally, metabolic pathway enrichment was analyzed using gene set enrichment analysis combined with Kyoto Encyclopedia of Genes and Genomes and gene ontology biological process analyses. This model consisting of the ERAP2, mesenchymal-epithelial transition factor (MET), CXCL9, and angiotensinogen (AGT) genes can be used to help predict the prognosis of pancreatic cancer patients more accurately than existing models. ERAP2 is involved in immune activation and is important in cancer immune evasion. MET binds to hepatocyte growth factor, leading to the dimerization and phosphorylation of c-MET. This activates various signaling pathways, including MAPK and PI3K, to regulate the proliferation, invasion, and migration of cancer cells. CXCL9 overexpression is associated with a poor patient prognosis and reduces the number of CD8 + cytotoxic T lymphocytes in the PAAD tumor microenvironment. AGT is cleaved by the renin enzyme to produce angiotensin 1, and AGT-converting enzyme cleaves angiotensin 1 to produce angiotensin 2. Exposure to AGT-converting enzyme inhibitors after pancreatic cancer diagnosis is associated with improved survival. The 4 genes identified in the present study - ERAP2, MET, CXCL9, and AGT - are expected to serve as targets for messenger ribonucleic acid vaccine development and need to be further investigated in depth.