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.

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.

A phase-I study of second-line S-IROX for unresectable pancreatic cancer after gemcitabine plus nab-paclitaxel failure.

Gemcitabine plus nab-paclitaxel (GnP) and FOLFIRINOX are widely used as first-line regimens for unresectable pancreatic cancer (PC). When GnP therapy is selected, considering patient age or condition, second-line FOLFIRINOX is sometimes difficult to administer owing to its toxicity. This study aimed to determine the recommended dose (RD) of S-IROX (S-1, oxaliplatin, and irinotecan combination) regimens in patients with unresectable PC after first-line GnP failure. This phase-I study used the "3 + 3" dose-escalation design with two dose levels. Patients who failed first-line GnP therapy for unresectable PC were enrolled. Oxaliplatin and irinotecan were administered on day 1, and S-1 was administered orally twice daily on days 1-7, followed by 7 days of rest. The primary endpoints were dose-limiting toxicities (DLTs) and determination of RD. The secondary endpoint was the evaluation of potential antitumor activity. Nine patients received the second-line S-IROX regimen. In level-0 (S-1, 80 mg/m2; oxaliplatin, 85 mg/m2; and irinotecan, 120 mg/m2), no patient experienced DLT; however, one patient experienced grade 3 neutropenia. At level-1 (irinotecan increased to 150 mg/m2), one of six patients experienced DLTs, including G3 diarrhea. The RD was confirmed at the level-1 dose. The response rate, disease control rate, median progression-free survival, and median overall survival were 33.3%, 77.8%, 172 (range:77-422) days, and 414 (101-685) days, respectively. One patient underwent surgery after the second-line S-IROX therapy. Second-line S-IROX treatment was deemed acceptable. The RD was set at level-1 dose (S-1, 80 mg/m2; oxaliplatin, 85 mg/m2; and irinotecan, 150 mg/m2).

Cancer-Derived Immunoglobulin G and Pancreatic Cancer.

Immunoglobulin (Ig) is traditionally believed to be produced solely by B cells. Nonetheless, mounting evidence has demonstrated that various types of Igs are extensively expressed in many cell types. Among them, IgG is found to be highly expressed in cancer cells and is thus labeled as cancer-derived IgG. Cancer-derived IgG shares identical fundamental structures with B cell-derived IgG, but displays several unique characteristics, including restricted variable region sequences and unique glycosylation modifications for those expressed by epithelial cancers. Cancer-derived IgG plays multiple crucial roles in carcinogenesis, including facilitating cancer invasion and metastasis, enhancing cancer stemness, contributing to chemoresistance, and remodeling the tumour microenvironment. Recent studies have discovered that cancer-derived sialylated IgG (SIA-IgG) is extensively expressed in pancreatic cancer cells and is predominantly located in the cytoplasm and on the cell membrane. Cancer-derived IgG expressed by pancreatic cancer presents a restrictive variable region sequence and contains a unique sialylation site of the Fab region. Functionally, cancer-derived IgG participates in pancreatic cancer progression via different mechanisms, such as promoting proliferation, facilitating migration and invasion, resisting apoptosis, inducing inflammation, and modulating the tumour microenvironment. SIA-IgG has shown potential as a clinical biomarker. The expression of SIA-IgG is associated with poor tumour differentiation, metastasis, and chemoresistance in pancreatic cancer. High expression of SIA-IgG can serve as an independent prognostic factor for pancreatic cancer. Additionally, SIA-IgG expression elevated with malignant progression for the precursor lesions of pancreatic cancer. These findings present a prospect of applying cancer-derived IgG as a novel diagnostic and therapeutic target in the management of pancreatic cancer, and aiding in overcoming the challenge in the treatment of this stubborn malignancy.

A powerful machine learning approach to identify interactions of differentially abundant gut microbial subsets in patients with metastatic and non-metastatic pancreatic cancer.

Pancreatic cancer has a dismal prognosis, as it is often diagnosed at stage IV of the disease and is characterized by metastatic spread. Gut microbiota and its metabolites have been suggested to influence the metastatic spread by modulating the host immune system or by promoting angiogenesis. To date, the gut microbial profiles of metastatic and non-metastatic patients need to be explored. Taking advantage of the 16S metagenomic sequencing and the PEnalized LOgistic Regression Analysis (PELORA) we identified clusters of bacteria with differential abundances between metastatic and non-metastatic patients. An overall increase in Gram-negative bacteria in metastatic patients compared to non-metastatic ones was identified using this method. Furthermore, to gain more insight into how gut microbes can predict metastases, a machine learning approach (iterative Random Forest) was performed. Iterative Random Forest analysis revealed which microorganisms were characterized by a different level of relative abundance between metastatic and non-metastatic patients and established a functional relationship between the relative abundance and the probability of having metastases. At the species level, the following bacteria were found to have the highest discriminatory power: Anaerostipes hadrus, Coprobacter secundus, Clostridium sp. 619, Roseburia inulinivorans, Porphyromonas and Odoribacter at the genus level, and Rhodospirillaceae, Clostridiaceae and Peptococcaceae at the family level. Finally, these data were intertwined with those from a metabolomics analysis on fecal samples of patients with or without metastasis to better understand the role of gut microbiota in the metastatic process. Artificial intelligence has been applied in different areas of the medical field. Translating its application in the field of gut microbiota analysis may help fully exploit the potential information contained in such a large amount of data aiming to open up new supportive areas of intervention in the management of cancer.

Comparative immune profiling of pancreatic ductal adenocarcinoma progression among South African patients.

BACKGROUND: Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive cancer characterized by an immunosuppressive microenvironment. Patients from specific ethnicities and population groups have poorer prognoses than others. Therefore, a better understanding of the immune landscape in such groups is necessary for disease elucidation, predicting patient outcomes and therapeutic targeting. This study investigated the expression of circulating key immune cell markers in South African PDAC patients of African ancestry. METHODS: Blood samples were obtained from a total of 6 healthy volunteers (HC), 6 Chronic Pancreatitis (CP) and 34 PDAC patients consisting of 22 resectable (RPC), 8 locally advanced (LAPC) and 4 metastatic (MPC). Real-time Quantitative Polymerase Chain reactions (RT-qPCR), Metabolomics, Enzyme-Linked Immunosorbent Assay (ELISA), Reactive Oxygen Species (ROS), and Immunophenotyping assays were conducted. Statistical analysis was conducted in R (v 4.3.2). Additional analysis of single-cell RNA data from 20 patients (16 PDAC and 4 controls) was conducted to interrogate the distribution of T-cell and Natural Killer cell populations. RESULTS: Granulocyte and neutrophil levels were significantly elevated while lymphocytes decreased with PDAC severity. The total percentages of CD3 T-cell subpopulations (helper and double negative T-cells) decreased when compared to HC. Although both NK (p = 0.014) and NKT (p < 0.001) cell levels increased as the disease progressed, their subsets: NK CD56dimCD16- (p = 0.024) and NKTs CD56+ (p = 0.008) cell levels reduced significantly. Of note is the negative association of NK CD56dimCD16- (p < 0.001) cell levels with survival time. The gene expression analyses showed no statistically significant correlation when comparing the PDAC groups with the controls. The inflammatory status of PDAC was assessed by ROS levels of serum which were elevated in CP (p = 0.025), (RPC (p = 0.003) and LAPC (p = 0.008)) while no significant change was observed in MPC, compared to the HC group. ROS was shown to be positively correlated with GlycA (R = 0.45, p = 0.0096). Single-cell analyses showed a significant difference in the ratio of NKT cells per total cell counts in LAPC (p < 0.001) and MPC (p < 0.001) groups compared with HC, confirming observations in our sample group. CONCLUSION: The expression of these immune cell markers observed in this pilot study provides insight into their potential roles in tumour progression in the patient group and suggests their potential utility in the development of immunotherapeutic strategies.

Pancreatic carcinoma, its variants and precursors: Overview of the current WHO classification.

Pancreatic carcinoma is a relatively common malignant tumor with increasing incidence and mortality. The tumor is usually diagnosed at an advanced stage and generally has a poor prognosis, with only 5% of patients surviving 5 years from the time of diagnosis. The stage of the disease at the time of diagnosis is a crucial factor for the prognosis; 25% of patients with localized tumors survive 3 years from diagnosis, compared to only 1% of those with generalized tumors. Radical surgical removal of the tumor (partial or total pancreatectomy) is a key factor in improving survival. Therefore, the topic is highly relevant to surgeons. Statistics on pancreatic carcinoma mainly focus on ductal adenocarcinoma, which is the most common and least favorable malignant tumor of the pancreas. This review focuses on ductal adenocarcinoma, its variants, and precancerous lesions. The article summarizes information from the latest WHO classification of 2019, which was released 11 years after the previous edition. Compared to the previous version, this new WHO classification introduced rather minor changes in the field of ductal adenocarcinoma. The delineation of rare variants of ductal adenocarcinoma is justified based on genetic and morphological similarities and clinical relevance, as individual subtypes significantly differ in prognosis. The article also includes a description of macroscopic and microscopic precursors of ductal adenocarcinoma and their definitions. Genetic and immunohistochemical differential diagnostic aspects are briefly discussed, as these are more relevant to pathologists than to surgeons.