Pancreatic Cancer: Changing Epidemiology and New Approaches to Risk Assessment, Early Detection, and Prevention

LUNETR: Language-Infused UNETR for precise pancreatic tumor segmentation in 3D medical image

The identification of early micro-lesions and adjacent blood vessels in CT scans plays a pivotal role in the clinical diagnosis of pancreatic cancer, considering its aggressive nature and high fatality rate. Despite the widespread application of deep learning methods for this task, several challenges persist: (1) the complex background environment in abdominal CT scans complicates the accurate localization of potential micro-tumors; (2) the subtle contrast between micro-lesions within pancreatic tissue and the surrounding tissues makes it challenging for models to capture these features accurately; and (3) tumors that invade adjacent blood vessels pose significant barriers to surgical procedures. To address these challenges, we propose LUNETR (Language-Infused UNETR), an advanced multimodal encoder model that combines textual and image information for precise medical image segmentation. The integration of an autoencoding language model with cross-attention enabling our model to effectively leverage semantic associations between textual and image data, thereby facilitating precise localization of potential pancreatic micro-tumors. Additionally, we designed a Multi-scale Aggregation Attention (MSAA) module to comprehensively capture both spatial and channel characteristics of global multi-scale image data, enhancing the model's capacity to extract features from micro-lesions embedded within pancreatic tissue. Furthermore, in order to facilitate precise segmentation of pancreatic tumors and nearby blood vessels and address the scarcity of multimodal medical datasets, we collaborated with Zhuzhou Central Hospital to construct a multimodal dataset comprising CT images and corresponding pathology reports from 135 pancreatic cancer patients. Our experimental results surpass current state-of-the-art models, with the incorporation of the semantic encoder improving the average Dice score for pancreatic tumor segmentation by 2.23 %. For the Medical Segmentation Decathlon (MSD) liver and lung cancer datasets, our model achieved an average Dice score improvement of 4.31 % and 3.67 %, respectively, demonstrating the efficacy of the LUNETR.

Radiomics-based histological grading of pancreatic ductal adenocarcinoma using 18F-FDG PET/CT: A two-center study

OBJECTIVE

To explore the value of radiomics features derived from 18F-FDG PET/CT images in predicting the histological grade of pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

A retrospective analysis was conducted using data from patients with suspected pancreatic cancer, who histologically confirmed as PDAC within 14 days after 18F-FDG PET/CT scan in one of two hospitals. Tumors were divided into high-grade (undifferentiated or poorly differentiated), and low-grade (moderately or well differentiated). Two researchers independently used uRP to perform layer-by-layer tumor segmentation in both PET and CT images of each patient, and extract features. Model performance was evaluated using 5-fold cross-validation on the entire multi-center cohort, with results averaged across all folds. The least absolute shrinkage and selection was used for feature selection, and support vector machine (SVM), random forest (RF), and logistic regression (LR) were employed to distinguish the grade of PDAC. The performance of the model was evaluated using the receiver operating characteristic curve.

RESULTS

This study comprised 111 patients (72 males and 39 females), comprising 52 patients with high-grade PDAC tumors and 59 patients with low-grade. A series of models were established by SVM, LR, and RF algorithms based on selected features. In the test set, the mean areas under the curve (AUCs) for PET image-based models using SVM, LR, and RF algorithms were 0.773, 0.772, and 0.760. For CT-based models, the mean AUCs were 0.764, 0.770, and 0.576. For PET/CT-based models, the mean AUCs were 0.840, 0.844, and 0.773.

CONCLUSION

Despite the lack of external validation, the PET/CT-derived radiomics model enables accurate preoperative histological grading of PDAC, offering a clinically actionable tool to neoadjuvant therapy stratification and further guide personalized medical decision-making.

Concurrent pancreatic ductal adenocarcinoma and poorly differentiated neuroendocrine carcinoma: A case report and review of the literature

INTRODUCTION

Concurrent pancreatic ductal adenocarcinoma (PDAC) and poorly differentiated neuroendocrine carcinoma (NEC) is a rare condition. This simultaneous occurrence poses significant diagnostic and therapeutic challenges due to the unique characteristics and treatment protocols of each cancer. An accurate diagnosis is crucial to optimizing treatment outcomes and prognosis.

PRESENTATION OF CASE

We present a case of a 55-year-old male with type 2 diabetes and psoriatic arthritis, referred for an elevated serum CA 19-9 level found during a check-up. Imaging studies, including CT and EUS, revealed a 6 cm mass in the pancreatic head. EUS-guided biopsy confirmed PDAC. After a Whipple procedure, pathology showed concurrent poorly differentiated NEC with a 30 % neuroendocrine component. After surgery, the patient received gemcitabine-based chemotherapy and was disease-free at six months post-surgery.

DISCUSSION

This case illustrates the diagnostic intricacy of simultaneous PDAC and poorly differentiated NEC. Effective management in such scenarios benefits from a collaborative approach among surgeons, oncologists, and pathologists. Due to the limited number of documented cases, there is insufficient evidence to inform the best treatment strategies, particularly concerning the most effective chemotherapy options. This case adds to the growing body of literature on rare concurrent pancreatic tumors and highlights the need for further research to enhance understanding and develop comprehensive clinical guidelines.

CONCLUSION

The combination of PDAC and poorly differentiated NEC poses unique diagnostic and treatment challenges. This case underscores the importance of a multidisciplinary approach and calls for further research to develop evidence-based management protocols for these rare malignancies.

The lncRNA ST18-AS1 suppresses pancreatic cancer progression by enhancing ST18 mRNA stability through anchoring FUS in the cytoplasm

Pancreatic ductal adenocarcinoma (PDAC) is associated with a high mortality rate and short survival time. Long noncoding RNAs (lncRNAs) play a significant role in the progression of PDAC. However, prognostic lncRNAs associated with overall survival (OS) in patients with PDAC remain elusive. RNA sequencing was used to identify differential lncRNA expression between short-term and long-term PDAC patients. We identified a novel lncRNA (ENSG00000253924), termed ST18-AS1 (ST18-associated lncRNA), that is highly expressed in the tissues of long-term PDAC patients. High ST18-AS1 expression was correlated with favorable clinical outcomes, and the upregulation of ST18-AS1 expression in PDAC cell lines suppressed cell proliferation and promoted apoptosis both in vivo and in vitro. The key downstream target regulated by ST18-AS1 was Suppression of tumorigenicity 18 (ST18). We also found that ST18 expression was lower in PDAC tissues compared to non-tumorous adjacent tissues (NATs) and that higher ST18 expression was correlated with better clinical outcomes. Accordingly, the forced expression of ST18 inhibited proliferation and promoted apoptosis in tumor cells. Mechanistic studies showed that ST18-AS1 maintained the stability of ST18 mRNA by binding to Fused in sarcoma (FUS) and anchoring FUS in the cytoplasm. Overall, we identified ST18-AS1 as a novel biomarker that inhibits PDAC cell proliferation and promotes PDAC cell apoptosis through ST18. Targeting ST18-AS1/ST18 may be a potential therapeutic strategy for treating PDAC.

Development and validation of a nomogram model based on ultrasound and contrast-enhanced ultrasound features for differentiating mass-forming pancreatitis and pancreatic ductal adenocarcinoma

PURPOSE

To explore the value of ultrasound (US) and contrast-enhanced ultrasound (CEUS) in differentiating mass-forming Pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC).

METHODS

This retrospective study analyzed clinical and imaging data from 281 patients who underwent pancreatic CEUS between January 2018 and December 2023. Patients were randomly divided into training (n = 196) and validation (n = 85) sets. Logistic regression analyses were conducted to identify independent predictive imaging features for differentiating PDAC from MFP in the training set. Based on the identified predictors, two nomogram models were constructed: the US model and the US + CEUS model. The diagnostic performance of both models was assessed via the area under the receiver operating characteristic curve (AUC), calibration plots, Hosmer-Lemeshow test, and decision-curve analysis (DCA).

RESULTS

Multivariate logistic regression analysis based on these factors identified taller-than-wide shape (P = 0.002, OR = 0.12), calcification (P = 0.003, OR = 13.76), and washout pattern (P = 0.002, OR = 0.13) as independent predictive factors for distinguishing PDAC from MFP. Compared to the US model, the US + CEUS model demonstrated better performance with AUC values 0.930 (95% CI: 0.895-0.965) in the training set and 0.914 (95% CI: 0.853-0.976) in the validation set. Calibration curve plots and the Hosmer-Lemeshow test (P > 0.05) confirmed that the model has good calibration, and DAC showed significant clinical benefit.

CONCLUSION

The nomogram model constructed using taller-than-wide shape, calcification, and washout pattern demonstrated excellent discriminative ability, accuracy, and clinical utility in differentiating PDAC from MFP.

Engineering Pt Single-Atom Doped SeS2/Ti3CNTx MXene with Molecularly Imprinted Polymer for Precision Pancreatic Cancer Diagnostics: DFT and Molecular Dynamics Perspectives

Cyclophilin-B (CypB) is overexpressed in pancreatic cancer, thus, the potential screening of CypB in biofluids and tissue samples may boost the identification of early-stage pancreatic cancer. A novel strategy of CypB detection utilizing the molecularly imprinted polymer platform, comprising higher binding affinity exhibiting cavities against the CypB protein was developed. Specifically, a nanocatalyst consisting of Pt single atom (Ptsa)-doped selenium disulfide (SeS2)/Ti3CNTx MXene nanocomposite is designed. The sluggish diffusion of Ptsa caused by the highest migration energy barrier of 6.39 eV unveils exceptionally high stability (2.89 ×1088 d (300 K) and 1.053 × 1024 d (750 K)) with (SeS2)/Ti3CNTx surface. The Ptsa boosted charge transfer kinetics paves the improved performance of the CypB sensor, while SeS2/Ti3CNTx supports the stable current density overall. The system establishes a dynamic linear range from 0.12 to 250 nm of CypB detection which correlates with the physiological existence of the CypB in human biofluids and tissues and the excellent detection limit of 80 pm. The liquid chromatography integrated mass spectrometer investigation warranted the significant enhancement of CypB associates with the progression of pancreatic cancer.

Modulating immune cells within pancreatic ductal adenocarcinoma via nanomedicine

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by a dense extracellular matrix (ECM) and a uniquely immunosuppressive tumor microenvironment (TME), which together form a formidable barrier that hinders deep drug penetration, limiting the efficacy of conventional therapies and leading to poor patient outcomes. Nanocarrier technology emerges as a promising strategy to improve treatment efficacy in PDAC. Nanocarriers can not only improve drug penetration through their adjustable physicochemical properties but also effectively regulate immune cell function in pancreatic cancer TME and promote anti-tumor immune response. This mini-review discusses the effects of nanocarriers on the immune microenvironment of PDAC, analyzing their mechanisms in modulating immune cells, overcoming ECM barriers, and reshaping the TME.

Discovery of homocamptothecin derivative TOP-0618 as a radiosensitive agent for the treatment of pancreatic cancer

BACKGROUND

Pancreatic cancer is one of the most lethal malignancies characterized by a complex tumor microenvironment (TME) and highly heterogeneous nature, making it resistant to radiotherapy. This study aims to evaluate the radiosensitizing effect of homocamptothecin derivative TOP-0618 on pancreatic cancer.

METHODS

Clonogenic assays and cell viability assays were used to evaluate the radiosensitizing effects of TOP-0618 on pancreatic cancer cells. Cell cycle and apoptosis were detected using flow cytometry. A pancreatic bi-flank xenograft tumor model was used to evaluate the radiosensitivity of TOP-0618. H&E staining analyses and TUNEL staining were used to examine necrosis and apoptosis of pancreatic xenograft tumors.

RESULTS

Cytotoxicity assays revealed that IC50 values of TOP-0618 against PANC-1 and MIAPaCa-2 cells were 1.442 µmol/L and 1.198 µmol /L, respectively. Additionally, clonogenic assays revealed that TOP-0618 exerted radiosensitizing effects on both pancreatic cells, and the sensitizer enhancement ratio (SER) of TOP-0618 was 1.14 for the PANC-1 cell line and 1.65 for the MIAPaCa-2 cell line. The preliminary study revealed that TOP-0618 improved radiosensitivity by enhancing G2/M phase arrest and increasing the apoptosis of pancreatic cells. Subsequently, in a pancreatic bi-flank xenograft tumor model, TOP-0618 combined with irradiation significantly inhibited tumor growth, and increased necrosis and apoptosis in pancreatic xenograft tumors.

CONCLUSIONS

Our work demonstrates the radiosensitizing effect of homocamptothecin derivative TOP-0618 on pancreatic cancer both in vivo and vitro, and lays a foundation for clinical transformation.

Global Epidemiology of Early-Onset Digestive System Malignancy: A Systematic Analysis for the Global Burden of Disease Study 2021

BACKGROUND AND AIM

The researches on the global burden of digestive system malignancy in young populations were limited. This study aimed to comprehensively investigate the burden of early-onset digestive system malignancy (often defined as cancers diagnosed below the age of 50) based on the Global Burden of Disease 2021.

METHODS

Data of incidence, prevalence, deaths, disability-adjusted life years (DALYs), and risk factors for the five major early-onset digestive system malignancies, including early-onset esophageal cancer (EOEC), early-onset gastric cancer (EOGC), early-onset liver cancer (EOLC), early-onset pancreatic cancer (EOPC), and early-onset colorectal cancer (EOCRC), were extracted from GBD 2021. The average annual percent change (AAPC) was calculated using joinpoint regression analysis. The Bayesian age-period-cohort (BAPC) model was utilized to predict the burden up to 2030.

RESULTS

From 1990 to 2021, the age-standardized incidence rate (ASIR) of early-onset digestive system malignancies, except for EOCRC (AAPC, 0.37), showed a decreasing pattern. Meanwhile, the age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) of early-onset digestive system malignancy presented a downward trend. Notably, high-middle sociodemographic index (SDI) countries experienced higher disease burdens. Dietary risk factors, tobacco, alcohol consumption, and metabolic factors were the main risk factors. The ASIR of EOEC and EOCRC was projected to increase in 2030, whereas the trend for EOGC, EOLC, and EOPC was projected to decrease.

CONCLUSIONS

Early-onset digestive system malignancy presented notable heterogeneity across gender, geography, and cancer types. This emphasizes the urgency of addressing the public health challenge of early-onset digestive system malignancy.

The Role of Nanoparticles in Therapy of Real-World Patients with Pancreatic Cancer: A Scoping Review

Pancreatic cancer (PC) is one of the most aggressive and fatal malignancies worldwide, posing a significant global health challenge due to its high mortality rates, late-stage diagnosis, and limited therapeutic efficacy [...].

Self-emulsifying Nano-PND oral delivery systems of PND1186: In silico modeling for bioavailability estimation

Focal adhesion kinase (FAK) inhibitors have proven to aid the therapeutic potential of anti-cancer agents. PND1186 (PND) is a FAK inhibitor disrupting the oncogenic processes such as cell survival, proliferation, adhesion, migration and angiogenesis, as well as remodeling of tumor microenvironment. However, the pharmacological potential of PND is limited by its poor solubility and bioavailability due to rapid precipitation of weakly basic PND in the intestinal milieu. As a solution, we have developed a self-nanoemulsifying PND oral delivery system (NanoPODS) for rapid dissolution of PND while Soluplus containing system (NanoPODS-S) was prepared to prevent the precipitation of PND. Optimized NanoPODS-S depicted a particle size of 107.0 ± 3.6 nm, PDI of 0.223 ± 0.016, and a surface potential of -4.2 ± 0.007 mV, along with > 70% PND released at pH 6.8. In silico pharmacokinetics predicted 99% oral bioavailability for NanoPODS-S. This study evaluates the efficacy of NanoPODS and NanoPODS-S for improved oral bioavailability with better cytotoxicity efficacy on Pancreatic Ductal Adenocarcinoma (PDAC) cell lines. NanoPODS-S is the first of its kind, self-nanoemulsifying system containing a polymeric precipitation inhibitor mimicking a "spring-parachute effect". It will be a novel platform technology for rapid and enhanced dissolution of poorly soluble molecules.

HSPB1/KDM1 A facilitates ANXA2 expression via hypomethylated DNA promoter to inhibit ferroptosis and enhance gemcitabine resistance in pancreatic cancer

Chemotherapy resistance contributes to the unsatisfied prognosis in pancreatic cancer (PC) patients. Heat shock protein beta-1 (HSPB1) plays a tumor promoting role in PC by inhibiting ferroptosis. This study aims to explore whether high expression of HSPB1 was responsible for ferroptosis and gemcitabine (GEM) resistance in PC. Here, we found that HSPB1 was upregulated in GEM-resistant PC cells and tumor tissues, as confirmed by RT-qPCR and Western blotting assays. Knockdown of HSPB1 enhanced GEM sensitivity, decreased the abilities of proliferation and invasion, and promoted apoptosis in GEM-resistant PC cells. Utilizing commercial kits, HSPB1 inhibition triggered ferroptosis, as indicated by increased levels of reactive oxygen species, malondialdehyde, and Fe2+, along with reduced glutathione (GSH) levels. Furthermore, the methylation specific PCR (MSP) results demonstrated a significant decrease in the methylation level of annexin A2 (ANXA2) CpG. The Chromatin immunoprecipitation (ChIP), ChIP-Re-ChIP, and Co-IP experiments revealed that HSPB1 interacts with lysine-specific histone demethylase 1A (KDM1A), recruiting KDM1A-CoREST complex to the ANXA2 promoter to enhance ANXA2 expression through demethylation of H3K9me2. Additionally, ANXA2 depletion further inhibited cell proliferation and invasion and induced ferroptosis in KDM1A-silenced cells, whereas ANXA2 overexpression produced the opposite effects. Finally, HSPB1 overexpression reduced gemcitabine sensitivity by promoting tumor growth in nude mice. Altogether, HSPB1 promoted ANXA2 expression by facilitating H3K9me2 demethylation through the recruitment of KDM1A-CoREST complex to the ANXA2 promoter, thereby inhibiting ferroptosis and enhancing GEM resistance in PC. These data provided a new insight for overcoming GEM-resistant PC.

Reversing VTN deficiency inhibits the progression of pancreatic cancer and enhances sensitivity to anti-PD1 immunotherapy

Background

Pancreatic cancer, a highly lethal malignancy with limited therapeutic options, necessitates the identification of novel prognostic biomarkers and therapeutic targets. The extracellular matrix protein vitronectin (VTN) has been implicated in tumor progression, but its specific role in pancreatic cancer progression and immunotherapy response remains unclear.

Methods

This study employed an integrative approach combining single-cell RNA sequencing, analysis of public databases, and functional assays. In vitro experiments assessed the impact of VTN knockdown and overexpression on pancreatic cancer cell proliferation, invasion, and migration. Mechanistic investigations explored associations between VTN expression and immune regulatory factors. A syngeneic mouse subcutaneous tumor model evaluated the therapeutic efficacy of VTN overexpression combined with anti-PD1 immunotherapy.

Results

VTN was significantly downregulated in pancreatic cancer tissues compared to normal tissues. Lower VTN levels correlated with poorer overall survival. VTN knockdown promoted pancreatic cancer cell proliferation, invasion, and migration in vitro, whereas VTN overexpression suppressed these phenotypes. VTN expression was linked to immune regulatory pathways. High VTN levels predicted improved survival in patients receiving anti-PD1/PD-L1 therapy. In a mouse model, VTN overexpression inhibited tumor growth and synergized with anti-PD1 therapy to enhance antitumor efficacy, suggesting combinatorial therapeutic potential.

Conclusions

This study identifies VTN as a dual-functional regulator in pancreatic cancer, acting as both a suppressor of tumor progression and a modulator of immunotherapy response. These findings position VTN as a prognostic biomarker and a therapeutic target to sensitize pancreatic tumors to anti-PD1-based immunotherapy, providing a potential strategy for overcoming treatment resistance in this aggressive malignancy.

Comparative study of the anti-tumour effects of the imipridone, ONC201 and its fluorinated analogues on pancreatic cancer cell line

Pancreatic ductal adenocarcinoma has a high mortality rate, with a 5-year survival rate of ~ 12%. Therefore, developing new targeted therapies is urgently needed. ONC-201, a promising candidate, is currently undergoing clinical trials. The main objective of the present work is to investigate the anti-tumour activity of ONC-201 and its two fluorinated analogues (TBP-134, TBP-135). The viability of two pancreatic adenocarcinoma cell lines (PANC-1, MIA PaCa-2) and three other tumour cell lines (A2058, EBC-1, COLO-205) was assessed after 72-hour treatment with drugs at 0.5, 10, and 25 µM. Significant antiproliferative effects were observed, with 0.5 µM TBP-134 achieving the highest potency, reducing cell viability to approximately 50%. None of the molecules exhibited significant cytotoxicity toward normal human dermal fibroblast cells or cardiomyocytes, indicating a selective anti-tumour profile. The analogues showed more effective results than ONC201 on PANC-1 cells (IC50: 0.35 and 1.8 µM vs. IC50: 6.1 µM, respectively). All analogues induced G2/M phase arrest followed by apoptosis in PANC-1 cells. The site of the fluorination influenced the mechanism of apoptotic action of these compounds. Overall, TBP-134 showed superior efficacy, making it a promising candidate for structural optimization within the imipridone family to develop more effective, selective treatments for pancreatic tumours.

PSMD14 Transcriptionally Activated by MEF2A Promotes Pancreatic Cancer Development by Upregulating SPON2 Expression

Proteasome 26S subunit non-ATPase 14 (PSMD14) plays a pro-carcinogenic role in various cancers. However, its specific effects and mechanisms in pancreatic cancer (PC) remain unclear. We aimed to assess the function and mechanism of PSMD14 in PC. Fifteen paired pancreatic ductal adenocarcinoma (PDAC) tissues and adjacent non-tumorous tissues were clinically obtained. Cell proliferation, migration, and invasion were assessed using colony formation, scratch, and Transwell assays. The interaction between the MEF2A transcription factor and the PSMD14 promoter verified by chromatin immunoprecipitation (ChIP) or dual luciferase assay. The interaction between RBM15B and SPON2 mRNA was validated by RNA immunoprecipitation (RIP) assay. The interaction between the proteins PSMD14 and RBM15B was detected by co-immunoprecipitation (Co-IP) assay. The m6A level of SPON2 was detected by methylated RNA immunoprecipitation (MeRIP, a common method for detecting m6A levels of mRNAs). The ubiquitination level of RNA-binding motif protein 15B (RBM15B) was detected using Co-IP. The role of PSMD14 in PC was further explored subcutaneous and lung metastasis models. PSMD14 was upregulated in PDAC tissues. PSMD14 knockdown inhibited PC cell viability, proliferation, migration, and invasion. MEF2A transcriptionally activated PSMD14 expression. PSMD14 knockdown promoted the ubiquitination degradation of RBM15B. Additionally, PSMD14 enhanced SPON2 mRNA stability through RBM15B-mediated m6A modification. SPON2 overexpression impaired the effect of knockdown PSMD14. Finally, PSMD14 knockdown in PC arrested tumor growth and lung metastasis. PSMD14, transcriptionally activated by MEF2A, promotes the de-ubiquitination of RBM15B, which upregulates SPON2 expression in an m6A-RBM15B-dependent manner, thereby facilitating PC proliferation, migration, and invasion.

Molecular structure and mechanism of protein MSMB, TPPP3, SPI1: Construction of novel 4 pancreatic cancer-related protein signatures model based on machine learning

The high mortality rate of pancreatic cancer is closely related to its inconspicuous early symptoms and difficult diagnosis. In recent years, with the rapid development of proteomics and bioinformatics, the use of machine learning technology to analyze protein characteristics provides a new idea for the early diagnosis and treatment of pancreatic cancer. The main purpose of this study is to deeply analyze the molecular mechanism and action mechanism of MSMB, TPPP3 and SPI1, which are closely related to pancreatic cancer, by constructing a feature model based on machine learning. The study collected a large number of proteomic data from pancreatic cancer patients and screened out candidate proteins associated with pancreatic cancer. Then the molecular characteristics of MSMB, TPPP3 and SPI1 were analyzed by bioinformatics tools. On this basis, machine learning algorithms were used to model the expression patterns and functions of these proteins. The accuracy and generalization ability of the model were verified by cross-validation and independent test sets, and finally a feature model that effectively distinguished pancreatic cancer from normal tissue was determined. Through the construction and verification of the machine learning model, we found that the expression patterns of MSMB, TPPP3 and SPI1 proteins in pancreatic cancer tissues were significantly different. The expression of MSMB protein is down-regulated in pancreatic cancer tissue, while the expression of TPPP3 and SPI1 protein is up-regulated. Further functional analysis indicated that MSMB may be involved in the development of pancreatic cancer through regulation of cell cycle and apoptosis, TPPP3 may be related to cytoskeleton stability and cell migration ability, and SPI1 may play an important role in immune escape of pancreatic cancer. These findings provide new insights into the molecular mechanisms of pancreatic cancer.

Comprehensive analysis of SQOR involvement in ferroptosis resistance of pancreatic ductal adenocarcinoma in hypoxic environments

Introduction

Pancreatic ductal adenocarcinoma (PDAC) exhibits higher hypoxia level than most solid tumors, and the presence of intratumoral hypoxia is associated with a poor prognosis. However, the identification of hypoxia levels based on pathological images, and the mechanisms regulating ferroptosis resistance, remain to be elucidated. The objective of this study was to construct a deep learning model to evaluate the hypoxia characteristics of PDAC and to explore the role of Sulfide quinone oxidoreductase (SQOR) in hypoxia-mediated ferroptosis resistance.

Methods

Multi-omics data were integrated to analyze the correlation between hypoxia score of PDAC, SQOR expression and prognosis, and ferroptosis resistance level. A deep learning model of Whole Slide Images (WSIs) were constructed to predict the hypoxia level of patients. In vitro hypoxia cell models, SQOR knockdown experiments and nude mouse xenograft models were used to verify the regulatory function of SQOR on ferroptosis.

Results

PDAC exhibited significantly higher hypoxia levels than normal tissues, correlating with reduced overall survival in patients. In slide level, our deep learning model can effectively identify PDAC hypoxia levels with good performance. SQOR was upregulated in tumor tissues and positively associated with both hypoxia score and ferroptosis resistance. SQOR promotes the malignant progression of PDAC in hypoxic environment by enhancing the resistance of tumor cells to ferroptosis. SQOR knockdown resulted in decreased cell viability, decreased migration ability and increased MDA level under hypoxic Ersatin induced conditions. Furthermore, SQOR inhibitor in combination with ferroptosis inducer has the potential to inhibit tumor growth in vivo in a synergistic manner.

Discussion

This study has established a hypoxia detection model of PDAC based on WSIs, providing a new tool for clinical evaluation. The study revealed a new mechanism of SQOR mediating ferroptosis resistance under hypoxia and provided a basis for targeted therapy.

Machine learning‑based construction of damage‑associated molecular patterns related score identifies subtypes of pancreatic adenocarcinoma with distinct prognosis

The present study aimed to assess the prognostic significance of Damage-Associated Molecular Pattern (DAMP)-related gene expression in pancreatic adenocarcinoma (PAAD) and to develop a scoring system based on these genes. Consensus clustering was performed on patients with PAAD using data from The Cancer Genome Atlas (TCGA) and Meta-cohort datasets, identifying three distinct clusters: C1 (pro-DAMP), C2 (intermediate) and C3 (anti-DAMP). Differential gene expression analysis between clusters C1 and C3 identified 141 significant genes. Least Absolute Shrinkage and Selection Operator Cox regression was utilized to derive an optimal predictor set, leading to the identification of six hub genes associated with the DAMP status, which were then employed to calculate the DAMPscore. Weighted Gene Co-expression Network Analysis revealed a strong correlation between these eight hub genes and the DAMPscore. The functionality of these hub genes in PAAD was validated using a Cell Counting Kit-8 assay and Transwell assays. The results indicated that patients with PAAD with elevated DAMPscores exhibited significantly reduced survival times. Receiver operating characteristic (ROC) curve analysis indicated that the DAMPscore has robust prognostic capabilities. In the Meta-cohort, the area under the ROC curve (AUC) values for the DAMPscore to predict overall survival at 1, 3 and 5 years were 0.65, 0.70 and 0.77, respectively, while the AUC values for the TCGA-PAAD cohort were 0.71, 0.73 and 0.72, respectively. Additional cohorts, such as E-MTAB-6134 and ICGC-AU, corroborated the predictive power of the DAMPscore. A comparison of the DAMPscore with other prognostic models revealed that it consistently exhibited a superior C-index across most PAAD cohorts. Furthermore, in vitro experiments demonstrated that PLEK2, a hub gene related to the DAMPscore, is involved in critical biological processes such as cell proliferation, migration and invasion. In conclusion, the DAMPscore is a promising prognostic biomarker for PAAD, surpassing traditional models in various datasets. This study emphasizes the role of DAMP-related pathways in influencing tumor biology and highlights the importance of immune modulation in PAAD prognosis, suggesting that therapeutic strategies targeting DAMP signaling could improve patient outcomes.

Early-Stage Pancreatic Cancer Diagnosis: Serum Biomarkers and the Potential for Aptamer-Based Biosensors

Pancreatic cancer has a high mortality rate, and both the incidence and mortality are continuing to increase in many countries globally. The poor prognosis of pancreatic cancer is in part due to the challenges in early diagnosis. Improving early-stage pancreatic cancer diagnosis would improve survival outcomes. Aptamer-based biosensors provide an alternative technological approach for the analysis of serum biomarkers with several potential advantages. This review summarizes the major pancreatic cancer serum biomarkers, as well as discusses recent progress in biomarker exploration and aptasensor development. Here, we review both established and novel serum biomarkers identified recently, emphasizing their potential for early-stage pancreatic cancer diagnosis. We also propose strategies for further expanding multiplex biomarker panels beyond the established CA19-9 biomarker to enhance diagnostic performance. We discuss technological advancements in aptamer-based sensors for pancreatic cancer-related biomarkers over the last decade. Optical and electrochemical sensors are highlighted as two primary modalities in aptasensor design, each offering unique advantages. Finally, we propose steps towards clinical application using aptamer-based sensors with multiplexed biomarker detection for improved pancreatic cancer diagnostics.

Exosomes derived from umbilical cord blood NK cells inhibit the progression of pancreatic cancer by targeting ROS-mediated mitochondrial dysfunction

Emerging research indicates that natural killer (NK) cell-derived exosomes (NK-exo) play a significant role in cancer development. However, their regulatory mechanisms, particularly in pancreatic cancer, remain poorly elucidated. This study employed an in vitro co-culture system and an in vivo subcutaneous tumor model to evaluate the anti-tumor effect of NK-exo on pancreatic cancer. Umbilical cord blood (UCB)-derived NK-exo displayed characteristic exosomal morphology, size, and marker expression and was internalized by PANC- 1 cells. NK-exo significantly and dose-dependently reduce cell proliferation, migration, and invasion (P < 0.01). Further analysis demonstrated that NK-exo induced mitochondrial apoptosis in PANC- 1 cells by altering reactive oxygen species (ROS, P < 0.0001) and mitochondrial membrane potential (MPP) levels (P < 0.0001), effects that were significantly diminished with N-acetylcysteine (NAC) treatment (P < 0.0001). Furthermore, NK-exo treated PANC- 1 cells showed upregulation of the apoptotic markers Caspase3 (P < 0.0001) and Caspase9 (P = 0.0086) and reduced the release of PGC- 1α (P = 0.0064), TFAM (P < 0.0001), and SOD2 (P = 0.0021) as demonstrated by qRT-PCR. Western blot analyses revealed a dose dependent significant elevation of total Caspase3, Caspase9, Bax, and cytochrome c level and depression in the anti-apoptotic Bcl- 2. Animal experiments further confirmed that NK-exo treatment significantly reduced tumor volume and weight and increased Bax protein expression relative to the tumor model group. These findings indicate that NK-exo can enter PANC- 1 cells via endocytosis, induce mitochondrial oxidative damage, and suppress PANC- 1 cell progression, thereby demonstrating a robust anti-pancreatic cancer effect.

Inflammation, Immunosuppression, and Immunotherapy in Pancreatic Cancer-Where Are We Now?

Pancreatic cancer (PC) is one of the most commonly diagnosed and deadliest neoplasms in the modern world. Over the past few years, the incidence of PC has risen with only a slight improvement in overall survival. Moreover, the improvement in survival is primarily driven by diagnoses in the localized stage of the disease, rather than by new treatment methods. The inflammatory process is a key mediator of PC development, yet PC is also one of the most immune-resistant tumors. Patients rarely benefit from monotherapy with immune checkpoint inhibitors; nevertheless, the latest biological findings on the complexity of the pancreatic tumor microenvironment might be translated into designing new clinical studies that combine various approaches to overcome single-agent immunotherapy resistance. On the other hand, focusing on inflammation may lead to the development of new inflammation-based prognostic markers for patients. This review aims to describe the current state of knowledge regarding the complex relationships between systemic and local inflammation, immune response, immunosuppression, and therapeutic options in PC.

ANP32E expression in pancreatic cancer is associated with impaired gemcitabine efficacy and poor patient prognosis

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive and fatal malignancy, although gemcitabine is administered as a single or combined therapeutic agent. Our previous study demonstrated that ANP32E overexpression promoted PDAC cell proliferation. However, whether it affects treatment outcome and clinical prognosis is still unclear. In the present study, we aimed to determine whether ANP32E is negatively associated with the treatment outcome of gemcitabine.

METHODS

We collected clinical characteristics and treatment information from a total of 75 PDAC patients to assess the association of ANP32E expression via immunohistochemical (IHC) staining with overall survival (OS) in patients who were or were not treated with gemcitabine-based chemotherapy, followed by a clinical replication study with transcriptomic data from the TCGA database and functional validation experiments involving the knockdown of ANP32E in the Hup-T3 and SU86.86 human pancreatic cancer cell lines.

RESULTS

We demonstrated the interference effect of ANP32E on gemcitabine efficacy and patient prognosis in PDAC patients by using our own clinical samples or publicly available TCGA datasets. Downregulation of ANP32E significantly sensitized Hup-T3 and SU86.86 cells to gemcitabine, which was consistent with the results of the above association studies.

CONCLUSION

Our findings suggest that ANP32E might serve as a negative biomarker for poor prognosis and a predictive indicator for poor gemcitabine efficacy. These findings suggest that ANP32E might be a potential therapeutic target to help develop effective drugs to overcome gemcitabine resistance and reduce the risk for relapse or metastasis in patients with PDAC.

Identification of prognostic and therapeutic biomarkers associated with macrophage and lipid metabolism in pancreatic cancer

Although macrophages and lipid metabolism significantly influence the progression of various cancers, their precise roles in pancreatic cancer (PC) remain unclear. This study focuses on identifying and validating biomarkers associated with macrophage-related genes (MRGs) and lipid metabolism-related genes (LMRGs), providing new targets and strategies for therapeutic intervention. This research utilized datasets from TCGA-PAAD, GSE62452, and GSE57495. Candidate genes were identified by overlapping differentially expressed genes with MRGs from WGCNA and LMRGs. Regression analyses were performed to pinpoint potential biomarkers and construct a risk model, which underwent evaluation. A nomogram was subsequently developed and validated. Additional analyses, including functional enrichment, somatic mutation profiling, immune landscape assessment, and RT-qPCR, were performed to investigate the underlying biological mechanisms in PC. The study identified ADH1A, ACACB, CD36, CERS4, PDE3B, ALOX5, and CRAT as biomarkers for PC. RT-qPCR results revealed reduced expression of ADH1A, ACACB, CD36, CERS4, PDE3B, and CRAT in tumor samples compared to adjacent tissues, whereas ALOX5 expression was significantly elevated in tumor samples. A risk model utilizing these biomarkers classified PC patients into high- and low-risk cohorts, with high-risk patients showing lower survival probabilities. Subsequently, risk score and N stage were identified as independent prognostic factors, leading to the development of a nomogram. Notably, both risk cohorts showed significant enrichment in the "cell cycle" pathway. Furthermore, TP53 mutations were prevalent in both high-risk (76%) and low-risk (50%) cohorts. Correlation analysis indicated that PVRL2 (an immunosuppressive factor), CD276 (an immunoactivator), and CCL20 (a chemotactic factor) had the highest positive correlation with the risk score. In this study, ADH1A, ACACB, CD36, CERS4, PDE3B, ALOX5, and CRAT were identified as biomarkers for PC, with their expression levels validated in clinical samples. These findings offered a potential theoretical foundation for developing targeted treatments for PC.

Single-Molecule Liquid Biopsy Detects Low- and High-Abundance Protein Markers Simultaneously for Pancreatic Cancer Diagnosis

Simultaneous analysis of multiple biomarkers can typically improve the sensitivity and specificity of a disease diagnosis. Low-abundance serum proteins have recently emerged as a novel class of biomarkers for diseases. Due to the low concentration, the low-abundance protein analysis relies on single-molecule immunoassay, which has a very limited dynamic range. As a result, simultaneous analysis of low- and high-abundance protein markers requires multiple instruments, which demands larger sample volumes and is cost-/labor-consuming. To overcome these limitations, we developed a single-molecule imaging technique that can detect low- and high-abundance protein markers simultaneously in one chip. By employing a hybrid biomarker capture strategy that involves both glass surface and bead immobilization, our method greatly extended the detection range of the single-molecule assay. We used the method for pancreatic cancer diagnosis and analyzed three serum biomarkers of different abundances, including LIF, CA19-9, and CA125. Combined analysis of the three biomarkers yielded exceptional sensitivity and specificity (AUC = 0.996), which is better than using any of the markers alone, including CA19-9 that is used in clinical practice (AUC = 0.804). Overall, we demonstrated a simple and cost-effective method that greatly extended the dynamic range of single-molecule imaging while maintaining the sensitivity, which has great potential in various clinical applications.

Machine learning-based prognostic modelling of NK cells in PAAD for immunotherapy guidance

Pancreatic cancer's high incidence and mortality rates are underscored by ineffective treatments, particularly immunotherapy's poor performance. This could stem from an unclear immune microenvironment, where NK cells may play a unique role. Analyzing the NK cell-differentially expressed genes (NKDEGs) from the PAAD_GSE162708 single-cell dataset and utilizing the TCGA-PAAD and ICGC-PACA-AU datasets, we identified 11 NKDEGs linked to pancreatic adenocarcinoma (PAAD) prognosis and developed a prognostic model. This model's risk scores significantly outperformed traditional grading and TNM staging systems, validated through clinical and pathological analyses. Functional enrichment analysis pointed to the Neuroactive ligand-receptor interaction and MAPK signaling pathways, suggesting NK cells' distinctive role in PAAD. High-risk groups showed decreased overall NK cells but increased activated NK cells, which may mediate adverse inflammatory responses. NK cells exhibit synergistic interactions with plasma cells and macrophages and negative regulation by monocytes and naive B cells. Our model accurately predicts immunotherapy responses, indicating potential for targeted drugs to enhance treatment. Additionally, we introduced an NKDEGs-based immunotyping approach for personalized medicine and clinical decision-making in PAAD. This study emphasizes NK cells' potential in PAAD treatment, offering precise patient stratification and therapeutic targets for immunotherapy.

Fecal profiling reveals a common microbial signature for pancreatic cancer in Finnish and Iranian cohorts

BACKGROUND

Pancreatic cancer (PC) presents a significant challenge in oncology because of its late-stage diagnosis and limited treatment options. The inadequacy of current screening methods has prompted investigations into stool-based assays and microbial classifiers as potential early detection markers. The gut microbiota composition of PC patients may be influenced by population differences, thereby impacting the accuracy of disease prediction. However, comprehensive profiling of the PC gut microbiota and analysis of these cofactors remain limited. Therefore, we analyzed the stool microbiota of 33 Finnish and 50 Iranian PC patients along with 35 Finnish and 34 Iranian healthy controls using 16S rRNA gene sequencing. We assessed similarities and differences of PC gut microbiota in both populations while considering sociocultural impacts and generated a statistical model for disease prediction based on microbial classifiers. Our aim was to expand the current understanding of the PC gut microbiota, discuss the impact of population differences, and contribute to the development of early PC diagnosis through microbial biomarkers.

RESULTS

Compared with healthy controls, PC patients presented reduced microbial diversity, with discernible microbial profiles influenced by factors such as ethnicity, demographics, and lifestyle. PC was marked by significantly higher abundances of facultative pathogens including Enterobacteriaceae, Enterococcaceae, and Fusobacteriaceae, and significantly lower abundances of beneficial bacteria. In particular, bacteria belonging to the Clostridia class, such as butyrate-producing Lachnospiraceae, Butyricicoccaceae, and Ruminococcaceae, were depleted. A microbial classifier for the prediction of pancreatic ductal adenocarcinoma (PDAC) was developed in the Iranian cohort and evaluated in the Finnish cohort, where it yielded a respectable AUC of 0.88 (95% CI 0.78, 0.97).

CONCLUSIONS

This study highlights the potential of gut microbes as biomarkers for noninvasive PC screening and the development of targeted therapies, emphasizing the need for further research to validate these findings in diverse populations. A comprehensive understanding of the role of the gut microbiome in PC could significantly enhance early detection efforts and improve patient outcomes.

RNA biosensors for detection of pancreatic cancer

Pancreatic cancer is recognized as one of the most lethal types of cancer globally, characterized by a high mortality rate and a bleak prognosis, which greatly contributes to cancer-related deaths. Forecasts suggest that by 2030, pancreatic cancer will exceed other cancer types in prevalence. The disease presents considerable difficulties owing to the lack of prominent symptoms in its early stages, restricted options for early detection, rapid progression, and unfavorable outcomes. Presently, traditional methods for diagnosing pancreatic cancer primarily rely on imaging techniques. However, these methods often entail significant costs, require considerable time, and necessitate specialized skills for both operating the equipment and interpreting the resulting images. To overcome these obstacles, the use of biosensors has been proposed as a potentially valuable tool for the early detection of pancreatic cancer. MicroRNAs (miRs), a type of small non-coding RNA molecules, have emerged as highly sensitive molecular diagnostic tools that have the potential to function as precise indicators for a range of diseases, including cancer. Biosensors have been suggested as a potential solution for tackling these challenges, offering a promising approach for the early detection of pancreatic cancer. Small non-coding RNA molecules known as MicroRNAs (miRs) have become recognized as extremely sensitive molecular diagnostic tools and can act as precise biomarkers for different diseases, such as cancer. Moreover, this manuscript presents a thorough summary of the latest innovations in nano-biosensors that have been specifically developed for the identification of non-coding RNAs related to pancreatic cancer.

A novel peptide RR-171 derived from human umbilical cord serum induces apoptosis and pyroptosis in pancreatic cancer cells

Human umbilical cord serum is full of molecules that play vital roles in foetal development. This study aimed to explore the effects of RR-171, a novel peptide derived from umbilical cord serum, on pancreatic cancer cells and to elucidate its mechanisms. The anti-pancreatic cancer properties of RR-171 were detected by a cell counting kit-8, colony formation, flow cytometry, LDH release and EdU incorporation assays. RNA sequencing and gene enrichment analysis were applied to identify the differentially expressed genes and enriched pathways. Western blotting analysis was used to detect the expression of proteins. A subcutaneous xenograft model was used to examine the effect of RR-171 on pancreatic cancer cells in vivo. The results demonstrated that RR-171 inhibited the viability, proliferation and colony formation of pancreatic cancer cells in a dose-dependent manner. Gene enrichment analysis revealed that RR-171 inhibits the Wnt signaling pathway. Moreover, RR-171 significantly induced apoptosis and pyroptosis in pancreatic cancer cells in a dose-dependent manner. Z-VAD-FMK partly reversed the proapoptotic effect of RR-171, and VX-765 partly reversed the pro-pyroptotic effect of RR-171. Finally, RR-171 inhibited the growth of pancreatic cancer cells in a subcutaneous xenograft mice model and suppressed the expression of Ki-67 and PCNA in tumors. In conclusion, RR-171 induces apoptosis and pyroptosis through multiple pathways and inhibits pancreatic cancer growth, suggesting that RR-171 might be a potential agent for the treatment of pancreatic cancer.

The trend in pancreatic cancer incidence from 2009 to 2019 and the prediction from 2020 to 2030: An analysis of provincial data in China

OBJECTIVE

As a malignant tumour with a very high mortality rate, the incidence of pancreatic cancer is on the rise globally, but the long-term trend at the provincial level in China is not yet clear. This study aimed to investigate the trend of pancreatic cancer incidence in Jiangsu Province from 2009 to 2019 and to predict pancreatic cancer incidence from 2020 to 2030.

STUDY DESIGN

Descriptive study.

METHODS

Data on pancreatic cancer incidence in Jiangsu Province were obtained from the Jiangsu Cancer Registry. Trends in pancreatic cancer incidence from 2009 to 2019 were examined based on the Joinpoint regression model. Age-period-cohort (APC) models were introduced to estimate the independent effects of age, period, and cohort on the incidence of pancreatic cancer and to project pancreatic cancer incidence from 2020 to 2030.

RESULTS

From 2009 to 2019, the number of pancreatic cancer cases in Jiangsu Province increased from 1146 to 2088, and the age-standardized incidence rate (ASIR) increased from 4.59 to 5.64 per 100,000 people. In 2019, the ASIR was higher in males than in females, and the ASIR was higher in urban areas than in rural areas. The APC analysis also showed that the age effect was the most important factor influencing pancreatic cancer incidence in Jiangsu Province. Predictions suggest that pancreatic cancer incidence will continue to increase from 2020 to 2030.

CONCLUSIONS

From 2009 to 2019, the pancreatic cancer incidence in Jiangsu Province showed an increasing trend. The incidence rate is higher among males and urban residents. It is expected that the incidence of pancreatic cancer will continue to increase in the next decade. Therefore, pancreatic cancer prevention and control efforts should continue to focus on older adults and males. This study develops an advanced provincial prediction model, which provides a quantitative basis for allocating screening resources to high-risk populations and provides a reference paradigm for cancer prevention and control strategies in other developing countries undergoing industrialization.

The acidic microenvironment promotes pancreatic cancer progression via the lncRNA-LOC100507424/E2F1/FOXM1 axis

Pancreatic cancer is highly aggressive and sensitive to acidic microenvironments, which promote cancer cell survival and invasion. Long non-coding RNAs (lncRNAs) play crucial roles in cancer biology, helping cells adapt to microenvironmental changes, but their functions in the acidic microenvironment of pancreatic cancer are understudied. This study investigated the role of lncRNA LOC100507424 in pancreatic cancer, previously linked to glioma stem cells. Clinical specimens and cell line models cultured under acidic conditions showed that LOC100507424 was upregulated in pancreatic cancer tissues and further increased in acidic environments. Functional assays demonstrated that knockdown of LOC100507424 inhibited cell proliferation, invasion and metastasis. Mechanistically, LOC100507424 transcriptionally regulated FOXM1 expression through its interaction with E2F1. In vivo studies confirmed that LOC100507424 promoted tumor growth in nude mice. These findings highlight the significance of lncRNAs in the acidic microenvironment of pancreatic cancer and suggest potential therapeutic targets.

Polyphenol-based pH-responsive nanoparticles enhance chemo-immunotherapy in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is challenging to treat due to its difficulty in early diagnosis, highly invasive nature, and high metastatic potential. Currently, the primary treatments for PDAC are chemotherapy and immunotherapy. However, the abundance of extracellular matrix and immunosuppressive cells in the tumor microenvironment (TME) severely impedes the effectiveness of chemotherapy and immunotherapy, promoting tumor growth and metastasis. Indoleamine 2,3-dioxygenase 1 (IDO1), an immunosuppressive tryptophan-metabolizing enzyme, is upregulated in PDAC and degrades tryptophan (Trp) into kynurenine (Kyn), which is toxic to effector T cells and induces regulatory T cells (Treg) recruitment. Herein, we propose a concise strategy to construct a biocompatible, polyphenol-based, pH-responsive nanoparticle to co-deliver docetaxel (DTX) and NLG919 (an IDO1 inhibitor) to significantly enhance chemo-immunotherapy for PDAC by remodeling the TME. The DTX/NLG919-loaded nanoparticles (FPND) effectively elicited immunogenic cell death (ICD) in PDAC cells while limiting immunosuppressive Kyn production through IDO1 inhibition. FPND triggered an effective anti-tumor immune response, characterized by increased CD8+ T cells infiltration and decreased Treg recruitment, leading to significant inhibition of subcutaneous tumor growth in KPC mice through a combination of chemotherapy and immunotherapy. Overall, FPND nanoparticles showed excellent anti-tumor efficacy as a PDAC therapeutic strategy with broad potential in precision medicine.

To Predict the Prognosis and Immunological Characteristics of Pancreatic Cancer Based on Disulfide-Death Gene Death-Related lncRNA

Background: Disulfide-dependent cell death, known as disulfide death, plays a pivotal regulatory role in the onset and progression of various cancers including pancreatic cancer. Despite its significance, little attention has been given to the study of disulfide death-related long non-coding RNAs (lncRNAs) in pancreatic cancer development and progression. Methods: This study utilized data from the Cancer Genome Atlas Project (TCGA) to analyze the transcriptome of pancreatic cancer. Co-expression analysis of genes associated with disulfide death was performed and six lncRNAs closely linked to disulfide death were identified through univariate and multivariate analysis. These lncRNAs were used to develop clinical prognostic models. The prognostic value of this model was then analyzed and further investigations included pathway enrichment analysis, tumor mutation load analysis, immune cell infiltration analysis, analysis of the tumor microenvironment (TME), and drug sensitivity analysis. Results: The developed prognostic model based on disulfide-associated lncRNAs exhibited significant prognostic value, allowing for reliable predictions of patient outcomes in pancreatic adenocarcinoma (PAAD). The analysis revealed that the six identified lncRNAs serve as independent prognostic factors, significantly correlating with patient survival and recurrence rates. Additionally, findings indicated notable differences in immune cell infiltration and drug sensitivity between high-risk and low-risk patient groups, suggesting potential therapeutic targets for enhancing treatment efficacy. Conclusions: Our findings revealed six disulfide death-associated lncRNAs with independent prognostic value, offering a crucial indicator for predicting the prognosis of pancreatic adenocarcinoma (PAAD) patients. Additionally, the analysis of tumor immune invasion and drug sensitivity provides a novel avenue for controlling tumor invasion and metastasis as well as reducing drug tolerance.

Construction of Bispecific T-Cell Engager Radiotracer and Its Micro-PET Evaluation in Pancreatic Cancer

Mucin 17 (MUC17), a transmembrane mucin, is overexpressed in pancreatic cancer and is associated with tumor proliferation and metastasis. CD3 is an indispensable molecule on the surface of T lymphocytes, which is associated with T cell activation and participates in immune responses. Here, we developed a bispecific T-cell engager radiotracer, 89Zr-M17C3, targeting MUC17 and CD3, to enable noninvasive PET imaging of both tumor cells and T-cell infiltration in pancreatic cancer. 89Zr-M17C3 was synthesized by conjugating AMG199 with zirconium-89 and verified for its radiochemical purity and in vitro stability. The 89Zr-M17C3 probe demonstrated excellent radiochemical purity (>99%) and stability (maintained ≥99% over 120 h). Cellular uptake assays and binding affinity studies were conducted to evaluate the probe's specificity for MUC17 and CD3. Micro-PET/CT imaging and biodistribution studies were performed in MUC17-expressing nude mice and CD3 humanized mice to assess probe uptake in tumors and T-cell-infiltrated tissues. In MUC17-expressing AsPC-1 tumors, probe uptake was significantly higher than in MUC17-negative PANC-1 tumors (SUVmax: 2.26 ± 0.18 vs 1.13 ± 0.14, P < 0.001) and was confirmed to be MUC17-dependent through blocking studies. In CD3 humanized mice, the probe was able to visualize both T-cell infiltration and MUC17-positive tumors, with peak uptake in AsPC-1 tumors (SUVmax: 2.35 ± 0.46) and spleen (SUVmax: 2.19 ± 0.40) at 216 h. Immunohistochemical analysis confirmed the spatial correlation between MUC17 expression and CD3-positive T-cell infiltration in AsPC-1 tumors but not in PANC-1 tumors. In summary, the 89Zr-M17C3 radiotracer exhibited high affinity for MUC17 and CD3 and successfully differentiated MUC17-positive tumors from MUC17-negative tumors while simultaneously providing insight into the T-cell distribution. This study highlights the potential of 89Zr-M17C3 as a versatile imaging tool to support patient stratification and therapeutic monitoring in tumor-targeted immunotherapy, particularly for bispecific T-cell engager-based approaches such as AMG199.

Tongue coating microbiota-based machine learning for diagnosing digestive system tumours

Background

Digestive system tumours (DSTs) often diagnosed late due to nonspecific symptoms. Non-invasive biomarkers are crucial for early detection and improved outcomes.

Patients and Methods

We collected tongue coating samples from 710 patients diagnosed with DST and 489 healthy controls (HC) from April 2023, to December 2023. Microbial composition was analyzed using 16S rRNA sequencing, and five machine learning algorithms were applied to assess the diagnostic potential of tongue coating microbiota.

Results

Alpha diversity analysis showed that the microbial diversity in the tongue coating was significantly increased in DST patients. LEfSe analysis identified DST-enriched genera Alloprevotella and Prevotella, contrasting with HC-dominant taxa Neisseria, Haemophilus, and Porphyromonas (LDA >4). Notably, when comparing each of the four DST subtypes with the HC group, the proportion of Haemophilus in the HC group was significantly higher, and it was identified as an important feature for distinguishing the HC group. Machine learning validation demonstrated superior diagnostic performance of the Extreme Gradient Boosting (XGBoost) model, achieving an AUC of 0.926 (95% CI: 0.893-0.958) in internal validation, outperforming the other four machine learning models.

Conclusion

Tongue coating microbiota shows promise as a non-invasive biomarker for DST diagnosis, supported by robust machine learning models.

Use of the Malaria Protein VAR2CSA for the Detection of Small Extracellular Vesicles to Diagnose Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge for early diagnosis due to the lack of sensitive and specific biomarkers. This encouraged us to explore the diagnostic value of cancer-derived small extracellular vesicles (sEVs) as early detection biomarkers. We previously showed that the recombinant malaria protein VAR2CSA (rVAR2) selectively binds to oncofetal chondroitin sulfate (ofCS) on the surfaces of cancer cells, which might be useful for identifying cancer-derived sEVs. Indeed, flow cytometry revealed strong ofCS expression in PDAC cell-derived sEVs, as evidenced by the presence of mutant KRAS, a common genetic alteration in PDAC. Plasma from PDAC patients showed significantly higher ofCS+ sEV levels compared to healthy donors and patients with benign gastrointestinal diseases. ROC analysis for ofCS+ sEVs revealed an AUC of 0.9049 for the detection of all-stage and 0.9222 for early-stage PDAC. Notably, mutant KRAS was also detected in these patient-derived sEVs. Most intriguingly, combining ofCS+ sEVs and CA19-9 resulted in an AUC of 0.9707 for the detection of early PDAC. Our study demonstrates that rVAR2 is suitable for detecting ofCS+ cancer-derived sEVs in plasma, thereby providing high efficiency for identifying PDAC patients among a diverse population. These findings suggest that rVAR2-based sEV detection could serve as a powerful diagnostic tool to improve patient survival through early detection.

The global progress and quality assessment of research on the association between circulating tumor DNA and clinical prognosis: a systematic review

Objective

Circulating tumor DNA (ctDNA) has shown potential as a prognostic biomarker in patients with solid tumors. This study aimed to systematically summarize the global application of ctDNA in the prognostic management of solid tumor patients and to evaluate the quality of the current studies.

Methods

PubMed, Web of Science, Embase, Cochrane Library, Scopus, and clinical trials.gov databases were searched to collect cohort studies on ctDNA in the prognosis of solid tumor patients from January 2016 to May 2022. The language was limited to English. Information including general information, participants and cancer characteristics, ctDNA and outcome information were extracted. The quality of the studies was assessed using the Newcastle-Ottawa Scale checklist.

Results

A total of 214 studies were included in the final analysis, encompassing 21,076 patients. The number of studies has increased annually from 2016 to 2022. The most common types of solid tumors studied were colorectal cancer (27.10 %), lung cancer (20.09 %), pancreatic cancer (16.82 %), and breast cancer (14.02 %). The top three journals by number of publications had an impact factor in 2023 greater than 10. Of the studies, the median sample size was 69 (interquartile range: 41-111), 69.81 % had a sample size <100, 68.92 % had a median/mean age ≥60 years, and 74.05 % were from developed countries. Multi-center studies accounted for 40.36 %. Additionally, 29.82 % of the studies had a bias risk score ≤6. Only 16.67 % of studies on liver cancer had a bias risk score >6. The primary criteria not met by the studies included "Adequacy of follow-up of cohorts" (33.33 %), "Assessment of outcome" (32.16 %) and "Representativeness of the exposed cohort" (27.49 %).

Conclusions

The prognostic value of ctDNA in patients with solid tumors is gaining increasing attention, leading to a steady rise in the number of studies. However, many studies still suffer from small sample sizes and a lack of representativeness. Furthermore, details regarding ctDNA detection methods and results reporting are often insufficiently described. There is an urgent need to improve the quality of such research.

Therapeutic potential of flavonoids in gastrointestinal cancer: Focus on signaling pathways and improvement strategies (Review)

Flavonoids are a group of polyphenolic compounds distributed in vegetables, fruits and other plants, which have considerable antioxidant, anti‑tumor and anti‑inflammatory activities. Several types of gastrointestinal (GI) cancer are the most common malignant tumors in the world. A large number of studies have shown that flavonoids have inhibitory effects on cancer, and they are recognized as a class of potential anti‑tumor drugs. Therefore, the present review investigated the molecular mechanisms of flavonoids in the treatment of different types of GI cancer and summarized the drug delivery systems commonly used to improve their bioavailability. First, the classification of flavonoids and the therapeutic effects of various flavonoids on human diseases were briefly introduced. Then, to clarify the mechanism of action of flavonoids on different types of GI cancer in the human body, the metabolic process of flavonoids in the human body and the associated signaling pathways causing five common types of GI cancer were discussed, as well as the corresponding therapeutic targets of flavonoids. Finally, in clinical settings, flavonoids have poor water solubility, low permeability and inferior stability, which lead to low absorption efficiency in vivo. Therefore, the three most widely used drug delivery systems were summarized. Suggestions for improving the bioavailability of flavonoids and the focus of the next stage of research were also put forward.

A study of the association between Helicobacter pylori infection type and pancreatic cancer risk: A systematic review and meta‑analysis

Pancreatic cancer is a highly invasive malignant tumor with a complex pathogenesis that makes early diagnosis challenging. The potential association between Helicobacter pylori infection and pancreatic cancer risk has been noted; however, the available results are still highly divergent. The aim of the present study was to systematically evaluate the association between different types of H. pylori infection and pancreatic cancer risk as well as to explore the possible causes. A systematic search was conducted using the PubMed, Embase and Cochrane Library databases up to August 2023. The literature quality was evaluated using the Newcastle-Ottawa Scale. All studies that met the criteria were included in the overall meta-analysis to calculate the odds ratios (ORs) and corresponding 95% confidence intervals (CIs). In addition, subgroup analyses were performed based on factors such as diagnostic criteria for H. pylori infection, study region, type of study design and CagA status. The effect of publication bias on the quantitative synthesis results was assessed using the trim-and-fill analysis, and sensitivity analyses were used to verify the robustness of the quantitative synthesis results. A total of 17 studies involving 67,910 participants, including 64,372 controls and 3,538 patients with pancreatic cancer, were included in the present study. The overall analysis showed that no significant association was observed between H. pylori infection and pancreatic cancer risk (OR, 1.15; 95% CI, 0.93-1.41). Further subgroup analyses, which did not consider the effects of study quality, diagnostic criteria, geographical distribution and the type of study design, did not produce new findings that contradicted the results of the overall analysis. CagA+ H. pylori infection did not significantly affect the risk of pancreatic cancer (OR, 0.95; 95% CI, 0.78-1.16), whereas CagA- H. pylori infection may be a possible risk factor for pancreatic cancer (OR, 1.24; 95% CI, 1.004-1.541). The H. pylori infection did not significantly increase the risk of pancreatic cancer. However, it is noteworthy that CagA- H. pylori infection could be a potential factor that elevated the risk of pancreatic cancer.

Risk Factors for Financial Toxicity in Patients With Pancreatic Cancer

BACKGROUND

The increasing costs of cancer treatment impose a tremendous economic burden on patients and their families, adversely impacting their quality of life and patients' outcomes. Financial toxicity (FT), as a concept describing the economic burden on patients, is crucial to comprehend the extent and determinants within specific contexts.

OBJECTIVE

To understand the current status of FT among Chinese pancreatic cancer (PC) patients, identify risk factors for FT, and summarize the characteristics of high-risk groups.

METHODS

A cross-sectional study involving 296 PC patients was conducted to investigate their general information, financial toxicity, quality of life, positive and negative affects, and social support. Univariate and multiple linear regression analyses were used to examine the correlation between FT and other variables.

RESULTS

The PC patient's FT score was 54.27 ± 14.50, with 25.7% being forced to change their work status due to the disease diagnosis and 29.4% exhibiting economically related treatment nonadherence behaviors. Factor analysis showed financial toxicity associated with fewer household savings, more total out-of-pocket (OOP) costs, treatment nonadherence, unemployment, diminished positive affect, and insufficient social support.

CONCLUSIONS

FT was highly prevalent among PC patients and associated with factors such as household savings and total OOP costs. There was a need to identify and manage patients exhibiting high-risk characteristics and to implement targeted interventions to mitigate their economic burden.

Accurate Diagnosis of Pancreatic Ductal Adenocarcinoma by Detection of miRNA-196a Biomarker in Exosome Using Solution-Gated Graphene Transistor with Antifouling Design

The accurate diagnosis of pancreatic ductal adenocarcinoma (PDAC) suffers low specify, and low sensitivity of biomarker detection. In complex biological fluid environments, nonspecific adsorption is prevalent, posing challenges to the accurate detection of biomarkers at low concentrations. Herein, a highly sensitive and selective solution-gated graphene transistor (SGGT) is fabricated for the detection of miRNA-196a in exosomes to diagnose PDAC. The antifouling modification on the surface of the gate electrode is employed through using bovine serum albumin as a common sealing agent and poly adenine (polyA8) to enhance surface hydrophilicity. The effect of background noise on the detection is effectively reduced. The limit of detection reached 1.82 × 10-19 m without the need for labeling or amplification, and the detection time is within 25 min. The clinical experiments verify that receiver operating characteristic curve values of miRNA-196a detection in clinical diagnosis are higher than that of carbohydrate antigen 19-9 biomarker, and are as high as 0.98. The miRNA-196a detection can well distinguish PDAC from non-PDAC subjects. The SGGT sensor platform demonstrates significant potential for the accurate detection and diagnosis of PDAC within the milieu of complex biological samples.

Integrated analysis of scRNA-seq and bulk RNA-seq data identifies BHLHE40 as a key gene in pancreatic cancer progression and gemcitabine resistance

OBJECTIVE

Pancreatic cancer is characterized by its high mortality rate and short survival periods, and novel therapeutic targets and tailor personalized strategies are urgently needed. In this study, we aim to investigate the molecular mechanisms underlying pancreatic ductal adenocarcinoma (PDAC) progression and chemoresistance, with a focus on identifying novel therapeutic targets.

METHODS

Multiomics approaches were integrated to identify novel actionable targets for PDAC. Public datasets such as TCGA and GEO were utilized to investigate the relationship between gene expression and clinical outcomes. Functional enrichment, cell-cell communication, and metabolic pathway analyses were performed to reveal PDAC heterogeneity and therapeutic resistance mechanisms.

RESULTS

BHLHE40 was identified as a hub gene linked to high-CNV PDAC cells, Gemcitabine resistance, and poor prognosis in PDAC. High BHLHE40 expression is significantly correlated with immunosuppressive tumor microenvironment (TME) features such as reduced CD8+ T infiltration, TCR richness, and lower tumor mutational burden (TMB). ChIP-seq data analysis confirmed BHLHE40 could directly bind to the SAT1 promoter, establishing a transcriptional axis promoting chemoresistance. Single-cell RNA-seq analysis further revealed that the BHLHE40+/SAT1+ subpopulation cells are resistant to Gemcitabine in PDAC.

CONCLUSIONS

BHLHE40 is significantly correlated with PDAC malignancy and chemoresistance via SAT1 regulation and immune evasion. Targeting BHLHE40 may sensitize PDACs to Gemcitabine and facilitate personalized treatment for BHLHE40+ PDAC patients.

Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes?

Pancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from the lack of effective screening strategies in increased pancreatic cancer risk groups. One population that may be appropriate for screening is new-onset diabetes (NOD) patients. Such a conclusion stems from the fact that pancreatic cancer can cause diabetes several months before diagnosis. The most widely used screening tool for this population, the ENDPAC (Enriching New-Onset Diabetes for Pancreatic Cancer) model, has not achieved satisfactory results in validation trials. This provoked the first attempts at using artificial intelligence (AI) to create larger, multi-parameter models that could better identify the at-risk population, which would be suitable for screening. The results shown by the authors of these trials seem promising. Nonetheless, the number of publications is limited, and the downfalls of using AI are not well highlighted. This narrative review presents a summary of previous publications, recent advancements and feasible solutions for effective screening of patients with NOD for pancreatic cancer.

Gut Microbiota-Based Immunotherapy: Engineered Escherichia coli Nissle 1917 for Oral Delivery of Glypican-1 in Pancreatic Cancer

Background and Objectives: The administration of oral vaccines offers a potential strategy for cancer immunotherapy; yet, the development of effective platforms continues to pose a difficulty. This study examines Escherichia coli Nissle 1917 (EcN) as a microbial vector for the precise delivery of Glypican-1 (GPC1), a tumor-associated antigen significantly overexpressed in pancreatic ductal adenocarcinoma (PDAC).To evaluate the effectiveness of EcN as a vector for the delivery of GPC1 and assess its potential as an oral vaccination platform for cancer immunotherapy. Materials and Methods: EcN was genetically modified to produce a GPC1-flagellin fusion protein (GPC1-FL) to augment antigen immunogenicity. The expression and stability of GPC1 were confirmed in modified PANC02 cells using Western blot and flow cytometry, indicating that GPC1 expression did not influence tumor cell growth. A mouse model was employed to test immunogenicity post-oral delivery, measuring systemic IgG, IL-10, IL-2, and IFN-γ levels to indicate immune activation. Results: Oral immunization with EcN GPC1-FL elicited a robust systemic immune response, demonstrated by markedly increased levels of IgG and IL-10. IL-2 and IFN-γ concentrations were elevated in vaccinated mice relative to controls; however, the differences lacked statistical significance. Western blot examination of fecal samples verified consistent antigen expression in the gastrointestinal tract, indicating effective bacterial colonization and antigen retention. No detrimental impacts were noted, hence substantiating the safety of this methodology. Conclusions: These findings confirm EcN as a feasible and patient-friendly oral vaccination platform for cancer immunotherapy. The effective production of GPC1 in tumor cells, along with continuous antigen delivery and immune activation, underscores the promise of this approach for PDAC and other cancers. This study promotes microbial-based antigen delivery as a scalable, non-invasive substitute for traditional vaccine platforms.

Complex interplay between type 2 diabetes mellitus and pancreatic cancer: insights from observational and mendelian randomization analyses

BACKGROUND

To investigate the causal relationship between type 2 diabetes mellitus (T2DM), pancreatic cancer (PC) risk and identify the mediating effects of various risk factors on that relationship.

METHODS

581 PC patients and 582 healthy controls who visited our center from January 2013 to December 2023 were included in this retrospective study. Multivariable logistic regression was performed to evaluate the association between T2DM and PC through odds ratios (ORs) and 95% confidence intervals (CIs). Mendelian randomization (MR) studies were then conducted to explore the causal relationship between T2DM and PC, and causal mediation analysis (CMA) to examine the mediating role of common risk factors.

RESULTS

After adjusting for confounding factors, retrospective analysis revealed significant association between new-onset diabetes mellitus (NODM) and PC risk, with insulin treatment also linked to increased PC development. The standard inverse-variance weighted (IVW) method indicated that genetic susceptibility to T2DM was associated with an increased risk of developing PC (OR = 1.11; 95% CI = 1.034-1.193). Furthermore, MR showed T2DM, insulin treatment, FGF-4, and sulfhydryl oxidase 2 may be independently associated with the prevalence of PC. Specially, CMA demonstrated that insulin treatment, FGF4, and sulfhydryl oxidase 2 mediate the pathway from T2DM to PC, contributing 56.8%, 55.8%, and 5.9% of the total effect, respectively.

CONCLUSION

This study supports the association between T2DM, specifically NODM, and increased PC risk, with insulin therapy, FGF4, and sulfhydryl oxidase 2 mediating this pathway. Further research is required to elucidate the mechanisms underlying these mediating effects.

CLINICAL TRIAL NUMBER

not applicable.

PSMD11 and PSMD14 may serve as novel biomarkers for the prognosis of pancreatic ductal adenocarcinoma

Background

The ubiquitin proteasome system is involved in the regulation of cellular gene transcription and cellular receptor function through the degradation of proteins, thus affecting tumorigenesis and development. In this study, bioinformatics analysis revealed the expression of PSMD11 and PSMD14 in pancreatic ductal adenocarcinoma, which can be used as biomarkers for the prognosis of patients with PDAC. This study provides new targets for the prognostic assessment and targeted therapy of pancreatic ductal adenocarcinoma.

Methods

The expression levels and prognostic value of PSMD11 and PSMD14 in pancreatic ductal adenocarcinoma patients were analyzed using the GEPIA2, GEO, TCGA and GTEx databases, and the relationships between these expression levels and clinical case data and the survival and prognosis of patients with pancreatic ductal adenocarcinoma were analyzed. The effects of PSMD11 and PSMD14 on the malignant biological behaviors of pancreatic cancer cells, such as proliferation, migration and invasion, were investigated by in vitro experiments.

Results

Bioinformatics analysis revealed that the expression levels of PSMD11 and PSMD14 mRNAs were significantly higher in pancreatic ductal adenocarcinoma (PDAC) tissues than in normal pancreatic tissues and that this high expression was correlated with a poor prognosis in patients with PDAC. Further evaluation of the expression of PSMD11 and PSMD14 and correlation of the results with the clinical characteristics and survival of patients with PDAC revealed that high expression of PSMD11 and PSMD14 was associated with lymph node metastasis, TNM grade, degree of differentiation, and poor prognosis in patients with PDAC. Knockdown of PSMD11 and PSMD14 significantly inhibited the proliferation, migration, and invasion ability of pancreatic cancer cells.

Conclusion

PSMD11 and PSMD14 are highly expressed in pancreatic ductal adenocarcinoma tissues and are correlated with the degree of malignancy of pancreatic ductal adenocarcinoma; thus, PSMD11 and PSMD14 can be used as potential prognostic biomarkers and therapeutic targets for PDAC patients.

Role of the oral-gut microbiota axis in pancreatic cancer: a new perspective on tumor pathophysiology, diagnosis, and treatment

Pancreatic cancer, one of the most lethal malignancies, remains challenging due to late diagnosis, aggressive progression, and therapeutic resistance. Recent advances have revealed the presence of intratumoral microbiota, predominantly originating from the oral and gut microbiomes, which play pivotal roles in pancreatic cancer pathogenesis. The dynamic interplay between oral and gut microbial communities, termed the "oral-gut microbiota axis," contributes multifacetedly to pancreatic ductal adenocarcinoma (PDAC). Microbial translocation via anatomical or circulatory routes establishes tumor-resident microbiota, driving oncogenesis through metabolic reprogramming, immune regulation, inhibition of apoptosis, chronic inflammation, and dysregulation of the cell cycle. Additionally, intratumoral microbiota promote chemoresistance and immune evasion, further complicating treatment outcomes. Emerging evidence highlights microbial signatures in saliva and fecal samples as promising non-invasive diagnostic biomarkers, while microbial diversity correlates with prognosis. Therapeutic strategies targeting this axis-such as antibiotics, probiotics, and engineered bacteria-demonstrate potential to enhance treatment efficacy. By integrating mechanisms of microbial influence on tumor biology, drug resistance, and therapeutic applications, the oral-gut microbiota axis emerges as a critical regulator of PDAC, offering novel perspectives for early detection, prognostic assessment, and microbiome-based therapeutic interventions.

Genetically proxied therapeutic inhibition of antihypertensive drug targets and risk of pancreatic cancer: a mendelian randomization analysis

BACKGROUND

Conventional epidemiological studies have reported inconsistent results regarding the potential adverse effects of long-term use of antihypertensive drugs on cancer risk. Nevertheless, evidence of their impact on pancreatic cancer risk is limited and deserves further elucidation.

METHODS

We selected genetic variants from the genes encoding the target proteins (angiotensin-converting enzyme, beta-1 adrenergic receptor, and solute carrier family 12 member 3) of the examined antihypertensive drugs as instruments based on expression quantitative trait loci (eQTL) studies. Genetic summary statistics of blood pressure and pancreatic cancer were obtained from genome-wide association studies (GWASs) in Europeans and East Asians. Inverse-variance weight and MR-Egger methods were employed to estimate the effect of genetic variations in the drug targets on pancreatic cancer risk, and meta-analysis was used to combine the results from 3 independent datasets. Positive control analysis was conducted by using Wald ratio test to justify the genetic instruments of the drug by demonstrating the expected effect on the blood pressure which has an established causal relationship with the drug of interest.

RESULTS

Genetically proxied ACEIs were associated with lower pancreatic risk (OR = 0.506, 95% CI: 0.284-0.901, P = 0.021; OR = 0.265, 95% CI: 0.094-0.751, P = 0.012; OR = 0.236, 95% CI:0.078-0.712, P = 0.010, respectively) in 3 independent datasets and the combined results were validated in a meta-analysis using a random effects model (OR = 0.37, 95% CI: 0.22-0.64, P < 0.01) or fixed effects model (OR = 0.39, 95% CI: 0.25-0.62, P < 0.01). Other drug targets did not show consistent significant associations with pancreatic cancer risk in all 3 independent datasets.

CONCLUSIONS

Our study indicated that genetically proxied therapeutic inhibition of ACE was associated with a lower risk of pancreatic cancer, which may have translational potential in clinical practice. However, further long-term randomized controlled trials and observational studies are needed to clarify the effect of ACEIs on the pancreatic cancer risk.

Integrating OMICS-based platforms and analytical tools for diagnosis and management of pancreatic cancer: a review

Cancer remains the second leading cause of death worldwide, surpassed only by cardiovascular disease. From the different types of cancer, pancreatic cancer (PaC) has one of the lowest survival rates, with a survival rate of about 20% after the first year of diagnosis and about 8% after 5 years. The lack of highly sensitive and specific biomarkers, together with the absence of symptoms in the early stages, determines a late diagnosis, which is associated with a decrease in the effectiveness of medical intervention, regardless of its nature - surgery and/or chemotherapy. This review provides an updated overview of recent studies combining multi-OMICs approaches (e.g., proteomics, metabolomics) with analytical tools, highlighting the synergy between high-throughput molecular data generation and precise analytical tools such as LC-MS, GC-MS and MALDI-TOF MS. This combination significantly improves the detection, quantification and identification of biomolecules in complex biological systems and represents the latest advances in understanding PaC management and the search for effective diagnostic tools. Large-scale data analysis coupled with bioinformatics tools enables the identification of specific genetic mutations, gene expression patterns, pathways, networks, protein modifications and metabolic signatures associated with PaC pathogenesis, progression and treatment response through the integration of multi-OMICs data.