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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Circulating cell-free DNA methylation analysis of pancreatic cancer patients for early noninvasive diagnosis

Background

Aberrant hypermethylation of genomic DNA CpG islands (CGIs) is frequently observed in human pancreatic cancer (PAC). A plasma cell-free DNA (cfDNA) methylation analysis method can be utilized for the early and noninvasive detection of PAC. This study also aimed to differentiate PAC from other cancer types.

Methods

We employed the methylated CpG tandem amplification and sequencing (MCTA-Seq) method, which targets approximately one-third of CGIs, on plasma samples from PAC patients (n = 50) and healthy controls (n = 52), as well as from cancerous and adjacent noncancerous tissue samples (n = 66). The method's efficacy in detecting PAC and distinguishing it from hepatocellular carcinoma (HCC), colorectal cancer (CRC), and gastric cancer (GC) was evaluated. Additionally, a methylation score and typing system for PAC was also established.

Results

We identified a total of 120 cfDNA methylation biomarkers, including IRX4, KCNS2, and RIMS4, for the detection of PAC in blood. A panel comprising these biomarkers achieved a sensitivity of 97% and 86% for patients in the discovery and validation cohorts, respectively, with a specificity of 100% in both cohorts. The methylation scoring and typing systems were clinically applicable. Furthermore, we identified hundreds of differentially methylated cfDNA biomarkers between PAC and HCC, CRC, and GC. Certain combinations of these markers can be used in a highly specific (approximately 100%) algorithm to differentiate PAC from HCC, CRC, and GC in blood.

Conclusions

Our study identified cfDNA methylation markers for PAC, offering a novel approach for the early, noninvasive diagnosis of PAC.

Aspirin is associated with lower risk of pancreatic cancer and cancer-related mortality in patients with diabetes mellitus

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) have higher pancreatic cancer (PC) risk. While aspirin has chemopreventive effects on digestive cancers, its effect on PC among patients with T2DM is unclear.

METHODS

This retrospective cohort study identified newly diagnosed adult patients with T2DM in Hong Kong between 2001 and 2015 from a territory-wide healthcare registry. Exclusion criteria were history of PC, pancreatic cyst, IgG4 disease, or pancreatectomy. To address reverse causality between PC and T2DM, we excluded patients with PC diagnosed within 1 year of T2DM. We also excluded patients with less than 1 year of observation. Primary outcome was PC, and secondary outcomes were PC-related and all-cause mortality. Aspirin use was treated as time-varying variable (≥180 day-use/year) to address immortal-time bias, and multivariable Cox regression model was employed to derive adjusted HR (aHR). Propensity-score (PS) matching was used as secondary analysis.

RESULTS

Among 343 966 newly diagnosed patients with T2DM (median follow-up: 10.5 years; IQR: 7.7-14.5 years), 1224 (0.36%) developed PC. There were 51 151 (14.9%) deaths from any cause, and 787 (0.2%) died from PC. Aspirin use was associated with lower PC risk in both time-dependent (aHR: 0.58; 95% CI 0.49 to 0.69) and PS matching analysis (aHR: 0.61; 95% CI 0.48 to 0.77). An inverse relationship was observed with increasing dose and duration of aspirin use (P trend<0.001). Aspirin was also associated with a lower risk of PC-related mortality (aHR: 0.43; 95% CI 0.34 to 0.53) and all-cause mortality (aHR: 0.78; 95% CI 0.76 to 0.80).

CONCLUSION

Aspirin use may be an oncopreventive strategy to reduce PC risk in patients with T2DM. Further studies are warranted to validate the study findings.

FOSL1 drives the malignant progression of pancreatic cancer cells by regulating cell stemness, metastasis and multidrug efflux system

BACKGROUND

Targeted therapy is an effective strategy for the treatment of advanced and metastatic pancreatic cancer, one of the leading causes for cancer-related death worldwide. To address the limitations of existing targeted drugs, there is an urgently need to find novel targets and therapeutic strategies. Transcription factor FOS like 1 (FOSL1) is a potential therapeutic target for challenging pancreatic cancer, which contributes to the malignant progression and poor gnosis of pancreatic cancer. High mobility group A1 (HMGA1) is a nonhistone chromatin structural protein that contributes to malignant progression and poor prognosis of cancer.

METHODS

Human FOSL1 complete RNA, shRNA against FOSL1 and shRNA against HMGA1 lentiviral recombination vectors were used to overexpress FOSL1 and knock down FOSL1 and HMGA1. RNA sequencing, Q-PCR and Western blots were used to investigate the mechanism of FOSL1 in regulating the proliferation of pancreatic cancer cells. The relationship between FOSL1 and HMGA1 were analyzed by co-immunoprecipitation Mass spectrometry, Q-PCR of chromatin immunoprecipitation and Western blots. The regulation of FOSL1 and HMGA1 in the invasion and migration, stemness, and multidrug efflux system were determined by transwell assay, sphere formation assay, immunofluorescence, Q-PCR and Western blots.

RESULTS

We found that FOSL1 promoted the proliferation and progression of pancreatic cancer by trigging stemness, invasion and metastasis, and drug resistance. HMGA1 was a key downstream target regulated by FOSL1 at the transcriptional level and directly interacted with FOSL1. Knockdown of HMGA1 inhibited the proliferation of pancreatic cancer cells by regulating the expression of genes related to stemness, epithelial-mesenchymal transition and multidrug efflux system. Targeted inhibition of FOSL1 and HMGA1 expression significantly inhibited the proliferation of pancreatic cancer cells.

CONCLUSION

FOSL1 promote the malignant progression of pancreatic cancer by promoting HMGA1 expression. Targeting FOSL1 and HMGA1 in monotherapy or combination therapy is a promising strategy for the treatment of advanced and metastasis pancreatic cancer.

Exploring radiation resistance-related genes in pancreatic cancer and their impact on patient prognosis and treatment

Background

Pancreatic cancer is a highly lethal disease with increasing incidence worldwide. Despite surgical resection being the main curative option, only a small percentage of patients are eligible for surgery. Radiotherapy, often combined with chemotherapy, remains a critical treatment, especially for locally advanced cases. However, pancreatic cancer's aggressiveness and partial radio resistance lead to frequent local recurrence. Understanding the mechanisms of radiotherapy resistance is crucial to improving patient outcomes.

Methods

Pancreatic cancer related gene microarray data were downloaded from GEO database to analyze differentially expressed genes before and after radiotherapy using GEO2R online tool. The obtained differentially expressed genes were enriched by GO and KEGG to reveal their biological functions. Key genes were screened by univariate and multivariate Cox regression analysis, and a risk scoring model was constructed, and patients were divided into high-risk group and low-risk group. Subsequently, Kaplan-Meier survival analysis was used to compare the survival differences between the two groups of patients, further analyze the differential genes of the two groups of patients, and evaluate their sensitivity to different drugs.

Results

Our model identified 10 genes associated with overall survival (OS) in pancreatic cancer. Based on risk scores, patients were categorized into high- and low-risk groups, with significantly different survival outcomes and immune profile characteristics. High-risk patients showed increased expression of pro-inflammatory immune markers and increased sensitivity to specific chemotherapy agents, while low-risk patients had higher expression of immune checkpoints (CD274 and CTLA4), indicating potential sensitivity to targeted immunotherapies. Cross-dataset validation yielded consistent AUC values above 0.77, confirming model stability and predictive accuracy.

Conclusion

This study provides a scoring model to predict radiotherapy resistance and prognosis in pancreatic cancer, with potential clinical application for patient stratification. The identified immune profiles and drug sensitivity variations between risk groups highlight opportunities for personalized treatment strategies, contributing to improved management and survival outcomes in pancreatic cancer.

Claudin 18.2: An attractive marker in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDA) is a highly aggressive tumor with limited treatment options. Zolbetuximab, a monoclonal antibody against the tight junction protein Claudin 18.2 has recently been developed. At present, few and conflicting data have been reported regarding the clinical-pathological features of Claudin 18.2 expression in PDA. The present study investigated the expression of Claudin 18.2 in histological samples from PDA patients with the aim of verifying its utility as a therapeutic biomarker. Claudin 18.2 immunoreactivity was assessed by immunohistochemical staining on 70 formalin-fixed, paraffin-embedded PDA specimens (28 surgical specimens and 42 fine needle aspiration biopsies). The results obtained were associated with the clinicopathological characteristics and the survival rate of patients. Claudin 18.2 was detected only in neoplastic cells, not in normal pancreatic tissue. Claudin 18.2 was positive in 50% of samples and a higher expression was associated with well- and moderately-differentiated tumors and lymph node-negative status. The high expression of Claudin 18.2 in neoplastic tissue and absence in normal cells suggested that this protein had an attractive role in PDA as both a diagnostic and a prognostic-therapeutic marker. High expression of Claudin 18.2 in neoplastic tissue was associated with more favorable prognostic parameters and the high percentage of positive samples obtained suggests that Zolbetuximab may be suitable for a large number of patients.

PIWI-interacting RNA biomarkers in gastrointestinal disease

Detection and diagnosis of neoplastic and inflammatory gastrointestinal (GI) diseases are typically based on endoscopic and pathologic examination. In GI neoplastic diseases, diagnosis can be delayed due to the expense and invasive nature of this approach. Recently, PIWI-interacting RNAs (piRNAs), a group of small non-coding RNA molecules containing 24-31 nucleotides, have been thought to serve as biomarkers in many disease processes. For example, piRNAs are differentially expressed in GI cancer but their biologic role remains unclear. Using next-generation sequencing and microarray analyses, researchers have suggested that monitoring piRNAs could facilitate diagnosis and prognosis in GI disease. Herein, we reviewed the use of piRNAs in neoplastic, inflammatory, functional, and other diseases of the digestive system, which could shed new light on cancer screening, early detection, and personalized treatment.

Unlocking the potential of chimeric antigen receptor T cell engineering immunotherapy: Long road to achieve precise targeted therapy for hepatobiliary pancreatic cancers

Innovative therapeutic strategies are urgently needed to address the ongoing global health concern of hepatobiliary pancreatic malignancies. This review summarizes the latest and most comprehensive research of chimeric antigen receptor (CAR-T) cell engineering immunotherapy for treating hepatobiliary pancreatic cancers. Commencing with an exploration of the distinct anatomical location and the immunosuppressive, hypoxic tumor microenvironment (TME), this review critically assesses the limitations of current CAR-T therapy in hepatobiliary pancreatic cancers and proposes corresponding solutions. Various studies aim at enhancing CAR-T cell efficacy in these cancers through improving T cell persistence, enhancing antigen specificity and reducing tumor heterogeneity, also modulating the immunosuppressive and hypoxic TME. Additionally, the review examines the application of emerging nanoparticles and biotechnologies utilized in CAR-T therapy for these cancers. The results suggest that constructing optimized CAR-T cells to overcome physical barrier, manipulating the TME to relieve immunosuppression and hypoxia, designing CAR-T combination therapies, and selecting the most suitable delivery strategies, all together could collectively enhance the safety of CAR-T engineering and advance the effectiveness of adaptive cell therapy for hepatobiliary pancreatic cancers.

Trends in the Global Incidence of Pancreatic Cancer and a Brief Review of its Histologic and Molecular Subtypes

The global burden of pancreatic cancer has more than doubled in recent decades. It is now the sixth leading cause of cancer-related death worldwide, with an estimated 510,922 new cases and 467,409 deaths in 2022. The incidence of the disease continues to rise annually, with projections indicating a 95.4% increase in new cases by 2050, potentially reaching a total of 998,663 new cases globally. The overall five-year survival rate for pancreatic cancer is 10% worldwide, showing only a modest improvement compared to the past decade. The rising trends in the incidence rates are likely to continue as the global population ages and access to healthcare improves. The relatively low survival rate is primarily attributed to late-stage diagnoses and the lack of an effective screening method. Currently, population-based screening for asymptomatic individuals is not recommended, highlighting the importance of identifying and monitoring individuals at high risk for pancreatic cancer. Numerous studies have highlighted the differences in the molecular pathology of pancreatic cancer, underscoring the need for continued research to better understand these differences. The silent progression of the disease, poor prognosis, lack of screening options, and the necessity to improve our comprehension of its molecular characteristics emphasize the critical need for ongoing monitoring of disease trends at the population level. This review article analyses trends in the incidence of pancreatic cancer and its histological subtypes and provides an update on its molecular subtypes.

Examining the dietary contributions of lipids to pancreatic cancer burden (1990-2021): incidence trends and future projections

BACKGROUND

Pancreatic cancer (PC) ranks sixth globally among cancer deaths, imposing a significant burden on healthcare systems worldwide. Although diet is known to be a major risk factor, Although diet is a well-established risk factor for PC, the precise dietary components linked to the disease remain inconclusive, with studies showing varying results across different populations and regions. This study addresses this gap through a comprehensive analysis of PC incidence trends from 1990 to 2021, with a specific focus on associations with age, dietary patterns, and socio-demographic determinants.

METHODS

The data utilized in this study were obtained from the 2021 Global Burden of Disease (GBD) results database, updated on May 16, 2024. Unlike traditional single-variable correlation analyses, a Bayesian generalized linear model was applied to assess the association between food intake and disease incidence during the period 1990-2021. To account for variations related to year and region, these variables were incorporated as covariates in the model, allowing for a more nuanced and comprehensive analysis of the background factors. Finally, the "BAPC" package was employed to project age-standardized incidence rates of PC through the year 2051.

RESULTS

The global incidence of PC increased from 3.90 per 100,000 people (95% CI: 3.69, 4.08) in 1990 to 6.44 per 100,000 (95% CI: 5.86, 6.93) in 2021. The analysis revealed significant associations between PC incidence and the intake of nuts, omega-3 fatty acids, polyunsaturated fatty acids (PUFA), trans fats, dietary sodium, and calcium. In typical countries, higher intake of nuts and PUFA was associated with a reduced incidence of PC, while trans fats were positively correlated with increased incidence. The age-standardized Bayesian Age-Period-Cohort (BAPC) prediction indicates that the incidence rates of PC will show a downward trend after 2021.

CONCLUSIONS

From 1990 to 2021, the global incidence of PC exhibited a rapid upward trend, suggesting an increasing global healthcare burden. The findings of this study suggest that dietary lipid intake is significantly associated with PC incidence at a global level. This finding underscores the importance of dietary fat composition, particularly in the context of pancreatic cancer prevention, suggesting that individuals should pay attention to the types and sources of fats in their diets to mitigate disease risk.

Discovering Signature Disease Trajectories in Pancreatic Cancer and Soft-tissue Sarcoma from Longitudinal Patient Records

Understanding the disease trajectories of specific diseases can provide important clinical insights. In this paper, we aimed to discover signature disease trajectories of 3 rare cancer types: pancreatic cancer, soft tissue sarcoma (STS) of the trunk and extremity (STS-TE), and STS of the abdomen and retroperitoneum (STS-AR), leveraging IQVIA Oncology Electronic Medical Record. We identified significant diagnosis pairs in patients with these cancers through matched cohort sampling, statistical computation, right-tailed binomial hypothesis test, and visualized trajectories up to 3 progressions. Results included 266 significant diagnosis pairs for pancreatic cancer, 130 for STS-TE, and 118 for STS-AR. We further found 44 2-hop (i.e., 2-progression) and 136 3-hop trajectories before pancreatic cancer, 36 2-hop and 37 3-hop trajectories before STS-TE, and 17 2-hop and 5 3-hop trajectories before STS-AR. Meanwhile, we found 54 2-hop and 129 3-hop trajectories following pancreatic cancer, 11 2-hop and 17 3-hop trajectories following STS-TE, 5 2-hop and 0 3-hop trajectories following STS-AR. Systematic validation of discovered trajectories with the UTHealth Electronic Health Records confirmed the feasibility and reliability of our method. Our result suggested that some key clinical features can potentially serve as early markers of rare cancers. This approach is generalizable to other disease types and real-world longitudinal patient records.

Transcytosis-Triggering Nanoparticles for Overcoming Stromal Barriers and Reversing Immunosuppression in Pancreatic Cancer Combinatorial Therapy

In pancreatic ductal adenocarcinoma (PDAC), stromal cells and matrix proteins form a dense physical barrier that, while preventing the outward spread of tumor cells, also limits the penetration of drugs and CD8+ T cells inward. Additionally, the overactivated TGF-β/SMAD signaling pathway further promotes matrix proliferation and immune suppression. Therefore, crossing the stromal barrier while preserving the integrity of the stroma, releasing drugs intratumorally, remodeling the stroma, and activating the immune system is a promising drug delivery strategy. In this work, a type of enamine N-oxides modified nanoparticle was prepared, with stearic acid-modified gemcitabine prodrug (GemC18) and pSMAD2/3 inhibitor galunisertib encapsulated. The peripheral enamine N-oxides can trigger transcytosis and then respond to hypoxia and acidic microenvironments, turning the surface charge of the nanoparticles to a positive charge and enhancing penetration. The released galunisertib inhibits the TGF-β/SMAD signaling pathway, reshapes the matrix, activates antitumor immunity, and combines with gemcitabine (Gem) to kill tumor cells.

Predictive value of perioperative fasting blood glucose for post pancreatectomy diabetes mellitus in pancreatic ductal carcinoma patients

BACKGROUND

To explore the risk factors of post pancreatectomy diabetes mellitus (PPTDM)in pancreatic ductal carcinoma (PDAC) patients and the value of perioperative fasting blood glucose (FBG) level expression on the long-term survival after surgery.

MATERIALS AND METHODS

Between December 2015 and December 2019, a cohort of 509 patients diagnosed with PDAC and undergoing resection at our hospital was analyzed. They were stratified into two groups, Control group (Control) and study group (PPTDM), depending on the onset of postoperative diabetes mellitus. We analyzed the survival rates at 6 months, 12 months and 24 months post-operation in the two groups. We use univariate and logostic multivariate regressions to analyze the risk factors for PPTDM. ROC curve analysis was conducted to assess the diagnostic significance of perioperative FBG levels regarding patients' long-term survival rates. The Kaplan-Meier method was employed to assess the impact of both preoperative and postoperative FBG levels on the survival rates within 24 months for each patient group.

RESULTS

The comparison of general clinical data between the two groups shows marginal differences without statistical significance(P > 0.05); Patients in PPTDM group had significantly higher BMI, preoperative jaundice proportion, larger tumor diameter, higher TNM stage and higher proportion of distal pancreatectomy (DP), with P values of 0.023, 0.010, 0.040, 0.012 and 0.005, respectively. The levels of preoperative FBG and postoperative FBG in PPTDM patients exhibited statistically significant elevation compared to the control group (P < 0.05). There were no significant differences in surgery-related indicators between the two groups in operative time, number of dissected positive lymph nodes, total number of dissected lymph nodes, intraoperative blood loss and other related data (P > 0.05). Hospitalization duration of PPTDM patients was longer than control group (P = 0.047). PPTDM group had significantly higher expression concentrations of BUN, Cr, TG, LDL and Apo-B factors (P = 0.023, 0.024, 0.013, 0.045 and 0.017). 17 patients (5.03%) died in the PPTDM group and 4 patients (2.35%) in control group which had significantly difference (P = 0.020). In univariate and logostic multivariate regression analysis indicated tumor size, jaundice, BUN, Cr, TG, LDL, Apo-B concentrations and DP approach were significantly correlated to the risk for PPTDM (P < 0.05). ROC curve analysis results showed combining of preoperative and postoperation FBG showed the highest diagnostic efficacy, followed by postoperation FBG and preoperative FBG. The AUC areas of the three groups were 0.745, 0.623 and 0.588, respectively, and the critical values of the three groups were 9.81/9.95 mmol/L, 10.18 mmol/L and 10.23 mmol/L, respectively, with statistical significance (P < 0.05). Results were considered statistically significant if the p-value was less than 0.05.

CONCLUSION

PPTDM stands as a significant postoperative complication following pancreatic cancer surgery, characterized by a high incidence and severity. Several risk factors have garnered considerable attention among clinical surgeon. PPTDM may be an influential factor in postoperative prognosis of pancreatic cancer. The expression levels of preoperative and postoperative blood glucose hold diagnostic value for the long-term prognosis of pancreatic cancer patients. Early regulation and intervention by surgeons concerning perioperative FBG could potentially mitigate the risk of PPTDM.

Systematic review and meta-analysis: diagnostic accuracy of exosomes in pancreatic cancer

BACKGROUND

Early, non-invasive identification can generally enhance the survival rate for asymptomatic pancreatic cancer (PC). This systematic review and meta-analysis is conducted to evaluate the precision of diagnosing PC using serum and duodenal fluid exosomes.

METHODS

Following the guidelines of PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses), searches were conducted in the PubMed, Embase, Cochrane Library, and Web of Science databases in April 2024. A study was considered appropriate if it provided diagnostic precision and accuracy for patients with pancreatic cancer. The combined diagnostic impact was assessed by calculating the area beneath the aggregated SROC curve, and the quality of the studies included was evaluated using the QUADAS-2 checklist. All statistical evaluations and graphical representations utilized STATA 14.0.

RESULTS

Employing the terms "exosomes" and "pancreatic cancer" along with the search methodology, research was conducted across PubMed, Web of Science, Cochrane, and Embase databases. A total of 1202 studies were extracted from the databases, out of which nine were ultimately selected based on specific inclusion and exclusion standards. Across eight studies, exosomes were isolated from serum, while in a different one, they were taken from duodenal fluid. This document conducts subgroup analyses focusing on various types of exosome biomarkers, their origins, isolation techniques, and methods for analyzing biomarkers. Within the subset of exosome biomarker types, the group with exosomal cell surface proteoglycan exhibited the greatest combined sensitivity (0.96 (95% CI = 0.81-0.99) and specificity (0.90 (95% CI = 0.83-0.95)). Additionally, the set of exosomal cell surface proteoglycans showed the highest aggregated diagnostic ratio (215.92), combined positive likelihood ratio (9.96), area under the curve (0.93), and kombiniertes negative Likelihood-Ratio (0.05). The combined sensitivity of serum-derived exosomes stood at (0.86 (95% CI = 0.77-0.92)), the collective specificity at (0.83 (95% CI = 0.77-0.89)), the aggregate positive likelihood ratio at (5.22), the combined diagnostic ratio at (31.48), the overall area beneath the curve at (0.91), and the combined negative likelihood ratio at (0.17). Within the subgroup examination of exosome isolation techniques, ultracentrifugation emerged as the most sensitive method (0.90 (95% CI = 0.74-0.97)), the most specific method (0.89 (95% CI = 0.83-0.93)), the top positive likelihood ratio (8.35), the highest diagnostic ratio (76.48), the largest combined curve area (0.92), and the smallest negative likelihood ratio (0.11) in the aggregated data. Within the subset of biomarker analysis methods, the aggregate sensitivity via qRT-PCR was (0.84 (95% CI = 0.74-0.90)), the collective specificity (0.78 (95% CI = 0.64-0.87)), the aggregate diagnostic ratio (18.11), the aggregate area under the curve (0.88), the aggregate positive likelihood ratio (3.77), and the combined negative likelihood ratio (0.21).

CONCLUSION

Overall, exosomes are still valuable in the diagnosis of pancreatic cancer. In subgroup analyses, the proteoglycan found on exosomal cell surfaces is highly valuable for diagnosing pancreatic cancer. The more frequent separation method used in the nine included studies was ultracentrifugation, and it did demonstrate good data. Nonetheless, to verify their practicality and usefulness in clinical environments, a significant amount of clinical trials are still necessary.

Current Approaches of Pancreatic Cancer Surveillance in High-Risk Individuals

Currently, those recommended to undergo pancreatic cancer (PC) surveillance include appropriately aged individuals at high risk of PC due to an identifiable genetic susceptibility or those without identifiable genetic susceptibility who nonetheless have a strong family history of PC. With increases in identification of individuals at high risk for PC and increased use of PC surveillance in clinical practice, there has been increasing debate about who should undergo surveillance as well as how surveillance should be performed including use of imaging and blood-based testing. Furthermore, there is increasing interest in the outcomes of PC surveillance in high-risk individuals with some studies demonstrating that surveillance leads to downstaging of PC and improvements in survival. In this review, we summarize the current state of PC surveillance in high-risk individuals, providing an overview of the risk factors associated with PC, selection of high-risk individuals for PC surveillance, and the current, but non-uniform, recommendations for performing PC surveillance. Additionally, we review approaches to apply various imaging and blood-based tests to surveillance and the outcomes of PC surveillance.

Inhibition Effects and Mechanism Study of rAj-HRP30, a Recombinant Histidine-Rich Peptide from Apostichopus japonicus, on the Viability of Pancreatic Ductal Adenocarcinoma Cells Panc01 and Panc02

rAj-HRP30 is a recombinant peptide derived from the wild-type rAj-HRP of Apostichopus japonicus through a gene-shortening mutation. It has a high histidine content (53.3% in its primary structure) and a molecular weight of 3.919 kDa, classifying it as a histidine-rich peptide. The literature reports indicate that human histidine-rich peptides exhibit antitumor activity. Previous research by our group demonstrated similar properties in rAj-HRP, the precursor of rAj-HRP30. Therefore, this study used Panc01 (human) and Panc02 (mouse) cells-highly malignant models with limited targeted therapies-to investigate the antitumor activity and mechanisms of rAj-HRP30 and evaluate its potential for pancreatic cancer treatment. This study designed a gene-shortening strategy for rAj-HRP and artificially synthesized the gene sequence of rAj-HRP30. The cDNA sequence of rAj-HRP30 was cloned into the pET23b vector, and the recombinant plasmid pET23b-HRP30 was transformed into E. coli BL21 for expression. Following IPTG induction, the recombinant peptide was purified using nickel ion affinity chromatography, yielding rAj-HRP30 with a purity exceeding 95%. rAj-HRP30 markedly inhibited the adhesion, migration, and invasion of Panc01 and Panc02 cells. It also disrupted cellular morphology and cytoskeletal structure while inducing apoptosis. These effects were dose-dependent. After confirming the in vitro anticancer activity of rAj-HRP30, this study employed Panc02 cells as a model to investigate its inhibitory mechanisms using Western blot analysis. The results revealed that rAj-HRP30 reduced FGFR1 expression in Panc02 cells and inhibited the downstream FYN and FAK signaling pathways, subsequently blocking the PI3K/AKT signaling and apoptosis pathways. In the apoptotic pathway, rAj-HRP30 was able to downregulate the expression of Bcl-2, Caspase-9, Caspase-3, Caspase-7, and PARP1 and upregulate the expression of Bax, cleaved Caspase-9, cleaved Caspase-3, cleaved Caspase-7, and cleaved-PARP1 to induce apoptosis in Panc02 cells. Furthermore, rAj-HRP30 also downregulated the expression of MMP2 and MMP9, thereby inhibiting the migration and invasion of Panc02 cells. Conclusion: rAj-HRP30 exhibits significant inhibitory effects on pancreatic ductal adenocarcinoma Panc01 and Panc02 cells in vitro. Its mechanism involves FGFR1-related signaling and apoptosis pathways. rAj-HRP30 shows promise as a therapeutic agent targeting FGFR for pancreatic cancer.

Multidisciplinary Therapeutic Approaches to Pancreatic Cancer According to the Resectability Status

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers, characterized by late diagnosis, rapid progression, and limited therapeutic options. Despite advancements, only 20% of patients are eligible for surgical resection at diagnosis, the sole curative treatment. Multidisciplinary evaluation is critical to optimize care, stratifying patients based on resectability into resectable, borderline resectable, locally advanced, and metastatic stages. Preoperative imaging, such as computed tomography (CT) and endoscopic ultrasound (EUS), remains central for staging, for vascular assessment, and tissue acquisition. Endoscopic and systemic approaches are pivotal for addressing complications like biliary obstruction and improving outcomes. Endoscopic retrograde cholangiopancreatography (ERCP) has been considered for years the gold standard for biliary drainage, although EUS-guided drainage is increasingly utilized due to its efficacy in both resectable and unresectable disease. Systemic therapies play a key role in neoadjuvant, adjuvant, and palliative settings, with ongoing trials exploring their impact on survival and resectability chance. This review highlights the evolving multidisciplinary approaches tailored to the disease stage, focusing on biliary drainage techniques, systemic therapies, and their integration into comprehensive care pathways for PDAC. The continuous refinement of these strategies offers incremental survival benefits and underscores the importance of personalized, multidisciplinary management.

Global, regional, and national burden of pancreatic cancer from 1990 to 2021, its attributable risk factors, and projections to 2050: a systematic analysis of the global burden of disease study 2021

BACKGROUND

The incidence and mortality rates of pancreatic cancer are rising globally. This study examines global and regional trends in pancreatic cancer incidence, Disability Adjusted Life Years (DALYs), and mortality from 1990 to 2021, utilizing data from the most recent Global Burden of Disease (GBD) 2021 database.

METHODS

Data were sourced from the GBD database over the period from 1990 to 2021. Age-standardized rates for incidence, DALYs, and mortality were calculated per 100,000 population. We also calculated the proportion of DALYs and mortality attributable to risk factors. The Bayesian age-period-cohort model was applied to project future trends until 2050.

RESULTS

Between 1990 and 2021, the global incidence of pancreatic cancer increased significantly, with the number of cases rising from approximately 207,905 to 508,533 and the age-standardized incidence rate (ASIR) increasing from 5.47 to 5.96 per 100,000 population. The global burden of pancreatic cancer, measured in DALYs, rose from 5.21 million to 11.32 million. Mortality rates showed a similar upward trend, with the number of deaths increasing from around 211,613 to 505,752, and the age-standardized mortality rate (ASMR) rising from 5.655 to 5.948 per 100,000 population. Notable increases in ASIR and ASMR were observed in low-middle and low sociodemographic index regions with males experienced higher rates compared to females. Age-standardized DALYs rate (ASDR) and ASMR worldwide were attributable to tobacco smoking, high BMI, and high fasting plasma glucose. Furthermore, our projection model estimates that the ASIR and ASMR of pancreatic cancer will significantly decline, while the ASDR is anticipated to maintain a steady downward trend by 2050.

CONCLUSION

This study offers a comprehensive analysis of pancreatic cancer trends, providing crucial insights for public health planning and policy-making. Addressing identified risk factors and targeting high-risk populations are essential for effective strategies to reduce the global burden of pancreatic cancer.

THBS1 knockdown suppresses pancreatic cancer progression through JAK2/STAT3 signaling pathway

BACKGROUND

Thrombospondin 1 (THBS1), a secreted protein, is implicated in the progression of numerous cancers, yet its specific contributions to pancreatic cancer (PC) remain underexplored.

METHODS

The association between THBS1 levels and prognosis in PC was investigated. Functional experiments in vitro were used to determine the cell functions of siTHBS1 through CCK8 assay for cell proliferation, Muse® Cell Analyzer for apoptosis, and transwell assay for invasion and migration. Colivelin was applied in recovery experiment to investigate the mechanism of THBS1 regulating the JAK2/STAT3 pathway in BXPC-3 cell. In addition, the LV-shTHBS1 lentivirus was used to construct subcutaneous tumors in nude mice to verify the function of THBS1 in vivo.

RESULTS

THBS1 expression was elevated in PC and associated with a poorer prognosis. THBS1 was highly expressed in these PC cells. siTHBS1 repressed cell growth, migration and invasiveness, while promoting apoptosis of BXPC-3 cells. THBS1 suppression also led to a decrease in the phosphorylation of JAK2 and STAT3. JAK2/STAT3 signaling activator (Colivelin) could partially reverse the biological effects. In addition, shTHBS1 can suppress the growth of implanted tumors in nude mice.

CONCLUSIONS

THBS1 knockdown suppressed cell proliferation, migration, and invasion while enhanced cell apoptosis through the JAK2/STAT3 signaling pathway.

Arachidonic acid metabolism as a novel pathogenic factor in gastrointestinal cancers

Gastrointestinal (GI) cancers are a major global health burden, representing 20% of all cancer diagnoses and 22.5% of global cancer-related deaths. Their aggressive nature and resistance to treatment pose a significant challenge, with late-stage survival rates below 15% at five years. Therefore, there is an urgent need to delve deeper into the mechanisms of gastrointestinal cancer progression and optimize treatment strategies. Increasing evidence highlights the active involvement of abnormal arachidonic acid (AA) metabolism in various cancers. AA is a fatty acid mainly metabolized into diverse bioactive compounds by three enzymes: cyclooxygenase, lipoxygenase, and cytochrome P450 enzymes. Abnormal AA metabolism and altered levels of its metabolites may play a pivotal role in the development of GI cancers. However, the underlying mechanisms remain unclear. This review highlights a unique perspective by focusing on the abnormal metabolism of AA and its involvement in GI cancers. We summarize the latest advancements in understanding AA metabolism in GI cancers, outlining changes in AA levels and their potential role in liver, colorectal, pancreatic, esophageal, gastric, and gallbladder cancers. Moreover, we also explore the potential of targeting abnormal AA metabolism for future therapies, considering the current need to explore AA metabolism in GI cancers and outlining promising avenues for further research. Ultimately, such investigations aim to improve treatment options for patients with GI cancers and pave the way for better cancer management in this area.

Informatics strategies for early detection and risk mitigation in pancreatic cancer patients

This review provides a comprehensive overview of the current landscape in pancreatic cancer (PC) screening, diagnosis, and early detection. This emphasizes the need for targeted screening in high-risk groups, particularly those with familial predispositions and genetic mutations, such as BRCA1, BRCA2, and PALB2. This review highlights the sporadic nature of most PC cases and significant risk factors, including smoking, alcohol consumption, obesity, and diabetes. Advanced imaging techniques, such as Endoscopic Ultrasound (EUS) and Contrast-Enhanced Harmonic Imaging (CEH-EUS), have been discussed for their superior sensitivity in early detection. This review also explores the potential of novel biomarkers, including those found in body fluids, such as serum, plasma, urine, and bile, as well as the emerging role of liquid biopsy technologies in analyzing circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes. AI-driven approaches, such as those employed in Project Felix and CancerSEEK, have been highlighted for their potential to enhance early detection through deep learning and biomarker discovery. This review underscores the importance of universal genetic testing and the integration of AI with traditional diagnostic methods to improve outcomes in high-risk individuals. Additionally, this review points to future directions in PC diagnostics, including next-generation imaging, molecular biomarkers, and personalized medicine, aiming to overcome current diagnostic challenges and improve survival rates. Ultimately, the review advocates the adoption of informatics and AI-driven strategies to enhance early detection, reduce morbidity, and save lives in the fight against pancreatic cancer.

High prevalence of pancreatic steatosis in pancreatic cancer patients: A meta-analysis and systematic review

OBJECTIVE

In the last decade there has been increasing interest in defining pancreatic steatosis (PS) and establishing its association with pancreatic ductal adenocarcinoma (PDAC). However, no consensus guidelines have yet been published on the management of PS. In this systematic review and meta-analysis performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we investigated the association between PS and PDAC.

DESIGN

Medical literature between 2007 and 2023 was reviewed for eligible trials investigating the prevalence of PS in patients with PDAC. Eligible studies reporting on PS, assessed via imaging or histology, were included. The primary objective was to determine the association between PDAC and PS by comparing the prevalence of PS in individuals with- and without PDAC. Secondary, an evaluation was conducted to establish whether the method of assessment correlated with the association of PDAC and PS, and the prevalence of PDAC in individuals with PS. Measures of effect size were determined using odds ratios (ORs) and corresponding 95 % confidence intervals (95 % CI).

RESULTS

The systematic review identified a total of 23 studies, of which seventeen studies examined PS prevalence among PDAC patients and were included in the meta-analysis. Overall, the pooled prevalence of PS in patients with PDAC was 53.6 % (95 % CI 40.9-66.2). No significant difference in PS prevalence was observed across various diagnostic methods or geographical regions. Overall, the pooled OR for PS in patients with PDAC compared to controls was 3.23 (95 % CI 1.86-5.60).

CONCLUSIONS

PDAC patients have a high prevalence of PS, and they are significantly more likely to have PS compared to controls. These findings emphasize the need to prioritize a standardized approach to the diagnosis, follow-up, and treatment of PS, with future studies focusing on identifying patients who would benefit from PDAC surveillance programs.

The global, regional burden of pancreatic cancer and its attributable risk factors from 1990 to 2021

BACKGROUND

Pancreatic cancer is the 12th most common type of cancer, and the sixth leading cause of cancer-related mortality, worldwide. Up-to-date statistics on pancreatic cancer would provide us with a better understanding of epidemiology and identify the causative risk factors for the prevention of this disease.

METHODS

The degree and change patterns of exposure as well as the attributable cancer burden, including incidence, mortality, disability-adjusted life years (DALYs), and prevalence in global and regional, by sex, age, year, for pancreatic cancer, with the data extracted from the Global Burden of Diseases Study (GBD) 2021. All data analyses were conducted using linear regression analysis and the Joinpoint software (version 5.0.1).

RESULTS

In 2021, 508,533 new cases of pancreatic cancer have been reported; the mortality and prevalence rate increased to 5.95, and 5.12 respectively; and the global DALYs rate increased to 130.33 this year. Besides, the pancreatic cancer-associated rates of incidence, mortality, DALYs, and prevalence were higher in males than in females. In addition, these indicators in the high SDI (Sociodemographic index) region were higher than the global mean. To date, the high fasting plasma glucose remained the major risk factor that influenced the incidence, mortality, DALYs, and prevalence of pancreatic cancer, followed by tobacco and high body mass index (BMI).

CONCLUSIONS

Results of this study suggest that the burden of pancreatic cancer is increasing generally, therefore, more attention and measures should be taken to cope with this situation.

The burden and temporal trend of early onset pancreatic cancer based on the GBD 2021

In the context of the global increase in early-onset tumours, investigating the global disease burden caused by early-onset pancreatic cancer (EOPC) is imperative. Data on the burden of EOPC were obtained from the Global Burden of Disease Study 2021. A joinpoint regression model was used to analyse the temporal trend of the EOPC burden, and an age‒period‒cohort (APC) model was used to analyse the influence of age, period, and birth cohort on burden trends. Globally, the number of EOPC cases increased from 24,480 to 42,254, and the number of deaths increased from 17,193 to 26,996 between 1990 and 2021. The results of the APC model showed that the burden of EOPC increases with increasing age, whereas the variations in period and cohort effects exhibited a complex pattern across different sociodemographic index regions. Consequently, the disease burden of EOPC is increasing worldwide, highlighting the need for effective interventions.