Blood levels of adiponectin and IL-1Ra distinguish type 3c from type 2 diabetes: Implications for earlier pancreatic cancer detection in new-onset diabetes

Biomarkers, omics and artificial intelligence for early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in its late stages when treatment options are limited. Unlike other common cancers, there are no population-wide screening programmes for PDAC. Thus, early disease detection, although urgently needed, remains elusive. Individuals in certain high-risk groups are, however, offered screening or surveillance. Here we explore advances in understanding high-risk groups for PDAC and efforts to implement biomarker-driven detection of PDAC in these groups. We review current approaches to early detection biomarker development and the use of artificial intelligence as applied to electronic health records (EHRs) and social media. Finally, we address the cost-effectiveness of applying biomarker strategies for early detection of PDAC.

Recommendations, evidence and sustainability of screening for pancreatic cancer in high-risk individuals

Pancreatic cancer is a highly lethal malignancy and is predicted to become the second leading cause of cancer-related deaths by 2030. Early detection significantly improves outcomes, but general population screening remains infeasible due to the low prevalence of the disease and lack of specific biomarkers. This review evaluates current recommendations for pancreatic cancer surveillance in high-risk individuals, synthesises evidence from recent studies and explores the sustainability of current imaging-based surveillance programmes. Challenges such as overdiagnosis, economic feasibility and disparities in access highlight the need for targeted, cost-effective strategies. Collaborative initiatives and consortia are needed to advance biomarker research and refine risk stratification. By integrating evidence-based recommendations with sustainable approaches, this review outlines pathways to improve early detection and reduce mortality from pancreatic cancer.

The Added Value of Blood Glucose Monitoring in High-Risk Individuals Undergoing Pancreatic Cancer Surveillance

OBJECTIVES

The study aimed to investigate the added value of blood glucose monitoring in high-risk individuals (HRIs) participating in pancreatic cancer surveillance.

MATERIALS AND METHODS

High-risk individuals with a CDKN2A/p16 germline pathogenic variant participating in pancreatic cancer surveillance were included in this study. Multivariable logistic regression was performed to assess the relationship between new-onset diabetes (NOD) and pancreatic ductal adenocarcinoma (PDAC). To quantify the diagnostic performance of NOD as a marker for PDAC, receiver operating characteristic curve with area under the curve was computed.

RESULTS

In total, 220 HRIs were included between 2000 and 2019. Median age was 61 (interquartile range. 53-71) years and 62.7% of participants were female. During the study period, 26 (11.8%) HRIs developed NOD, of whom 5 (19.2%) later developed PDAC. The other 23 (82.1%) PDAC cases remained NOD-free. Multivariable analysis showed no statistically significant relationship between NOD and PDAC (odds ratio, 1.21; 95% confidence interval, 0.39-3.78) and 4 of 5 PDAC cases seemed to have NOD within 3 months before diagnosis. Furthermore, NOD did not differentiate between HRIs with and without PDAC (area under the curve, 0.54; 95% confidence interval, 0.46-0.61).

CONCLUSIONS

In this study, we found no added value for longitudinal glucose monitoring in CDKN2A pathogenic variant carriers participating in an imaging-based pancreatic cancer surveillance program.

CD161+CD127+CD8+ T cell subsets can predict the efficacy of anti-PD-1 immunotherapy in non-small cell lung cancer with diabetes mellitus

The role of CD161+CD127+CD8+ T cells in non-small cell lung cancer (NSCLC) patients with diabetes remains unexplored. This study determined the prevalence, phenotype, and function of CD8+ T cell subsets in NSCLC with diabetes. We recruited NSCLC patients (n = 436) treated with anti-PD-1 immunotherapy as first-line treatment. The progression-free survival (PFS), overall survival (OS), T cells infiltration, and peripheral blood immunological characteristics were analyzed in NSCLC patients with or without diabetes. NSCLC patients with diabetes exhibited shorter PFS and OS (p = 0.0069 and p = 0.012, respectively) and significantly lower CD8+ T cells infiltration. Mass cytometry by time-of-flight (CyTOF) showed a higher percentage of CD161+CD127+CD8+ T cells among CD8+T cells in NSCLC with diabetes before anti-PD-1 treatment (p = 0.0071) than that in NSCLC without diabetes and this trend continued after anti-PD-1 treatment (p = 0.0393). Flow cytometry and multiple-immunofluorescence confirmed that NSCLC with diabetes had significantly higher CD161+CD127+CD8+ T cells to CD8+T cells ratios than NSCLC patients without diabetes. The RNA-sequencing analysis revealed immune-cytotoxic genes were reduced in the CD161+CD127+CD8+ T cell subset compared to CD161+CD127-CD8+ T cells in NSCLC with diabetes. CD161+CD127+CD8+ T cells exhibited more T cell-exhausted phenotypes in NSCLC with diabetes. NSCLC patients with diabetes with ≥ 6.3% CD161+CD127+CD8+ T cells to CD8+T cells ratios showed worse PFS. These findings indicate that diabetes is a risk factor for NSCLC patients who undergo anti-PD-1 immunotherapy.CD161+CD127+CD8+ T cells could be a key indicator of a poor prognosis in NSCLC with diabetes. Our findings would help in advancing anti-PD-1 therapy in NSCLC patients with diabetes.

Challenges of Managing Type 3c Diabetes in the Context of Pancreatic Resection, Cancer and Trauma

Type 3c diabetes mellitus (T3cDM), also known as pancreatogenic or pancreoprivic diabetes, is a specific type of DM that often develops as a result of diseases affecting the exocrine pancreas, exhibiting an array of hormonal and metabolic characteristics. Several pancreatic exocrine diseases and surgical procedures may cause T3cDM. Diagnosing T3cDM remains difficult as the disease characteristics frequently overlap with clinical presentations of type 1 DM (T1DM) or type 2 DM (T2DM). Managing T3cDM is likewise challenging due to numerous confounding metabolic dysfunctions, including pancreatic endocrine and exocrine insufficiencies and poor nutritional status. Treatment of pancreatic exocrine insufficiency is of paramount importance when managing patients with T3cDM. This review aims to consolidate the latest information on surgical etiologies of T3cDM, focusing on partial pancreatic resections, total pancreatectomy, pancreatic cancer and trauma.

Leucine rich repeat LGI family member 3: Integrative analyses support its prognostic association with pancreatic adenocarcinoma

Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Previous studies of our group have reported that LGI3 is expressed in adipose tissue, skin and brain, and serves as a multifunctional cytokine. LGI3 may also be involved in cytokine networks in various cancers. This study aimed to analyze differentially expressed genes in pancreatic adenocarcinoma (PAC) tissues and PAC cohort data in order to evaluate the prognostic role of LGI3. The expression microarray and the PAC cohort data were analyzed by bioinformatic methods for differential expression, protein-protein interactions, functional enrichment and pathway analyses, gene co-expression network analysis, and prognostic association analysis. Results showed that LGI3 expression was significantly reduced in PAC tissues. Nineteen upregulated genes and 31 downregulated genes in PAC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that 92% (46/50) of the LGI3-regulated genes that were altered in PACs belonged to a protein-protein interaction network cluster. Functional enrichment and gene co-expression network analyses demonstrated that these genes in the network cluster were associated with various processes including inflammatory and immune responses, metabolic processes, cell differentiation, and angiogenesis. PAC cohort analyses revealed that low expression levels of LGI3 were significantly associated with poor PAC prognosis. Analysis of favorable or unfavorable prognostic gene products in PAC showed that 93 LGI3-regulated genes were differentially associated with PAC prognosis. LGI3 expression was correlated with the tumor-infiltration levels of various immune cells. Taken together, these results suggested that LGI3 may be a potential prognostic marker of PAC.

Interleukin-1 receptor antagonist: An alternative therapy for cancer treatment

The interleukin-1 receptor antagonist (IL-1Ra) is an anti-inflammatory cytokine and a naturally occurring antagonist of the IL-1 receptor. It effectively counteracts the IL-1 signaling pathway mediated by IL-1α/β. Over the past few decades, accumulating evidence has suggested that IL-1 signaling plays an essential role in tumor formation, growth, and metastasis. Significantly, anakinra, the first United States Food and Drug Administration (FDA)-approved IL-1Ra drug, has demonstrated promising antitumor effects in animal studies. Numerous clinical trials have subsequently incorporated anakinra into their cancer treatment protocols. In this review, we comprehensively discuss the research progress on the role of IL-1 in tumors and summarize the significant contribution of IL-1Ra (anakinra) to tumor immunity. Additionally, we analyze the potential value of IL-1Ra as a biomarker from a clinical perspective. This review is aimed to highlight the important link between inflammation and cancer and provide potential drug targets for future cancer therapy.

Genome, Metabolism, or Immunity: Which Is the Primary Decider of Pancreatic Cancer Fate through Non-Apoptotic Cell Death?

Pancreatic ductal adenocarcinoma (PDAC) is a solid tumor characterized by poor prognosis and resistance to treatment. Resistance to apoptosis, a cell death process, and anti-apoptotic mechanisms, are some of the hallmarks of cancer. Exploring non-apoptotic cell death mechanisms provides an opportunity to overcome apoptosis resistance in PDAC. Several recent studies evaluated ferroptosis, necroptosis, and pyroptosis as the non-apoptotic cell death processes in PDAC that play a crucial role in the prognosis and treatment of this disease. Ferroptosis, necroptosis, and pyroptosis play a crucial role in PDAC development via several signaling pathways, gene expression, and immunity regulation. This review summarizes the current understanding of how ferroptosis, necroptosis, and pyroptosis interact with signaling pathways, the genome, the immune system, the metabolism, and other factors in the prognosis and treatment of PDAC.

A protein-based machine learning approach to the identification of inflammatory subtypes in pancreatic ductal adenocarcinoma

BACKGROUND/OBJECTIVES

The inherently immunosuppressive tumor microenvironment along with the heterogeneity of pancreatic ductal adenocarcinoma (PDAC) limits the effectiveness of available treatment options and contributes to the disease lethality. Using a machine learning algorithm, we hypothesized that PDAC may be categorized based on its microenvironment inflammatory milieu.

METHODS

Fifty-nine tumor samples from patients naïve to treatment were homogenized and probed for 41 unique inflammatory proteins using a multiplex assay. Subtype clustering was determined using t-distributed stochastic neighbor embedding (t-SNE) machine learning analysis of cytokine/chemokine levels. Statistics were performed using Wilcoxon rank sum test and Kaplan-Meier survival analysis.

RESULTS

t-SNE analysis of tumor cytokines/chemokines revealed two distinct clusters, immunomodulating and immunostimulating. In pancreatic head tumors, patients in the immunostimulating group (N = 26) were more likely to be diabetic (p = 0.027), but experienced less intraoperative blood loss (p = 0.0008). Though there were no significant differences in survival (p = 0.161), the immunostimulating group trended toward longer median survival by 9.205 months (11.28 vs. 20.48 months).

CONCLUSION

A machine learning algorithm identified two distinct subtypes within the PDAC inflammatory milieu, which may influence diabetes status as well as intraoperative blood loss. Opportunity exists to further explore how these inflammatory subtypes may influence treatment response, potentially elucidating targetable mechanisms of PDAC's immunosuppressive tumor microenvironment.

Assessment of the Role of Leptin and Adiponectinas Biomarkers in Pancreatic Neuroendocrine Neoplasms

Data on the possible connection between circulating adipokines and PanNENs are limited. This novel study aimed to assess the serum levels of leptin and adiponectin and their ratio in patients with PanNENs and to evaluate the possible relationship between them and PanNEN's grade or stage, including the presence of metastases. The study group consisted of PanNENs (n = 83), and healthy controls (n = 39). Leptin and adiponectin measurement by an ELISA assay was undertaken in the entire cohort. The serum concentration of adiponectin was significantly higher in the control group compared to the study group (p < 0.001). The concentration of leptin and adiponectin was significantly higher in females than in males (p < 0.01). Anincreased leptin-adiponectin ratio was observed in well-differentiated PanNENs (G1) vs. moderatelydifferentiated PanNENs (G2) (p < 0.05). An increased leptin-adiponectin ratio was found in PanNENs with Ki-67 < 3% vs. Ki-67 ≥ 3% (p < 0.05). PanNENs with distal disease presented lower leptin levels (p < 0.001) and a decreased leptin-adiponectin ratio (p < 0.01) compared with the localized disease group. Leptin, adiponectin, and the leptin-adiponectin ratio may serve as potential diagnostic, prognostic, and predictive biomarkers for PanNENs. Leptin levels and the leptin-adiponectin ratio may play an important role as predictors of malignancy and metastasis in PanNENs.

Role of Pancreatic Tumour-Derived Exosomes and Their Cargo in Pancreatic Cancer-Related Diabetes

One of the most common and deadly types of pancreatic cancer (PC) is pancreatic ductal adenocarcinoma (PDAC), with most patients succumbing to the disease within one year of diagnosis. Current detection strategies do not address asymptomatic PC; therefore, patients are diagnosed at an advanced stage when curative treatment is often no longer possible. In order to detect PC in asymptomatic patients earlier, the risk factors that could serve as reliable markers need to be examined. Diabetic mellitus (DM) is a significant risk factor for this malignancy and can be both a cause and consequence of PC. Typically, DM caused by PC is known as new-onset, pancreatogenic, pancreoprivic, or pancreatic cancer-related diabetes (PCRD). Although PCRD is quite distinct from type 2 DM (T2DM), there are currently no biomarkers that differentiate PCRD from T2DM. To identify such biomarkers, a better understanding of the mechanisms mediating PCRD is essential. To this end, there has been a growing research interest in recent years to elucidate the role of tumour-derived exosomes and their cargo in the pathogenesis of PCRD. Exosomes derived from tumours can be recognized for their specificity because they reflect the characteristics of their parent cells and are important in intercellular communication. Their cargo consists of proteins, lipids, and nucleic acids, which can be transferred to and alter the behaviour of recipient cells. This review provides a concise overview of current knowledge regarding tumour-derived exosomes and their cargo in PCRD and discusses the potential areas worthy of further study.

Glycemic Abnormalities in Pancreatic Cystic Lesions—A Single-Center Retrospective Analysis

Background and Objectives: Glucose metabolism alterations are very common in solid pancreatic lesions, particularly in pancreatic cancer. Similarly, diabetes and especially new-onset diabetes (NOD) have been associated with the malignant transformation of pancreatic cysts. We aimed to assess the prevalence and relevant associations of glycemic abnormalities in pancreatic cystic lesions (PCLs) in a retrospective analysis. Materials and Methods: We retrospectively recruited all patients who underwent endoscopic ultrasound for a PCL over a period of 36 months (January 2018 to December 2021). Final diagnosis was set by means of tissue acquisition, surgery, follow-up, or board decision. Demographic and clinical data, laboratory workup, and imaging features were extracted from the patients’ charts according to a predefined protocol. We considered fasting blood glucose (FBG) and HbA1c values and stratified the patients as nondiabetic (FBG ≤ 99 mg/dL, HbA1c ≤ 5.6%, no history of glycemic abnormalities), prediabetic (FBG 100–125 mg/dL, HbA1c 5.7–6.4%), or diabetic (long-lasting diabetes or NOD). Results: Altogether, 81 patients were included, with a median age of 66 years, and 54.3% of them were male. The overall prevalence of fasting hyperglycemia was 54.3%, comprising 34.6% prediabetes and 22.2% diabetes, of which 16.7% had NOD. The mean FBG and HbA1c levels were higher in malignant and premalignant PCLs (intraductal papillary mucinous neoplasm (IPMN), mucinous cystic neoplasm (MCN), cystadenocarcinoma, and cystic neuroendocrine tumor) compared to the benign lesions (pseudocysts, walled-off necrosis, and serous cystadenoma): 117.0 mg/dL vs. 108.3 mg/dL and 6.1% vs. 5.5%, respectively. Conclusions: Hyperglycemia and diabetes are common in PCLs, with a high prevalence in premalignant and malignant cysts. Screening and follow-up for glycemic abnormalities should be routinely conducted for PCLs, as they can contribute to a tailored risk assessment of cysts.

Glycemic Abnormalities in Pancreatic Cystic Lesions—A Single-Center Retrospective Analysis

Background and Objectives: Glucose metabolism alterations are very common in solid pancreatic lesions, particularly in pancreatic cancer. Similarly, diabetes and especially new-onset diabetes (NOD) have been associated with the malignant transformation of pancreatic cysts. We aimed to assess the prevalence and relevant associations of glycemic abnormalities in pancreatic cystic lesions (PCLs) in a retrospective analysis. Materials and Methods: We retrospectively recruited all patients who underwent endoscopic ultrasound for a PCL over a period of 36 months (January 2018 to December 2021). Final diagnosis was set by means of tissue acquisition, surgery, follow-up, or board decision. Demographic and clinical data, laboratory workup, and imaging features were extracted from the patients’ charts according to a predefined protocol. We considered fasting blood glucose (FBG) and HbA1c values and stratified the patients as nondiabetic (FBG ≤ 99 mg/dL, HbA1c ≤ 5.6%, no history of glycemic abnormalities), prediabetic (FBG 100–125 mg/dL, HbA1c 5.7–6.4%), or diabetic (long-lasting diabetes or NOD). Results: Altogether, 81 patients were included, with a median age of 66 years, and 54.3% of them were male. The overall prevalence of fasting hyperglycemia was 54.3%, comprising 34.6% prediabetes and 22.2% diabetes, of which 16.7% had NOD. The mean FBG and HbA1c levels were higher in malignant and premalignant PCLs (intraductal papillary mucinous neoplasm (IPMN), mucinous cystic neoplasm (MCN), cystadenocarcinoma, and cystic neuroendocrine tumor) compared to the benign lesions (pseudocysts, walled-off necrosis, and serous cystadenoma): 117.0 mg/dL vs. 108.3 mg/dL and 6.1% vs. 5.5%, respectively. Conclusions: Hyperglycemia and diabetes are common in PCLs, with a high prevalence in premalignant and malignant cysts. Screening and follow-up for glycemic abnormalities should be routinely conducted for PCLs, as they can contribute to a tailored risk assessment of cysts.

Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning

BACKGROUND

Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough.

METHODS

The primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets.

RESULTS

Here we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75-1.0), sensitivity of 92% (95% CI 0.54-1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74-0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17-0.83, at 90% specificity).

CONCLUSIONS

The ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.

Role of Up-Regulated Transmembrane Channel-Like Protein 5 in Pancreatic Adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is a malignant tumor responsible for a heavy disease burden. Previously, only one pan-cancer study of Transmembrane channel-like protein 5 (TMC5) showed that TMC5 was highly expressed in PAAD, but the results lacked comprehensive verification, and the mechanism of TMC5 in PAAD was still unclear.

METHODS

For exploring the expression and clinical value of TMC5 in PAAD better, we adopted a comprehensive evaluation method, using internal immunohistochemistry (IHC) data combined with microarray and RNA-sequencing data collected from public databases. The single cell RNA-sequencing (scRNA-seq) data were exploited to explore the TMC5 expression in cell populations and intercellular communication. The potential mechanism of TMC5 in PAAD was analyzed from the aspects of immune infiltration, transcriptional regulation, function and pathway enrichment.

RESULTS

Our IHC data includes 148 PAAD samples and 19 non-PAAD samples, along with the available microarray and RNA-sequencing data (1166 PAAD samples, 704 non-PAAD samples). The comprehensive evaluation results showed that TMC5 was evidently up-regulated in PAAD (SMD = 1.17). Further analysis showed that TMC5 was over-expressed in cancerous epithelial cells. Furthermore, TMC5 was up-regulated in more advanced tumor T and N stages. Interestingly, we found that STAT3 as an immune marker of Th17 cells was not only positively correlated with TMC5 and up-regulated in PAAD tissues, but also the major predicted TMC5 transcription regulator. Moreover, STAT3 was involved in cancer pathway of PAAD.

CONCLUSION

Up-regulated TMC5 indicates advanced tumor stage in PAAD patients, and its role in promoting PAAD development may be regulated by STAT3.

Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma cancer (PDAC) is a highly lethal malignancy requiring efficient detection when the primary tumor is still resectable. We previously developed the MxPancreasScore comprising 9 analytes and serum carbohydrate antigen 19-9 (CA19-9), achieving an accuracy of 90.6%. The necessity for 5 different analytical platforms and multiple analytical runs, however, hindered clinical applicability. We therefore aimed to develop a simpler single-analytical run, single-platform diagnostic signature.

METHODS

We evaluated 941 patients (PDAC, 356; chronic pancreatitis [CP], 304; nonpancreatic disease, 281) in 3 multicenter independent tests, and identification (ID) and validation cohort 1 (VD1) and 2 (VD2) were evaluated. Targeted quantitative plasma metabolite analysis was performed on a liquid chromatography-tandem mass spectrometry platform. A machine learning-aided algorithm identified an improved (i-Metabolic) and minimalistic metabolic (m-Metabolic) signatures, and compared them for performance.

RESULTS

The i-Metabolic Signature, (12 analytes plus CA19-9) distinguished PDAC from CP with area under the curve (95% confidence interval) of 97.2% (97.1%-97.3%), 93.5% (93.4%-93.7%), and 92.2% (92.1%-92.3%) in the ID, VD1, and VD2 cohorts, respectively. In the VD2 cohort, the m-Metabolic signature (4 analytes plus CA19-9) discriminated PDAC from CP with a sensitivity of 77.3% and specificity of 89.6%, with an overall accuracy of 82.4%. For the subset of 45 patients with PDAC with resectable stages IA-IIB tumors, the sensitivity, specificity, and accuracy were 73.2%, 89.6%, and 82.7%, respectively; for those with detectable CA19-9 >2 U/mL, 81.6%, 88.7%, and 84.5%, respectively; and for those with CA19-9 <37 U/mL, 39.7%, 94.1%, and 76.3%, respectively.

CONCLUSIONS

The single-platform, single-run, m-Metabolic signature of just 4 metabolites used in combination with serum CA19-9 levels is an innovative accurate diagnostic tool for PDAC at the time of clinical presentation, warranting further large-scale evaluation.

United Kingdom Early Detection Initiative (UK-EDI): protocol for establishing a national multicentre cohort of individuals with new-onset diabetes for early detection of pancreatic cancer

INTRODUCTION

Pancreatic cancer is a leading cause of cancer deaths worldwide. Screening for this disease has potential to improve survival. It is not feasible, with current screening modalities, to screen the asymptomatic adult population. However, screening of individuals in high-risk groups is recommended. Our study aims to provide resources and data that will inform strategies to screen individuals with new-onset diabetes (NOD) for pancreatic cancer.

METHODS AND ANALYSIS

The United Kingdom Early Detection Initiative (UK-EDI) for pancreatic cancer is a national, prospective, observational cohort study that aims to recruit 2500 individuals with NOD (<6 months postdiagnosis) aged 50 years and over, with follow-up every 6 months, over a 3-year period. For study eligibility, diagnosis of diabetes is considered to be clinical measurement of haemoglobin A1c ≥48 mmol/mol. Detailed clinical information and biospecimens will be collected at baseline and follow-up to support the development of molecular, epidemiological and demographic biomarkers for earlier detection of pancreatic cancer in the high-risk NOD group. Socioeconomic impacts and cost-effectiveness of earlier detection of pancreatic cancer in individuals with NOD will be evaluated. The UK-EDI NOD cohort will provide a bioresource for future early detection research to be conducted.

ETHICS AND DISSEMINATION

The UK-EDI study has been reviewed and approved by the London-West London and GTAC Research Ethics Committee (Ref 20/LO/0058). Study results will be disseminated through presentations at national and international symposia and publication in peer-reviewed, Open Access journals.

Pancreatic cancer, pancreatogenic diabetes, type 2 diabetes mellitus

Pancreatic cancer (PC) is the fourth leading cause of death among all types of cancer. PC is very aggressive with a low 5-year overall survival rate. The highest prevalence of diabetes mellitus (DM), significantly exceeding the average population, is registered among patients with prostate cancer Recommendations for systemic screening of patients with diabetes for the detection of PC are not standardized. The purpose of this review is to present an analysis of current literature data on pathogenetic relationships between DM and PC and prospects for PC screening. Research data indicate that there is a bidirectional relationship between DM and PC, in which DM can act either as a risk factor for PC or as a marker of paraneoplastic syndrome of PC. In the differential diagnosis of type 2 diabetes, pancreatogenic diabetes and diabetes associated with PC, a set of clinical signs can be used. Patients with DM who have additional signs/symptoms of increased risk can be considered as a group subject to mandatory screening. Numerous studies of various proteomic, metabolomic, genetic and transcriptomic biomarkers PC have been published. The search for an easy-to-use clinically useful and cost-effective PC marker is still ongoing.

Obesity and Pancreatic Cancer: Recent Progress in Epidemiology, Mechanisms and Bariatric Surgery

More than 30% of people in the United States (US) are classified as obese, and over 50% are considered significantly overweight. Importantly, obesity is a risk factor not only for the development of metabolic syndrome but also for many cancers, including pancreatic ductal adenocarcinoma (PDAC). PDAC is the third leading cause of cancer-related death, and 5-year survival of PDAC remains around 9% in the U.S. Obesity is a known risk factor for PDAC. Metabolic control and bariatric surgery, which is an effective treatment for severe obesity and allows massive weight loss, have been shown to reduce the risk of PDAC. It is therefore clear that elucidating the connection between obesity and PDAC is important for the identification of a novel marker and/or intervention point for obesity-related PDAC risk. In this review, we discussed recent progress in obesity-related PDAC in epidemiology, mechanisms, and potential cancer prevention effects of interventions, including bariatric surgery with preclinical and clinical studies.

The Role of Nonapoptotic Programmed Cell Death — Ferroptosis, Necroptosis, and Pyroptosis — in Pancreatic Ductal Adenocarcinoma Treatment

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer, with a dismal 5-year survival rate of less than 10%. It is estimated that approximately 80% of pancreatic ductal carcinoma (PDAC) patients are diagnosed at an advanced or metastatic stage. Hence, most patients are not appropriate candidates for surgical resection and therefore require systemic chemotherapy. However, it has been reported that most patients develop chemoresistance within several months, partly because of antiapoptotic mechanisms. Hence, inducing alternative programmed cell death (PCD), including ferroptosis, necroptosis or pyroptosis, seems to be a promising strategy to overcome antiapoptosis-mediated chemoresistance. In this review, we shed light on the molecular mechanisms of ferroptosis, necroptosis and pyroptosis and suggest several potential strategies (e.g., compounds and nanoparticles [NPs]) that are capable of triggering nonapoptotic PCD to suppress PDAC progression. In conclusion, these strategies might serve as adjuvants in combination with clinical first-line chemotherapies to improve patient survival rates.