Dyslipidemia in Chinese Pancreatic Cancer Patients: A Two-Center Retrospective Study

Robotic pancreaticoduodenectomy in patients with overweight or obesity: a meta-analysis protocol

INTRODUCTION

The prevalence of overweight or obesity among patients undergoing pancreaticoduodenectomy is on the rise. The utilisation of robotic assistance has the potential to enhance the feasibility of performing minimally invasive pancreaticoduodenectomy in this particular group of patients who are at a higher risk. The objective of this meta-analysis is to assess the safety and effectiveness of robotic pancreaticoduodenectomy in individuals with overweight or obesity.

METHODS AND ANALYSIS

This investigation will systematically search for randomised controlled trials (RCTs) and non-randomised comparative studies that compare robotic pancreaticoduodenectomy with open or laparoscopic pancreaticoduodenectomy in patients with overweight or obesity, using PubMed, Embase and the Cochrane Library databases. The methodological quality of studies will be evaluated using the Cochrane risk of bias tool for RCTs and the Newcastle-Ottawa Scale for observational studies. RevMan software (V.5.4.1) will be used for statistical analysis. The OR and weighted mean differences will be calculated separately for dichotomous and continuous data. The selection of a fixed-effects or random-effects model will depend on the level of heterogeneity observed among the included studies.

ETHICS AND DISSEMINATION

This study will be conducted based on data in the published literature from publicly available databases. Therefore, ethics approval is not applicable. The results will be disseminated in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42023462321.

Coupling magnetic levitation of graphene oxide–protein complexes with blood levels of glucose for early detection of pancreatic adenocarcinoma

Introduction

Pancreatic adenocarcinoma (PDAC) has a poor prognosis since often diagnosed too late. Dyslipidemia and hyperglycemia are considered risk factors, but the presence of the tumor itself can determine the onset of these disorders. Therefore, it is not easy to predict which subjects with diabetes or dyslipidemia will develop or have already developed PDAC. Over the past decade, tests based on the use of nanotechnology, alone or coupled with common laboratory tests (e.g., hemoglobin levels), have proven useful in aiding the diagnosis of PDAC. Tests based on magnetic levitation (MagLev) have demonstrated high diagnostic accuracy in compliance with the REASSURED criteria. Here, we aimed to assess the ability of the MagLev test in detecting PDAC when coupled with the blood levels of glycemia, cholesterol, and triglycerides.

Methods

Blood samples from 24 PDAC patients and 22 healthy controls were collected. Human plasma was let to interact with graphene oxide (GO) nanosheets and the emerging coronated systems were put in the MagLev device. Outcomes from Maglev experiments were coupled to glycemia, cholesterol, and triglycerides levels. Linear discriminant analysis (LDA) was carried out to evaluate the classification ability of the test in terms of specificity, sensitivity, and global accuracy. Statistical analysis was performed with Matlab (MathWorks, Natick, MA, USA, Version R2022a) software.

Results

The positions of the levitating bands were measured at the starting point (i.e., as soon as the cuvette containing the sample was subjected to the magnetic field). Significant variations in the starting position of levitating nanosystems in controls and PDACs were detected. The combination of the MagLev outcomes with the blood glycemic levels returned the best value of global accuracy (91%) if compared to the coupling with those of cholesterol and triglycerides (global accuracy of ~ 77% and 84%, respectively).

Conclusion

If confirmed by further studies on larger cohorts, a multiplexed Maglev-based nanotechnology-enabled blood test could be employed as a screening tool for PDAC in populations with hyperglycemia.

Mechanisms of obesity- and diabetes mellitus-related pancreatic carcinogenesis: a comprehensive and systematic review

Research on obesity- and diabetes mellitus (DM)-related carcinogenesis has expanded exponentially since these two diseases were recognized as important risk factors for cancers. The growing interest in this area is prominently actuated by the increasing obesity and DM prevalence, which is partially responsible for the slight but constant increase in pancreatic cancer (PC) occurrence. PC is a highly lethal malignancy characterized by its insidious symptoms, delayed diagnosis, and devastating prognosis. The intricate process of obesity and DM promoting pancreatic carcinogenesis involves their local impact on the pancreas and concurrent whole-body systemic changes that are suitable for cancer initiation. The main mechanisms involved in this process include the excessive accumulation of various nutrients and metabolites promoting carcinogenesis directly while also aggravating mutagenic and carcinogenic metabolic disorders by affecting multiple pathways. Detrimental alterations in gastrointestinal and sex hormone levels and microbiome dysfunction further compromise immunometabolic regulation and contribute to the establishment of an immunosuppressive tumor microenvironment (TME) for carcinogenesis, which can be exacerbated by several crucial pathophysiological processes and TME components, such as autophagy, endoplasmic reticulum stress, oxidative stress, epithelial-mesenchymal transition, and exosome secretion. This review provides a comprehensive and critical analysis of the immunometabolic mechanisms of obesity- and DM-related pancreatic carcinogenesis and dissects how metabolic disorders impair anticancer immunity and influence pathophysiological processes to favor cancer initiation.

Exploration of Risk Factors for Pancreatic Cancer and Development of a Clinical High-Risk Group Rating Scale

(1) Background: There are few studies on people at high risk for clinical pancreatic cancer (PC). We aimed to explore the risk factors of PC and establish a scale for identifying high-risk populations of clinical PC. (2) Methods: We conducted a matched case-control study, retrospectively collecting demographic data and common clinical indicators from all subjects. Logistic regression was used to explore the risk factors of PC. Based on these factors, we created a high-risk population rating scale, which showed a higher diagnostic value. (3) Results: 385 cases and 428 controls were finally enrolled in our study. Multivariate analysis showed that body mass index (BMI) below 18.5 kg/m2 (OR 5.944, 95%CI: 1.759~20.084), smoking (OR 2.745, 95%CI: 1.555~4.844), new-onset diabetes (OR 5.239, 95%CI: 2.091~13.125), low high-density lipoprotein cholesterol (HDL-C) levels (OR 1.790, 95%CI: 1.044~3.069), and carbohydrate antigen 19-9 (CA19-9) levels no less than 35 U/mL (OR 160.328, 95%CI: 83.392~308.243) were associated with an increased risk of PC, whereas high total cholesterol (TC) levels were related to a lower risk of PC (OR 0.392, 95%CI: 0.211~0.730). The high-risk population scale, whose area under the receiver operating curve reached 0.948 (p < 0.001), showed a greater clinical diagnostic value. (4) Conclusions: Smoking history, new-onset diabetes, BMI, TC, HDL-C, and CA19-9 levels were associated with the risk of PC. The high-risk population rating scale might be used for early clinical PC screening.

The characteristics of serum lipid spectrum in PanNENs and its correlation with clinicopathological features and prognosis

BACKGROUND

The role of dyslipidemia in pancreatic neuroendocrine tumors (PanNENs) is unclear. The aim of this study is to analyze the characteristics of serum lipid spectrum in PanNENs, and the effect of the variation in lipid profile on the development of PanNENs clinicopathological features and prognosis.

METHODS

All PanNENs patients between November 2012 and September 2020 in the authors' research center were identified from patient medical records and databases. A total of 185 with PanNENs patients were ultimately included in this study, including 100 nonfunctional PanNENs and 85 insulinomas. Clinicopathologic features, serum lipid level and overall survival results were retrospectively analyzed using statistical methods.

RESULTS

In 185 PanNENs, 95 (51.4%) patients appear to have dyslipidemia. Patients with insulinoma had a lower proportion of abnormal HDL than those with nonfunctional PanNENs (10.6% vs 23%, P=0.026). The mean serum HDL levels of insulinomas were 0.131 mmol/L higher than the NF-PanNENs (1.306 ± 0.324 vs 1.175 ± 0.315, P=0.006). In multivariate logistic analysis, high levels of HDL are negatively correlated to tumor size (OR 0.233, 95% CI: 0.069-0.790, P=0.019), but HDL was not associated with pathological grade or metastasis. And a correlation has been found between hypercholesterolemia and the original location of the tumor (OR:0.224, 95%CI: 0.066-0.753, P =0.016). In addition, the outcome of the survival analysis revealed that dyslipidemia did not influence the prognosis of PanNENs patients (P>0.05).

CONCLUSIONS

HDL was negatively correlated with the tumor size of PanNENs. The serum HDL level of insulinoma patients is higher than nonfunctional PanNENs.

The tangled web of dyslipidemia and cancer: Is there any association?

Cancer is a primary cause of mortality around the world and imposes a significant physiological, psychological, and financial burden on patients. Lipids regulate cell cycle progression and affect cell proliferation, migration, and apoptosis. Therefore, alterations in serum lipid levels might contribute to carcinogenesis. In this article, we review the relationships between triglyceride (TG), total cholesterol, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels and different types of cancer. Then, we examine the association between cancer and familial hypercholesterolemia. Finally, we evaluate the impact of statins on different types of cancer. Increased total cholesterol has been reported to increase cellular proliferation and angiogenesis in tumors and inhibit apoptosis. Increased LDL-C has been reported to induce inflammation and increase susceptibility to oxidative damage. HDL-C has anti-oxidation, anti-inflammatory, and antiproliferative properties. Increased levels of serum TG can induce oxidative stress and a chronic inflammatory state and therefore contribute to the proliferation and progression of cancer cells. Statins decrease downstream products of cholesterol synthesis that are crucial in cell proliferation and growth. Thus, lipid components can have prognostic value in cancer and management of serum lipid levels through lifestyle changes and medical therapy can be beneficial in cancer prevention and treatment.

Lipid metabolism in pancreatic cancer: emerging roles and potential targets

Pancreatic cancer is one of the most serious health issues in developed and developing countries, with a 5-year overall survival rate currently <9%. Patients typically present with advanced disease due to vague symptoms or lack of screening for early cancer detection. Surgical resection represents the only chance for cure, but treatment options are limited for advanced diseases, such as distant metastatic or locally progressive tumors. Although adjuvant chemotherapy has improved long-term outcomes in advanced cancer patients, its response rate is low. So, exploring other new treatments is urgent. In recent years, increasing evidence has shown that lipid metabolism can support tumorigenesis and disease progression as well as treatment resistance through enhanced lipid synthesis, storage, and catabolism. Therefore, a better understanding of lipid metabolism networks may provide novel and promising strategies for early diagnosis, prognosis estimation, and targeted therapy for pancreatic cancer patients. In this review, we first enumerate and discuss current knowledge about the advances made in understanding the regulation of lipid metabolism in pancreatic cancer. In addition, we summarize preclinical studies and clinical trials with drugs targeting lipid metabolic systems in pancreatic cancer. Finally, we highlight the challenges and opportunities for targeting lipid metabolism pathways through precision therapies in pancreatic cancer.