Glucose metabolism during tumorigenesis in the genetic mouse model of pancreatic cancer

Establishment of a Transplantation Model of PDAC-Derived Liver Metastases

BACKGROUND

The highly metastatic nature of pancreatic ductal adenocarcinoma (PDAC) and the difficulty to achieve favorable patient outcomes emphasize the need for novel therapeutic solutions. For preclinical evaluations, genetically engineered mouse models are often used to mimic human PDAC but frequently fail to replicate synchronous development and metastatic spread. This study aimed to develop a transplantation model to achieve synchronous and homogenous PDAC growth with controlled metastatic patterns in the liver.

METHODS

To generate an orthotopic PDAC model, the DT6606 cell line was injected into the pancreas head of C57BL/6 mice, and their survival was monitored over time. To generate a heterotopic transplantation model, growing doses of three PDAC cell lines (DT6606, DT6606lm, and K8484) were injected into the portal vein of mice. Magnetic resonance imaging (MRI) was used to monitor metastatic progression, and histologic analysis was performed.

RESULTS

Orthotopically injected mice succumbed to the tumor within an 11-week period (average survival time, 78.2 ± 4.45 days). Post-mortem examinations failed to identify liver metastasis. In the intraportal model, 2 × 105 DT6606 cells resulted in an absence of liver metastases by day 21, whereas 5 × 104 DT6606lm cells and 7 × 104 K8484 cells resulted in steady metastatic growth. Higher doses caused significant metastatic liver involvement. The use of K8484 cells ensured the growth of tumors closely resembling the histopathologic characteristics of human PDAC.

CONCLUSIONS

This report details the authors' efforts to establish an "optimal" murine model for inducing metastatic PDAC, which is critical for advancing our understanding of the disease and developing more effective treatments.

Metabolic responses to the occurrence and chemotherapy of pancreatic cancer: biomarker identification and prognosis prediction

As the most malignant tumor, the prognosis of pancreatic cancer is not ideal even in the small number of patients who can undergo radical surgery. As a highly heterogeneous tumor, chemotherapy resistance is a major factor leading to decreased efficacy and postoperative recurrence of pancreatic cancer. In this study, nuclear magnetic resonance (NMR)-based metabolomics was applied to identify serum metabolic characteristics of pancreatic ductal adenocarcinoma (PDAC) and screen the potential biomarkers for its diagnosis. Metabolic changes of patients with different CA19-9 levels during postoperative chemotherapy were also monitored and compared to identify the differential metabolites that may affect the efficacy of chemotherapy. Finally, 19 potential serum biomarkers were screened to serve the diagnosis of PDAC, and significant metabolic differences between the two CA19-9 stratifications of PDAC were involved in energy metabolism, lipid metabolism, amino acid metabolism, and citric acid metabolism. Enrichment analysis of metabolic pathways revealed six shared pathways by PDAC and chemotherapy such as alanine, aspartate and glutamate metabolism, arginine biosynthesis, glutamine and glutamate metabolism, citrate cycle, pyruvate metabolism, and glycogolysis/gluconeogeneis. The similarity between the metabolic characteristics of PDAC and the metabolic responses to chemotherapy provided a reference for clinical prediction of benefits of postoperative chemotherapy in PDAC patients.

Dynamics of intestinal and intratumoral microbiome signatures in genetically engineered mice and human pancreatic ductal adenocarcinoma

BACKGROUND

Emerging evidence has recently revealed a prominent role of the microbiome in pancreatic ductal adenocarcinoma (PDAC). However, while most observations were made in patients, mouse models still require a precise characterization of their disease-related microbiome to employ them for mechanistic and interventional preclinical studies.

METHODS

To investigate the fecal and tumoral microbiome of LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) and control (CTRL) mice, Oxford Nanopore sequencing was applied. Feces were collected from 10 KPC mice and 10 CTRLs at 3 timepoints (6 weeks, 12 weeks, and when tumor-bearing (KPC) or 6 months (CTRL), respectively). Metagenomic sequencing was performed on feces DNA. KPC tumor and healthy pancreas DNA samples were subjected to 16S rRNA gene sequencing. Bacterial marker components were detected in KPC tumor tissue over time by fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC).

RESULTS

Murine fecal samples showed a significantly different microbiome compared to age-matched healthy CTRLs regarding beta diversity (p = 0.001, R2 = 0.2-0.25 for Bray-Curtis). Adjusted human PDAC classifiers predicted disease status from feces of KPC mice achieving area under the receiver operating characteristic (AUROC) values of 80%. Furthermore, KPC tumors harbored significantly more bacterial components than healthy pancreas. Also the microbial composition differs significantly between KPC tumors and healthy pancreas tissue (p = 0.042 for Bray-Curtis). Microbiota found highly abundant in human PDAC samples were considerably more abundant in KPC tumors as compared to healthy pancreas samples (p-value <0.001).

CONCLUSION

KPC fecal samples show similarities with the microbial composition of stool samples from human PDAC patients.

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.

Obesity-Associated Cancers: Evidence from Studies in Mouse Models

Obesity, one of the major problems in modern human society, is correlated with various diseases, including type 2 diabetes mellitus (T2DM). In particular, epidemiological and experimental evidence indicates that obesity is closely linked to at least 13 different types of cancer. The mechanisms that potentially explain the link between obesity and cancer include hyperactivation of the IGF pathway, metabolic dysregulation, dysfunctional angiogenesis, chronic inflammation, and interaction between pro-inflammatory cytokines, endocrine hormones, and adipokines. However, how the largely uniform morbidity of obesity leads to different types of cancer still needs to be investigated. To study the link between obesity and cancer, researchers have commonly used preclinical animal models, particularly mouse models. These models include monogenic models of obesity (e.g., ob/ob and db/db mice) and genetically modified mouse models of human cancers (e.g., Kras-driven pancreatic cancer, Apc-mutated colorectal cancer, and Her2/neu-overexpressing breast cancer). The experimental results obtained using these mouse models revealed strong evidence of a link between obesity and cancer and suggested their underlying mechanisms.

Ubiquitous Aberration in Cholesterol Metabolism across Pancreatic Ductal Adenocarcinoma

Pancreatic cancer (PC) is characterized by metabolic deregulations that often manifest as deviations in metabolite levels and aberrations in their corresponding metabolic genes across the clinical specimens and preclinical PC models. Cholesterol is one of the critical metabolites supporting PC, synthesized or acquired by PC cells. Nevertheless, the significance of the de novo cholesterol synthesis pathway has been controversial in PC, indicating the need to reassess this pathway in PC. We utilized preclinical models and clinical specimens of PC patients and cell lines and utilized mass spectrometry-based sterol analysis. Further, we also performed in silico analysis to corroborate the significance of de novo cholesterol synthesis pathway in PC. Our results demonstrated alteration in free sterol levels, including free cholesterol, across in vitro, in vivo, and clinical specimens of PC. Especially, our sterol analyses established consistent alterations in free cholesterol across the different PC models. Overall, this study demonstrates the significance and consistency in deviation of cholesterol synthesis pathway in PC while showing the aberrations in sterol metabolite intermediates and the related genes using preclinical models, in silico platforms, and the clinical specimens.

Risk of cancer in patients treated with dipeptidyl peptidase-4 inhibitors: an extensive meta-analysis of randomized controlled trials

AIMS

Observational studies and meta-analyses of randomized trials on dipeptidyl peptidase-4 inhibitors (DPP4i) reported discordant results on the risk of malignancies with this class of drugs. Aim of the present meta-analysis is the assessment of the effect of DPP4i treatment on the incidence of different types of cancer, collecting all available evidence from randomized controlled trials.

METHODS

An extensive MEDLINE, EMBASE, and Cochrane database search for sitagliptin or vildagliptin or omarigliptin or saxagliptin or alogliptin or trelagliptin or anagliptin or linagliptin or gemigliptin or evogliptin or teneligliptin was performed up to September 30th, 2019. All trials performed on type 2 diabetes, with duration ≥ 24 weeks, and comparing of DPP4i with placebo or active drugs were collected. The study has been registered on PROSPERO (#153344). Mantel-Haenszel odds ratio (MH-OR) with 95% confidence interval (95% CI) was calculated for all outcomes.

RESULTS

A total of 157 eligible trials were identified. DPP-4i were not associated with an increased risk of overall cancer (MH-OR 0.93 [0.86, 1.00]; p = 0.07), with no significant differences across individual molecules of the class. When compared with placebo/none, a lower risk of cancer with DPP-4i was observed in placebo-controlled trials (MH-OR 0.90 [0.82, 0.99], p = 0.030), whereas no significant differences have been detected with any other comparators. DPP-4i was associated with a significant reduction in colorectal cancer (MH-OR 0.70 [0.53, 0.94], p = 0.020).

CONCLUSIONS

Available data do not support the hypothesis of an association of DPP4i treatment with malignancies, with a possible beneficial effect for colon-rectal cancer.

Pancreatic cancer triggers diabetes through TGF-β-mediated selective depletion of islet β-cells

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease that remains incurable because of late diagnosis, which renders any therapeutic intervention challenging. Most PDAC patients develop de novo diabetes, which exacerbates their morbidity and mortality. How PDAC triggers diabetes is still unfolding. Using a mouse model of KrasG12D-driven PDAC, which faithfully recapitulates the progression of the human disease, we observed a massive and selective depletion of β-cells, occurring very early at the stages of preneoplastic lesions. Mechanistically, we found that increased TGF beta (TGF-β) signaling during PDAC progression caused erosion of β-cell mass through apoptosis. Suppressing TGF-β signaling, either pharmacologically through TGF-β immunoneutralization or genetically through deletion of Smad4 or TGF-β type II receptor (TβRII), afforded substantial protection against PDAC-driven β-cell depletion. From a translational perspective, both activation of TGF-β signaling and depletion of β-cells frequently occur in human PDAC, providing a mechanistic explanation for the pathogenesis of diabetes in PDAC patients, and further implicating new-onset diabetes as a potential early prognostic marker for PDAC.

Nicotinamide Inhibits Glycolysis of HL-60 Cells by Modulating Sirtuin 1 (SIRT1)/Peroxisome Proliferator-Activated Receptor γ Coactivator 1α (PGC-1α)/Hypoxia-Inducible Factor-2α (HIF2α) Signaling Pathway

Background

Nicotinamide can affect differentiation and proliferation of leukemia cells. This research aimed to explore the regulatory effect of nicotinamide on glycolysis metabolism of leukemia cells and to clarify the associated mechanisms.

Material/Methods

HL-60 cells were treated with nicotinamide and divided into 0.1, 1, and 10 μmol/l groups. HL-60 cells without any administration were assigned as negative control (CT group). Glucolytic activity was evaluated by detecting lactic acid production, and glucose level was measured using glucose consumption assay. Apoptosis of HL-60 was examined using flow cytometry assay, when cells were cultured for 24 h. Expressions of sirtuin 1 (SIRT1), peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), and hypoxia-inducible factor-2α (HIF2α) were evaluated using a reverse transcription PCR assay and Western blotting assay, respectively.

Results

Nicotinamide remarkably decreased lactic acid production and glucose levels in leukemia cells compared with that of the CT group (p<0.05). Nicotinamide significantly induced the apoptosis of HL-60 cells compared to that of the negative control group (p<0.05). Nicotinamide significantly inhibited the SIRT1/PGC-1α/HIF2α signaling pathway mRNAs compared to that of the CT group (p<0.05). Nicotinamide remarkably reduced mitochondrial regulatory factors SIRT1/PGC-1α expression compared to that in the CT group (p<0.05). Nicotinamide obviously downregulated HIF2α compared with that of the CT group (p<0.05). Moreover, all of the above nicotinamide-induced effects, including glycolytic activity, apoptosis, and expression of SIRT1/PGC-1α/HIF2α, were changed in a dose-dependent manner.

Conclusions

Nicotinamide can inhibit glycolysis of HL-60 cells by inhibiting the mitochondrial regulatory factor SIRT1/PGC-1α and suppressing transcription factor HIF2α.

Exploring and validating the clinical risk factors for pancreatic cancer in chronic pancreatitis patients using electronic medical records datasets: three cohorts comprising 2,960 patients

Background

Patients with chronic pancreatitis (CP) have an increased risk of developing pancreatic cancer (PC). The purpose of this study was to identify predictors of PC in CP patients.

Methods

Electronic medical records (EMRs) of CP patients from two cohorts were collected, and a logistic regression analysis was performed to investigate the risk factors for PC. Subsequently, we validated the value of the risk prediction model with the EMRs of a third cohort.

Results

The derivation cohort consisted of 2,545 CP patients, and among them, 14 patients developed PC 7 years after CP diagnosis. Cyst of the pancreas [COP; odds ratio (OR): 4.37, 95% confidence interval (CI): 1.11 to 18.40, P=0.033], loss of weight (LW; OR: 3.21, 95% CI: 0.76 to 12.91, P=0.096) and high platelet (PLT) count (OR: 1.01 per 1 increment, 95% CI: 1.00 to 1.01, P=0.042) were independent risk factors for PC among CP patients. A risk prediction equation was constructed as follows: ln[p/(1–p)] = –6.68 + 1.55COP + 1.23LW + 0.0046PLT. The areas under the receiver operating characteristic (ROC) curve of our risk score were 0.83 and 0.72 in the derivation and validation cohorts, respectively. A score >0.0128 and >0.0122 had the best balance between sensitivity and specificity in the derivation and validation cohorts, respectively.

Conclusions

In CP patients, LW, COP and high PLT count were identified as novel predictors of PC. A risk prediction model based on these factors exhibited moderate predictive value for CP patients.

The intricate relationship between diabetes, obesity and pancreatic cancer

Pancreatic cancer is one of the leading determinants of global cancer mortality, and its incidence is predicted to increase, to become in 2030 the second most common cause of cancer-related death. Obesity and diabetes are recognized risk factors for the development of pancreatic cancer. In the last few decades an epidemic of diabetes and obesity has been spreading worldwide, forewarning an increase in incidence of pancreatic cancer. This review considers the most recent literature, covering the multiple molecular axis linking these three pathologies, aiming to draw a more comprehensive view of pancreatic cancer for a better theragnostic stratification of the population.