Re: Etiology of Pancreatic Cancer, With a Hypothesis Concerning the Role of N-Nitroso Compounds and Excess Gastric Acidity

Association of Smoking with progression from low-risk to high-risk intraductal papillary mucinous neoplasms and pancreatic cancer

BACKGROUND

Factors associated with the risk of pancreatic adenocarcinoma (PDAC) may play a role in the development and progression of Intraductal Papillary Mucinous Neoplasms (IPMNs). However, data are limited.

AIM

To compare exposome factors in three groups of patients with "high or low-risk" IPMNs, as assessed at diagnosis and during a 24-months follow-up, and with PDAC.

METHODS

Patients were matched (same sex, age ±5) 1:1. Exposure variables were compared across groups using Kruskal-Wallis, ANOVA, or Chi-square tests with Bonferroni correction.

RESULTS

A total of 151 patients were enrolled in each of the three groups (453 overall). The proportion of current smokers was progressively higher in "low-risk", "high-risk" IPMNs and PDAC patients (8.1 %, 11.2 %, 23.3 %; p = 0.0002). The three groups did not differ in terms of ever or heavy smoking, BMI, history of diabetes, cancer, cholecystectomy or chronic pancreatitis, use of statins or aspirin, and family history of cancer. A history of peptic ulcer was more common in PDAC (7.2 %) than in either "low-risk" (2.0 %) or "high-risk" (2.6%) IPMNs (p = 0.02, not significant after Bonferroni correction).

CONCLUSION

Active smoking seems associated with the progression of IPMNs to malignancy, and cessation of active smoking might be advised in patients with IPMN.

The Microbiome and Pancreatic Cancer: An Evidence-based Association?

Many risk factors for pancreatic cancer are related with microbiome alteration. In the past few years, the human microbiome and its relation with the immune system have been linked with carcinogenesis of different organs distant from the gut, including the pancreas. Patterns of oral microbiome associated with periodontitis are associated with an increased risk of pancreatic cancer, possibly because of the increased systemic inflammatory response, or to the capacity of some specific bacteria to alter the host immune response, making it more favorable to cancer cells. Helicobacter pylori infection when affecting the gastric body mucosa with subsequent hypochlorhydria also seems associated with an increased risk of pancreatic cancer. The composition of the intestinal microbiome is different in animal models and in humans with pancreatic cancer who have a distinct microbiome population compared with controls. Some specific bacteria can migrate from the intestine to the pancreas, and their ablation restores the immune system activity through its reprogramming with a switch toward a Th1 response and displays a protective effect toward tumor growth. More research in this area might lead to progress in terms of pancreatic cancer prevention and treatment, possibly in association with immunotherapy.

Toxicity of chemotherapy regimens in advanced and metastatic pancreatic cancer therapy: A network meta-analysis

This network meta-analysis is adopted in order to compare the toxicity of different chemotherapy regimens in the treatment of advanced/metastatic pancreatic cancer (PC). Randomized controlled trials (RCTs) about different chemotherapy regimens for advanced/metastatic PC were included in this network meta-analysis using Cochrane Library and PubMed electronic databases. The network meta-analysis was performed to combine direct and indirect evidence in order to calculate the odd ratios (OR) and draw a surface under the cumulative ranking (SUCRA) curve. A total of 19 RCTs were enrolled in this network meta-analysis including 12 chemotherapy regimens (Gemcitabine, Gemcitabine + S-1 [tegafur], Gemcitabine + nab-paclitaxel, Gemcitabine + Capecitabine, Gemcitabine + Cisplatin, FOLFIRINOX [oxaliplatin + irinotecan + fluorouracil + leucovorin], Gemcitabine + oxaliplatin, Gemcitabine + irinotecan, Gemcitabine + Exatecan, Gemcitabine + pemetrexed, Gemcitabine + 5-FU, S-1). The incidence of anemia of Gemcitabine + Capecitabine regimen was higher compared with Gemcitabine regimen, Gemcitabine + pemetrexed regimen exhibited the highest incidence rates of anemia and neutropenia; while Gemcitabine + S-1, Gemcitabine + Cisplatin and FOLFIRINOX regimens exhibited the highest incidence rates of neutropenia. However, S-1 regimen exhibited lower incidence rates of leukopenia and thrombocytopenia. Moreover, the incidence rates of nausea/vomiting and rash of Gemcitabine + S-1 regimen were higher compared with Gemcitabine regimen, while Gemcitabine + Cisplatin regimen had the highest incidence rate of nausea/vomiting. This study demonstrated that the hematologic toxicity of S-1 regimen was the lowest, while Gemcitabine regimen exhibited the lowest incidence rate of non-hematologic toxicity, providing guidance for the treatment of advanced/metastatic PC.

Familial pancreatic cancer in Italy. Risk assessment, screening programs and clinical approach: a position paper from the Italian Registry

In Italy, pancreatic cancer is the fifth leading cause of tumor related death with about 7000 new cases per year and a mortality rate of 95%. In a recent prospective epidemiological study on the Italian population, a family history was found in about 10% of patients suffering from a ductal adenocarcinoma of the pancreas (PDAC). A position paper from the Italian Registry for Familial Pancreatic Cancer was made to manage these high-risk individuals. Even though in the majority of high-risk individuals a genetic test to identify familial predisposition is not available, a screening protocol seems to be reasonable for subjects who have a >10-fold greater risk for the development of PDAC. However this kind of screening should be included in clinical trials, performed in centers with high expertise in pancreatic disease, using the least aggressive diagnostic modalities.

Classification of the carcinogenicity of N-nitroso compounds based on support vector machines and linear discriminant analysis

The support vector machine (SVM), as a novel type of learning machine, was used to develop a classification model of carcinogenic properties of 148 N-nitroso compounds. The seven descriptors calculated solely from the molecular structures of compounds selected by forward stepwise linear discriminant analysis (LDA) were used as inputs of the SVM model. The obtained results confirmed the discriminative capacity of the calculated descriptors. The result of SVM (total accuracy of 95.2%) is better than that of LDA (total accuracy of 89.8%).