Metabolome analysis for pancreatic cancer risk in nested case-control study: Japan Public Health Center-based prospective Study

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.

Metabolomics Study Reveals Systematic Metabolic Dysregulation and Early Detection Markers Associated with Incident Pancreatic Cancer

Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n=192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < 0.05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormone, vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer. This article is protected by copyright. All rights reserved.

Primary Ciliogenesis by 2-Isopropylmalic Acid Prevents PM2.5-Induced Inflammatory Response and MMP-1 Activation in Human Dermal Fibroblasts and a 3-D-Skin Model

Particulate matters (PMs) increase oxidative stress and inflammatory response in different tissues. PMs disrupt the formation of primary cilia in various skin cells, including keratinocytes and melanocytes. In this study, we found that 2-isopropylmalic acid (2-IPMA) promoted primary ciliogenesis and restored the PM2.5-induced dysgenesis of primary cilia in dermal fibroblasts. Moreover, 2-IPMA inhibited the generation of excessive reactive oxygen species and the activation of stress kinase in PM2.5-treated dermal fibroblasts. Further, 2-IPMA inhibited the production of pro-inflammatory cytokines, including IL-6 and TNF-α, which were upregulated by PM2.5. However, the inhibition of primary ciliogenesis by IFT88 depletion reversed the downregulated cytokines by 2-IPMA. Moreover, we found that PM2.5 treatment increased the MMP-1 expression in dermal fibroblasts and a human 3-D-skin model. The reduced MMP-1 expression by 2-IPMA was further reversed by IFT88 depletion in PM2.5-treated dermal fibroblasts. These findings suggest that 2-IPMA ameliorates PM2.5-induced inflammation by promoting primary ciliogenesis in dermal fibroblasts.

Vitamin B6, vitamin B12 and methionine and risk of pancreatic cancer: a meta-analysis

Background

Nutrients involved in one-carbon metabolism may play a key role in pancreatic carcinogenesis. The aim of this study was to examine the association between pancreatic cancer risk and intake or blood levels of vitamins B6, B12 and methionine via meta-analysis.

Methods

A systematic search was performed in PubMed, Web of Knowledge and Chinese National Knowledge Infrastructure (CNKI) up to April 2020 to identify relevant studies. Risk estimates and their 95% confidence intervals (CIs) were retrieved from the studies and combined by a random-effect model.

Results

A total of 18 studies were included in this meta-analysis on the association of vitamin B6, B12 and methionine with pancreatic cancer risk. The combined risk estimate (95% CI) of pancreatic cancer for the highest vs lowest category of vitamin B6 intake and blood pyridoxal 5′-phosphate (PLP, active form of vitamin B6) levels was 0.63 (0.48–0.79) and 0.65 (0.52–0.79), respectively. The results indicated a non-linear dose-response relationship between vitamin B6 intake and pancreatic risk. Linear dose–response relationship was found, and the risk of pancreatic cancer decreased by 9% for every 10 nmol/L increment in blood PLP levels. No significant association were found between pancreatic cancer risk and vitamin B12 intake, blood vitamin B12 levels, methionine intake and blood methionine levels.

Conclusion

Our study suggests that high intake of vitamin B6 and high concentration of blood PLP levels may be protective against the development of pancreatic cancer. Further research are warranted to confirm the results.

A prospective evaluation of serum methionine-related metabolites in relation to pancreatic cancer risk in two prospective cohort studies

Deficiencies in methyl donor status may render DNA methylation changes and DNA damage, leading to carcinogenesis. Epidemiological studies reported that higher dietary intake of choline is associated with lower risk of pancreatic cancer, but no study has examined the association of serum choline and its metabolites with risk of pancreatic cancer. Two parallel case-control studies, one nested within the Shanghai Cohort Study (129 cases and 258 controls) and the other within the Singapore Chinese Health Study (58 cases and 104 controls), were conducted to evaluate the associations of baseline serum concentrations of choline, betaine, methionine, total methyl donors (i.e., sum of choline, betaine and methionine), dimethylglycine and trimethylamine N-oxide (TMAO) with pancreatic cancer risk. In the Shanghai cohort, odds ratios and 95% confidence intervals of pancreatic cancer for the highest quartile of choline, betaine, methionine, total methyl donors and TMAO were 0.27 (0.11-0.69), 0.57 (0.31-1.05), 0.50 (0.26-0.96), 0.37 (0.19-0.73) and 2.81 (1.37-5.76), respectively, compared to the lowest quartile. The corresponding figures in the Singapore cohort were 0.85 (0.23-3.17), 0.50 (0.17-1.45), 0.17 (0.04-0.68), 0.33 (0.10-1.16) and 1.42 (0.50-4.04). The inverse associations of methionine and total methyl donors including choline, betaine and methionine with pancreatic cancer risk in both cohorts support that DNA repair and methylation play an important role against the development of pancreatic cancer. In the Shanghai cohort, TMAO, a gut microbiota-derived metabolite of dietary phosphatidylcholine, may contribute to higher risk of pancreatic cancer, suggesting a modifying role of gut microbiota in the dietary choline-pancreatic cancer risk association.

Possibility of detecting intraductal papillary mucinous neoplasms using metabolite biomarkers for pancreatic cancer

Aim: The aim of this study was to identify whether metabolite biomarker candidates for pancreatic cancer (PC) could aid detection of intraductal papillary mucinous neoplasms (IPMN), recognized as high-risk factors for PC. Materials & methods: The 12 metabolite biomarker candidates, which were found to be useful to detect PC in our previous study, were evaluated for plasma samples from patients with PC (n = 44) or IPMN (n = 24) or healthy volunteers (n = 46). Results: Regarding the performance of individual biomarkers of PC and PC high-risk IPMN, lysine exhibited the best performance (sensitivity: 67.8%; specificity: 86.9%). The multiple logistic regression analysis-based detection model displayed high sensitivity and specificity values of 92.5 and 90.6%, respectively. Conclusion: Metabolite biomarker candidates for PC are useful for detecting high-risk IPMN, which can progress to PC.

Developing a preoperative serum metabolome-based recurrence-predicting nomogram for patients with resected pancreatic ductal adenocarcinoma

We investigated the potential application of preoperative serum metabolomes in predicting recurrence in patients with resected pancreatic cancer. From November 2012 to June 2014, patients who underwent potentially curative pancreatectomy for pancreatic ductal adenocarcinoma were examined. Among 57 patients, 32 were men; 42 had pancreatic head cancers. The 57 patients could be clearly categorized into two main clusters using 178 preoperative serum metabolomes. Patients within cluster 2 showed earlier tumor recurrence, compared with those within cluster 1 (p = 0.034). A nomogram was developed for predicting the probability of early disease-free survival in patients with resected pancreatic cancer. Preoperative cancer antigen (CA) 19-9 levels and serum metabolomes PC.aa.C38_4, PC.ae.C42_5, and PC.ae.C38_6 were the most powerful preoperative clinical variables with which to predict 6-month and 1-year cancer recurrence-free survival after radical pancreatectomy, with a Harrell's concordance index of 0.823 (95% CI: 0.750-0.891) and integrated area under the curve of 0.816 (95% CI: 0.736-0.893). Patients with resected pancreatic cancer could be categorized according to their different metabolomes to predict early cancer recurrence. Preoperative detectable parameters, serum CA 19-9, PC.aa.C38_4, PC.ae.C42_5, and PC.ae.C38_6 were the most powerful predictors of early recurrence of pancreatic cancer.

Diagnostic yield of the plasma free amino acid index for pancreatic cancer in patients with diabetes mellitus

OBJECTIVES

A multivariate index calculated using plasma free amino acids (PFAA index) was reported as a diagnostic biomarker for pancreatic cancer (PaC). Although diabetes mellitus (DM) is expected to be an early diagnostic indicator of PaC, identifying the high-risk individuals among patients with DM is warranted. We evaluated the diagnostic yield of the PFAA index for PaC in patients with DM.

METHODS

We compared the diagnostic yield of the PFAA index between individuals with and those without DM. Cases and controls were recruited prospectively, and controls were matched to cases at a 1:1 ratio for age, sex, and DM status.

RESULTS

A total of 180 case-control pairs were included in the analysis. The prevalence of DM was 53.3%. The sensitivity of the PFAA index was 66.7% in cases with DM and 56.0% in those without DM (P = 0.14), and the specificity was 92.7% in controls with DM and 94.0% in those without DM (P = 0.95).

CONCLUSIONS

This matched case-control study revealed a comparable diagnostic yield of the PFAA index for PaC in individuals with and those without DM. The PFAA index can be used as a biomarker for further diagnostic imaging in selected patients with DM.

A review of lifestyle, metabolic risk factors, and blood-based biomarkers for early diagnosis of pancreatic ductal adenocarcinoma

We aimed to review the epidemiologic literature examining lifestyle and metabolic risk factors, and blood-based biomarkers including multi-omics (genomics, proteomics, and metabolomics) and to discuss how these predictive markers can inform early diagnosis of pancreatic ductal adenocarcinoma (PDAC). A search of the PubMed database was conducted in June 2018 to review epidemiologic studies of (i) lifestyle and metabolic risk factors for PDAC, genome-wide association studies, and risk prediction models incorporating these factors and (ii) blood-based biomarkers for PDAC (conventional diagnostic markers, metabolomics, and proteomics). Prospective cohort studies have reported at least 20 possible risk factors for PDAC, including smoking, heavy alcohol drinking, adiposity, diabetes, and pancreatitis, but the relative risks and population attributable fractions of individual risk factors are small (mostly < 10%). High-throughput technologies have continued to yield promising genetic, metabolic, and protein biomarkers in addition to conventional biomarkers such as carbohydrate antigen 19-9. Nonetheless, most studies have utilized a hospital-based case-control design, and the diagnostic accuracy is low in studies that collected pre-diagnostic samples. Risk prediction models incorporating lifestyle and metabolic factors as well as other clinical parameters have shown good discrimination and calibration. Combination of traditional risk factors, genomics, and blood-based biomarkers can help identify high-risk populations and inform clinical decisions. Multi-omics investigations can provide valuable insights into disease etiology, but prospective cohort studies that collect pre-diagnostic samples and validation in independent studies are warranted.

Metabolome analysis for pancreatic cancer risk in nested case-control study: Japan Public Health Center-based prospective Study

Discovery of a high-risk group for pancreatic cancer is important for prevention of pancreatic cancer. The present study was conducted as a nested case-control study including 170 pancreatic cancer cases and 340 matched controls of our population-based cohort study involving 30 239 subjects who answered a baseline questionnaire and supplied blood samples. Twelve targeted metabolites were quantitatively analyzed by gas chromatography/tandem mass spectrometry. Odds ratios (OR) and their corresponding 95% confidence intervals (CI) were calculated using conditional logistic regression models. Statistically significant P-value was defined as P < .05. Increasing 1,5-anhydro-d-glucitol (1,5-AG) levels were associated with a decreasing trend in pancreatic cancer risk (OR of quartile 4 [Q4], 0.50; 95% CI, 0.27-0.93; P = .02). Increasing methionine levels were also associated with an increasing trend of pancreatic cancer risk (OR of Q4, 1.79; 95% CI, 0.94-3.40: P = .03). Additional adjustment for potential confounders attenuated the observed associations of 1,5-AG and methionine (P for trend = .06 and .07, respectively). Comparing subjects diagnosed in the first 0-6 years, higher levels of 1,5-AG, asparagine, tyrosine and uric acid showed a decreasing trend for pancreatic cancer risk (P for trend = .04, .04, .04 and .02, respectively), even after adjustment for potential confounders. We found that the 12 target metabolites were not associated with pancreatic cancer risk. However, metabolic changes in the subjects diagnosed in the first 0-6 years showed a similar tendency to our previous reports. These results might suggest that these metabolites are useful for early detection but not for prediction of pancreatic cancer.