Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

He, Xiangyi; Zhong, Jie; Wang, Shuwei; Zhou, Yufen; Wang, Lei; Zhang, Yongping; Yuan, Yaozong

doi:10.18632/oncotarget.16249

Cited by 33 publications

(25 citation statements)

References 23 publications

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“…One study found that the metabolite profiles are distinct among 50 patients with pancreatic cancer, 50 diabetic patients, and 50 healthy controls (23). In another study of 30 patients with pancreatic cancer and 30 patients with new-onset diabetes, N-succinyl-L-diaminopimelic acid and phosphatidylethanolamine (18:2) were shown to have a high sensitivity (93.3%) and specificity (93.1%) in discriminating pancreatic cancer (24). The other study found that the metabolites in combination with CA19-9 can improve early detection rate of pancreatic cancer (25).…”

Section: Introductionmentioning

confidence: 96%

A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women

Jiao

Maity

Coarfa

et al. 2019

Cancer Prevention Research

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To examine the association between metabolic deregulation and pancreatic cancer, we conducted a two-stage case-control targeted metabolomics study using prediagnostic sera collected one year before diagnosis in the Women's Health Initiative study. We used the LC/MS to quantitate 470 metabolites in 30 matched case/control pairs. From 180 detectable metabolites, we selected 14 metabolites to be validated in additional 18 matched case/control pairs. We used the paired t test to compare the concentrations of each metabolite between cases and controls and used the log fold change (FC) to indicate the magnitude of difference. FDR adjusted q-value < 0.25 was indicated statistically significant. Logistic regression model and ROC curve analysis were used to evaluate the clinical utility of the metabolites. Among 30 case/control pairs, 1-methyl-L-tryptophan (L-1MT) was significantly lower in the cases than in the controls (log 2 FC ¼ À0.35; q-value ¼ 0.03). The area under the ROC curve was 0.83 in the discrimination analysis based on the levels of L-1MT, acadesine, and aspartic acid. None of the metabolites was validated in additional independent 18 case/control pairs. No significant association was found between the examined metabolites and undiagnosed pancreatic cancer.

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Section: Introductionmentioning

confidence: 96%

A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women

Jiao

Maity

Coarfa

et al. 2019

Cancer Prevention Research

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“…Pancreatic cancer is usually diagnosed in an advanced stage of the disease, resulting in a poor prognosis. Most pancreatic cancer biomarker studies executed until today (9,10,(13)(14)(15)(16) collected samples at the time of diagnosis or even later, and therefore have limited clinical utility.…”

Section: Discussionmentioning

confidence: 99%

“…Patients may present with glucose intolerance, anorexia and severe weight loss (3,8). In line with this, circulating metabolites have been proposed as a potentially useful screening tool in pancreatic cancer (9)(10)(11)(12)(13)(14)(15)(16). The study by Mayers et al(11) stood out from other metabolomic biomarker studies, as they analyzed blood samples taken two to more than ten years prior to diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Search for early pancreatic cancer blood biomarkers in five European prospective population biobanks using metabolomics

Fest

Vijfhuizen

Goeman

et al. 2019

Preprint

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Background and aim: Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Methods:The low incidence rate complicates prospective biomarker studies. Here, we took advantage of the availability of biobanked samples from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian biobank, Rotterdam Study) and identified prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between one month and seventeen years after blood sampling, and compared these with age-and gender-matched controls from the same cohorts. We applied 1 H-NMR-based metabolomics on the Nightingale platform on these samples and applied logistic regression to assess the predictive value of individual metabolite concentrations, with gender, age, body mass index, smoking status, type 2 diabetes mellitus status, fasting status, and cohort as covariates.Results: After quality assessment, we retained 356 cases and 887 controls. We identified two interesting hits, glutamine (p=0.011) and histidine (p=0.012), and obtained Westfall-Young familywise error rate adjusted p-values of 0.43 for both. Stratification in quintiles showed a 1.5x elevated risk for the lowest 20% of glutamine and a 2.2x increased risk for the lowest 20% of histidine.Stratification by time to diagnosis (<2 years, 2-5 years, >5 years) suggested glutamine to be involved in an earlier process, tapering out closer to onset, and histidine in a process closer to the actual onset. Lasso-penalized logistic regression showed a slight improvement of the area under the Receiver Operator Curves when including glutamine and histidine in the model. Finally, our data did not support the earlier identified branched-chain amino acids as potential biomarkers for pancreatic cancer in several American cohorts. Conclusion:While identifying glutamine and histidine as early biomarkers of potential biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers. acknowledged for their contribution to the analysis presented in the manuscript. Annika Wolin is thanked for her contribution to the FINRISK sample selection. We would like to thank Peter Würtz (Nightingale) for very useful comments on the study. This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative.The Nord-Trøndelag Health Study (The HUNT Study) is a collaboration between

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“…In this study, 39 distinct metabolites and eight main metabolic pathways were revealed. The AUC of the optimized model was indicated the satisfactory sensitivity and specificity [ 31 , 32 ]. Moreover, we performed an independent test experiment including 3 samples of 1 week and 6 sample of start point and the results showed that these 34 metabolites could differentiate samples of 1 week from start point, which indicated that the model had a high clinical value for the diagnosis of SANFH.…”

Section: Discussionmentioning

confidence: 99%

A metabolomic study on early detection of steroid-induced avascular necrosis of the femoral head

Ren

Shao

et al. 2018

Oncotarget

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The early and accurate diagnosis of steroid-induced avascular necrosis of the femoral head (SANFH) is appealing considering its irreversible progression and serious consequence for the patients. The purpose of this study was to investigate the metabolic change of SANFH for its early detection. Two stages were designed in this study, namely discovery and verification. Except the biochemical index anomaly and the accidental death, 30 adult healthy adult Japanese white rabbits were used for screening out the potential metabolites in discovery experiment and 13 rabbits were used in verification experiment. The femoral heads were assessed with magnetic resonance imaging and transmission electron microscopy. The metabolomic profiling of serum samples were analysis by UHPLC-MS/MS. Metabolomic cluster analysis enable us to differentiate the rabbits without and with injection of the glucocorticoid in 1 week even when there is no obvious abnormal symptom in behaviors or imaging diagnosis. The majority of differential metabolites were identified as phospholipids which were observed significant change after injection of glucocorticoid in 1, 2, 3 weeks. And the results obtained in verification experiment of 6 weeks showed that these differential metabolites exhibited consistent trends in late progression with that in early-stage. At the end of 6 weeks the damage of SANFH could be verified by pathological imaging. Therefore the finding of serum metabolite profile links to the progression of SANFH and provides the potential of early detection of SANFH.

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Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

Cited by 33 publications

References 23 publications

A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women

A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women

Search for early pancreatic cancer blood biomarkers in five European prospective population biobanks using metabolomics

A metabolomic study on early detection of steroid-induced avascular necrosis of the femoral head

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