Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis

Mahajan, Ujjwal Mukund; Oehrle, Bettina; Sirtl, Simon; Alnatsha, Ahmed; Goni, Elisabetta; Regel, Ivonne; Beyer, Georg; Vornhülz, Marlies; Vielhauer, Jakob; Chromik, Ansgar M.; Bahra, M.; Klein, Fritz; Uhl, Waldemar; Fahlbusch, Tim; Distler, Marius; Weitz, Jürgen; Grützmann, Robert; Pilarsky, Christian; Weiß, Frank Ulrich; Adam, G.; Neoptolemos, John P.; Kalthoff, Holger; Rad, Roland; Christiansen, Nicole; Bethan, Bianca; Kamlage, Beate; Lerch, Markus M.; Mayerle, Julia

doi:10.1053/j.gastro.2022.07.047

Cited by 19 publications

(8 citation statements)

References 55 publications

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“…In one MS study, lung cancer patients had lower levels of PCs and PEs in pleural effusions than did tuberculosis patients ( 66 ). Differences in blood PCs and PEs between cancer patients and controls were also reported in four studies ( 28 , 64 , 65 , 70 ). Interestingly, in α-fetoprotein (AFP)-negative hepatocellular carcinoma, the concentrations of PC (22:6/18:2) and PC (18:2/18:2) were increased while the concentrations of PC (16:0/16:0) were decreased, which indicated that serological alterations in PCs would help us to identify patients with hepatocellular carcinoma missed by AFP at an early stage ( 64 ).…”

Section: Metabolomic Biomarkers For Cancer Screening and Diagnosissupporting

confidence: 60%

“…Lysophosphatidylcholines (LPCs) and lysophosphatidylethanolamines are metabolic intermediates of PCs and PEs that are hydrolyzed by phospholipases. A significant body of literature has documented that changes in their levels in biological fluids are associated with early tumor diagnosis ( 35 , 54 , 59 , 63 , 67 – 70 ).…”

Section: Metabolomic Biomarkers For Cancer Screening and Diagnosismentioning

confidence: 99%

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Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Wang,

Zhen,

Ping

et al. 2024

Front. Oncol.

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Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

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Section: Metabolomic Biomarkers For Cancer Screening and Diagnosissupporting

confidence: 60%

Section: Metabolomic Biomarkers For Cancer Screening and Diagnosismentioning

confidence: 99%

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Wang,

Zhen,

Ping

et al. 2024

Front. Oncol.

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“…These metabolites were associated with adiposity/insulin resistance, gamma-glutamyl cycle metabolism, and subclinical pancreatic cancer. A nine-metabolic signature identified at pancreatic cancer diagnosis is currently being evaluated in a prospective setting (Deutsche Register Klinischer Studien registration ID: DRKS00010866) and in pre-diagnostic pancreatic cancer samples ( 17 , 18 ).…”

Section: Introductionmentioning

confidence: 99%

Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank

Borgmästars,

Jacobson,

Simm

et al. 2024

J Gastrointest Oncol

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Background Pancreatic ductal adenocarcinoma (pancreatic cancer) is often detected at late stages resulting in poor overall survival. To improve survival, more patients need to be diagnosed early when curative surgery is feasible. We aimed to identify circulating metabolites that could be used as early pancreatic cancer biomarkers. Methods We performed metabolomics by liquid and gas chromatography-mass spectrometry in plasma samples from 82 future pancreatic cancer patients and 82 matched healthy controls within the Northern Sweden Health and Disease Study (NSHDS). Logistic regression was used to assess univariate associations between metabolites and pancreatic cancer risk. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to design a metabolite-based risk score. We used receiver operating characteristic (ROC) analyses to assess the discriminative performance of the metabolite-based risk score. Results Among twelve risk-associated metabolites with a nominal P value <0.05, we defined a risk score of three metabolites [indoleacetate, 3-hydroxydecanoate (10:0-OH), and retention index (RI): 2,745.4] using LASSO. A logistic regression model containing these three metabolites, age, sex, body mass index (BMI), smoking status, sample date, fasting status, and carbohydrate antigen 19-9 (CA 19-9) yielded an internal area under curve (AUC) of 0.784 [95% confidence interval (CI): 0.714–0.854] compared to 0.681 (95% CI: 0.597–0.764) for a model without these metabolites (P value =0.007). Seventeen metabolites were significantly associated with pancreatic cancer survival [false discovery rate (FDR) <0.1]. Conclusions Indoleacetate, 3-hydroxydecanoate (10:0-OH), and RI: 2,745.4 were identified as the top candidate biomarkers for early detection. However, continued efforts are warranted to determine the usefulness of these metabolites as early pancreatic cancer biomarkers.

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“…The application of targeted metabolomics to pancreatic cancer diagnostics remains in its infancy, but several groups have made important strides mostly through the application of un-targeted MS/MS [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Diagnostic and Prognostic Performance of Metabolic Signatures in Pancreatic Ductal Adenocarcinoma: The Clinical Application of Quantitative NextGen Mass Spectrometry

D’Amora,

Silva,

Evans

et al. 2024

Metabolites

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With 64,050 new diagnoses and 50,550 deaths in the US in 2023, pancreatic ductal adenocarcinoma (PDAC) is among the most lethal of all human malignancies. Early detection and improved prognostication remain critical unmet needs. We applied next-generation metabolomics, using quantitative tandem mass spectrometry on plasma, to develop biochemical signatures that identify PDAC. We first compared plasma from 10 PDAC patients to 169 samples from healthy controls. Using metabolomic algorithms and machine learning, we identified ratios that incorporate amino acids, biogenic amines, lysophosphatidylcholines, phosphatidylcholines and acylcarnitines that distinguished PDAC from normal controls. A confirmatory analysis then applied the algorithms to 30 PDACs compared with 60 age- and sex-matched controls. Metabolic signatures were then analyzed to compare survival, measured in months, from date of diagnosis to date of death that identified metabolite ratios that stratified PDACs into distinct survival groups. The results suggest that metabolic signatures could provide PDAC diagnoses earlier than tumor markers or radiographic measures and offer insights into disease severity that could allow more judicious use of therapy by stratifying patients into metabolic-risk subgroups.

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Independent Validation and Assay Standardization of Improved Metabolic Biomarker Signature to Differentiate Pancreatic Ductal Adenocarcinoma From Chronic Pancreatitis

Cited by 19 publications

References 55 publications

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Metabolomics for early pancreatic cancer detection in plasma samples from a Swedish prospective population-based biobank

Diagnostic and Prognostic Performance of Metabolic Signatures in Pancreatic Ductal Adenocarcinoma: The Clinical Application of Quantitative NextGen Mass Spectrometry

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