Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

Abstract

This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC) from malignant diseases, such as biliary tract cancer (BTC), intraductal papillary mucinous carcinoma (IPMC), and various benign pancreaticobiliary diseases. Capillary electrophoresis−mass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41) of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140). Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test). Four multiple logistic regression models (MLR) were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC) of 0.970 (95% confidential interval (CI), 0.946–0.994, p < 0.0001). Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020) with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), pancreatic cancer-associated antigen (DUPAN2) and s-pancreas-1 antigen (SPAN1). Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.

Identification of ENTPD8 and cytidine in pancreatic cancer by metabolomic and transcriptomic conjoint analysis

“…It is well recognized that metabolomic can provide snapshots of physiological conditions in biological samples by acquiring qualitative and quantitative information of low‐molecular‐mass endogenous metabolites, and it has been applied to identify potential molecular biomarkers of various cancers . A previous study suggested that malignant cancers had markedly altered intermediate metabolites in metabolic pathways compared with nontumor tissue . In addition, Budhu et al found that metabolic profiles were significantly different among several cancer types, and those distinct metabolites or metabolic pathways in particular cancer types might be helpful to distinguish primary tumors.…”

“…[19][20][21] A previous study suggested that malignant cancers had markedly altered intermediate metabolites in metabolic pathways compared with nontumor tissue. 22 In addition, Budhu et al 23 found that metabolic profiles were significantly different among several cancer types, and those distinct metabolites or metabolic pathways in particular cancer types might be helpful to However, an effective integration of metabolomic with transcriptomic data could better interpret results that could not be obtained from one single metabolomic dataset. 25 To date, numerous researchers have unveiled significantly altered pathways and the associated metabolites with high diagnostic accuracy through merging metabolomic and transcriptomic.…”

Elevated Polyamines in Saliva of Pancreatic Cancer

“…The meta-analysis of these blood metabolomics for PC has also been reported [15]. We also recently reported the diagnostic ability of serum metabolomics [16], indicating the spread of metabolomic change from PC cells to metabolites in blood vessels as well as a range of biofluids.…”

Elevated Polyamines in Saliva of Pancreatic Cancer

“…These metabolites are secreted from the tumor tissue and spread to surrounding tissues and blood vessels [ 5 ]. Therefore, the combination of polyamine or metabolites has been used for the development of non- or low-invasive screening, such as blood, urine, and fecal-based tests [ 8 , 15 , 16 , 17 , 18 , 19 ], to identify patients with CRC or polyps, a precursor of CRC. Elevated concentration of urinary N 1 , N 12 -acetylspermine of CRC has been consistently observed in various studies [ 20 , 21 ].…”

“…Meta-analysis of these blood metabolomics for PC has also been reported [ 18 ]. We also recently reported the diagnostic ability of serum metabolomics [ 19 ], indicating the spread of metabolomic change from PC cells to metabolites in blood vessels as well as a range of biofluids.…”