Discovery of serum biomarkers for pancreatic adenocarcinoma using proteomic analysis

Xue, Aiqun; Scarlett, Christopher J.; Chung, Liping; Butturini, Giovanni; Scarpa, Aldo; Gandy, Robert C.; Wilson, Susan R.; Baxter, Robert C.; Smith, Ross C.

doi:10.1038/sj.bjc.6605764

Cited by 54 publications

(41 citation statements)

References 38 publications

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“…Consistent with these findings, APOC1 has been reported to be a promising serum marker for the diagnosis and treatment of multiple cancers, such as gastric cancer,25 pancreatic cancer,26 colorectal cancer,27 thyroid carcinoma,28 and non‐small cell lung cancer 29…”

Section: Discussionsupporting

confidence: 56%

Apolipoprotein C1 promotes prostate cancer cell proliferation in vitro

Sun

Yang

et al. 2018

J Biochem & Molecular Tox

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Here, we aimed to investigate the carcinogenic effects of apolipoprotein C1 (APOC1) in prostate cancer (PCa). APOC1 expression was evaluated in PCa and normal prostate specimens, and lentivirus‐mediated RNA interference was used to knockdown APOC1 in DU145 cells. The effects of APOC1 silencing on cell proliferation, cell cycle arrest, and apoptosis were assessed. APOC1 expression was much higher in PCa tissues than in normal tissues. Moreover, APOC1 silencing inhibited cell proliferation and colony formation, arrested cell cycle progression, and enhanced apoptosis in DU145 cells. Additionally, APOC1 silencing decreased survivin, phospho‐Rb, and p21 levels and increased cleaved caspase‐3 expression. These data supported the procarcinogenic effects of APOC1 in the pathogenesis of PCa and suggested that targeting APOC1 may have applications in the treatment of PCa.

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Section: Discussionsupporting

confidence: 56%

Apolipoprotein C1 promotes prostate cancer cell proliferation in vitro

Sun

Yang

et al. 2018

J Biochem & Molecular Tox

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“…These three metabolites, LPE 16:0, TCA, and LPC 22:5, referred to as the marker metabolites, were finally defined for their potential applications. Using the binary logistic regression method (33), the capacity of the above three marker metabolites to discriminate liver diseases in rats was evaluated. The results provided preliminary evidence for these metabolites to be used as markers for the classification of HCC and chronic liver diseases.…”

Section: Discussionmentioning

confidence: 99%

“…The data were analyzed using the Wilcoxon Mann-Whitney Test, with p Ͻ 0.05 set as the level of statistical significance. A binary logistic regression was also performed using this software (33). After the regression, the values of the prediction probability were applied to the discrimination of the samples.…”

Section: Methodsmentioning

confidence: 99%

Metabolomics Study of Stepwise Hepatocarcinogenesis From the Model Rats to Patients: Potential Biomarkers Effective for Small Hepatocellular Carcinoma Diagnosis

Tan

Yin

Tang

et al. 2012

Molecular & Cellular Proteomics

138

126

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The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as "marker metabolites," which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of ␣-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of ␣-fetoprotein (61.2 and 64%). These results indicate metabolomics method has

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“…This had enabled the discovery of both classification trees including patterns of proteins/peptides and single potential biomarkers, including acute phase proteins 20 and proteins involved in lipid metabolism. 23 However, few studies have been conducted to compare findings of PaCa sera with those obtained in patients with type 2 DM, who make up the category of patients at risk, to be screened for PaCa. 21 The present paper reports findings made in a study conducted by us using serum MALDI-TOF/MS analysis aimed at identifying in the low molecular weight range, valid biomarkers to be used for differentiating PaCa patients from those with DM and/or ChrPa.…”

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confidence: 99%