High-Throughput LC–MS/MS Based Simultaneous Determination of Polyamines Including N-Acetylated Forms in Human Saliva and the Diagnostic Approach to Breast Cancer Patients

2013 ◽  
Vol 85 (24) ◽  
pp. 11835-11842 ◽  
Author(s):  
Haruhito Tsutsui ◽  
Toshiki Mochizuki ◽  
Koichi Inoue ◽  
Tatsuya Toyama ◽  
Nobuyasu Yoshimoto ◽  
...  
Heliyon ◽  
2021 ◽  
pp. e07558
Author(s):  
Yahdiana Harahap ◽  
Athalia Theda Tanujaya ◽  
Farhan Nurahman ◽  
Aurelia Maria Vianney ◽  
Denni Joko Purwanto

2006 ◽  
Vol 17 (3) ◽  
pp. 424-428 ◽  
Author(s):  
L. Mercatali ◽  
V. Valenti ◽  
D. Calistri ◽  
S. Calpona ◽  
G. Rosti ◽  
...  

1999 ◽  
Vol 45 (8) ◽  
pp. 1206-1213 ◽  
Author(s):  
Anders N Pedersen ◽  
Nils Brünner ◽  
Gunilla Høyer-Hansen ◽  
Peter Hamer ◽  
David Jarosz ◽  
...  

Abstract Background: The complex between urokinase (uPA) and its type-1 inhibitor (PAI-1) is formed exclusively from the active forms of these components; thus, the complex concentration in a biological sample may reflect the ongoing degree of plasminogen activation. Our aim was to establish an ELISA for specific quantification of the uPA:PAI-1 complex in plasma of healthy donors and breast cancer patients. Methods: A kinetic sandwich format immunoassay was developed, validated, and applied to plasma from 19 advanced-stage breast cancer patients, 39 age-matched healthy women, and 31 men. Results: The assay detection limit was <2 ng/L, and the detection of complex in plasma was validated using immunoabsorption, competition, and recovery tests. Eighteen cancer patients had a measurable complex concentration (median, 68 ng/L; range, <16 to 8700 ng/L), whereas for healthy females and males the median signal values were below the detection limit (median, <16 ng/L; range, <16 to 200 ng/L; P <0.0001). For patient plasma, a comparison with total uPA and PAI-1 showed that the complex represented a variable, minor fraction of the uPA and PAI-1 concentrations of each sample. Conclusion: The reported ELISA enables detection of the uPA:PAI-1 complex in blood and, therefore, the evaluation of the complex as a prognostic marker in cancer.


2015 ◽  
Vol 33 (28_suppl) ◽  
pp. 145-145 ◽  
Author(s):  
Hiromitsu Jinno ◽  
Takeshi Murata ◽  
Makoto Sunamura ◽  
Masahiro Sugimoto

145 Background: Saliva is an easily accessible and informative biological fluid which has high potential for the early diagnosis of diseases. Saliva-based diagnostics, particularly those based on metabolomics technology, offer a promising clinical strategy by characterizing the association between salivary analysts and a particular disease. The aim of this study is to investigate potential biomarkers in human saliva to facilitate the early diagnosis of breast cancer. Methods: We conducted a comprehensive metabolite analysis of saliva samples obtained from 60 breast cancer patients and 20 healthy controls, using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). Statistical analyses were performed by using a nonparametric Mann-Whitney U test, multiple logistic regression and the receiver operating characteristics (ROC) to evaluate the predictive power of biomarkers. Results: Forty-nine patients (81.7 %) had invasive ductal carcinoma (IDC) and 9 patients (15.0 %) had ductal carcinoma in situ. In 33 patients receiving neoadjuvant treatment, saliva samples were obtained just before surgery. After removing the concomitantly observed peaks and noise peaks, an average of 205 peaks were derived from the metabolites. Among these peaks, five potential salivary biomarkers demonstrated significantly higher concentrations in breast cancer patients comparing with healthy individuals (p < 0.05). Especially, salivary biomarkers obtained from patients with IDC before neoadjuvant treatments tended to be higher concentrations than those obtained after treatment. In these metabolites, the area under the ROC curves (AUCs) were 0.765 for substance A, 0.716 for substance B, 0.809 for substance C, 0.819 for substance D and 0.850 for substance E. Conclusions: Salivary metabolites are promising biomarkers for the early diagnosis of breast cancer.


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