Comparison of the Diagnostic Performance of Urine and Serum Protein Biomarkers in Ovarian Cancer

2014 ◽  
Vol 6 (1) ◽  
pp. 73-82
Author(s):  
Hye-Jeong Song ◽  
Ju-Hyun Cho ◽  
Chan-Young Park ◽  
Yu-Seop Kim ◽  
Jong-Dae Kim
Keyword(s):  
Ovarian Cancer ◽  
Serum Protein ◽  
Diagnostic Performance ◽  
Protein Biomarkers ◽  
Urine And Serum

Proteomic analysis for early detection of ovarian cancer: A realistic approach?

2003 ◽  
Vol 13 (Suppl 2) ◽  
pp. 133-139 ◽  
Author(s):  
E. V. Stevens ◽  
L. A. Liotta ◽  
E. C. Kohn
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Serum Protein ◽  
Mass Spectroscopy ◽  
Biomarker Discovery ◽  
Protein Pattern ◽  
Protein Biomarkers ◽  
Promising Tool ◽  
Chip Technology ◽  
Stage Disease

Ovarian cancer is a multifaceted disease wherein most women are diagnosed with advanced stage disease. One of the most imperative issues in ovarian cancer is early detection. Biomarkers that allow cancer detection at stage I, a time when the disease is amenable to surgical and chemotherapeutic cure in over 90% of patients, can dramatically alter the horizon for women with this disease. Recent developments in mass spectroscopy and protein chip technology coupled with bioinformatics have been applied to biomarker discovery. The complexity of the proteome is a rich resource from which the patterns can be gleaned; the pattern rather than its component parts is the diagnostic. Serum is a key source of putative protein biomarkers, and, by its nature, can reflect organ-confined events. Pioneering use of mass spectroscopy coupled with bioinformatics has been demonstrated as being capable of distinguishing serum protein pattern signatures of ovarian cancer in patients with early- and late-stage disease. This is a sensitive, precise, and promising tool for which further validation is needed to confirm that ovarian cancer serum protein signature patterns can be a robust biomarker approach for ovarian cancer diagnosis, yielding improved patient outcome and reducing the death and suffering from ovarian cancer.

Abstract B20: Simultaneous measurement of 92 serum protein biomarkers for the development of a multiprotein classifier for ovarian cancer detection

2018 ◽  
Author(s):  
Amy P.N. Skubitz ◽  
Kristin L.M. Boylan ◽  
Kate Geschwind ◽  
Qing Cao ◽  
Timothy K. Starr ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Serum Protein ◽  
Cancer Detection ◽  
Simultaneous Measurement ◽  
Protein Biomarkers

Prognostic value of serum protein biomarkers in patients with epithelial ovarian cancer.

2010 ◽  
Vol 28 (15_suppl) ◽  
pp. 10567-10567
Author(s):  
M. Wang ◽  
S. Bush ◽  
S. A. Ghamande ◽  
J. She
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Serum Protein ◽  
Prognostic Value ◽  
Protein Biomarkers

scholarly journals Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multiprotein Classifier for Ovarian Cancer Detection

2019 ◽  
Vol 12 (3) ◽  
pp. 171-184 ◽  
Author(s):  
Amy P.N. Skubitz ◽  
Kristin L.M. Boylan ◽  
Kate Geschwind ◽  
Qing Cao ◽  
Timothy K. Starr ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Serum Protein ◽  
Cancer Detection ◽  
Simultaneous Measurement ◽  
Protein Biomarkers

scholarly journals Plasma Protein Biomarkers Associated with Higher Ovarian Cancer Risk in BRCA1/2 Carriers

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2300
Author(s):  
Hee-Sung Ahn ◽  
Jung Yoon Ho ◽  
Jiyoung Yu ◽  
Jeonghun Yeom ◽  
Sanha Lee ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Plasma Protein ◽  
Normal Subjects ◽  
Genetic Alterations ◽  
Enzyme Linked Immunosorbent Assay ◽  
Ovarian Cancer Risk ◽  
Protein Markers ◽  
Protein Biomarkers ◽  
Proteomics Approach ◽  
Risk Reducing

Ovarian cancer (OC) is the most lethal gynecologic malignancy and in-time diagnosis is limited because of the absence of effective biomarkers. Germline BRCA1/2 genetic alterations are risk factors for hereditary OC; risk-reducing salpingo-oophorectomy (RRSO) is pursued for disease prevention. However, not all healthy carriers develop the disease. Therefore, identifying predictive markers in the BRCA1/2 carrier population could help improve the identification of candidates for preventive RRSO. In this study, plasma samples from 20 OC patients (10 patients with BRCA1/2 wild type (wt) and 10 with the BRCA1/2 variant (var)) and 20 normal subjects (10 subjects with BRCA1/2wt and 10 with BRCA1/2var) were analyzed for potential biomarkers of hereditary OC. We applied a bottom-up proteomics approach, using nano-flow LC-MS to analyze depleted plasma proteome quantitatively, and potential plasma protein markers specific to the BRCA1/2 variant were identified from a comparative statistical analysis of the four groups. We obtained 1505 protein candidates from the 40 subjects, and SPARC and THBS1 were verified by enzyme-linked immunosorbent assay. Plasma SPARC and THBS1 concentrations in healthy BRCA1/2 carriers were found to be lower than in OC patients with BRCA1/2var. If plasma SPARC concentrations increase over 337.35 ng/ml or plasma THBS1 concentrations increase over 65.28 mg/ml in a healthy BRCA1/2 carrier, oophorectomy may be suggested.

Serum protein biomarkers screening in HCC patients with liver cirrhosis by ICAT-LC-MS/MS

2010 ◽  
Vol 136 (8) ◽  
pp. 1151-1159 ◽  
Author(s):  
Xiaonan Kang ◽  
Lu Sun ◽  
Kun Guo ◽  
Hong Shu ◽  
Jun Yao ◽  
...  
Keyword(s):  
Liver Cirrhosis ◽  
Serum Protein ◽  
Protein Biomarkers

scholarly journals Serum Protein Profile at Remission Can Accurately Assess Therapeutic Outcomes and Survival for Serous Ovarian Cancer

PLoS ONE ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. e78393 ◽  
Author(s):  
Jinhua Wang ◽  
Ashok Sharma ◽  
Sharad A. Ghamande ◽  
Stephen Bush ◽  
Daron Ferris ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Serum Protein ◽  
Protein Profile ◽  
Serous Ovarian Cancer ◽  
Therapeutic Outcomes ◽  
Serum Protein Profile

scholarly journals Screening and validation of serum protein biomarkers for early postmenopausal osteoporosis diagnosis

2017 ◽  
Vol 16 (6) ◽  
pp. 8427-8433 ◽  
Author(s):  
Long Wang ◽  
Ya-Qian Hu ◽  
Zhuo-Jie Zhao ◽  
Hong-Yang Zhang ◽  
Bo Gao ◽  
...  
Keyword(s):  
Postmenopausal Osteoporosis ◽  
Serum Protein ◽  
Protein Biomarkers ◽  
Osteoporosis Diagnosis

scholarly journals Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis

2020 ◽  
Author(s):  
Angela Mc Ardle ◽  
Anna Kwasnik ◽  
Agnes Szenpetery ◽  
Melissa Jones ◽  
Belinda Hernandez ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Serum Protein ◽  
Clinical Decision Making ◽  
Multiple Reaction Monitoring ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Additional Patient ◽  
Second Phase ◽  
Protein Biomarkers ◽  
Protein Discovery

AbstractObjectivesTo identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention.MethodsIn an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167).ResultsMultivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85.ConclusionWe report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.

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