Acute phase serum amyloid A in ovarian cancer as an important component of proteome diagnostic profiling

Abstract

In the context of serum amyloid A (SAA) identification as ovarian cancer marker derived by SELDI-MS, its serum levels were measured by immunoassay in different stages of ovarian cancer, in benign gynecological tumors, and in healthy controls. In addition, SELDI-TOF-MS spectra were obtained by protocol optimized for the SAA peak intensity. SELDI data on small proteins (5.5-17.5 kDa) and SAA immunoassay data were combined with cancer antigen (CA)125 data in order to study the classification accuracy between cancer and noncancer by support vector machine (SVM), logistic regression, and top scoring pair classifiers. Although an addition of SAA immunoassay data to CA125 data did not significantly improve cancer/noncancer discrimination, SVM applied to combined biomarker data (CA125 and SAA immunoassay variables plus 48 SELDI peak variables) yielded the best classification rate (accuracy 95.2% vs. 86.2% for CA125 alone). Notably, most of discriminatory peaks selected by the classifiers have significant correlation with the major known peaks of SAA (11.7 kDa) and transthyretin (13.9 kDa). Acute phase serum amyloid A (A-SAA) was proved to be an important member of cancer discriminatory protein profile. Among the eight known ovarian cancer SELDI profile components, A-SAA is the most relevant to molecular pathogenesis of cancer and it has the highest degree of up-regulation in disease.

Understanding Ovarian Cancer: iTRAQ-Based Proteomics for Biomarker Discovery

“…The expression of SAA gradually increased during progression from BOT and borderline tumors to OC [37]. SAA1 was also identified by SELDI-TOF MS, and further validated by immunoassay, as a potential biomarker of OC [21,38]. Moreover, up-regulation of SAA1 was observed in OC patients by Rauniyar et al [31].…”

Identifying Serum Biomarkers for Ovarian Cancer by Screening With Surface-Enhanced Laser Desorption/Ionization Mass Spectrometry and the Artificial Neural Network

“…Among the 8 known ovarian cancer SELDI profile components, acute-phase serum amyloid A is the most relevant to the molecular pathogenesis of cancer, and it has the highest degree of up-regulation in disease. 20 11.7 kd protein as amyloid A1, the potential biomarker for ovarian cancer. We think that the 11.7 kd biomarker identified in our study is serum amyloid A1 because this protein has also been identified as a tumor biomarker in studies of several other types of malignancies.…”

OMICS for Tumor Biomarker Research

“…Candidate protein biomarkers are often validated by independent assay, such as immunoassay (Moshkovskii et al 2007;Zhang et al 2004). Most, if not all, peptide and protein candidates identified by MALDI-TOF plasma profiling represent highly abundant products, such as inflammatory acute-phase proteins (complement fragments, serum amyloid A), lipoproteins, and protease inhibitors (inter-alpha-trypsin inhibitor).…”