AI Article Synopsis
- - The study aimed to identify specific serum protein profiles associated with ovarian cancer by comparing samples from 36 cancer patients and 30 healthy individuals using specialized mass spectrometry.
- - Researchers found 29 protein peaks that were significantly different between the groups, with three specific peaks identified as potential ovarian cancer biomarkers, displaying high sensitivity and specificity.
- - The findings support that serum biomarkers can help diagnose ovarian cancer and detect cases related to drug resistance, particularly through the expression of MDR1 and MRP proteins in patients.
Article Abstract
Objective: To develop the rationales for ovarian cancer-specific protein profiles in serum and to analyze the protein profiles of multidrug resistance P-glucoprotein (MDR1) and multidrug resistance-associated protein (MRP) positive and negative expression sets for a rapid and sensitive serum protein pattern.
Method: Serum protein profiles from 36 epithelial ovarian cancer cases were compared with 30 healthy controls using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (DELDI-TOF-MS). Blinded test was conducted subsequently for identification of the protein pattern. Expression of MDR and MRP were detected in set of training cases by immunohistochemistry. The spectra were analyzed statistically between positive and negative groups.
Results: Twenty-nine peaks were significantly different between ovarian cancer and healthy controls (P < 0.01, 15 peaks up-regulated and 14 down-regulated). A set of three peaks, at 5 486, 6 463 and 8 575 m/z respectively, were selected from 29 sense peaks as an ovarian cancer biomarker. The sensitivity was 100% and specificity 93.33%. Identification by blinded validation indicated a positive predictive value of 90%. MDR1 expression in ovarian cancer was 69.4 %. Twenty peaks were significantly different between positive and negative sets (P < 0.01). MRP expression in ovarian cancer was 63.8%. But one peak was detected (P < 0.01).
Conclusion: It was an ideal pattern for employing the SELDI mass spectrum approach to diagnose ovarian cancer and select the multidrug resistance cases. Serum biomarkers for detecting drug resistance in ovarian cancer can be established on the basis of MDR1 immunohistochemistry.
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