BACKGROUNDEndometriosis is a common gynecological disease. This study aimed to screen proteins that were expressed differently in patients with endometriosis versus normal controls using proteomic techniques, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS).

METHODSProtein chip SELDI-TOF-MS combines the advantages of microarray and mass spectrometry, and can screen latent markers in sera of patients with endometriosis. Serum samples from patients and normal volunteers were analyzed by SELDI-TOF-MS.

RESULTSAfter comparing the serum protein spectra of 36 patients with 24 normal controls, 24 differently expressed potential biomarkers (P < 0.01) were identified. Using Biomarker Pattern software, we established a tree model of the 60 serum protein spectra. When using the three biomarkers to classify the samples, the sensitivity for diagnosing endometriosis was 91.7%, specificity was 95.8%, and coincidence rate was 93.3%. Then we used serum samples from 12 patients and 8 normal controls to validate the tree model and report the sensitivity for diagnosing endometriosis was 91.7%, specificity was 75%, and coincidence rate was 85%.

CONCLUSIONSSELDI-TOF-MS may be a useful tool in high-risk population screening for endometriosis. The identification and application of the biomarkers need to further study.