ABSTRACT
Objective To probe the clinical values of the human serum glycoprotein profiles for the diagnosis of common gynecological tumors. Methods A total of 123 clinical serum samples which included 31 breast cancer, 24 cervical cancer, 19 ovarian cancer and 49 healthy individuals were collected. A lectin microarray consisting of 15 lectins with different glycan binding specificities was used to determine the glycoprotein profiles of serum sam-ples. Stepwise discrimination analysis method was adopted to establish function model of clinical serum samples classification with SPSS 15. 0 software. Results Two grades of diagnostic discrimination function models were es-tablished. The first grade discrimination function could differentiate gynecological tumors from healthy individuals, the diagnostic accuracy rates of retrospective inspection were 85. 7% and 83. 8% respectively, and the total diag-nostic accuracy rate was 84.6%. The second grade discrimination function was used to differentiate breast tumor, cervical tumor and ovarian tumor, the diagnostic accuracy rates of retrospective inspection were 96.8%,75.0%and 78.9% respectively, and the total diagnostic accuracy rate was 85.1%. Conclusion The human serum gly-coprotein profiles are associated with gynecological tumors, and the established discrimination function models based on lectin microarray data have a helpful reference value for the clinical diagnosis of gynecological tumors.