Integrated proteomic analysis of human cancer cells and plasma from tumor bearing mice for ovarian cancer biomarker discovery.

BACKGROUND: The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery. METHODOLOGY/PRINCIPAL FINDINGS: We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease. CONCLUSIONS/SIGNIFICANCE: Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.

Focused glycomic analysis of the N-linked glycan biosynthetic pathway in ovarian cancer.

Epithelial ovarian cancer is the deadliest female reproductive tract malignancy in Western countries. Less than 25% of cases are diagnosed when the cancer is confined, however, pointing to the critical need for early diagnostics for ovarian cancer. Identifying the changes that occur in the glycome of ovarian cancer cells may provide an avenue to develop a new generation of potential biomarkers for early detection of this disease. We performed a glycotranscriptomic analysis of endometrioid ovarian carcinoma using human tissue, as well as a newly developed mouse model that mimics this disease. Our results show that the N-linked glycans expressed in both nondiseased mouse and human ovarian tissues are similar; moreover, malignant changes in the expression of N-linked glycans in both mouse and human endometrioid ovarian carcinoma are qualitatively similar. Lectin reactivity was used as a means for rapid validation of glycan structural changes in the carcinomas that were predicted by the glycotranscriptome analysis. Among several changes in glycan expression noted, the increase of bisected N-linked glycans and the transcripts of the enzyme responsible for its biosynthesis, GnT-III, was the most significant. This study provides evidence that glycotranscriptome analysis can be an important tool in identifying potential cancer biomarkers.