Comprehensive serum proteomic analysis in early endometrial cancer

Objective: Endometrial cancer is the most common gynecologic cancer and yet much is still unknown about this disease. Our goal was to identify unique biomarkers of disease by performing a comprehensive proteomic analysis of early stage, low-grade endometrial cancer through analysis of serum collected from patients pre- and post-definitive surgery. Methods: We used mass spectrometry (MS)-based proteomics to identify serum proteins from these patients. Serum samples from women undergoing hysterectomy with bilateral salpingo-oophorectomy for benign reasons served as control samples for the correlative studies. We then correlated our findings with The Cancer Genome Atlas (TCGA) database for additional confirmation. Results: The Ingenuity Pathway Analysis of proteins that were differentially expressed in endometrial cancer showed increased cell survival and decreased organismal death, the most common hallmarks of cancer. We identified over expression of FAM83D (family with sequence similarity 83, member D) in the serum of patients with early stage low-grade endometrial cancer and verified the same in the endometrial cancer cell lines and patient tumors. We also confirmed our hypothesis that FAM83D may serve as a biomarker for endometrial cancer in a cohort of patients with endometrial cancer from The Cancer Genome Atlas (TCGA) project. Conclusion: Comprehensive proteomic analysis is a feasible strategy for potential biomarker identification. Using this technique, FAM83D was identified as a candidate biomarker in early endometrial cancer in our patient samples and was not present in benign control samples. FAM83D has been associated with poor clinical outcomes in several human malignancies. Significance: Our manuscript describes an alternative approach to comprehensive protein analysis in a model pre and post tumor removal for a sample of patients with early endometrial cancer. The model is innovative and the findings of over expression FAM83D in this population of early cancer may be useful in the study of a disease where there are few biomarkers or targetable therapies.