Access Type

Open Access Dissertation

Date of Award

January 2020

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Cancer Biology

First Advisor

Michael A. Tainsky

Abstract

The majority of ovarian cancer cases are diagnosed at an advanced stage metastatic disease with poor prognosis due to non-specific symptoms and lack of early detection methods. This study evaluates autoantibodies against tumor antigens to identify candidate biomarkers for the early detection of ovarian tumors in high-risk women. Paraneoplastic antigens are associated with autoimmune diseases termed paraneoplastic neurological syndromes (PNSs), which develop when the unregulated immune response against a tumor also targets healthy cells. Notably, a set of antibodies is found in PNS patients with ovarian cancer, identifying highly immunogenic antigens in the tumor. In this dissertation work, we have detected paraneoplastic antibodies present in the sera of patients with high-grade serous ovarian cancer (HGSOC) using line blots, western blots, and ELISA. A panel of five paraneoplastic antigens (HARS, TRIM21, COR, CDR2, CDR2L) along with 2 established tumor antigens (NY-ESO-1, p53) were purified from E. coli for screening on western blot and ELISA. Screening was performed with a patient serum set consisting of: 50 late stage HGSOC, 14 early stage HGSOC, 50 benign ovarian cyst, and 50 healthy volunteer samples. On western blot, the paraneoplastic antigen with the best performance was TRIM21with 35% sensitivity. Combining TRIM21 with p53 and NYESO-1 yielded a sensitivity of 60% with 90% specificity. In the early stage HGSOC sample set, HARS demonstrated 31% sensitivity individually, and 46% sensitivity with 98% specificity when combined with p53 and NYESO-1. The identified markers will were tested in an independent validation serum set consisting of n=150 samples. The work in this dissertation identified the paraneoplastic antigen TRIM21 that can enhance autoantibody biomarker panels for the early detection of HGSOC.

Included in

Biology Commons

Share

COinS