Correlation between centromere protein-F autoantibodies and cancer analyzed by enzyme-linked immunosorbent assay

BACKGROUND: Centromere protein-F (CENP-F) is a large nuclear protein of 367 kDa, which is involved in multiple mitosis-related events such as proper assembly of the kinetochores, stabilization of heterochromatin, chromosome alignment and mitotic checkpoint signaling. Several studies have shown a correlation between CENP-F and cancer, e.g. the expression of CENP-F has been described to be upregulated in cancer cells. Furthermore, several studies have described a significant correlation between the expression of autoantibodies to CENP-F and cancer. METHODS: Autoantibodies to CENP-F were detected in a small number of samples during routine indirect immunofluorescence (IIF) analysis for anti-nuclear antibodies (ANA) using HEp-2 cells as substrate. Using overlapping synthetic peptides covering a predicted structural maintenance of chromosomes (SMC) domain, we developed an enzyme-linked immunosorbent assay (ELISA) for detection of CENP-F antibodies. RESULTS: Analyzing the reactivity of the sera positive in IIF for CENP-F antibodies to overlapping CENP-F peptides, we showed that autoantibodies to several peptides correlate with the presence of antibodies to CENP-F and a diagnosis of cancer, as increased CENP-F antibody expression specific for malignant cancer patients to five peptides was found (A9, A12, A14, A16, A27). These antibodies to CENP-F in clinical samples submitted for ANA analysis were found to have a positive predictive value for cancer of 50%. Furthermore, the expression of cancer-correlated CENP-F antibodies seemed to increase as a function of time from diagnosis. CONCLUSION: These results conform to previous findings that approximately 50% of those patients clinically tested for ANA analyses who express CENP-F antibodies are diagnosed with cancer, confirming that these antibodies may function as circulating tumor markers. Thus, a peptide-based CENP-F ELISA focused on the SMC domain may aid in identifying individuals with a potential cancer.