Autoantibody signature for the serologic detection of ovarian cancer

Karen Anderson, Daniel W. Cramer, Sahar Sibani, Garrick Wallstrom, Jessica Wong, Jin Park, Ji Qiu, Allison Vitonis, Joshua LaBaer

Research output: Contribution to journalArticlepeer-review

87 Scopus citations

Abstract

Sera from patients with ovarian cancer contain autoantibodies (AAb) to tumor-derived proteins that are potential biomarkers for early detection. To detect AAb, we probed high-density programmable protein microarrays (NAPPA) expressing 5177 candidate tumor antigens with sera from patients with serous ovarian cancer (n = 34 cases/30 controls) and measured bound IgG. Of these, 741 antigens were selected and probed with an independent set of ovarian cancer sera (n = 60 cases/60 controls). Twelve potential autoantigens were identified with sensitivities ranging from 13 to 22% at >93% specificity. These were retested using a Luminex bead array using 60 cases and 60 controls, with sensitivities ranging from 0 to 31.7% at 95% specificity. Three AAb (p53, PTPRA, and PTGFR) had area under the curve (AUC) levels >60% (p < 0.01), with the partial AUC (SPAUC) over 5 times greater than for a nondiscriminating test (p < 0.01). Using a panel of the top three AAb (p53, PTPRA, and PTGFR), if at least two AAb were positive, then the sensitivity was 23.3% at 98.3% specificity. AAb to at least one of these top three antigens were also detected in 7/20 sera (35%) of patients with low CA 125 levels and 0/15 controls. AAb to p53, PTPRA, and PTGFR are potential biomarkers for the early detection of ovarian cancer.

Original languageEnglish (US)
Pages (from-to)578-586
Number of pages9
JournalJournal of Proteome Research
Volume14
Issue number1
DOIs
StatePublished - Jan 2 2015

Keywords

  • Ovarian cancer
  • autoantibodies
  • biomarker
  • protein microarrays
  • proteomics

ASJC Scopus subject areas

  • General Chemistry
  • Biochemistry

Fingerprint

Dive into the research topics of 'Autoantibody signature for the serologic detection of ovarian cancer'. Together they form a unique fingerprint.

Cite this