Autoantibody biomarkers for the detection of serous ovarian cancer

Benjamin A. Katchman, Diego Chowell, Garrick Wallstrom, Allison F. Vitonis, Joshua LaBaer, Daniel W. Cramer, Karen Anderson

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

Objective The purpose of this study was to identify a panel of novel serum tumor antigen-associated autoantibody (TAAb) biomarkers for the diagnosis of high-grade serous ovarian cancer. Methods To detect TAAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/30 benign disease controls/30 healthy controls). Thirty-nine potential tumor autoantigens were identified and evaluated using an orthogonal programmable ELISA platform against a total of 153 sera samples (n = 63 cases/30 benign disease controls/60 healthy controls). Sensitivities at 95% specificity were calculated and a classifier for the detection of high-grade serous ovarian cancer was constructed. Results We identified 11-TAAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished high-grade serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 98% specificity. Conclusion These are potential circulating biomarkers for the detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts.

Original languageEnglish (US)
Pages (from-to)129-136
Number of pages8
JournalGynecologic Oncology
Volume146
Issue number1
DOIs
StatePublished - Jul 2017

Keywords

  • Autoantibody
  • Biomarker
  • Diagnostics
  • Ovarian cancer
  • Proteomics

ASJC Scopus subject areas

  • Oncology
  • Obstetrics and Gynecology

Fingerprint

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

Cite this