Neural autoantibody clusters aid diagnosis of cancer

Erika S. Horta, Vanda A. Lennon, Daniel H. Lachance, Sarah M. Jenkins, Carin Y. Smith, Andrew McKeon, Christopher Klein, Sean J. Pittock

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


Purpose: Clustering of neural autoantibodies in patients with paraneoplastic neurologic disorders may predict tumor type. A mathematical analysis of neural autoantibody clusters was performed in 78,889 patients undergoing evaluation for a suspected paraneoplastic autoimmune neurologic disorder. Tumor predictive autoantibody profiles were confirmed in sera from patients with histologically proven tonsillar cancer, thymoma, and lung cancer. Patients and Methods: Of note, 78,889 patient sera were tested for 15 defined neural autoantibodies (1.2 million tests). The observed and hypothesized frequencies of autoantibody clusters were compared and their tumor associations defined. A tumor validation study comprised serum from 368 patients with a variety of tumors (thymoma, lung, or tonsil). Results: Informative oncological associations included (i) thymoma in 85% of patients with muscle striational, acetylcholine receptor antibodies plus CRMP5 autoantibodies; (ii) lung carcinoma in 80% with both P/Q-type and N-type calcium channel antibodies plus SOX1-IgG; and (iii) in men, prostate carcinoma frequency more than doubled when striational and muscle AChR specificities were accompanied by ganglionic AChR antibody. In women, amphiphysin-IgG alone was associated commonly with breast carcinoma, but amphiphysin-IgG, coexisting with antineuronal nuclear autoantibody-type 1 or CRMP5-IgG, was associated with lung cancer (P < 0.0001). In the validation cohorts, many tumor-associated profiles were encountered that matched the clusters identified in the screening study (e.g., 15% of thymoma patients had striational, acetylcholine receptor antibodies plus collapsin response-mediator protein-5 autoantibodies). Conclusions: Neural autoantibodies commonly coexist in specific clusters that are identifiable by comprehensive screening. Signature autoantibody clusters may predict a patient's cancer risk and type.

Original languageEnglish (US)
Pages (from-to)3862-3869
Number of pages8
JournalClinical Cancer Research
Issue number14
StatePublished - Jul 15 2014

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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