IgG Responses to Tissue-Associated Antigens as Biomarkers of Immunological Treatment Efficacy

Abstract

We previously demonstrated that IgG responses to a panel of 126 prostate tissue-associated antigens are common in patients with prostate cancer. In the current report we questioned whether changes in IgG responses to this panel might be used as a measure of immune response, and potentially antigen spread, following prostate cancer-directed immune-active therapies. Sera were obtained from prostate cancer patients prior to and three months following treatment with androgen deprivation therapy (n = 34), a poxviral vaccine (n = 31), and a DNA vaccine (n = 21). Changes in IgG responses to individual antigens were identified by phage immunoblot. Patterns of IgG recognition following three months of treatment were evaluated using a machine-learned Bayesian Belief Network (ML-BBN). We found that different antigens were recognized following androgen deprivation compared with vaccine therapies. While the number of clinical responders was low in the vaccine-treated populations, we demonstrate that ML-BBN can be used to develop potentially predictive models.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2011
Accession Number
ADA535502

Entities

People

  • Benjamin Peterson
  • Brett B. Maricque
  • Douglas G. Mcneel
  • Heath A. Smith
  • James L. Gulley
  • Jeffrey Schlom
  • John Eberhardt

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Biological Markers
  • Biotechnology
  • Blood
  • Cancer
  • Cells
  • Chemistry
  • Computer Science
  • Data Sets
  • Diseases And Disorders
  • Immune System
  • Immunomodulation
  • Lymphocytes
  • Machine Learning
  • Neoplasms
  • Prostate Cancer
  • Vaccines

Fields of Study

  • Biology
  • Medicine

Readers

  • Immunology
  • Neural Network Machine Learning.
  • Oncology (Cancer Research).

Technology Areas

  • AI & ML
  • Biotechnology