A Multiplex Cancer/Testis Antigen-Based Biomarker Panel to Predict Aggressive Phenotype of Prostate Cancer

Abstract

The Cancer/Testis Antigens (CTAs) are a group of proteins normally confined to germ cells but aberrantly expressed in several cancers. The central hypothesis of this grant application is that a CTA-based biomarker can be used to discern LPCa from MPCa. In the first year of this grant, we determined gene expression of 22 candidate CTAs by Nanostring and validated by qRT-PCR. During the second year of the grant, we used ROC curve analysis and identified 8 CTA genes (CEP55, NUF2, PAGE4, PBK, RQCD1, SPAG4, SSX2 and TTK), which expression pattern is significant different between aggressive and indolent tumors. For the third year of the grant, we evaluated the gene expression of these 8 CTAs in PCa and benign adjacent paired tissues from 24 patients. The only CTAs differentially expressed between non-cancer and cancer areas were PAGE4, SPAG4 and SSX2. For all the selected biomarker candidates, we obtained commercial antibodies from two sources and performed optimization using training TMAs containing normal and tumor prostate tissue. Quantification of the CTAs protein expression is being performed using an automated image system. We also performed CTA expression analysis in PCa cell lines (DU145, LNCAP, PC3, PC3 Epi, PC3 EMT and BPH1) by qRT-PCR and Western Blot. Absence of gene expression correlated with no protein translation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2015
Accession Number
AD1008364

Entities

People

  • Robert W. Veltri

Organizations

  • Johns Hopkins University

Tags

DTIC Thesaurus Topics

  • Antibodies
  • Antigens
  • Biological Markers
  • Cell Line
  • Cells
  • Diseases And Disorders
  • Gene Expression
  • Genes
  • Germ Cells
  • Neoplasms
  • Optimization
  • Prostate
  • Prostate Cancer
  • Proteins
  • Regression Analysis
  • Statistical Analysis
  • Tissues

Fields of Study

  • Biology

Readers

  • Molecular Biology and Genetics
  • Oncology and Biomarker-Based Cancer Detection.
  • Prostate Cancer Biology.

Technology Areas

  • AI & ML