Hyaluronic Acid and Hyaluronidase in Prostate Cancer: Evaluation of Their Therapeutic and Prognostic Potential

Abstract

Identification of accurate prognostic indicators could aid in individualization of treatment and better prediction of outcome or prostate cancer patients. Treatment modalities that target these molecules could effectively control CaP progression. The results of this project identify HYAL1 type hyaluronidase (HAase) as one such molecule. HA is a glycosaminoglycan and HAase is an enzyme that degrades HA into angiogenic fragments. Immunohistochemical analysis using archival radical prostatectomy CaP specimens from patients on whom there is 72-131 month follow-up show that HYAL1 and combined HA-HYAL1 inferences staining are independent predictors for biochemical recurrence. Studies on HYAL1 transfectants show that blocking HYAL1 expression in CaP cells, decreases growth and invasive activity by 3-4 fold. Lack of HYAL1 expression blocks CaP cells in G2-M phase of the cell cycle. HYAL1-AS transfectants show a 4-7 fold decrease in tumor growth, and generate tumors that are non-infiltrating and less vascularized. HAase inhibitors such as inhibit CaP cell growth in a dose-dependent manner. Transfectants expressing high HYAL1 levels also grow 4-fold slower and undergo apoptosis. High HYAL1 producing transfectants show either decreased tumor growth (3-fold) or do not form tumors. Ongoing studies are examining the effect of HAase inhibition on gene expression by cDNA microarray analysis.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA434622

Entities

People

  • Vinata B. Lokeshwar

Organizations

  • University of Miami

Tags

DTIC Thesaurus Topics

  • Blood
  • Breast Cancer
  • Cancer
  • Carcinoma
  • Cell Physiological Processes
  • Cells
  • Chemical Synthesis
  • Chemistry
  • Colon Cancer
  • Dna Microarrays
  • Medical Personnel
  • Microarray Analysis
  • Neoplasms
  • Oncology
  • Prostate Cancer

Fields of Study

  • Biology

Readers

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  • Molecular and genetic basis of cancer.
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Technology Areas

  • AI & ML