Identification of Prostate Cancer Predisposition Genes on the Y Chromosome

Abstract

We hypothesize the existence of Y chromosome genes/variants related to increased risk, and propose multiple genetic analyses to efficiently identify the responsible genes or variants. We used a unique genealogical resource and a novel study design to identify men carrying Y chromosomes exhibiting high- and low-risk of prostate cancer. We sequenced the Y chromosome to identify rare variants associated with risk, and validated candidate variants in additional high- and low-risk Y chromosome carriers. Analysis of the 10 high risk Y sequence data compared to the 10 low risk data identified a set of 3 coding and 3 non-coding candidate variants seen in excess in high-risk Y chromosomes and not observed in the low risk set We selected 100 Utah Y chromosomes for complete Y chromosome sequencing as cases and acquired Y chromosome sequence data for 1,800 control men. Data fur the 100 additional samples was used to statistically test the 6 candidate variants identified in the initial set of 10 high risk cases and 10 controls; there were no significant results. We also used the high-risk YID cases' sequence data to identify 3 additional candidate variants observed in excess in high-risk Y chromosomes; these 3 candidates were tested with a taqman assay in an additional 150 high risk YID samples and 650 low to normal prostate risk YID samples. No significant results were found

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2019
Accession Number
AD1095290

Entities

People

  • Lisa Cannon-Albright

Organizations

  • University of Utah

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Chromosomes
  • Computational Biology
  • Computer Programming
  • Computer Programs
  • Data Sets
  • Genes
  • Genetic Phenomena
  • Genetic Structures
  • Genetics
  • Genome
  • Genotypes
  • Neoplasms
  • Prostate
  • Prostate Cancer
  • Quality Control
  • Sequences

Fields of Study

  • Biology

Readers

  • Molecular and genetic basis of cancer.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • Biotechnology