Prostate Cancer Prognostics Based on Genome Architecture

Abstract

Our objective was to develop a novel approach to distinguish indolent from aggressive prostate cancer, based on the differential non-random spatial organization of the genome. Individual genes occupy preferred positions within interphase nuclei, with the position of some genes altering in diseased states. We previously identified several genes that occupy different nuclear positions in cancerous prostate and breast tissue, compared to normal tissues. Here, we extend our studies for prognostic purposes, to identify genes that differentially localize in aggressive prostate cancer compared to indolent. Such markers are highly sought after by clinicians, to reduce the growing problem of overtreatment. We find that directional repositioning of SP100 and TGFB3 gene loci stratifies prostate cancers of differing Gleason scores. A more peripheral position of SP100 and TGFB3 in the nucleus, compared to benign tissues, is associated with low Gleason score cancers, whereas more internal positioning correlates with higher Gleason scores. Conversely, LMNA is more internally positioned in many non-metastatic prostate cancers, while its position is indistinguishable from benign tissue in metastatic cancer. The false positive rates were relatively low, whereas, the false negative rates of single or combinations of genes were high, limiting the clinical utility of this assay in its current form. Additionally, the positioning patterns of SATB1 did not correlate with prognostics clinical features. Nevertheless, our results provide the first proof-of-principle that the spatial positioning of the genes can be used for clinal prognostic purposes.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2019
Accession Number
AD1097347

Entities

People

  • Karen Meaburn
  • Tom Misteli

Organizations

  • Geneva Foundation

Tags

DTIC Thesaurus Topics

  • Cell Physiological Processes
  • Cells
  • Chemical Synthesis
  • Chemistry
  • Chromosomes
  • Colon Cancer
  • Disease Attributes
  • Fungi
  • Genetics
  • Health Services
  • Medical Personnel
  • Oncology
  • Proteins

Fields of Study

  • Biology

Readers

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