From sequence to molecular pathology, and a mechanism driving the neuroendocrine phenotype in prostate cancer Academic Article uri icon

Overview

MeSH Major

  • Adenocarcinoma
  • Biomarkers, Tumor
  • Cell Transformation, Neoplastic
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Neoplasms, Hormone-Dependent
  • Neuroendocrine Cells
  • Oligonucleotide Array Sequence Analysis
  • Prostatic Neoplasms

abstract

  • The current paradigm of cancer care relies on predictive nomograms which integrate detailed histopathology with clinical data. However, when predictions fail, the consequences for patients are often catastrophic, especially in prostate cancer where nomograms influence the decision to therapeutically intervene. We hypothesized that the high dimensional data afforded by massively parallel sequencing (MPS) is not only capable of providing biological insights, but may aid molecular pathology of prostate tumours. We assembled a cohort of six patients with high-risk disease, and performed deep RNA and shallow DNA sequencing in primary tumours and matched metastases where available. Our analysis identified copy number abnormalities, accurately profiled gene expression levels, and detected both differential splicing and expressed fusion genes. We revealed occult and potentially dormant metastases, unambiguously supporting the patients' clinical history, and implicated the REST transcriptional complex in the development of neuroendocrine prostate cancer, validating this finding in a large independent cohort. We massively expand on the number of novel fusion genes described in prostate cancer; provide fresh evidence for the growing link between fusion gene aetiology and gene expression profiles; and show the utility of fusion genes for molecular pathology. Finally, we identified chromothripsis in a patient with chronic prostatitis. Our results provide a strong foundation for further development of MPS-based molecular pathology.

authors

publication date

  • January 2012

Research

keywords

  • Academic Article

Identity

Language

  • eng

PubMed Central ID

  • PMC3659819

Digital Object Identifier (DOI)

  • 10.1002/path.4047

PubMed ID

  • 22553170

Additional Document Info

start page

  • 286

end page

  • 97

volume

  • 227

number

  • 3