Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies

Radka Stoyanova, Alan Pollack, Mandeep Takhar, Charles Lynne, Nestor Parra, Lucia L.C. Lam, Mohammed Alshalalfa, Christine Buerki, Rosa Castillo, Merce Jorda, Hussam Al Deen Ashab, Oleksandr N. Kryvenko, Sanoj Punnen, Dipen J. Parekh, Matthew C. Abramowitz, Robert J. Gillies, Elai Davicioni, Nicholas Erho, Adrian Ishkanian

Research output: Contribution to journalArticlepeer-review

55 Scopus citations


Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective was to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues. Global gene expression profiles were generated from 17 mpMRI-directed diagnostic prostate biopsies using an Affimetrix platform. Spatially distinct imaging areas ('habitats') were identified on MRI/3D-Ultrasound fusion. Radiomic features were extracted from biopsy regions and normal appearing tissues. We correlated 49 radiomic features with three clinically available gene signatures associated with adverse outcome. The signatures contain genes that are over-expressed in aggressive prostate cancers and genes that are under-expressed in aggressive prostate cancers. There were significant correlations between these genes and quantitative imaging features, indicating the presence of prostate cancer prognostic signal in the radiomic features. Strong associations were also found between the radiomic features and significantly expressed genes. Gene ontology analysis identified specific radiomic features associated with immune/inflammatory response, metabolism, cell and biological adhesion. To our knowledge, this is the first study to correlate radiogenomic parameters with prostate cancer in men with MRI-guided biopsy.

Original languageEnglish (US)
Pages (from-to)53362-53376
Number of pages15
Issue number33
StatePublished - Aug 1 2016


  • Gene expression
  • MRI-targeted biopsies
  • Multiparametric MRI
  • Prostate cancer
  • Radiogenomics

ASJC Scopus subject areas

  • Oncology


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