AI Article Synopsis

  • The study focused on evaluating gene expression in normal-looking tissues next to prostate tumors to see if it could help predict clinical recurrence of cancer after surgery.
  • Researchers identified 46 genes linked to recurrence, many of which also corresponded to expressions in tumor tissue, indicating that both tissue types may share relevant biological markers.
  • The findings, particularly involving the Genomic Prostate Score (GPS), suggest that gene expression patterns in adjacent non-tumor tissue can signal aggressive prostate cancer, highlighting a significant "field effect" influencing the disease's outcome.

Article Abstract

Purpose: We evaluated gene expression in histologically normal-appearing tissue (NT) adjacent to prostate tumor in radical prostatectomy specimens, assessing for biological significance based on prediction of clinical recurrence (cR - metastatic disease or local recurrence).

Results: A total of 410 evaluable patients had paired tumor and NT. Forty-six genes, representing diverse biological pathways (androgen signaling, stromal response, stress response, cellular organization, proliferation, cell adhesion, and chromatin remodeling) were associated with cR in NT (FDR < 20%), of which 39 concordantly predicted cR in tumor (FDR < 20%). Overall GPS and its stromal response and androgen-signaling gene group components also significantly predicted time to cR in NT (RM-corrected HR/20 units = 1.25; 95% CI: 1.01-1.56; P = 0.024).

Experimental Design: Expression of 732 genes was measured by quantitative reverse transcriptase polymerase chain reaction (RT-PCR) separately in tumor and adjacent NT specimens from 127 patients with and 374 without cR following radical prostatectomy for T1/T2 prostate cancer. A 17-gene expression signature (Genomic Prostate Score [GPS]), previously validated to predict aggressive prostate cancer when measured in tumor tissue, was also assessed using pre-specified genes and algorithms. Analysis used Cox proportional hazards models, Storey's false discovery rate (FDR) control, and regression to the mean (RM) correction.

Conclusions: Gene expression profiles, including GPS, from NT adjacent to tumor can predict prostate cancer outcome. These findings suggest that there is a biologically significant field effect in primary prostate cancer that is a marker for aggressive disease.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5085124PMC
http://dx.doi.org/10.18632/oncotarget.8944DOI Listing

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