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Gene expression in normal-appearing tissue adjacent to prostate cancers are predictive of clinical outcome: evidence for a biologically meaningful field effect

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...

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Detalles Bibliográficos
Autores principales: Magi-Galluzzi, Cristina, Maddala, Tara, Falzarano, Sara Moscovita, Cherbavaz, Diana B., Zhang, Nan, Knezevic, Dejan, Febbo, Phillip G., Lee, Mark, Lawrence, Hugh Jeffrey, Klein, Eric A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5085124/
https://www.ncbi.nlm.nih.gov/pubmed/27121323
http://dx.doi.org/10.18632/oncotarget.8944
Descripción
Sumario: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. Fortysix 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.