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


METHODS
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.
Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio, USA.|Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Cristina
C
Magi-Galluzzi
Genomic Health, Inc., Redwood City, California, USA.
Tara
T
Maddala
Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Sara Moscovita
SM
Falzarano
Genomic Health, Inc., Redwood City, California, USA.
Diana B
DB
Cherbavaz
Genomic Health, Inc., Redwood City, California, USA.
Nan
N
Zhang
Genomic Health, Inc., Redwood City, California, USA.
Dejan
D
Knezevic
Genomic Health, Inc., Redwood City, California, USA.
Phillip G
PG
Febbo
Genomic Health, Inc., Redwood City, California, USA.
Mark
M
Lee
Genomic Health, Inc., Redwood City, California, USA.
Hugh Jeffrey
HJ
Lawrence
Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Eric A
EA
Klein
D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics*; D018450:Disease Progression; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis; D009364:Neoplasm Recurrence, Local; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011467:Prostate / Q000378:metabolism* / Q000473:pathology / Q000601:surgery; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology / Q000601:surgery; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012307:Risk Factors; D013997:Time Factors; D059467:Transcriptome; D016896:Treatment Outcome
D014408:Biomarkers, Tumor
gene expression profiling; molecular diagnostics; prognosis; prostate cancer; risk assessment