Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome.
Prostate cancer is a biologically heterogeneous disease with variable molecular alterations underlying cancer initiation and progression. Despite recent advances in understanding prostate cancer heterogeneity, better methods for classification of prostate cancer are still needed to improve prognostic accuracy and therapeutic outcomes. In this study, we computationally assembled a large virtual cohort (n = 1,321) of human prostate cancer transcriptome profiles from 38 distinct cohorts and, using pathway activation signatures of known relevance to prostate cancer, developed a novel classification system consisting of three distinct subtypes (named PCS1-3). We validated this subtyping scheme in 10 independent patient cohorts and 19 laboratory models of prostate cancer, including cell lines and genetically engineered mouse models. Analysis of subtype-specific gene expression patterns in independent datasets derived from luminal and basal cell models provides evidence that PCS1 and PCS2 tumors reflect luminal subtypes, while PCS3 represents a basal subtype. We show that PCS1 tumors progress more rapidly to metastatic disease in comparison with PCS2 or PCS3, including PSC1 tumors of low Gleason grade. To apply this finding clinically, we developed a 37-gene panel that accurately assigns individual tumors to one of the three PCS subtypes. This panel was also applied to circulating tumor cells (CTC) and provided evidence that PCS1 CTCs may reflect enzalutamide resistance. In summary, PCS subtyping may improve accuracy in predicting the likelihood of clinical progression and permit treatment stratification at early and late disease stages. Cancer Res; 76(17); 4948-58. ©2016 AACR.
Division of Cancer Biology and Therapeutics, Departments of Surgery & Biomedical Sciences, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.
Sungyong
S
You
Division of Cancer Biology and Therapeutics, Departments of Surgery & Biomedical Sciences, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.
Beatrice S
BS
Knudsen
GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
Nicholas
N
Erho
GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
Mohammed
M
Alshalalfa
GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
Mandeep
M
Takhar
GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
Hussam
H
Al-Deen Ashab
GenomeDx Biosciences Inc., Vancouver, British Columbia, Canada.
Elai
E
Davicioni
Department of Urology, Mayo Clinic, Rochester, Minnesota.
R Jeffrey
RJ
Karnes
Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
Eric A
EA
Klein
Department of Radiation Oncology, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania.
Robert B
RB
Den
Department of Urology, Northwestern University, Chicago, Illinois.
Ashley E
AE
Ross
Department of Urology, Northwestern University, Chicago, Illinois.
Edward M
EM
Schaeffer
Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, California.
Isla P
IP
Garraway
Division of Cancer Biology and Therapeutics, Departments of Surgery & Biomedical Sciences, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.
Jayoung
J
Kim
Division of Cancer Biology and Therapeutics, Departments of Surgery & Biomedical Sciences, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California. Michael.Freeman@cshs.org.
Michael R
MR
Freeman
D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis; D025341:Principal Component Analysis; D011471:Prostatic Neoplasms / Q000145:classification* / Q000235:genetics* / Q000473:pathology*; D059467:Transcriptome