Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study.
BACKGROUND
Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.


METHODS
In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.


RESULTS
We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.


CONCLUSIONS
For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
H
H
Ross-Adams
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK ; Department of Urology, Addenbrooke's Hospital, Cambridge CB2 2QQ, UK ; Academic Urology Group, University of Cambridge, Cambridge, CB2 0QQ, UK.
A D
AD
Lamb
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
M J
MJ
Dunning
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
S
S
Halim
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
J
J
Lindberg
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
C M
CM
Massie
Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
L A
LA
Egevad
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
R
R
Russell
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
A
A
Ramos-Montoya
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
S L
SL
Vowler
Nuffield Department of Surgical Sciences, University of Oxford, Roosevelt Drive, Oxford, UK.
N L
NL
Sharma
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK ; Molecular Diagnostics and Therapeutics Group, University College London, WC1E 6BT, UK.
J
J
Kay
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK ; Molecular Diagnostics and Therapeutics Group, University College London, WC1E 6BT, UK.
H
H
Whitaker
University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.
J
J
Clark
University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.
R
R
Hurst
Department of Urology, Addenbrooke's Hospital, Cambridge CB2 2QQ, UK ; Academic Urology Group, University of Cambridge, Cambridge, CB2 0QQ, UK.
V J
VJ
Gnanapragasam
Department of Urology, Addenbrooke's Hospital, Cambridge CB2 2QQ, UK.
N C
NC
Shah
Department of Pathology, Addenbrooke's Hospital, Cambridge CB2 2QQ, UK.
A Y
AY
Warren
University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.
C S
CS
Cooper
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
A G
AG
Lynch
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK.
R
R
Stark
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK ; Prostate Cancer Research Group, Centre for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, N-0318 Oslo, Norway ; Department of Molecular Oncology, Institute of Cancer Research, Oslo University Hospitals, N-0424 Oslo, Norway ; Prostate Cancer UK/Movember Centre of Excellence for Prostate Cancer Research, Centre for Cancer Research and Cell Biology, Queen's University, Belfast, UK.
I G
IG
Mills
Academic Urology Group, University of Cambridge, Cambridge, CB2 0QQ, UK.
H
H
Grönberg
Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK ; Department of Urology, Addenbrooke's Hospital, Cambridge CB2 2QQ, UK.
D E
DE
Neal
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016000:Cluster Analysis; D015331:Cohort Studies; D018628:Gene Dosage; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D015894:Genome, Human; D006801:Humans; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D012008:Recurrence; D015203:Reproducibility of Results; D012307:Risk Factors; D059467:Transcriptome / Q000235:genetics*
D012333:RNA, Messenger
Biochemical relapse; Gene signature; Genomics; Personalised medicine; Prognosis; Prostate cancer; Risk stratification