Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study

Study data are deposited in NCBI GEO (unique identifier number GSE70770).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. Findings : 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. Interpretation : 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.Publisher PDFPeer reviewe

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. FINDINGS: 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. INTERPRETATION: 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.Cambridge work was funded by a CRUK programme grant awarded to DEN; Swedish work and tissue collections were funded by grants from the Linne Centre for Breast and Prostate Cancer (CRISP, grant 70867901), Karolinska Institutet, the Swedish Research Council (K2010-70X-20430-04-3), and the Swedish Cancer Society (11-0287).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2015.07.01

Developing models to predict the effects of fuel reduction burning on habitat complexity, ground-dwelling mammals and understorey birds

The variation in vegetation structure is often recognised as one of the main factors attributing to the wide diversity of wildlife supported by Australian Eucalyptus forests. Disturbances that affect the vegetation structure can have repercussions to the animals that rely on certain compositions of plants. Many plants and animals are able to survive under certain disturbance regimes. However, changing the regime can threaten the flora and fauna species within a community. Inappropriate fire regimes are one such threatening process. Yet fuel reduction is a key element of fire management. There is often a conflict between the fire regime needed to keep fuel loads at a level thought to be adequate to assist in managing unplanned fire, and those that would maintain vegetation structure and therefore wildlife diversity. Therefore, in areas where the protection of biodiversity is particularly important there is a need to predict the ecological effects of a fuel reduction burn regime. A number of studies had shown that abundance and distribution of grounddwelling mammals and understorey birds can be estimated from measures of habitat complexity and is has been demonstrated that the effects of fire on these groups can be predicted by changes to vegetation structure. This study uses fuel levels and habitat complexity scores to develop a model to predict the impacts of prescribed burns with different intensities and extents on distribution and abundance of ground-dwelling mammals and understorey birds in 6 different vegetation communities at Coolah Tops National Park, NSW. Within each of the six vegetation communities 25 survey sites were randomly selected. Fuel loads were estimated using litter depth, the dominant plant species were identified and both mammal and bird habitat complexity scores established using revised tables from the literature. The model, devised using the data collected in the field, was used to calculate the change in habitat complexity scores after four different fire scenarios. These modifications were then used to predict the likely affects of the different fire models on ground-dwelling mammals and understorey birds and to produce some implications and recommendations for management. Fire extent had a larger impact on ground-dwelling mammals then fires intensity, with fires that left fewer patches unburnt reducing overall vegetation structure regardless of intensity. Birds however, were predicted to be affected by both intensity and extent, with the greatest impact being seen in the high intensity low patchiness burn models and the lowest impact in the low intensity high patchiness model. The implications for management of this study is that, at least for mammals, fire extent needs to be controlled more then the intensity in order to maintain some refuge areas. Overall, at least temporarily, mammal diversity may be expected to decline by 50-100% and bird diversity by half in the sort of fuel reduction burns that may be applied in a fire management program. Small ground-dwelling mammal abundance is likely to be reduced to zero, while medium to large ground-dwelling mammal abundance is likely to increase dramatically from zero under this fire management program. Understorey bird species likely to be promoted are those able to tolerate open vegetation while those that need dense understoreys will be disadvantaged

‘Once I knew there was a choice, I wanted to exercise that choice': using qualitative methods to understand why patients decline surgical trials

The BOLERO trial (Bladder cancer: Open versus Lapararoscopic or RObotic cystectomy) is a pilot study to determine the feasibility of randomisation to open versus laparoscopic access cystectomy in patients with bladder cancer. We describe the results of an embedded qualitative sub-study which explored why patients decline randomisation. Methods: 10 semi structured interviews were undertaken with patients recruited from 3 sites in England. Data were analysed for key themes. Results: Most patients declined the trial because they had preferences for, and could choose, which surgical method they would be given- in most cases the robotic option. Patients described an intuitive ‘sense' that favoured the new technology and had carried out their own inquiries, including internet research and talking with previous patients and with friends and family with medical backgrounds. Medical histories and lifestyle considerations also shaped these personalised choices. Of importance too, however, were the messages patients perceived from their clinical encounters. Whilst some patients felt their surgeon favoured the robotic option, others interpreted ‘indirect' cues such as the ‘established' reputation of the surgeon and surgical method and comments made during pre-op assessments. Many patients expressed a wish for greater direction from their surgeon when making these decisions. Conclusion: Patients like to exercise informed choice over the type of surgery they receive. For trials where the ‘new technology' is routinely available to patients, there will likely be difficulties with recruitment. This questions the feasibility of similar trials in the future