Current prognostic models of prostate cancer, including PSA, Gleason score and clinical stage fail to accurately predict disease progression, especially for men with intermediate disease. Two large randomized trials evaluating the effect of PSA screening on prostate-cancer mortality, namely the Prostate, Lung, Colorectal, and Ovarian (PLCO) and the European Randomized Study of Screening for Prostate Cancer (ERSPC), showed that during the first decade of follow-up, PSA screening has at best a modest effect (20% relative reduction of PCA specific death in the ERSPC) on PCA mortality, with substantial risks of negative biopsy, over diagnosis and over-treatment [30, 31]. The need to better identify patients with a more aggressive disease is thus an open challenge given the clinical observation that prostate cancer is a heterogeneous disease. This observation is based on the experience of clinicians who witness men with localized disease that should fair well but on occasion do not and less commonly men with apparently aggressive disease who do well. How can we account for this clinical heterogeneity? We anticipated that a well-designed molecular study interrogating thousands of genes implicated in cancer and specifically prostate cancer would help us determine a molecular signature for lethal and indolent disease. Perhaps what is clinically referred to as "heterogeneity" really represents our inability through Gleason grading or other clinical attributes to untangle the key elements that would, if known, help us predict which men will succumb to disease progression. The findings of the current study and other recent studies described below point to a more concerning reality about what accounts for heterogeneity.
This study found that molecular predictors can distinguish aggressive from indolent prostate cancer similarly to models generated from Gleason score and other clinical parameters. However, by combining clinical and molecular data, we were not able to improve on known predictors. The explanation is manifold. First, we must consider the important limitation of prostate cancer sampling. We know that a prostate gland harbors often up to 5 geographically distinct tumor nodules [32–36] and these nodules are often clonally distinct. If we consider the homogeneity of ERG rearrangement in circulating tumor cells (CTCs)  and that the ETS gene rearrangements occur early in the development of prostate cancer, as they are often seen in high-grade PIN , and, when observed, are present in all tumor cell within a nodule; then, we can consider this a possible marker of tumor clonality. Observations from three independent groups demonstrate that up to 50% of prostate cancers with multiple nodules have clonally distinct lesions [39–41]. This would strongly support why sampling of the "right" cancerous nodules is so critical in prostate cancer. A prostate needle biopsy or TURP sample may or may not capture the driving lesion leaving an important clone undetected. This inability to identify the molecularly dominant nodule (intra-tumor heterogeneity) would then help explain the "heterogeneity" observed in the clinical assessment at time of diagnosis with outcome.
However, if intra-tumor heterogeneity were the main explanation for our results, and inter-tumor heterogeneity, i.e. the presence of many alternative pathways which lead to lethality in prostate cancer, only marginal, then all cancer foci across individuals should share a similar molecular profile. How does sampling play a role in this scenario? The set of indolent prostate cancer samples is not affected by sampling, the set of lethal prostate cancer samples is affected, in that the lethal focus is 'sub-sampled'. Let assume that this causes a 50% dilution of the lethal molecular signal. Due to our study design and combinations of supervised and unsupervised analysis approaches, we should still have been able to detect the presence of a strong and consistent lethal signal, even if this was for a subset of the lethal prostate cancer population. Hence, we believe that our results are best explained by high degree of heterogeneity between lethal prostate cancers.
However, another possible alternative explanation for clinical heterogeneity might be that the lethal signature develops with the accumulation of molecular lesions over time and therefore may not be present at time of initial diagnosis in contrast to the homogeneity of ERG rearrangement in CTCs . This would not be mutually exclusive from inter-tumor heterogeneity but could compound the problem. Finally, the molecular signature may be embedded in the adjacent non-cancerous stromal tissue as recently observed in hepatocellular cancer  or perhaps due to a host immune response to the tumor that might not be measurable by examination of the tumor sample. Regardless of what the mechanism or combination of mechanisms is, we are still faced with an inability to consistently detect the lethal molecular signature as observed in the current study.
Our study results are in fact consistent with other emerging data from U.S. cohorts using similar and different molecular platforms. Nakagawa et al. recently attempted to develop a biomarker panel to predict which men with rising PSA following surgery would progress with clinically significant disease . They employed a case-control design where cases were defined as men with rising PSA who progressed within 5 years after initial surgery. Controls were men with rising PSA but no sign of clinical disease progression within the first 5 years following surgery. A total of 213 cases and 213 controls were used for this study and, similar to the current study, the cases and controls were divided into training and validation set. Although the results on the training set seemed promising (see Additional File 1), the validation phase showed mis-classifications in both directions and none of the models with molecular and clinical parameters performed better than an AUC of 0.75 .
Another recent study is significant because a two-phase biomarker development approach was used to classify long-term disease progression or death due to prostate cancer. Cheville et al. reported on a molecular classifier developed using a profile developed from tumor samples isolated by laser capture micro-dissection . They used quantitative RT-PCR to measure gene expression and cancer specific death following surgery or development of metastatic disease as the clinical endpoint. They used a 2-phase design with a training set of 157 high-risk patients and a validation set of 57 high-risk patients. Their results demonstrated that a model including topoisomerase-2a, cadherin-10, ETS genes involved in gene fusion (i.e., ERG, ETV1, and ETV4), and aneuploidy status had an AUC of 0.81 and 0.79 for training and validation sets, respectively.
Based on the published series (Nakagawa et al., Glinsky et al., Lapointe et al., Singh et al., Yu et al., Cheville et al.) and the current study, it is therefore impressive that all of these reports using different platforms and patient populations achieve similar results [43–49].
Although other explanations may be possible, we favor that inter-tumor heterogeneity plays a more critical role. The strongest evidence from the current study has to do with the association of ERG rearrangement status and lethality (see also Attard et al. ).
The association between ERG rearranged cases and the lethal phenotype suggests that ETS rearrangements describe a particularly aggressive subclass of prostate cancer. In the current study 41 of 46 ERG rearranged prostate cancers were lethal; the unadjusted odds ratio for lethal disease associated with ERG rearrangement status was 7.2 (95% CI 2.8-19.0). This confirms and extends observations from 111 men in the expectant management cohort from Örebro where men with ERG rearranged prostate cancer were significantly more likely to have lethal disease than men with fusion negative tumors (cumulative incidence ratio = 2.7, p-value < 0.01, 95% CI = [1.3,5.8]) . From the United Kingdom, Attard et al. reported associations between TMPRSS2-ERG fusion with interstitial deletion and cause specific survival taking into account age, Gleason score, and pre-treatment PSA in a cohort of 445 men conservatively treated for prostate cancer . Interestingly, aneuploidy in combination with TMPRSS2-ERG fusion was associated with the worst clinical outcome (hazard ratio = 6.10, 95% CI = [3.33,11.15], p-value < 0.001, 25% survival at 8 years). The relatively low frequency of ERG rearrangement in this cohort may represent the admixture of peripheral zone tumors with a presumed ERG rearrangement frequency of 45%  and transition zone tumors with a significantly lower ERG rearrangement frequency .