Tumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. However, it is unclear how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues. Here, we investigated how tumor heterogeneity evolves during prostate cancer progression. In this study, we performed proteogenomic analyses of 105 prostate samples, consisting of both benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer (PCa) patients. Exome sequencing, copy number analysis, RNA sequencing and quantitative proteomic data were integrated using a network-based approach and related to clinical and histopathological features. In general, the number and magnitude of alterations (DNA, RNA and protein) correlated with histopathological tumor grades. Although common sets of proteins were affected in high-grade tumors, the extent to which these proteins changed their concentrations varied considerably across tumors. Our multi-layer network integration identified a sub-network consisting of nine genes whose activity positively correlated with increasingly aggressive tumor phenotypes. Importantly, although the effects on individual gene members were barely detectable, together the perturbation of this sub-network was predictive for recurrence-free survival time. The multi-omics profiling of multiple tumor sites from the same patients revealed cases of likely shared clonal origins as well as the occasional co-existence of multiple clonally independent tumors in the same prostate. Overall, this study revealed molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

Proteogenomic heterogeneity of localized human prostate cancer progression