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Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average, 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1),&nbsp, frequent subclonal mutations with low variant allele frequency (&lt, 10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction and might explain the clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

Metastatic melanoma is an aggressive disease that is notoriously difficult to treat. Here, we used a BRAFV600E-driven mouse model to study melanoma progression and metastasis in the absence of extrinsic mutagenic factors such as UV radiation. The tumors were grown for different time periods in seven different mice such that disease progression was tracked over time. We sequenced the whole exome and whole transcriptome of 16 melanoma samples from these mice. The timed samples revealed that many genes are increasingly upregulated during progression, such as genes involved in extracellular matrix organization, and Vegfc, a factor that induces lymphatic vessel growth and metastases to lymph nodes, which was identified as an important signaling hub in our analysis. The Vegfc gene interaction network highlighted multiple genes from the MAPK pathway that are increasingly deregulated during tumor evolution. The genomic diversity of primary and metastatic tumors showed an increase over time. Additionally, our integrative multi-omics analysis adds further evidence that Rock1 is a crucial player driving metastasis formation, and may be upregulated due to mutations in the PI3K/AKT pathway. In summary, our study contributes towards an improved understanding of melanoma which may eventually lead to improved treatment strategies.

Background Genetic aberrations in hepatocellular carcinoma (HCC) are well known, but the functional consequences of such aberrations remain poorly understood. Results Here, we explored the effect of defined genetic changes on the transcriptome, proteome and phosphoproteome in twelve tumors from an mTOR-driven hepatocellular carcinoma mouse model. Using Network-based Integration of multi-omiCS data (NetICS), we detected 74 ‘mediators’ that relay via molecular interactions the effects of genetic and miRNA expression changes. The detected mediators account for the effects of oncogenic mTOR signaling on the transcriptome, proteome and phosphoproteome. We confirmed the dysregulation of the mediators YAP1, GRB2, SIRT1, HDAC4 and LIS1 in human HCC. Conclusions This study suggests that targeting pathways such as YAP1 or GRB2 signaling and pathways regulating global histone acetylation could be beneficial in treating HCC with hyperactive mTOR signaling.

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.

Bi-allelic inactivation of the VHL gene on chromosome 3p is the characteristic feature in most clear cell renal cell carcinomas (ccRCC). Frequent gene alterations were also identified in SETD2, BAP1 and PBRM1, all of which are situated on chromosome 3p and encode histone/chromatin regulators. The relationship between gene mutation, loss of protein expression and the correlations with clinicopathological parameters is important for the understanding of renal cancer progression. We analyzed PBRM1 and BAP1 protein expression as well as the tri-methylation state of H3K36 as a surrogate marker for SETD2 activity in more than 700 RCC samples. In ccRCC loss of nuclear PBRM1 (68%), BAP1 (40%) and H3K36me3 (47%) expression was significantly correlated with each other, advanced tumor stage, poor tumor differentiation (P, Neoplasia, 21 (2), ISSN:1522-8002, ISSN:1476-5586