Statistical tests for intra-tumour clonal co-occurrence and exclusivity.

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumoural pairs of mutations that are overrepresented in a co-occurring or clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical testing framework, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our framework for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 1 clonally co-occurring and 8 clonally exclusive gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

Multi-omics data integration reveals novel drug targets in hepatocellular carcinoma.

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.

Spatial Distribution of Private Gene Mutations in Clear Cell Renal Cell Carcinoma.

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), frequent subclonal mutations with low variant allele frequency (<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.

Convergent network effects along the axis of gene expression during prostate cancer progression.

BACKGROUND: Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. RESULTS: Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. CONCLUSIONS: This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions.

Expression and Mutation Patterns of PBRM1, BAP1 and SETD2 Mirror Specific Evolutionary Subtypes in Clear Cell Renal Cell Carcinoma.

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 < .0001 each), and necrosis (P < .005) Targeted next generation sequencing of 83 ccRCC samples demonstrated a significant association of genetic mutations in PBRM1, BAP1, and SETD2 with absence of PBRM1, BAP1, and HEK36me3 protein expression (P < .05, each). By assigning the protein expression patterns to evolutionary subtypes, we revealed similar clinical phenotypes as suggested by TRACERx Renal. Given their important contribution to tumor suppression, we conclude that combined functional inactivation of PBRM1, BAP1, SETD2 and pVHL is critical for ccRCC progression.

A switch in transcription and cell fate governs the onset of an epigenetically-deregulated tumor in Drosophila.

Tumor initiation is often linked to a loss of cellular identity. Transcriptional programs determining cellular identity are preserved by epigenetically-acting chromatin factors. Although such regulators are among the most frequently mutated genes in cancer, it is not well understood how an abnormal epigenetic condition contributes to tumor onset. In this work, we investigated the gene signature of tumors caused by disruption of the Drosophila epigenetic regulator, polyhomeotic (ph). In larval tissue ph mutant cells show a shift towards an embryonic-like signature. Using loss- and gain-of-function experiments we uncovered the embryonic transcription factor knirps (kni) as a new oncogene. The oncogenic potential of kni lies in its ability to activate JAK/STAT signaling and block differentiation. Conversely, tumor growth in ph mutant cells can be substantially reduced by overexpressing a differentiation factor. This demonstrates that epigenetically derailed tumor conditions can be reversed when targeting key players in the transcriptional network.