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We studied how intratumoral genetic heterogeneity shapes tumor growth and therapy response for isocitrate dehydrogenase (IDH)-wild-type glioblastoma, a rapidly regrowing tumor. We inferred the evolutionary trajectories of matched pairs of primary and relapsed tumors based on deep whole-genomesequencing data. This analysis suggests both a distant origin of de novo glioblastoma, up to 7 years before diagnosis, and a common path of early tumorigenesis, with one or more of chromosome 7 gain, 9p loss, or 10 loss, at tumor initiation. TERT promoter mutations often occurred later as a prerequisite for rapid growth. In contrast to this common early path, relapsed tumors acquired no stereotypical pattern of mutations and typically regrew from oligoclonal origins, suggesting sparse selective pressure by therapeutic measures.

The fibroblast growth factor receptor 2 (FGFR2) locus has been consistently identified as a breast cancer risk locus in independent genome-wide association studies. However, the molecular mechanisms underlying FGFR2-mediated risk are still unknown. Using model systems we show that FGFR2-regulated genes are preferentially linked to breast cancer risk loci in expression quantitative trait loci analysis, supporting the concept that risk genes cluster in pathways. Using a network derived from 2,000 transcriptional profiles we identify SPDEF, ERα, FOXA1, GATA3 and PTTG1 as master regulators of fibroblast growth factor receptor 2 signalling, and show that ERα occupancy responds to fibroblast growth factor receptor 2 signalling. Our results indicate that ERα, FOXA1 and GATA3 contribute to the regulation of breast cancer susceptibility genes, which is consistent with the effects of anti-oestrogen treatment in breast cancer prevention, and suggest that fibroblast growth factor receptor 2 signalling has an important role in mediating breast cancer risk.

Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html.

When fused to a rabies virus glycoprotein peptide that shuttles small RNAs across the blood–brain barrier, an HCMV noncoding RNA that protects mitochondrial Complex I activity, delivered intravenously, shows therapeutic efficacy in a rat model of Parkinson’s disease.

SummaryThe fibroblast growth factor receptor 2 (FGFR2) locus is the ‘top hit’ in genome-wide association studies for breast cancer. Here, we examine the effect of FGFR2 signalling on transcriptional networks in breast cancer and propose a mechanism for FGFR2 risk single-nucleotide polymorphism function.

Glioblastoma frequently exhibits therapy-associated subtype transitions to mesenchymal phenotypes with adverse prognosis. Here, we perform multi-omic profiling of 60 glioblastoma primary tumours and use orthogonal analysis of chromatin and RNA-derived gene regulatory networks to identify 38 subtype master regulators, whose cell population-specific activities we further map in published single-cell RNA sequencing data. These analyses identify the oligodendrocyte precursor marker and chromatin modifier SOX10 as a master regulator in RTK I-subtype tumours. In vitro functional studies demonstrate that SOX10 loss causes a subtype switch analogous to the proneural–mesenchymal transition observed in patients at the transcriptomic, epigenetic and phenotypic levels. SOX10 repression in an in vivo syngeneic graft glioblastoma mouse model results in increased tumour invasion, immune cell infiltration and significantly reduced survival, reminiscent of progressive human glioblastoma. These results identify SOX10 as a bona fide master regulator of the RTK I subtype, with both tumour cell-intrinsic and microenvironmental effects.

Background Glioblastoma is the most common primary malignancy of the central nervous system with dismal prognosis. Genomic signatures classify isocitrate dehydrogenase 1 (IDH)-wildtype glioblastoma into three subtypes: proneural, mesenchymal and classical. Dasatinib, an inhibitor of proto-oncogene kinase Src (SRC), is one of many therapeutics which, despite promising preclinical results, has failed to improve overall survival in glioblastoma patients in clinical trials. We examined whether glioblastoma subtypes differ in their response to dasatinib and could hence be evaluated for patient enrichment strategies in clinical trials. Methods We carried out in silico analyses on glioblastoma gene expression (TCGA) and single-cell RNA-Seq data. In addition, in vitro experiments using glioblastoma stem-like cells (GSCs) derived from primary patient tumors were performed, with complementary gene expression profiling and immunohistochemistry analysis of tumor samples. Results Patients with the mesenchymal subtype of glioblastoma showed higher SRC pathway activation based on gene expression profiling. Accordingly, mesenchymal GSCs were more sensitive to SRC inhibition by dasatinib compared to proneural and classical GSCs. Notably, SRC phosphorylation status did not predict response to dasatinib treatment. Furthermore, serpin peptidase inhibitor clade H member 1 (SERPINH1), a collagen related heat-shock protein associated with cancer progression, was shown to correlate with dasatinib response and with the mesenchymal subtype. Conclusion This work highlights further molecular-based patient selection strategies in clinical trials and suggests the mesenchymal subtype as well as SERPINH1 to be associated with response to dasatinib. Our findings indicate that stratification based on gene expression subtyping should be considered in future dasatinib trials.