HOT Models in Flux: Mitochondrial Glucose Oxidation Fuels Glioblastoma Growth

Cancer cells in culture obtain ATP and biosynthetic precursors primarily by aerobic glycolysis, not by mitochondrial glucose oxidation. In this issue of Cell Metabolism, Marin-Valencia et al. (2012) demonstrate that glioblastoma, an aggressive and, in culture, highly glycolytic cancer, primarily uses glucose oxidation to meet energetic and biosynthetic demands in vivo

Molecular and Genetic Determinants of Glioma Cell Invasion.

A diffusely invasive nature is a major obstacle in treating a malignant brain tumor, "diffuse glioma", which prevents neurooncologists from surgically removing the tumor cells even in combination with chemotherapy and radiation. Recently updated classification of diffuse gliomas based on distinct genetic and epigenetic features has culminated in a multilayered diagnostic approach to combine histologic phenotypes and molecular genotypes in an integrated diagnosis. However, it is still a work in progress to decipher how the genetic aberrations contribute to the aggressive nature of gliomas including their highly invasive capacity. Here we depict a set of recent discoveries involving molecular genetic determinants of the infiltrating nature of glioma cells, especially focusing on genetic mutations in receptor tyrosine kinase pathways and metabolic reprogramming downstream of common cancer mutations. The specific biology of glioma cell invasion provides an opportunity to explore the genotype-phenotype correlation in cancer and develop novel glioma-specific therapeutic strategies for this devastating disease

ViFi: accurate detection of viral integration and mRNA fusion reveals indiscriminate and unregulated transcription in proximal genomic regions in cervical cancer.

The integration of viral sequences into the host genome is an important driver of tumorigenesis in many viral mediated cancers, notably cervical cancer and hepatocellular carcinoma. We present ViFi, a computational method that combines phylogenetic methods with reference-based read mapping to detect viral integrations. In contrast with read-based reference mapping approaches, ViFi is faster, and shows high precision and sensitivity on both simulated and biological data, even when the integrated virus is a novel strain or highly mutated. We applied ViFi to matched genomic and mRNA data from 68 cervical cancer samples from TCGA and found high concordance between the two. Surprisingly, viral integration resulted in a dramatic transcriptional upregulation in all proximal elements, including LINEs and LTRs that are not normally transcribed. This upregulation is highly correlated with the presence of a viral gene fused with a downstream human element. Moreover, genomic rearrangements suggest the formation of apparent circular extrachromosomal (ecDNA) human-viral structures. Our results suggest the presence of apparent small circular fusion viral/human ecDNA, which correlates with indiscriminate and unregulated expression of proximal genomic elements, potentially contributing to the pathogenesis of HPV-associated cervical cancers. ViFi is available at https://github.com/namphuon/ViFi

Challenges in identifying cancer genes by analysis of exome sequencing data.

Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13-60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed

Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks

BACKGROUND: Genes and proteins are organized into functional modular networks in which the network context of a gene or protein has implications for cellular function. Highly connected hub proteins, largely responsible for maintaining network connectivity, have been found to be much more likely to be essential for yeast survival. RESULTS: Here we investigate the properties of weighted gene co-expression networks formed from multiple microarray datasets. The constructed networks approximate scale-free topology, but this is not universal across all datasets. We show strong positive correlations between gene connectivity within the whole network and gene essentiality as well as gene sequence conservation. We demonstrate the preservation of a modular structure of the networks formed, and demonstrate that, within some of these modules, it is possible to observe a strong correlation between connectivity and essentiality or between connectivity and conservation within the modules particularly within modules containing larger numbers of essential genes. CONCLUSION: Application of these techniques can allow a finer scale prediction of relative gene importance for a particular process within a group of similarly expressed genes

Glucose deprivation activates a metabolic and signaling amplification loop leading to cell death.

The altered metabolism of cancer can render cells dependent on the availability of metabolic substrates for viability. Investigating the signaling mechanisms underlying cell death in cells dependent upon glucose for survival, we demonstrate that glucose withdrawal rapidly induces supra-physiological levels of phospho-tyrosine signaling, even in cells expressing constitutively active tyrosine kinases. Using unbiased mass spectrometry-based phospho-proteomics, we show that glucose withdrawal initiates a unique signature of phospho-tyrosine activation that is associated with focal adhesions. Building upon this observation, we demonstrate that glucose withdrawal activates a positive feedback loop involving generation of reactive oxygen species (ROS) by NADPH oxidase and mitochondria, inhibition of protein tyrosine phosphatases by oxidation, and increased tyrosine kinase signaling. In cells dependent on glucose for survival, glucose withdrawal-induced ROS generation and tyrosine kinase signaling synergize to amplify ROS levels, ultimately resulting in ROS-mediated cell death. Taken together, these findings illustrate the systems-level cross-talk between metabolism and signaling in the maintenance of cancer cell homeostasis