<i>RHPN2</i> Drives Mesenchymal Transformation in Malignant Glioma by Triggering RhoA Activation

Danussi, Carla; Akavia, Uri David; Niola, Francesco; Jovic, Andreja; Lasorella, Anna; Pe’er, Dana; Iavarone, Antonio

doi:10.1158/0008-5472.can-13-1168-t

Cited by 53 publications

(60 citation statements)

References 34 publications

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“…Among the genetic alterations reported by the TCGA Consortium (TCGA-Consortium, 2008), only NF1 mutations/deletions were associated with MES-GBM tumors (~25% of samples) (Verhaak et al, 2010) while additional rare mutations and fusion events were recently reported (Danussi et al, 2013; Frattini et al, 2013). Thus, despite multiple studies, the genetic determinants of MES-GBM are still largely elusive and represent an ideal target for the new algorithm.…”

Section: Introductionmentioning

confidence: 99%

Identification of Causal Genetic Drivers of Human Disease through Systems-Level Analysis of Regulatory Networks

Chen

Alvarez

Talos

et al. 2014

Cell

177

145

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SUMMARY Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a novel framework for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. We tested this framework by identifying the genetic determinants of the mesenchymal subtype of glioblastoma. Our analysis uncovered KLHL9 deletions as upstream activators of two previously established master regulators of the subtype, C/EBPβ and C/EBPδ. Rescue of KLHL9 expression induced proteasomal degradation of C/EBP proteins, abrogated the mesenchymal signature, and reduced tumor viability in vitro and in vivo. Deletions of KLHL9 were confirmed in >50% of mesenchymal cases in an independent cohort, thus representing the most frequent genetic determinant of the subtype. The method generalized to study other human diseases, including breast cancer and Alzheimer’s disease.

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Section: Introductionmentioning

confidence: 99%

Identification of Causal Genetic Drivers of Human Disease through Systems-Level Analysis of Regulatory Networks

Chen

Alvarez

Talos

et al. 2014

Cell

177

145

View full text Add to dashboard Cite

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“…However, amplification and overexpression of Rhophilin-2 (RHPN2), another chromosome 19 protein, was recently linked to dramatically decreased survival in glioma patients. 8 In many cancer types, small subsets of tumor-initiating and treatment-resistant cells have been identified. In the cancer stem cell (CSC) hypothesis, stem cells have the capacity to make new tumors and produce progeny cells of many different types.…”

Section: ■ Introductionmentioning

confidence: 99%

Integrated Chromosome 19 Transcriptomic and Proteomic Data Sets Derived from Glioma Cancer Stem-Cell Lines

et al. 2013

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One subproject within the global Chromosome 19 Consortium is to define chromosome 19 gene and protein expression in glioma-derived cancer stem cells (GSCs). Chromosome 19 is notoriously linked to glioma by 1p/19q codeletions, and clinical tests are established to detect that specific aberration. GSCs are tumor-initiating cells and are hypothesized to provide a repository of cells in tumors that can self-replicate and be refractory to radiation and chemotherapeutic agents developed for the treatment of tumors. In this pilot study, we performed RNA-Seq, label-free quantitative protein measurements in six GSC lines, and targeted transcriptomic analysis using a chromosome 19-specific microarray in an additional six GSC lines. The data have been deposited to the ProteomeXchange with identifier PXD000563. Here we present insights into differences in GSC gene and protein expression, including the identification of proteins listed as having no or low evidence at the protein level in the Human Protein Atlas, as correlated to chromosome 19 and GSC subtype. Furthermore, the upregulation of proteins downstream of adenovirus-associated viral integration site 1 (AAVS1) in GSC11 in response to oncolytic adenovirus treatment was demonstrated. Taken together, our results may indicate new roles for chromosome 19, beyond the 1p/19q codeletion, in the future of personalized medicine for glioma patients.

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“…To further characterize the role of RSF-1 in breast cancer, we analyzed the TCGA gene expression data and identified gene-expression signatures associated with RSF-1 expression levels ((Akavia et al, 2010; Danussi et al, 2013), (Supplementary Methods). Genes associated with RSF-1 in this procedure are putative downstream targets of RSF-1 activity.…”

Section: Resultsmentioning

confidence: 99%

Integration of Genomic Data Enables Selective Discovery of Breast Cancer Drivers

Sanchez-Garcia

Villagrasa

Matsui

et al. 2014

Cell

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Identifying driver genes in cancer remains a crucial bottleneck in therapeutic development and basic understanding of the disease. We developed Helios, a novel algorithm that integrates genomic data from primary tumors with data from functional RNAi screens to pinpoint driver genes within large recurrently amplified regions of DNA. Applying Helios to breast cancer data identified a set of candidate drivers highly enriched with known drivers (p-value < e−14). 9/10 top scoring Helios genes are known drivers of breast cancer and in vitro validation of 12 novel candidates predicted by Helios found 10 conferred enhanced anchorage independent growth, demonstrating Helios’s exquisite sensitivity and specificity. We extensively characterized RSF-1, a driver identified by Helios whose amplification correlates with poor prognosis, and found increased tumorigenesis and metastasis in mouse models. We have demonstrated a powerful approach for identifying novel driver genes and how it can yield important insights into cancer.

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RHPN2 Drives Mesenchymal Transformation in Malignant Glioma by Triggering RhoA Activation

Cited by 53 publications

References 34 publications

Identification of Causal Genetic Drivers of Human Disease through Systems-Level Analysis of Regulatory Networks

Identification of Causal Genetic Drivers of Human Disease through Systems-Level Analysis of Regulatory Networks

Integrated Chromosome 19 Transcriptomic and Proteomic Data Sets Derived from Glioma Cancer Stem-Cell Lines

Integration of Genomic Data Enables Selective Discovery of Breast Cancer Drivers

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