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Featured researches published by Ari Kahn.


Cancer Cell | 2010

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

Roel G.W. Verhaak; Katherine A. Hoadley; Elizabeth Purdom; Victoria Wang; Yuan Qi; Matthew D. Wilkerson; C. Ryan Miller; Li Ding; Todd R. Golub; Jill P. Mesirov; Gabriele Alexe; Michael S. Lawrence; Michael O'Kelly; Pablo Tamayo; Barbara A. Weir; Stacey Gabriel; Wendy Winckler; Supriya Gupta; Lakshmi Jakkula; Heidi S. Feiler; J. Graeme Hodgson; C. David James; Jann N. Sarkaria; Cameron Brennan; Ari Kahn; Paul T. Spellman; Richard Wilson; Terence P. Speed; Joe W. Gray; Matthew Meyerson

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.


PLOS ONE | 2012

Concordance of Gene Expression and Functional Correlation Patterns across the NCI-60 Cell Lines and the Cancer Genome Atlas Glioblastoma Samples

Barry R. Zeeberg; Kurt W. Kohn; Ari Kahn; Vladimir Larionov; John N. Weinstein; William C. Reinhold; Yves Pommier

Background The NCI-60 is a panel of 60 diverse human cancer cell lines used by the U.S. National Cancer Institute to screen compounds for anticancer activity. We recently clustered genes based on correlation of expression profiles across the NCI-60. Many of the resulting clusters were characterized by cancer-associated biological functions. The set of curated glioblastoma (GBM) gene expression data from the Cancer Genome Atlas (TCGA) initiative has recently become available. Thus, we are now able to determine which of the processes are robustly shared by both the immortalized cell lines and clinical cancers. Results Our central observation is that some sets of highly correlated genes in the NCI-60 expression data are also highly correlated in the GBM expression data. Furthermore, a “double fishing” strategy identified many sets of genes that show Pearson correlation ≥0.60 in both the NCI-60 and the GBM data sets relative to a given “bait” gene. The number of such gene sets far exceeds the number expected by chance. Conclusion Many of the gene-gene correlations found in the NCI-60 do not reflect just the conditions of cell lines in culture; rather, they reflect processes and gene networks that also function in vivo. A number of gene network correlations co-occur in the NCI-60 and GBM data sets, but there are others that occur only in NCI-60 or only in GBM. In sum, this analysis provides an additional perspective on both the utility and the limitations of the NCI-60 in furthering our understanding of cancers in vivo.


Journal of Clinical Investigation | 2012

Prognostically relevant gene signatures of high-grade serous ovarian carcinoma

Roel G.W. Verhaak; Pablo Tamayo; Ji Yeon Yang; Diana Hubbard; Hailei Zhang; Chad J. Creighton; Sian Fereday; Michael S. Lawrence; Scott L. Carter; Craig H. Mermel; Aleksandar D. Kostic; Dariush Etemadmoghadam; Gordon Saksena; Kristian Cibulskis; Sekhar Duraisamy; Keren Levanon; Carrie Sougnez; Aviad Tsherniak; Sebastian Gomez; Robert C. Onofrio; Stacey Gabriel; Lynda Chin; Nianxiang Zhang; Paul T. Spellman; Yiqun Zhang; Rehan Akbani; Katherine A. Hoadley; Ari Kahn; Martin Köbel; David Huntsman


BMC Bioinformatics | 2011

RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis

Barry R. Zeeberg; Hongfang Liu; Ari Kahn; Martin Ehler; Vinodh N. Rajapakse; Robert F. Bonner; Jacob D. Brown; Brian P. Brooks; Vladimir L Larionov; William C. Reinhold; John N. Weinstein; Yves Pommier

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Barry R. Zeeberg

National Institutes of Health

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John N. Weinstein

University of Texas MD Anderson Cancer Center

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Katherine A. Hoadley

University of North Carolina at Chapel Hill

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Pablo Tamayo

University of California

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Roel G.W. Verhaak

University of Texas MD Anderson Cancer Center

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William C. Reinhold

National Institutes of Health

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Yves Pommier

National Institutes of Health

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