An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer

Xiao Song Wang; John R. Prensner; Guoan Chen; Qi Cao; Bo Han; Saravana M. Dhanasekaran; Rakesh Ponnala; Xuhong Cao; Sooryanarayana Varambally; Dafydd G. Thomas; Thomas J. Giordano; David G. Beer; Nallasivam Palanisamy; Maureen A. Sartor; Gilbert S. Omenn; Arul M. Chinnaiyan

doi:10.1038/nbt.1584

An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer

Xiao Song Wang, John R. Prensner, Guoan Chen, Qi Cao, Bo Han, Saravana M. Dhanasekaran, Rakesh Ponnala, Xuhong Cao, Sooryanarayana Varambally, Dafydd G. Thomas, Thomas J. Giordano, David G. Beer, Nallasivam Palanisamy, Maureen A. Sartor, Gilbert S. Omenn, Arul M. Chinnaiyan

Research output: Contribution to journal › Article › peer-review

64 Scopus citations

Abstract

Cancer genomes contain many aberrant gene fusionsa few that drive disease and many more that are nonspecific passengers. We developed an algorithm (the concept signature or 'ConSig' score) that nominates biologically important fusions from high-throughput data by assessing their association with 'molecular concepts' characteristic of cancer genes, including molecular interactions, pathways and functional annotations. Copy number data supported candidate fusions and suggested a breakpoint principle for intragenic copy number aberrations in fusion partners. By analyzing lung cancer transcriptome sequencing and genomic data, we identified a novel R3HDM2-NFE2 fusion in the H1792 cell line. Lung tissue microarrays revealed 2 of 76 lung cancer patients with genomic rearrangement at the NFE2 locus, suggesting recurrence. Knockdown of NFE2 decreased proliferation and invasion of H1792 cells. Together, these results present a systematic analysis of gene fusions in cancer and describe key characteristics that assist in new fusion discovery.

Original language	English (US)
Pages (from-to)	1005-1011
Number of pages	7
Journal	Nature Biotechnology
Volume	27
Issue number	11
DOIs	https://doi.org/10.1038/nbt.1584
State	Published - Nov 2009

ASJC Scopus subject areas

Biotechnology
Bioengineering
Applied Microbiology and Biotechnology
Molecular Medicine
Biomedical Engineering

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10.1038/nbt.1584

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Wang, X. S., Prensner, J. R., Chen, G., Cao, Q., Han, B., Dhanasekaran, S. M., Ponnala, R., Cao, X., Varambally, S., Thomas, D. G., Giordano, T. J., Beer, D. G., Palanisamy, N., Sartor, M. A., Omenn, G. S., & Chinnaiyan, A. M. (2009). An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer. Nature Biotechnology, 27(11), 1005-1011. https://doi.org/10.1038/nbt.1584

Wang, XS, Prensner, JR, Chen, G, Cao, Q, Han, B, Dhanasekaran, SM, Ponnala, R, Cao, X, Varambally, S, Thomas, DG, Giordano, TJ, Beer, DG, Palanisamy, N, Sartor, MA, Omenn, GS & Chinnaiyan, AM 2009, 'An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer', Nature Biotechnology, vol. 27, no. 11, pp. 1005-1011. https://doi.org/10.1038/nbt.1584

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title = "An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer",

abstract = "Cancer genomes contain many aberrant gene fusionsa few that drive disease and many more that are nonspecific passengers. We developed an algorithm (the concept signature or 'ConSig' score) that nominates biologically important fusions from high-throughput data by assessing their association with 'molecular concepts' characteristic of cancer genes, including molecular interactions, pathways and functional annotations. Copy number data supported candidate fusions and suggested a breakpoint principle for intragenic copy number aberrations in fusion partners. By analyzing lung cancer transcriptome sequencing and genomic data, we identified a novel R3HDM2-NFE2 fusion in the H1792 cell line. Lung tissue microarrays revealed 2 of 76 lung cancer patients with genomic rearrangement at the NFE2 locus, suggesting recurrence. Knockdown of NFE2 decreased proliferation and invasion of H1792 cells. Together, these results present a systematic analysis of gene fusions in cancer and describe key characteristics that assist in new fusion discovery.",

author = "Wang, {Xiao Song} and Prensner, {John R.} and Guoan Chen and Qi Cao and Bo Han and Dhanasekaran, {Saravana M.} and Rakesh Ponnala and Xuhong Cao and Sooryanarayana Varambally and Thomas, {Dafydd G.} and Giordano, {Thomas J.} and Beer, {David G.} and Nallasivam Palanisamy and Sartor, {Maureen A.} and Omenn, {Gilbert S.} and Chinnaiyan, {Arul M.}",

note = "Funding Information: We thank F. Mitelman for offering the fusion genes list from the Mitelman database; T.W. Glover for the important comments for improving the manuscript; J. Granger for help with editing the manuscript; S. Qin for useful discussions about biostatistics; NCIBI colleagues L. Ke and A. Ade for helping in the implementation of tools and technologies; C. Yang for the guidance in drug informatics; Z. Hu from Boston University for help with network visualization. This work was supported by the National Institutes of Health (NIH; U54 DA021519) and a National Institutes of Health Cancer Biology Training Grant (CA009676-18 to J.R.P). J.R.P. is a Fellow of the University of Michigan Medical Scientist Training Program. A.M.C. is supported by NIH early detection network U01 CA111275, DOD W81XWH-09-2-0014, the Doris Duke Foundation and the American Cancer Society. Copyright: Copyright 2010 Elsevier B.V., All rights reserved.",

year = "2009",

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doi = "10.1038/nbt.1584",

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AU - Cao, Qi

AU - Han, Bo

AU - Dhanasekaran, Saravana M.

AU - Ponnala, Rakesh

AU - Cao, Xuhong

AU - Varambally, Sooryanarayana

AU - Thomas, Dafydd G.

AU - Giordano, Thomas J.

AU - Beer, David G.

AU - Palanisamy, Nallasivam

AU - Sartor, Maureen A.

AU - Omenn, Gilbert S.

AU - Chinnaiyan, Arul M.

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AB - Cancer genomes contain many aberrant gene fusionsa few that drive disease and many more that are nonspecific passengers. We developed an algorithm (the concept signature or 'ConSig' score) that nominates biologically important fusions from high-throughput data by assessing their association with 'molecular concepts' characteristic of cancer genes, including molecular interactions, pathways and functional annotations. Copy number data supported candidate fusions and suggested a breakpoint principle for intragenic copy number aberrations in fusion partners. By analyzing lung cancer transcriptome sequencing and genomic data, we identified a novel R3HDM2-NFE2 fusion in the H1792 cell line. Lung tissue microarrays revealed 2 of 76 lung cancer patients with genomic rearrangement at the NFE2 locus, suggesting recurrence. Knockdown of NFE2 decreased proliferation and invasion of H1792 cells. Together, these results present a systematic analysis of gene fusions in cancer and describe key characteristics that assist in new fusion discovery.

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An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer

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