The Proteogenomic Landscape of Curable Prostate Cancer

Ankit Sinha; Vincent Huang; Julie Livingstone; Jenny Wang; Natalie S. Fox; Natalie Kurganovs; Vladimir Ignatchenko; Katharina Fritsch; Nilgun Donmez; Lawrence E. Heisler; Yu Jia Shiah; Cindy Q. Yao; Javier A. Alfaro; Stas Volik; Anna Lapuk; Michael Fraser; Ken Kron; Alex Murison; Mathieu Lupien; Cenk Sahinalp; Colin C. Collins; Bernard Tetu; Mehdi Masoomian; David M. Berman; Theodorus van der Kwast; Robert G. Bristow; Thomas Kislinger; Paul C. Boutros

doi:10.1016/j.ccell.2019.02.005

The Proteogenomic Landscape of Curable Prostate Cancer

Ankit Sinha, Vincent Huang, Julie Livingstone, Jenny Wang, Natalie S. Fox, Natalie Kurganovs, Vladimir Ignatchenko, Katharina Fritsch, Nilgun Donmez, Lawrence E. Heisler, Yu Jia Shiah, Cindy Q. Yao, Javier A. Alfaro, Stas Volik, Anna Lapuk, Michael Fraser, Ken Kron, Alex Murison, Mathieu Lupien, Cenk SahinalpColin C. Collins, Bernard Tetu, Mehdi Masoomian, David M. Berman, Theodorus van der Kwast, Robert G. Bristow, Thomas Kislinger^*, Paul C. Boutros

^*Corresponding author for this work

Division of Cancer Sciences (L5)

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

Abstract

DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

Original language	English
Pages (from-to)	414-427.e6
Journal	Cancer Cell
Volume	35
Issue number	3
Early online date	18 Mar 2019
DOIs	https://doi.org/10.1016/j.ccell.2019.02.005
Publication status	Published - 2019

Keywords

biomarker
epigenome
genome
multi-omic features
prostate cancer
proteome
transcriptome

Research Beacons, Institutes and Platforms

Manchester Cancer Research Centre

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.ccell.2019.02.005

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Sinha, A., Huang, V., Livingstone, J., Wang, J., Fox, N. S., Kurganovs, N., Ignatchenko, V., Fritsch, K., Donmez, N., Heisler, L. E., Shiah, Y. J., Yao, C. Q., Alfaro, J. A., Volik, S., Lapuk, A., Fraser, M., Kron, K., Murison, A., Lupien, M., ... Boutros, P. C. (2019). The Proteogenomic Landscape of Curable Prostate Cancer. Cancer Cell, 35(3), 414-427.e6. https://doi.org/10.1016/j.ccell.2019.02.005

@article{bcc0c5a32d1040d2ad48a4d109a21019,

title = "The Proteogenomic Landscape of Curable Prostate Cancer",

abstract = "DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10\% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.",

keywords = "biomarker, epigenome, genome, multi-omic features, prostate cancer, proteome, transcriptome",

author = "Ankit Sinha and Vincent Huang and Julie Livingstone and Jenny Wang and Fox, \{Natalie S.\} and Natalie Kurganovs and Vladimir Ignatchenko and Katharina Fritsch and Nilgun Donmez and Heisler, \{Lawrence E.\} and Shiah, \{Yu Jia\} and Yao, \{Cindy Q.\} and Alfaro, \{Javier A.\} and Stas Volik and Anna Lapuk and Michael Fraser and Ken Kron and Alex Murison and Mathieu Lupien and Cenk Sahinalp and Collins, \{Colin C.\} and Bernard Tetu and Mehdi Masoomian and Berman, \{David M.\} and \{van der Kwast\}, Theodorus and Bristow, \{Robert G.\} and Thomas Kislinger and Boutros, \{Paul C.\}",

year = "2019",

doi = "10.1016/j.ccell.2019.02.005",

language = "English",

volume = "35",

pages = "414--427.e6",

journal = "Cancer Cell",

issn = "1535-6108",

publisher = "Cell Press",

number = "3",

}

Sinha, A, Huang, V, Livingstone, J, Wang, J, Fox, NS, Kurganovs, N, Ignatchenko, V, Fritsch, K, Donmez, N, Heisler, LE, Shiah, YJ, Yao, CQ, Alfaro, JA, Volik, S, Lapuk, A, Fraser, M, Kron, K, Murison, A, Lupien, M, Sahinalp, C, Collins, CC, Tetu, B, Masoomian, M, Berman, DM, van der Kwast, T, Bristow, RG, Kislinger, T & Boutros, PC 2019, 'The Proteogenomic Landscape of Curable Prostate Cancer', Cancer Cell, vol. 35, no. 3, pp. 414-427.e6. https://doi.org/10.1016/j.ccell.2019.02.005

TY - JOUR

T1 - The Proteogenomic Landscape of Curable Prostate Cancer

AU - Sinha, Ankit

AU - Huang, Vincent

AU - Livingstone, Julie

AU - Wang, Jenny

AU - Fox, Natalie S.

AU - Kurganovs, Natalie

AU - Ignatchenko, Vladimir

AU - Fritsch, Katharina

AU - Donmez, Nilgun

AU - Heisler, Lawrence E.

AU - Shiah, Yu Jia

AU - Yao, Cindy Q.

AU - Alfaro, Javier A.

AU - Volik, Stas

AU - Lapuk, Anna

AU - Fraser, Michael

AU - Kron, Ken

AU - Murison, Alex

AU - Lupien, Mathieu

AU - Sahinalp, Cenk

AU - Collins, Colin C.

AU - Tetu, Bernard

AU - Masoomian, Mehdi

AU - Berman, David M.

AU - van der Kwast, Theodorus

AU - Bristow, Robert G.

AU - Kislinger, Thomas

AU - Boutros, Paul C.

PY - 2019

Y1 - 2019

N2 - DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

AB - DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

KW - biomarker

KW - epigenome

KW - genome

KW - multi-omic features

KW - prostate cancer

KW - proteome

KW - transcriptome

U2 - 10.1016/j.ccell.2019.02.005

DO - 10.1016/j.ccell.2019.02.005

M3 - Article

C2 - 30889379

AN - SCOPUS:85062152512

SN - 1535-6108

VL - 35

SP - 414-427.e6

JO - Cancer Cell

JF - Cancer Cell

IS - 3

ER -

The Proteogenomic Landscape of Curable Prostate Cancer

Abstract

Keywords

Research Beacons, Institutes and Platforms

UN SDGs

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