Integrated Omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact

Lei Li, Yuhong Wei, Christine To, Chang-Qi Zhu, Jiefei Tong, Nhu-An Pham, Paul Taylor, Vladimir Ignatchenko, Alex Ignatchenko, Wen Zhang, Dennis Wang, Naoki Yanagawa, Ming Li, Melania Pintilie, Geoffrey Liu, Lakshmi Muthuswamy, Frances A. Shepherd, Ming Sound Tsao, Thomas Kislinger and Michael F. Moran ()
Additional contact information
Lei Li: The Hospital For Sick Children
Yuhong Wei: The Hospital For Sick Children
Christine To: Princess Margaret Cancer Centre
Chang-Qi Zhu: Princess Margaret Cancer Centre
Jiefei Tong: The Hospital For Sick Children
Nhu-An Pham: Princess Margaret Cancer Centre
Paul Taylor: The Hospital For Sick Children
Vladimir Ignatchenko: Princess Margaret Cancer Centre
Alex Ignatchenko: Princess Margaret Cancer Centre
Wen Zhang: The Hospital For Sick Children
Dennis Wang: Princess Margaret Cancer Centre
Naoki Yanagawa: Princess Margaret Cancer Centre
Ming Li: Princess Margaret Cancer Centre
Melania Pintilie: Princess Margaret Cancer Centre
Geoffrey Liu: Princess Margaret Cancer Centre
Lakshmi Muthuswamy: University of Toronto
Frances A. Shepherd: Princess Margaret Cancer Centre
Ming Sound Tsao: Princess Margaret Cancer Centre
Thomas Kislinger: Princess Margaret Cancer Centre
Michael F. Moran: The Hospital For Sick Children

Nature Communications, 2014, vol. 5, issue 1, 1-12

Abstract: Abstract Cancer results from processes prone to selective pressure and dysregulation acting along the sequence-to-phenotype continuum DNA→RNA→protein→disease. However, the extent to which cancer is a manifestation of the proteome is unknown. Here we present an integrated omic map representing non-small cell lung carcinoma. Dysregulated proteins not previously implicated as cancer drivers are encoded throughout the genome including, but not limited to, regions of recurrent DNA amplification/deletion. Clustering reveals signatures composed of metabolism proteins particularly highly recapitulated between patient-matched primary and xenograft tumours. Interrogation of The Cancer Genome Atlas reveals cohorts of patients with lung and other cancers that have DNA alterations in genes encoding the signatures, and this was accompanied by differences in survival. The recognition of genome and proteome alterations as related products of selective pressure driving the disease phenotype may be a general approach to uncover and group together cryptic, polygenic disease drivers.

Date: 2014
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DOI: 10.1038/ncomms6469

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