Research Papers:

RNA sequencing-based cell proliferation analysis across 19 cancers identifies a subset of proliferation-informative cancers with a common survival signature

Ryne C. Ramaker, Brittany N. Lasseigne, Andrew A. Hardigan, Laura Palacio, David S. Gunther, Richard M. Myers and Sara J. Cooper _

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Oncotarget. 2017; 8:38668-38681. https://doi.org/10.18632/oncotarget.16961

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Ryne C. Ramaker1,2,*, Brittany N. Lasseigne1,*, Andrew A. Hardigan1,2, Laura Palacio1, David S. Gunther1, Richard M. Myers1, Sara J. Cooper1

1HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA

2Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA

*These authors contributed equally to this work

Correspondence to:

Richard M. Myers, email: [email protected]

Sara J. Cooper, email: [email protected]

Keywords: cell proliferation, cancer, reelin, survival, RNA-seq

Received: January 02, 2017     Accepted: March 29, 2017     Published: April 08, 2017


Despite advances in cancer diagnosis and treatment strategies, robust prognostic signatures remain elusive in most cancers. Cell proliferation has long been recognized as a prognostic marker in cancer, but the generation of comprehensive, publicly available datasets allows examination of the links between cell proliferation and cancer characteristics such as mutation rate, stage, and patient outcomes. Here we explore the role of cell proliferation across 19 cancers (n = 6,581 patients) by using tissue-based RNA sequencing data from The Cancer Genome Atlas Project and calculating a ‘proliferative index’ derived from gene expression associated with Proliferating Cell Nuclear Antigen (PCNA) levels. This proliferative index is significantly associated with patient survival (Cox, p-value < 0.05) in 7 of 19 cancers, which we have defined as “proliferation-informative cancers” (PICs). In PICs, the proliferative index is strongly correlated with tumor stage and nodal invasion. PICs demonstrate reduced baseline expression of proliferation machinery relative to non-PICs. Additionally, we find the proliferative index is significantly associated with gross somatic mutation burden (Spearman, p = 1.76 x 10−23) as well as with mutations in individual driver genes. This analysis provides a comprehensive characterization of tumor proliferation indices and their association with disease progression and prognosis in multiple cancer types and highlights specific cancers that may be particularly susceptible to improved targeting of this classic cancer hallmark.

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