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

View ORCID ProfileRyne C. Ramaker, View ORCID ProfileBrittany N. Lasseigne, View ORCID ProfileAndrew A. Hardigan, Laura Palacio, David S. Gunther, Marie K. Kirby, Richard M. Myers, Sara J. Cooper
doi: https://doi.org/10.1101/063057
Ryne C. Ramaker
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
2Department of Genetics, University of Alabama at Birmingham, Birmingham, AL
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Brittany N. Lasseigne
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
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Andrew A. Hardigan
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
2Department of Genetics, University of Alabama at Birmingham, Birmingham, AL
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Laura Palacio
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
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David S. Gunther
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
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Marie K. Kirby
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
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Richard M. Myers
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
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Sara J. Cooper
1HudsonAlpha Institute for Biotechnology, Huntsville, AL
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Abstract

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 it has not been thoroughly investigated across multiple cancers. Here we explore the role of cell proliferation across 19 cancers (n=6,581 patients) using tissue-based RNA sequencing from The Cancer Genome Atlas project by employing a ‘proliferative index’ derived from gene expression associated with PCNA expression. This proliferative index is significantly associated with patient survival (Cox, p-value<0.05) in 7/19 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 paradoxically demonstrate reduced baseline expression of proliferation machinery relative to non-PICs suggesting that non-PICs saturate their proliferative capacity early in tumor development and allow other factors to dictate prognostic outcomes. We also identify chemotherapies whose efficacy is correlated with proliferation index and highlight drugs capable of inhibiting proliferation associated expression. Additionally, we find that proliferative index is significantly associated with gross somatic mutation burden (Spearman, p=1.76×10−23) as well mutations in individual driver genes. This analysis provides a comprehensive characterization of tumor proliferation rates and their association with disease progression and prognosis across cancer types and highlights specific cancers that may be particularly susceptible to improved targeting of this classic cancer hallmark.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 10, 2016.
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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, Marie K. Kirby, Richard M. Myers, Sara J. Cooper
bioRxiv 063057; doi: https://doi.org/10.1101/063057
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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, Marie K. Kirby, Richard M. Myers, Sara J. Cooper
bioRxiv 063057; doi: https://doi.org/10.1101/063057

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