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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

2017; Impact Journals LLC; Volume: 8; Issue: 24 Linguagem: Inglês

10.18632/oncotarget.16961

1949-2553

Ryne C. Ramaker, Brittany N. Lasseigne, Andrew A. Hardigan, Laura Quevedo Palacio, David Gunther, R Myers, Sara J. Cooper,

Lung Cancer Treatments and Mutations

// Ryne C. Ramaker 1, 2, * , Brittany N. Lasseigne 1, * , Andrew A. Hardigan 1, 2 , Laura Palacio 1 , David S. Gunther 1 , Richard M. Myers 1 , Sara J. Cooper 1 1 HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA 2 Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA * These authors contributed equally to this work Correspondence to: Richard M. Myers, email: rmyers@hudsonalpha.org Sara J. Cooper, email: sjcooper@hudsonalpha.org Keywords: cell proliferation, cancer, reelin, survival, RNA-seq Received: January 02, 2017 Accepted: March 29, 2017 Published: April 08, 2017 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 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.