Cell Reports (May 2018)

A General Framework for Interrogation of mRNA Stability Programs Identifies RNA-Binding Proteins that Govern Cancer Transcriptomes

  • Gabrielle Perron,
  • Pouria Jandaghi,
  • Shraddha Solanki,
  • Maryam Safisamghabadi,
  • Cristina Storoz,
  • Mehran Karimzadeh,
  • Andreas I. Papadakis,
  • Madeleine Arseneault,
  • Ghislaine Scelo,
  • Rosamonde E. Banks,
  • Jorg Tost,
  • Mark Lathrop,
  • Simon Tanguay,
  • Alvis Brazma,
  • Sidong Huang,
  • Fadi Brimo,
  • Hamed S. Najafabadi,
  • Yasser Riazalhosseini

Journal volume & issue
Vol. 23, no. 6
pp. 1639 – 1650

Abstract

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Summary: Widespread remodeling of the transcriptome is a signature of cancer; however, little is known about the post-transcriptional regulatory factors, including RNA-binding proteins (RBPs) that regulate mRNA stability, and the extent to which RBPs contribute to cancer-associated pathways. Here, by modeling the global change in gene expression based on the effect of sequence-specific RBPs on mRNA stability, we show that RBP-mediated stability programs are recurrently deregulated in cancerous tissues. Particularly, we uncovered several RBPs that contribute to the abnormal transcriptome of renal cell carcinoma (RCC), including PCBP2, ESRP2, and MBNL2. Modulation of these proteins in cancer cell lines alters the expression of pathways that are central to the disease and highlights RBPs as driving master regulators of RCC transcriptome. This study presents a framework for the screening of RBP activities based on computational modeling of mRNA stability programs in cancer and highlights the role of post-transcriptional gene dysregulation in RCC. : Perron et al. develop a computational approach that models the functional activity of RBPs in individual cancer samples by monitoring their associated RNA stability programs. Applying this method to renal cell carcinoma transcriptomes, the authors identify RBPs that enhance cancer-associated pathways including hypoxia and cell cycle. Keywords: RNA-binding proteins, gene regulation, mRNA stability, renal cancer, regulatory networks, network modeling, MBNL2, PCBP2, ESRP2