Beyond Synthetic Lethality: Charting the Landscape of Pairwise Gene Expression States Associated with Survival in Cancer

Assaf Magen, Avinash Das Sahu, Joo Sang Lee, Mahfuza Sharmin, Alexander Lugo, J. Silvio Gutkind, Alejandro A. Schäffer*, Eytan Ruppin, Sridhar Hannenhalli

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The phenotypic effect of perturbing a gene's activity depends on the activity level of other genes, reflecting the notion that phenotypes are emergent properties of a network of functionally interacting genes. In the context of cancer, contemporary investigations have primarily focused on just one type of functional relationship between two genes—synthetic lethality (SL). Here, we define the more general concept of “survival-associated pairwise gene expression states” (SPAGEs) as gene pairs whose joint expression levels are associated with survival. We describe a data-driven approach called SPAGE-finder that when applied to The Cancer Genome Atlas (TCGA) data identified 71,946 SPAGEs spanning 12 distinct types, only a minority of which are SLs. The detected SPAGEs explain cancer driver genes’ tissue specificity and differences in patients’ response to drugs and stratify breast cancer tumors into refined subtypes. These results expand the scope of cancer SPAGEs and lay a conceptual basis for future studies of SPAGEs and their translational applications.

Original languageEnglish
Pages (from-to)938-948.e6
JournalCell Reports
Volume28
Issue number4
DOIs
StatePublished - 23 Jul 2019
Externally publishedYes

Keywords

  • cancer stratification
  • data mining
  • drug response
  • gene interactions
  • patient survival analysis
  • synthetic lethality

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