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

doi:10.1016/j.celrep.2019.06.067

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

Cell Rep. 2019 Jul 23;28(4):938-948.e6. doi: 10.1016/j.celrep.2019.06.067.

Authors

Assaf Magen¹, Avinash Das Sahu², Joo Sang Lee³, Mahfuza Sharmin⁴, Alexander Lugo⁵, J Silvio Gutkind⁶, Alejandro A Schäffer⁷, Eytan Ruppin⁸, Sridhar Hannenhalli⁹

Affiliations

¹ Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
² Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Department of Biostatistics and Computational Biology, Harvard School of Public Health, Boston, MA, USA; Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA.
³ Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
⁴ Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Department of Genetics, Stanford University, Stanford, CA, USA.
⁵ Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.
⁶ Moores Cancer Center, University of California San Diego, La Jolla, CA, USA.
⁷ Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: [email protected].
⁸ Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: [email protected].
⁹ Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: [email protected].

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.

Keywords: cancer stratification; data mining; drug response; gene interactions; patient survival analysis; synthetic lethality.

Publication types

Research Support, N.I.H., Intramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Antineoplastic Agents / pharmacology
Antineoplastic Agents / therapeutic use
Carcinogenesis / drug effects
Gene Expression Regulation, Neoplastic* / drug effects
Genes, Neoplasm
Humans
Neoplasms / drug therapy
Neoplasms / genetics*
Organ Specificity / genetics
Survival Analysis
Synthetic Lethal Mutations / genetics*

Substances

Antineoplastic Agents

Abstract

Publication types

MeSH terms

Substances

Grants and funding