Title: A census of pathway maps in cancer systems biology.
Authors: Kuenzi, Brent M; Ideker, Trey
Published In Nat Rev Cancer, (2020 04)
Abstract: A key goal of cancer systems biology is to use big data to elucidate the molecular networks by which cancer develops. However, to date there has been no systematic evaluation of how far these efforts have progressed. In this Analysis, we survey six major systems biology approaches for mapping and modelling cancer pathways with attention to how well their resulting network maps cover and enhance current knowledge. Our sample of 2,070 systems biology maps captures all literature-curated cancer pathways with significant enrichment, although the strong tendency is for these maps to recover isolated mechanisms rather than entire integrated processes. Systems biology maps also identify previously underappreciated functions, such as a potential role for human papillomavirus-induced chromosomal alterations in ovarian tumorigenesis, and they add new genes to known cancer pathways, such as those related to metabolism, Hippo signalling and immunity. Notably, we find that many cancer networks have been provided only in journal figures and not for programmatic access, underscoring the need to deposit network maps in community databases to ensure they can be readily accessed. Finally, few of these findings have yet been clinically translated, leaving ample opportunity for future translational studies. Periodic surveys of cancer pathway maps, such as the one reported here, are critical to assess progress in the field and identify underserved areas of methodology and cancer biology.
PubMed ID: 32066900
MeSH Terms: Animals; Computational Biology; Disease Susceptibility*; Energy Metabolism; Gene Expression Regulation, Neoplastic; Gene Regulatory Networks*; Humans; Mice; Neoplasms/etiology*; Neoplasms/metabolism*; Neoplasms/pathology; Signal Transduction*; Systems Biology