Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Jan 8;48(D1):D416-D421.
doi: 10.1093/nar/gkz871.

CancerGeneNet: linking driver genes to cancer hallmarks

Affiliations

CancerGeneNet: linking driver genes to cancer hallmarks

Marta Iannuccelli et al. Nucleic Acids Res. .

Abstract

CancerGeneNet (https://signor.uniroma2.it/CancerGeneNet/) is a resource that links genes that are frequently mutated in cancers to cancer phenotypes. The resource takes advantage of a curation effort aimed at embedding a large fraction of the gene products that are found altered in cancer cells into a network of causal protein relationships. Graph algorithms, in turn, allow to infer likely paths of causal interactions linking cancer associated genes to cancer phenotypes thus offering a rational framework for the design of strategies to revert disease phenotypes. CancerGeneNet bridges two interaction layers by connecting proteins whose activities are affected by cancer drivers to proteins that impact on the 'hallmarks of cancer'. In addition, CancerGeneNet annotates curated pathways that are relevant to rationalize the pathological consequences of cancer driver mutations in selected common cancers and 'MiniPathways' illustrating regulatory circuits that are frequently altered in different cancers.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Database content. (A) schematic representation of the layered information in the CancerGeneNet database. The second layer represents the cancer gene network that was specifically curated for this project. The yellow hexagons in the top layer represent the anticancer drugs that target sensitive signaling proteins. The cancer genes impact on the causal interactome network in SIGNOR (light green circles) that directly affect cancer phenotypes (green rectangles). (B) Venn diagram of the cancer genes annotated in the Cancer Gene Census and in DisGeNET. (C) Histogram representing the distribution of the number of relationships for each cancer gene in the Cancer Gene Census. (D) The diagram illustrates the size of the protein ensembles that are (i) annotated in Signor, (ii) included in the Cancer gene Census, (iii) specific targets of anti-cancer drugs or (iv) have been annotated as phenotype modifiers.
Figure 2.
Figure 2.
Connecting cancer associated genes. A tool based on graph algorithms offers the possibility to find functional connections in list of genes that can be user-defined or obtained from the Cancer Gene Census or DisGeNET. (A) Three types of graphs can be obtained. At level 1 only direct connections between query genes are shown. At level 2, two query genes can be linked by causal interactions with common proteins in the global causal interactome. Finally, at level 3, all the interactions of the query cancer genes are shown. (B) Once one of these graphs are shown it is possible to explore cross talks with a list of curated cancer MiniPathways.

References

    1. Hutter C., Zenklusen J.C.. The cancer genome Atlas: creating lasting value beyond its data. Cell. 2018; 173:283–285. - PubMed
    1. Tate J.G., Bamford S., Jubb H.C., Sondka Z., Beare D.M., Bindal N., Boutselakis H., Cole C.G., Creatore C., Dawson E. et al. .. COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res. 2019; 47:D941–D947. - PMC - PubMed
    1. Sondka Z., Bamford S., Cole C.G., Ward S.A., Dunham I., Forbes S.A.. The COSMIC cancer gene Census: describing genetic dysfunction across all human cancers. Nat. Rev. Cancer. 2018; 18:696–705. - PMC - PubMed
    1. Davis A.P., Grondin C.J., Johnson R.J., Sciaky D., McMorran R., Wiegers J., Wiegers T.C., Mattingly C.J.. The comparative toxicogenomics Database: update 2019. Nucleic Acids Res. 2019; 47:D948–D954. - PMC - PubMed
    1. Gonzalez-Perez A., Perez-Llamas C., Deu-Pons J., Tamborero D., Schroeder M.P., Jene-Sanz A., Santos A., Lopez-Bigas N.. IntOGen-mutations identifies cancer drivers across tumor types. Nat. Methods. 2013; 10:1081–1082. - PMC - PubMed

Publication types