KuNG FU: a database of KiNase Gene FUsions in cancer cell lines

KuNG FU (KiNase Gene FUsion) is a novel homogeneous user-friendly on line database collecting the largest manually curated catalogue of annotated, potentially active and experimentally validated kinase gene fusions identified in cancer cell lines. Only in-frame kinase gene fusions retaining an intact catalytic domain were included, to offer a druggable set of kinase gene fusion targets characterized in cancer cell line models. The KuNG FU database was developed and made available online to support the strong interest in kinase gene fusion research models in drug development and diagnostic tool design, often hampered by a lack of exhaustive and convenient specific databases.

KuNG FU main features:

 

Background

Kinases are a family of enzymes involved in key cellular functions, often found deregulated in cancer as a consequence of activating gene mutations, overexpression or gene fusions. They are characterized by a conserved ATP-binding pocket, which can be exploited for the binding of small molecules, thus representing ideal targets in drug discovery. The availability of cancer cell lines harboring kinase gene fusions represents a useful model, which can be exploited for target validation and drug development. Most of the reported gene fusions were obtained using algorithms predicting gene fusions based on RNA-seq data. They often lack of accurate annotation or are not supported by experimental validation. Moreover the available information is spread in different papers or reported as plain text lists, not allowing for interactive queries. To overcome these issues, we implemented KuNG FU (KiNase Gene FUsion), an integrated resource collecting validated and manually curated data on kinase gene fusions in cancer cell lines, thus providing a tool in support to cancer research and drug discovery.
 

KuNG FU Last Update: 31 January 2021


Reference:

Please cite the following paper:
Somaschini, A., Di Bella, S., Cusi, C., Raddrizzani, L., Leone, A., Carapezza, G., Mazza, T., Isacchi, A., & Bosotti, R.
Mining potentially actionable kinase gene fusions in cancer cell lines with the KuNG FU database.
Sci Data 7, 420 (2020). https://doi.org/10.1038/s41597-020-00761-2