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FusionCancer: a database of cancer fusion genes derived from RNA-seq data
Yunjin Wang1, Nan Wu2, Jiaqi Liu3
1Institute of Molecular Ecology and Evolution, SKLEC & IECR, East China Normal University, Shanghai, China. yunjinwang1222@gmail.com.
Background:
Fusion genes are chimeric results originated from previous separate genes with aberrant functions. The resulting protein products may lead to abnormal status of expression levels, functions and action sites, which in return may cause the abnormal proliferation of cells and cancer development.
Results:
With the emergence of next-generation sequencing technology, RNA-seq has spurred gene fusion discovery in various cancer types. In this work, we compiled 591 recently published RNA-seq datasets in 15 kinds of human cancer, and the gene fusion events were comprehensively identified. Based on the results, a database was developed for gene fusion in cancers (FusionCancer), with the attempt to provide a user-friendly utility for the cancer research community. A flexible query engine has been developed for the acquisition of annotated information of cancer fusion genes, which would help users to determine the chimera events leading to functional changes. FusionCancer can be accessible at the following hyperlink website: http://donglab.ecnu.edu.cn/databases/FusionCancer/
Conclusion:
To the best of our knowledge, FusionCancer is the first comprehensive fusion gene database derived only from cancer RNA-seq data.
Insights
Researchers created FusionCancer, a comprehensive database of gene fusions identified from cancer RNA-sequencing data. This resource aids in understanding cancer development by analyzing fusion events and their functional impacts.
Area of Science:
- Genomics
- Cancer Research
- Bioinformatics
Background:
- Fusion genes arise from separate genes, leading to aberrant protein functions.
- These alterations can cause abnormal cell proliferation and cancer development.
Purpose of the Study:
- To comprehensively identify gene fusion events across various human cancers.
- To develop a user-friendly database, FusionCancer, for the cancer research community.
Main Methods:
- Compiled and analyzed 591 recent RNA-sequencing datasets from 15 human cancer types.
- Developed a flexible query engine for accessing annotated information on cancer fusion genes.
Main Results:
- Successfully identified numerous gene fusion events in the analyzed cancer datasets.
- Developed FusionCancer, a dedicated database for cancer fusion genes.
- The database facilitates the determination of chimera events and their functional consequences.
Conclusions:
- FusionCancer is the first comprehensive database exclusively derived from cancer RNA-sequencing data.
- This resource provides valuable insights into gene fusions driving cancer development.
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