title: Kinase impact assessment in the landscape of fusion genes that retain kinase domains: a pan-cancer study.
abstract: Assessing the impact of kinase in gene fusion is essential for both identifying driver fusion genes (FGs) and developing molecular targeted therapies. Kinase domain retention is a crucial factor in kinase fusion genes (KFGs), but such a systematic investigation has not been done yet. To this end, we analyzed kinase domain retention (KDR) status in chimeric protein sequences of 914 KFGs covering 312 kinases across 13 major cancer types. Based on 171 kinase domain-retained KFGs including 101 kinases, we studied their recurrence, kinase groups, fusion partners, exon-based expression depth, short DNA motifs around the break points and networks. Our results, such as more KDR than 5'-kinase fusion genes, combinatorial effects between 3'-KDR kinases and their 5'-partners and a signal transduction-specific DNA sequence motif in the break point intronic sequences, supported positive selection on 3'-kinase fusion genes in cancer. We introduced a degree-of-frequency (DoF) score to measure the possible number of KFGs of a kinase. Interestingly, kinases with high DoF scores tended to undergo strong gene expression alteration at the break points. Furthermore, our KDR gene fusion network analysis revealed six of the seven kinases with the highest DoF scores (ALK, BRAF, MET, NTRK1, NTRK3 and RET) were all observed in thyroid carcinoma. Finally, we summarized common features of 'effective' (highly recurrent) kinases in gene fusions such as expression alteration at break point, redundant usage in multiple cancer types and 3'-location tendency. Collectively, our findings are useful for prioritizing driver kinases and FGs and provided insights into KFGs' clinical implications.
authors.affiliation: Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
authors.forename: Pora
authors.initials: P
authors.lastname: Kim
authors.affiliation: Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
authors.forename: Peilin
authors.initials: P
authors.lastname: Jia
authors.affiliation: Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.|Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
authors.forename: Zhongming
authors.initials: Z
authors.lastname: Zhao
mesh_terms: D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D050596:Oncogene Fusion; D015514:Oncogene Proteins, Fusion / Q000235:genetics*; D000072417:Protein Domains; D011505:Protein-Tyrosine Kinases / Q000235:genetics*; D020794:Receptor Protein-Tyrosine Kinases / Q000235:genetics*
chemical_list: D015514:Oncogene Proteins, Fusion; D011505:Protein-Tyrosine Kinases; D020794:Receptor Protein-Tyrosine Kinases