Domain retention in transcription factor fusion genes and its biological and clinical implications: a pan-cancer study
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Pora Kim1, Leomar Y. Ballester2 and Zhongming Zhao1,3
1Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
2Department of Pathology and Laboratory Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
3Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
Zhongming Zhao, email: email@example.com
Keywords: transcription factor fusion gene; functional domain retention; differential expression; gene fusion network; PML-RARA
Received: July 18, 2017 Accepted: October 25, 2017 Published: November 24, 2017
Genomic rearrangements involving transcription factors (TFs) can form fusion proteins resulting in either enhanced, weakened, or even loss of TF activity. Functional domain (FD) retention is a critical factor in the activity of transcription factor fusion genes (TFFGs). A systematic investigation of FD retention in TFFGs and their outcome (e.g. expression changes) in a pan-cancer study has not yet been completed. Here, we examined the FD retention status in 386 TFFGs across 13 major cancer types and identified 83 TFFGs involving 67 TFs that retained FDs. To measure the potential biological relevance of TFs in TFFGs, we introduced a Major Active Isofusion Index (MAII) and built a prioritized TFFG network using MAII scores and the observed frequency of fusion positive samples. Interestingly, the four TFFGs (PML-RARA, RUNX1-RUNX1T1, TMPRSS2-ERG, and SFPQ-TFE3) with the highest MAII scores showed 50 differentially expressed target genes (DETGs) in fusion-positive versus fusion-negative cancer samples. DETG analysis revealed that they were involved in tumorigenesis-related processes in each cancer type. PLAU, which encodes plasminogen activator urokinase and serves as a biomarker for tumor invasion, was found to be consistently activated in the samples with the highest MAII scores. Among the 50 DETGs, 21 were drug targetable genes. Fourteen of these 21 DETGs were expressed in acute myeloid leukemia (AML) samples. Accordingly, we constructed an AML-specific TFFG network, which included 38 DETGs in RUNX1-RUNX1T1 or PML-RARA positive samples. In summary, this study revealed several TFFGs and their potential target genes, and provided insights into the clinical implications of TFFGs.
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