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The landscape and therapeutic relevance of cancer-associated transcript fusions
Open accessAbstract
Transcript fusions as a result of chromosomal rearrangements have been a focus of attention in cancer as they provide attractive therapeutic targets. To identify novel fusion transcripts with the potential to be exploited therapeutically, we analyzed RNA sequencing, DNA copy number and gene mutation data from 4366 primary tumor samples. To avoid false positives, we implemented stringent quality criteria that included filtering of fusions detected in RNAseq data from 364 normal tissue samples. Our analysis identified 7887 high confidence fusion transcripts across 13 tumor types. Our fusion prediction was validated by evidence of a genomic rearrangement for 78 of 79 fusions in 48 glioma samples where whole-genome sequencing data were available. Cancers with higher levels of genomic instability showed a corresponding increase in fusion transcript frequency, whereas tumor samples harboring fusions contained statistically significantly fewer driver gene mutations, suggesting an important role for tumorigenesis. We identified at least one in-frame protein kinase fusion in 324 of 4366 samples (7.4%). Potentially druggable kinase fusions involving ALK, ROS, RET, NTRK and FGFR gene families were detected in bladder carcinoma (3.3%), glioblastoma (4.4%), head and neck cancer (1.0%), low-grade glioma (1.5%), lung adenocarcinoma (1.6%), lung squamous cell carcinoma (2.3%) and thyroid carcinoma (8.7%), suggesting a potential for application of kinase inhibitors across tumor types. In-frame fusion transcripts involving histone methyltransferase or histone demethylase genes were detected in 111 samples (2.5%) and may additionally be considered as therapeutic targets. In summary, we described the landscape of transcript fusions detected across a large number of tumor samples and revealed fusion events with clinical relevance that have not been previously recognized. Our results support the concept of basket clinical trials where patients are matched with experimental therapies based on their genomic profile rather than the tissue where the tumor originated.
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“Finally, a low ratio of chimeric to wild-type reads in the vicinity of the fusion boundary may indicate spurious mis-mapping of reads from a highly expressed gene (the transcript allele fraction described by Yoshihara et al. [87]).”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [87]
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Zehir, A., Benayed, R., Shah, R. H., Syed, A., Middha, S., Kim, H. R., Srinivasan, P., Gao, J., Chakravarty, D., Devlin, S. M., et al. (2017) · Nature Medicine · doi:10.1038/nm.4333 · Cited by 3,380
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“Filtering highly polymorphic genes and pairs of homologous genes is recommended [86, 87].”
BackgroundComprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.060 · Cited by 2,256
“, 2013), genomic fusions (Yoshihara et al., 2014), or methylation events (De Carvalho et al.”
BackgroundDistinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas
Cancer Genome Atlas Research Network, Campbell, J. D., Alexandrov, A., Kim, J., Wala, J., Berger, A. H., Pedamallu, C. S., Shukla, S. A., Guo, G., Brooks, A. N., et al. (2016) · Nature Genetics · doi:10.1038/ng.3564 · Cited by 1,200
Self-citationGenomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas
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“, 2017) and TCGA Fusion Gene Data Portal (Yoshihara et al., 2015) then manually checked for read alignments to identify 188 high-confidence fusion events that involved 108 DDR genes in 205 cancer samples (Figure S4C).”
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Metadata
- Authors
- Yoshihara, K., Wang, Q., Torres-Garcia, W., Zheng, S., Vegesna, R., Kim, H., & Verhaak, R. G. W.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- Corresponding author
- Verhaak, R G W
- Venue
- Oncogene
- Published
- 2014-12-15
- Volume
- 34
- Issue
- 37
- Pages
- 4845-4854
- ISSN
- 0950-9232 (ISSN-L)
- 1476-5594
- PMC
- PMC4468049
- OpenAlex
- W2042337609
- Cited by
- 450
- References
- 56
- Citations by year
- 2026: 8 · 2025: 26 · 2024: 38 · 2023: 23 · 2022: 41 · 2021: 59 · 2020: 37 · 2019: 56 · 2018: 43 · 2017: 54 · 2016: 48 · 2015: 16 · 2014: 1
- FWCI
- 12.71
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Oncogene (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Mary K. Chapman Foundation
- California Department of Transportation
- National Cancer Institute (CA083639, CA143883, U24CA143883, P50CA083639, P30CA016672)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- fusion transcripts, chromosomal rearrangements, kinase fusions, anaplastic lymphoma kinase, reactive oxygen species, RET, NTRK, fibroblast growth factor receptor, genomic instability, driver mutations, kinase inhibitors, glioma, bladder cancer, thyroid cancer, lung adenocarcinoma, lung squamous cell carcinoma, head and neck cancer, low-grade glioma, glioblastoma
- MeSH terms
- Cell Transformation, Neoplastic, DNA Mutational Analysis, Humans, Neoplasms, RNA, Messenger, RNA, Neoplasm, Oncogene Proteins, Fusion, Sequence Alignment, Genetic Heterogeneity, Computational Biology, Gene Expression Profiling, Chromatin Assembly and Disassembly, Molecular Targeted Therapy
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