The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895
Fast and accurate long-read alignment with Burrows-Wheeler transform.
Li, H., & Durbin, R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp698 · Cited by 12,063
In silico prediction of protein-protein interactions in human macrophages
Souiai, O., Guerfali, F. Z., Miled, S. B., Brun, C., & Benkahla, A. (2014) · BMC Research Notes · doi:10.1186/1756-0500-7-157 · Cited by 10,785
Significance analysis of microarrays applied to the ionizing radiation response
Tusher, V. G., Tibshirani, R., & Chu, G. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.091062498 · Cited by 10,568
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461
Identification of the transforming EML4–ALK fusion gene in non-small-cell lung cancer
Soda, M., Choi, Y. L., Enomoto, M., Takada, S., Yamashita, Y., Ishikawa, S., Fujiwara, S.-I., Watanabe, H., Kurashina, K., Hatanaka, H., et al. (2007) · Nature · doi:10.1038/nature05945 · Cited by 5,439
Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia
The Cancer Genome Atlas Research Network (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1301689 · Cited by 5,078
The Somatic Genomic Landscape of Glioblastoma
Brennan, C. W., Verhaak, R. G. W., McKenna, A., Campos, B., Noushmehr, H., Salama, S. R., Zheng, S., Chakravarty, D., Sanborn, J. Z., Berman, S. H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.09.034 · Cited by 5,016
Self-citation
Cited by
Sorted by citations
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
Self-citationA survey of best practices for RNA-seq data analysis
Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., Szcześniak, M. W., Gaffney, D. J., Elo, L. L., Zhang, X., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0881-8 · Cited by 2,794
“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
Knijnenburg, T., Wang, L., Zimmermann, M. T., Chambwe, N., Gao, G. F., Cherniack, A. D., Fan, H., Shen, H., Way, G. P., Greene, C. S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.076 · Cited by 1,145
“, 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).”
InfluentialCancer biomarkers: Emerging trends and clinical implications for personalized treatment
Passaro, A., Bakir, M. A., Hamilton, E. G., Diehn, M., André, F., Roy‐Chowdhuri, S., Mountzios, G., Wistuba, I. I., Swanton, C., & Peters, S. (2024) · Cell · doi:10.1016/j.cell.2024.02.041 · Cited by 726
“5,6 In all these examples, a targeted therapy by HER2, EGFR, KIT, and BRAF signaling inhibitors improved the outcome of patients with metastatic cancer presenting the genomic alteration.”
The emerging complexity of gene fusions in cancer
Mertens, F., Johansson, B., Fioretos, T., & Mitelman, F. (2015) · Nature reviews. Cancer · doi:10.1038/nrc3947 · Cited by 693
Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma
Zheng, S., Cherniack, A. D., Dewal, N., Moffitt, R. A., Danilova, L., Murray, B. A., Lerario, A. M., Else, T., Knijnenburg, T. A., Ciriello, G., et al. (2016) · Cancer Cell · doi:10.1016/j.ccell.2016.04.002 · Cited by 657
Self-citationHaas, B. J., Dobin, A., Li, B., Stransky, N., Pochet, N., & Regev, A. (2019) · Genome biology · doi:10.1186/s13059-019-1842-9 · Cited by 646
“The cancer-relevant fusions include those reported in the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer [90], ChimerDB 2.0 [91], COS-MIC [92, 93], and fusions discovered in cancer cell lines and surveys of tumor samples [1, 94, 95].”
BackgroundInfluentialSystematic analysis of telomere length and somatic alterations in 31 cancer types
Barthel, F. P., Wei, W., Tang, M., Martinez-Ledesma, E., Hu, X., Amin, S. B., Akdemir, K. C., Seth, S., Song, X., Wang, Q., et al. (2017) · Nature Genetics · doi:10.1038/ng.3781 · Cited by 614
Self-citationKim, H., Nguyen, N., Turner, K. M., Wu, S., Gujar, A. D., Luebeck, J., Liu, J., Deshpande, V., Rajkumar, U., Namburi, S., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0678-2 · Cited by 578
Self-citationMolecular characterization of cancers with NTRK gene fusions
Gatalica, Z., Xiu, J., Swensen, J. J., & Vranić, S. (2018) · Modern Pathology · doi:10.1038/s41379-018-0118-3 · Cited by 491
Benayed, R., Offin, M. D., Mullaney, K. A., Sukhadia, P., Rios, K., Desmeules, P., Ptashkin, R. N., Won, H. H., Chang, J. C., Halpenny, D. F., et al. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-0225 · Cited by 495
“It has been previously noted that tumors positive for gene fusions contained a low number of mutations (64).”
BackgroundGlioblastoma targeted therapy: updated approaches from recent biological insights
Touat, M., Idbaïh, A., Sanson, M., & Ligon, K. L. (2017) · Annals of Oncology · doi:10.1093/annonc/mdx106 · Cited by 460
Suda, K., Nakaoka, H., Yoshihara, K., Ishiguro, T., Tamura, R., Mori, Y., Yamawaki, K., Adachi, S., Takahashi, T., Kase, H., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.037 · Cited by 414
Self-citationTargeting RET-driven cancers: lessons from evolving preclinical and clinical landscapes
Drilon, A. E. D. C., Hu, Z. I., Lai, G. G. Y., & Tan, D. S. W. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.175 · Cited by 414
Weischenfeldt, J., Dubash, T., Drainas, A. P., Mardin, B. R., Chen, Y., Stütz, A. M., Waszak, S. M., Bosco, G., Halvorsen, A. R., Raeder, B., et al. (2017) · Nature Genetics · doi:10.1038/ng.3722 · Cited by 404
TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes
Zhao, M., Kim, P., Mitra, R., Zhao, J., & Zhao, Z. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1268 · Cited by 396
Fusions in solid tumours: diagnostic strategies, targeted therapy, and acquired resistance
Schram, A. M., Chang, M. T., Jonsson, P., & Drilon, A. E. D. C. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.127 · Cited by 334
Yasuhara, T., Kato, R., Hagiwara, Y., Shiotani, B., Yamauchi, M., Nakada, S., Shibata, A., & Miyagawa, K. (2018) · Cell · doi:10.1016/j.cell.2018.08.056 · Cited by 317
“The gene fusion data for each sample were obtained from TCGA Fusion gene Data Portal (Yoshihara et al., 2015).”
MethodProteogenomic Characterization of Human Early-Onset Gastric Cancer
Mun, D.-G., Bhin, J., Kim, S., Kim, H., Jung, J. H., Jung, Y., Jang, Y. E., Park, J. M., Kim, H., Jung, Y., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2018.12.003 · Cited by 294
Self-citationRubio-Perez, C., Tamborero, D., Schroeder, M. P., Antolín, A. A., Deu-Pons, J., Perez-Llamas, C., Mestres, J., Gonzalez-Perez, A., & Lopez-Bigas, N. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.02.007 · Cited by 296
“Then, we interrogated the TCGA Fusion Gene Data Portal (Yoshihara et al., 2014) to obtain a list of the samples exhibiting in-frame fusions of these genes with any partner in the core cohort (Supplemental Experimental Procedures).”
MethodSTAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-SeqPreprint
Haas, B. J., Dobin, A., Stransky, N., Li, B., Yang, X. F., Tickle, T. L., Bankapur, A., Ganote, C. L., Doak, T. G., Pochet, N. L. M. M., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/120295 · Cited by 300
Cancer transcriptome profiling at the juncture of clinical translation
Cieslik, M. P., & Chinnaiyan, A. M. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.96 · Cited by 266
The kinome 'at large' in cancer
Fleuren, E. D. G., Zhang, L., Wu, J., & Daly, R. J. (2016) · Nature reviews. Cancer · doi:10.1038/nrc.2015.18 · Cited by 268
TumorFusions: an integrative resource for cancer-associated transcript fusions
Hu, X., Wang, Q., Tang, M., Barthel, F. P., Amin, S. B., Yoshihara, K., Lang, F., Martínez-Ledesma, E., Lee, S. H., Zheng, S., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1018 · Cited by 238
Self-citationRecurrent MET fusion genes represent a drug target in pediatric glioblastoma
Bender, S., Gröbner, S. N., Pfaff, E., Kool, M., Northcott, P. A., Sturm, D., Worst, B. C., Pfister, S. M., Jones, D. T. W., van Tilburg, C. M., et al. (2016) · Nature Medicine · doi:10.1038/nm.4204 · Cited by 234
Hsiao, S. J., Zehir, A., Sireci, A. N., & Aisner, D. L. (2019) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2019.03.008 · Cited by 225
Recurrent chimeric fusion RNAs in non-cancer tissues and cells
Babiceanu, M., Qin, F., Xie, Z., Jia, Y., Lopez, K., Janus, N., Facemire, L., Kumar, S., Pang, Y., Qi, Y., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw032 · Cited by 208
Discovering and understanding oncogenic gene fusions through data intensive computational approaches
Latysheva, N. S., & Babu, M. M. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw282 · Cited by 201
A metabolic function of FGFR3-TACC3 gene fusions in cancer
Frattini, V., Pagnotta, S. M., Tala, Fan, J. J., Russo, M. V., Lee, S. B., Garofano, L., Zhang, J., Shi, P., Lewis, G., et al. (2018) · Nature · doi:10.1038/nature25171 · Cited by 189
“We selected 19 human samples harboring the F3-T3 fusions from Stransky et al. 31 and the TCGA fusion gene Data Portal 32 .”
Testing algorithm for identification of patients with TRK fusion cancer
Penault-Llorca, F. M., Rudzinski, E. R., & Sepulveda, A. R. (2019) · Journal of Clinical Pathology · doi:10.1136/jclinpath-2018-205679 · Cited by 176
Precision therapy for RET-altered cancers with RET inhibitors
Thein, K. Z., Velcheti, V., Mooers, B. H. M., Wu, J., & Subbiah, V. (2021) · Trends in cancer · doi:10.1016/j.trecan.2021.07.003 · Cited by 175
The RNA Atlas expands the catalog of human non-coding RNAs
Lorenzi, L., Chiu, H.-S., Avila Cobos, F., Gross, S., Volders, P.-J., Cannoodt, R., Nuytens, J., Vanderheyden, K., Anckaert, J., Lefever, S., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00936-1 · Cited by 163
Landscape of gene fusions in epithelial cancers: seq and ye shall find
Kumar‐Sinha, C., Sundaram, S. K., & Chinnaiyan, A. M. (2015) · Genome Medicine · doi:10.1186/s13073-015-0252-1 · Cited by 155
“org) [89].”
Genomic disorders 20 years on—mechanisms for clinical manifestations
Harel, T., & Lupski, J. R. (2017) · Clinical Genetics · doi:10.1111/cge.13146 · Cited by 150
“This has been well documented for the red-green opsin genes in color blindness,(89,90) as well as for specific proto-oncogenes in cancer syndromes, where fusion genes are potentially druggable.(91,92) Moreover, complex rearrangements with inversions can result in novel fusion transcripts that evolve novel genes.”
BackgroundGene fusions in soft tissue tumors: Recurrent and overlapping pathogenetic themes
Mertens, F., Antonescu, C. R., & Mitelman, F. (2015) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22335 · Cited by 145
“Because probably only a few of them will be pathogenetically relevant, the sorting out of driver mutations from passenger mutations will be an arduous task, hopefully facilitated by the development of more sophisticated algorithms for data analysis (Yoshihara et al., 2015).”
BackgroundResultInfluentialFGFR-TACC gene fusions in human glioma
Lasorella, A., Sanson, M., & Iavarone, A. (2016) · Neuro-Oncology · doi:10.1093/neuonc/now240 · Cited by 144
Cheng, C., Zhou, Y., Li, H., Xiong, T., Li, S. C., Bi, Y., Kong, P., Wang, F., Cui, H., Li, Y., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.12.013 · Cited by 139
“To further assess the recurrence of fusion genes identified in ESCCs, we compared our data with the resource of fusion transcripts from Yoshihara’s report.(42) We did not find in ESCC recurrent in-frame protein kinase fusions such as FGFR1-TACC3 that was implicated in bladder urothelial carcinoma (BLCA), GBM, HNSCC, l…”
BackgroundResultInfluentialGene Fusions in Thyroid Cancer
Yakushina, V. D., Lerner, L. V., & Лавров, А. В. (2017) · Thyroid · doi:10.1089/thy.2017.0318 · Cited by 136
“Gene fusions have been recognized as important driver events in different types of cancer and are considered as potential diagnostic markers or therapeutic targets in anticancer treatment (15,16).”
Molecular and clinicopathologic features of gliomas harboring NTRK fusions
Torre, M., Vasudevaraja, V., Serrano, J., DeLorenzo, M., Malinowski, S. W., Blandin, A.-F., Pagès, M., Ligon, A. H., Dong, F., Meredith, D. M., et al. (2020) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-00980-z · Cited by 138
Lee, J., Li, C., Huang, H.-Y., Zhu, M.-J., Mariño‐Enríquez, A., Lee, C., Ou, W., Hornick, J. L., & Fletcher, J. A. (2016) · The Journal of Pathology · doi:10.1002/path.4836 · Cited by 134
“177/PanCanFusV2/) [16], and neither did Giacomini et al find RRBP1–ALK in 974 human cancers studied with DNA breakpoint or RNA breakpoint analyses [17].”
FGFR Fusions in Cancer: From Diagnostic Approaches to Therapeutic Intervention
Luca, A. D., Abate, R. E., Rachiglio, A. M., Maiello, M. R., Esposito, C., Schettino, C., Izzo, F., Nasti, G., & Normanno, N. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21186856 · Cited by 131
Thind, A. S., Monga, I., Thakur, P. K., Kumari, P., Dindhoria, K., Krzak, M., Ranson, M., & Ashford, B. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab259 · Cited by 132
Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud
Griffith, M., Walker, J., Spies, N. C., Ainscough, B. J., & Griffith, O. L. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004393 · Cited by 134
Wang, K., Russell, J. S., McDermott, J. D., Elvin, J. A., Khaira, D., Johnson, A., Jennings, T. A., Ali, S. M., Murray, M., Marshall, C. B., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-2568 · Cited by 123
Yakirevich, E., Resnick, M. B., Mangray, S., Wheeler, M., Jackson, C. L., Lombardo, K. A., Lee, J., Kim, K., Gill, A. J., Wang, K., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-3000 · Cited by 124
In vivo CRISPR/Cas9 targeting of fusion oncogenes for selective elimination of cancer cells
Martínez-Lage, M., Torres-Ruiz, R., Puig-Serra, P., Moreno-Gaona, P., Martín, M. C., Moya, F., Bustamante, O. Q., Garcı́a-Silva, S., Carcaboso, A. M., Petazzi, P., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18875-x · Cited by 118
Tian, L., Li, Y., Edmonson, M. N., Zhou, X., Newman, S., McLeod, C., Thrasher, A., Liu, Y., Tang, B., Rusch, M., et al. (2020) · Genome biology · doi:10.1186/s13059-020-02043-x · Cited by 113
Comprehensive analysis of PD-L1 expression in glioblastoma multiforme
Heiland, D. H., Haaker, G., Delev, D., Mercas, B., Masalha, W., Heynckes, S., Gaebelein, A., Pfeifer, D., Carro, M. S., Weyerbrock, A., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.15031 · Cited by 113
“Additionally, the latter have been recently shown to correlate with NF1 mutation [21, 24].”
BackgroundGenetic Heterogeneity of BRAF Fusion Kinases in Melanoma Affects Drug Responses
Botton, T., Talevich, E., Mishra, V. K., Zhang, T., Shain, A. H., Berquet, C., Gagnon, A., Judson, R. L., Ballotti, R., Ribas, A., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.09.009 · Cited by 113
The translational challenges of precision oncology
Pich, O., Bailey, C., Watkins, T. B. K., Zaccaria, S., Jamal‐Hanjani, M., & Swanton, C. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.04.002 · Cited by 116
Docking, R., Parker, J., Jädersten, M., Duns, G., Chang, L., Jiang, J., Pilsworth, J. A., Swanson, L., Chan, S. K., Chiu, R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22625-y · Cited by 109
Dellino, G. I., Palluzzi, F., Chiariello, A. M., Piccioni, R., Bianco, S., Furia, L., Conti, G. D., Bouwman, B. A. M., Melloni, G. E. M., Guido, D., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0421-z · Cited by 104
The convergent roles of the nuclear factor I transcription factors in development and cancer
Chen, K., Lim, J. W. C., Richards, L. J., & Bunt, J. (2017) · Cancer Letters · doi:10.1016/j.canlet.2017.09.015 · Cited by 102
TissGDB: tissue-specific gene database in cancer
Kim, P., Park, A., Han, G., Sun, H., Jia, P., & Zhao, Z. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx850 · Cited by 102
Erdem‐Eraslan, L., van den Bent, M. J., Hoogstrate, Y., Naz-Khan, H., Stubbs, A., van der Spek, P. J., Böttcher, R., Gao, Y., de Wit, M., Taal, W., et al. (2016) · Cancer Research · doi:10.1158/0008-5472.can-15-0776 · Cited by 98
“Female 14 (40) 17 (46) 13 (30) 4 (26) 3 (30) 6 (67)”
BackgroundTRK Inhibition: A New Tumor-Agnostic Treatment Strategy
Kummar, S., & Lassen, U. (2018) · Targeted Oncology · doi:10.1007/s11523-018-0590-1 · Cited by 98
“Tyrosine kinase genes involved in such somatic fusions include ABL, ALK, ROS1 and RET [17, 18].”
BackgroundPrimary and Metastatic Melanoma With NTRK Fusions
Lezcano, C. M., Shoushtari, A. N., Ariyan, C. E., Hollmann, T. J., & BUSAM, K. J. (2018) · The American Journal of Surgical Pathology · doi:10.1097/pas.0000000000001070 · Cited by 96
The landscape of chimeric RNAs in non-diseased tissues and cells
Singh, S., Qin, F., Kumar, S., Elfman, J., Lin, E., Pham, L.-P., Yang, A. X., & Li, H. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkz1223 · Cited by 99
A Systematic Analysis of Oncogenic Gene Fusions in Primary Colon Cancer
Kloosterman, W. P., van den Braak, R. R. J. C., Pieterse, M., van Roosmalen, M. J., Sieuwerts, A. M., Stangl, C., Brunekreef, R., Lalmahomed, Z. S., Ooft, S., van Galen, A., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-3563 · Cited by 94
“Finally, a variety of kinase fusions have been observed in CRC, such as those involving BRAF or receptor tyrosine kinases (10,11,15,16).”
BackgroundJung, S., Kim, M. S., Jung, C. K., Park, H.-C., Kim, S. Y., Liu, J., Bae, J. S., Lee, S. H., Kim, T., Lee, S. H., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.11922 · Cited by 86
“The earlier TCGA report on PTC and thyroid medullary carcinoma [27] genomes also showed lower frequencies of genetic alterations than those in other solid cancers [26, 28].”
BackgroundResultZhang, Y., Yang, L., Kucherlapati, M. H., Chen, F., Hadjipanayis, A. G., Pantazi, A., Bristow, C. A., Lee, E. A., Mahadeshwar, H. S., Tang, J., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.06.025 · Cited by 84
Lee, M., Lee, K., Yu, N., Jang, I., Choi, I., Kim, P., Jang, Y. E., Kim, B., Kim, S., Lee, B., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1083 · Cited by 80
Zhang, J., Fujiwara, Y., Yamamoto, S., & Shibuya, H. (2019) · Nature Communications · doi:10.1038/s41467-019-08676-2 · Cited by 88
A Multiplexed Amplicon Approach for Detecting Gene Fusions by Next-Generation Sequencing
Beadling, C., Wald, A. I., Warrick, A., Neff, T. L., Zhong, S., Nikiforov, Y. E., Corless, C. L., & Nikiforova, M. N. (2015) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2015.10.002 · Cited by 78
Exploiting non-canonical translation to identify new targets for T cell-based cancer immunotherapy
Laumont, C. M., & Perreault, C. (2017) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-017-2628-4 · Cited by 80
“Of course, not all cancer types would be able to generate such TSAs; however, they are worth exploring for microsatellite instable colorectal [139, 140] and blood cancers [141, 142] as well as cancer types presenting with a lot of structural variants such as melanoma [143], prostate cancer [144], bladder urothelial ca…”
HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncologyPreprint
Shrestha, R., Hodzic, E., Sauerwald, T., Dao, P., Wang, K., Yeung, J., Anderson, S. A., Vandin, F., Haffari, G., Collins, C. C., et al. (2017) · Genome Research · doi:10.1101/gr.221218.117 · Cited by 77
“We used the fusion prediction calls as reported in the TCGA Fusion gene Data Portal (Yoshihara et al. 2014).”
InfluentialValidation of a Targeted RNA Sequencing Assay for Kinase Fusion Detection in Solid Tumors
Reeser, J. W., Patacsil, D., Miya, J., Kautto, E. A., Lyon, E., Zhu, E. Y., Wing, M. R., Smith, A. M., Reeder, M., Samorodnitsky, E., et al. (2017) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2017.05.006 · Cited by 77
“Therefore, RNAseq data have been extensively used to identify chimeric transcripts in diverse solid tumors.(8,9) Examination of transcriptome data”
BackgroundMethodLiu, H., Murphy, C. J., Karreth, F. A., Emdal, K. B., White, F. M., Elemento, O., Toker, A., Wulf, G. M., & Cantley, L. C. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-17-0679 · Cited by 73
“The importance of FGFR pathway in tumorigenesis has increasingly been recognized (56,57), and FGFR fusions have been found in bladder, thyroid, prostate, lung cancer, glioblastoma and cholangiocarcinomas (Figure S7H) (33,45,54).”
Genome-wide colocalization of RNA–DNA interactions and fusion RNA pairs
Yan, Z., Huang, N., Wu, W., Chen, W., Jiang, Y., Chen, J., Huang, X., Wen, X., Xu, J., Jin, Q., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1819788116 · Cited by 75
“The recently developed mapping of RNA– genome interactions (MARGI) technology enabled identification of diverse caRNAs and the respective genomic interacting locations of each caRNA (6).”
BackgroundMolecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer
Latysheva, N. S., Oates, M. E., Maddox, L., Flock, T., Gough, J., Buljan, M., Weatheritt, R. J., & Babu, M. M. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.07.008 · Cited by 74
“If fusion transcripts are translated, the resulting fusion proteins have the potential to redirect cellular signaling pathways and act as principal oncogenic drivers (see Watson et al., 2013; Yoshihara et al., 2015).”
BackgroundInfluentialIdentification of a novel PARP14‐TFE3 gene fusion from 10‐year‐old FFPE tissue by RNA‐seq
Huang, W., Goldfischer, M., Babayeva, S., Mao, Y., Volyanskyy, K. Y., Dimitrova, N., Fallon, J. T., & Zhong, M. (2015) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22261 · Cited by 72
Jain, P., Fierst, T. M., Han, H. J., Smith, T. L., Vakil, A., Storm, P. B., Resnick, A. C., & Waanders, A. J. (2017) · Oncogene · doi:10.1038/onc.2017.276 · Cited by 72
“Interestingly, several adult cancers such as prostate cancer 10, 11 , breast cancer 12 , pancreatic cancer 13 and thyroid cancer 12 also harbor CRAF-fusions.”
Molecular characterization of the histiocytoses: Neoplasia of dendritic cells and macrophages
Durham, B. H. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.03.002 · Cited by 72
Knott, M. M. L., Hölting, T. L. B., Ohmura, S., Kirchner, T., Cidre‐Aranaz, F., & Grünewald, T. G. P. (2019) · Cancer and Metastasis Reviews · doi:10.1007/s10555-019-09839-9 · Cited by 72
“, byproducts of spontaneous genomic rearrangements, which accumulate progressively over time [5, 6].”
BackgroundThe CLIP1–LTK fusion is an oncogenic driver in non‐small‐cell lung cancer
Izumi, H., Matsumoto, S., Liu, J., Tanaka, K., Mori, S., Hayashi, K., Kumagai, S., Shibata, Y., Hayashida, T., Watanabe, K., et al. (2021) · Nature · doi:10.1038/s41586-021-04135-5 · Cited by 70
Glioblastoma: To Target the Tumor Cell or the Microenvironment?
Vleeschouwer, S. D., & Bergers, G. (2017) · Codon Publications eBooks · doi:10.15586/codon.glioblastoma.2017.ch16 · Cited by 73
“This abnormal genetic information leads to “druggable” protein modifications in the cell in conventional chemotherapy (2) or more recently in the logic of the emerging immunotherapies, to “neoantigens” (neoepitopes) in case of nonsynonymous mutations (3, 4).”
BackgroundMutation accumulation in cancer genes relates to nonoptimal outcome in chronic myeloid leukemia
Adnan Awad, S., Kankainen, M., Ojala, T., Koskenvesa, P., Eldfors, S., Ghimire, B., Kumar, A., Kytölä, S., Kamel, M. M., Heckman, C. A., et al. (2020) · Blood Advances · doi:10.1182/bloodadvances.2019000943 · Cited by 67
“Other potentially oncogenic hybrids included DSCC1-TAF2 identified in breast cancer and RSL24D1-RAB27A detected in lung adenocarcinoma.(54) The TMEM236-MRC1 hybrid was found in 2 cases, being the only recurrent hybrid other than BCR-ABL1.”
BackgroundThe genomic landscape of 8-oxodG reveals enrichment at specific inherently fragile promoters
Gorini, F., Scala, G., Di Palo, G., Dellino, G. I., Cocozza, S., Pelicci, P. G., Lania, L., Majello, B., & Amente, S. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa175 · Cited by 67
Subbiah, V., Berry, J., Roxas, M., Guha‐Thakurta, N., Subbiah, I. M., Ali, S. M., McMahon, C., Miller, V. A., Cascone, T., Pai, S., et al. (2015) · Lung Cancer · doi:10.1016/j.lungcan.2015.04.004 · Cited by 67
“Multiple activating RET fusions with distinct fusion partners have been described in cancer[4, 8], with the KIF5B-RET and CCDC6-RET fusions being most the common variants in NSCLC.”
BackgroundRelevance of Fusion Genes in Pediatric Cancers: Toward Precision Medicine
Dupain, C., Harttrampf, A. C., Urbinati, G., Geoerger, B., & Massaad-Massade, L. (2017) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2017.01.005 · Cited by 67
“Another example of fusions belonging to the first category are PAX3/7-FKHR fusions found in alveolar rhabdomyosarcomas due to the translocation t(2;13)(q35;q14) or, less commonly, t(1;13)(p36;p14), leading to PAX3-FOXO1 (55%–70%) or PAX7FOXO1 (10%–22%) fusion genes, respectively.”
BackgroundInfluentialFusion Genes and RNAs in Cancer Development
Taniue, K., & Akimitsu, N. (2021) · Non-Coding RNA · doi:10.3390/ncrna7010010 · Cited by 71
“Many gene fusions are random events caused by genetic instability or abnormal splicing machinery [39,40].”
BackgroundInfluentialPicco, G., Petti, C., Centonze, A., Torchiaro, E., Crisafulli, G., Novara, L., Acquaviva, A., Bardelli, A., & Médico, E. (2017) · EMBO Molecular Medicine · doi:10.15252/emmm.201606773 · Cited by 62
“Cross-check with an available pan-cancer database of fusion transcripts in TCGA samples (http://www.tumorfusions.org; Yoshihara et al , 2015) revealed that no additional RSPO3 fusions were detected in the 450-sample TCGA dataset used for our analysis.”
Identification of recurrent fusion genes across multiple cancer types
Yu, Y., Liu, P., Nelson, J. B., Hamilton, R. L., Bhargava, R., Michalopoulos, G. K., Chen, Q., Zhang, J., Ma, D., Pennathur, A., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-38550-6 · Cited by 63
Novel therapeutic strategy for cervical cancer harboring FGFR3-TACC3 fusions
Tamura, R., Yoshihara, K., Saito, T., Ishimura, R., Martínez-Ledesma, E., Hu, X., Ishiguro, T., Mori, Y., Yamawaki, K., Suda, K., et al. (2018) · Oncogenesis · doi:10.1038/s41389-017-0018-2 · Cited by 60
Self-citationCroce, S., Lesluyes, T., Delespaul, L., Bonhomme, B., Pérot, G., Velasco, V., Mayeur, L., Rebier, F., Rejeb, H. B., Guyon, F., et al. (2018) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22694 · Cited by 57
Tang, R., Chen, W., He, R., Zeng, J., Liang, L., Li, S., Ma, J., Luo, D., & Chen, G. (2017) · Oncotarget · doi:10.18632/oncotarget.17098 · Cited by 56
Challenges and best practices in omics benchmarking
Brooks, T. G., Lahens, N. F., Mrčela, A., & Grant, G. R. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-023-00679-6 · Cited by 58
“This sample comprises a combination of ten human cancer cell lines and was created in 2004 for use in the reference channel for two-colour microarrays 140 .”
Condensates induced by transcription inhibition localize active chromatin to nucleoli
Yasuhara, T., Xing, Y., Bauer, N. C., Lee, L., Dong, R., Yadav, T., Soberman, R. J., Rivera, M. N., & Zou, L. (2022) · Molecular Cell · doi:10.1016/j.molcel.2022.05.010 · Cited by 52
Gene Fusion in Malignant Glioma: An Emerging Target for Next-Generation Personalized Treatment
Xu, T., Wang, H., Huang, X., Li, W., Huang, Q., Yan, Y., & Chen, J. (2018) · Translational Oncology · doi:10.1016/j.tranon.2018.02.020 · Cited by 56
“Conclusion and Perspectives Malignant gliomas are characterized by extensive genomic instability [89], while most of them are associated with a corresponding increase in fusion transcript frequency [8,90].”
BackgroundInfluentialFusion genes: A promising tool combating against cancer
Dai, X., Theobard, R., Cheng, H., Xing, M., & Zhang, J. (2018) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2017.12.003 · Cited by 53
The oncogenic fusion landscape in pediatric CNS neoplasms
Roosen, M. M., Odé, Z., Bunt, J., & Kool, M. (2022) · Acta Neuropathologica · doi:10.1007/s00401-022-02405-8 · Cited by 53
Guo, T. W., Gaykalova, D. A., Considine, M., Wheelan, S. J., Pallavajjala, A., Bishop, J. A., Westra, W. H., Ideker, T., Koch, W. M., Khan, Z. H., et al. (2016) · International Journal of Cancer · doi:10.1002/ijc.30081 · Cited by 52
“To date, TCGA has been the first study to report gene fusions present in HPV-related head and neck cancer.(10,25) To expand on this study, we performed a comprehensive analysis of gene fusions in a larger independent cohort of HPVpositive OPSCC tumors with additional biologic validation.”
BackgroundMethodVeeraraghavan, J., Ma, J., Hu, Y., & Wang, X.-S. (2016) · Breast Cancer Research and Treatment · doi:10.1007/s10549-016-3876-y · Cited by 51
“A considerable diversity in the incidence of gene fusions has been observed across different tumor types, with breast cancer falling more toward the higher end of this spectrum [40].”
Recurrent TRIO Fusion in Nontranslocation–Related Sarcomas
Delespaul, L., Lesluyes, T., Pérot, G., Brulard, C., Lartigue, L., Baud, J., Lagarde, P., Guellec, S. L., Neuville, A., Terrier, P., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-0290 · Cited by 50
“Moreover, in Yoshihara and colleagues' study (40), chimeric RNAseq data of 4,366 tumor samples have been submitted to fusion detection, and TRIO fusion transcripts have not been detected in the whole cohort of various tumors (excluding sarcomas).”
BackgroundMaguire, S. L., Peck, B., Wai, P. T., Campbell, J., Barker, H. E., Gulati, A., Daley, F. M., Vyse, S., Huang, P. H., Lord, C. J., et al. (2016) · The Journal of Pathology · doi:10.1002/path.4778 · Cited by 49
“An in-frame HRAS fusion gene was identified in a head and neck primary tumour (RNH1–HRAS) that leads to increased levels of HRAS expression [66]; however, no additional HRAS fusion genes were detected in primary breast cancers.”
BackgroundFluorescence in situ hybridization in surgical pathology: principles and applications
Liang Cheng, C., Zhang, S., Wang, L., MacLennan, G. T., & Davidson, D. D. (2017) · The Journal of Pathology Clinical Research · doi:10.1002/cjp2.64 · Cited by 52
Recurrent EP300-BCOR Fusions in Pediatric Gliomas With Distinct Clinicopathologic Features
Torre, M., Meredith, D. M., Dubuc, A. M., Solomon, D. A., Perry, A., Vasudevaraja, V., Serrano, J., Snuderl, M., Ligon, K. L., & Alexandrescu, S. (2019) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlz011 · Cited by 50
Glioblastomas harboring gene fusions detected by next-generation sequencing
Woo, H. Y., Na, K., Yoo, J., Chang, J. H., Park, Y. N., Shim, H. S., & Kim, S. H. (2020) · Brain Tumor Pathology · doi:10.1007/s10014-020-00377-9 · Cited by 50
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
