The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Kinase fusions are frequent in Spitz tumours and spitzoid melanomas
Open accessAbstract
Spitzoid neoplasms are a group of melanocytic tumours with distinctive histopathological features. They include benign tumours (Spitz naevi), malignant tumours (spitzoid melanomas) and tumours with borderline histopathological features and uncertain clinical outcome (atypical Spitz tumours). Their genetic underpinnings are poorly understood, and alterations in common melanoma-associated oncogenes are typically absent. Here we show that spitzoid neoplasms harbour kinase fusions of ROS1 (17%), NTRK1 (16%), ALK (10%), BRAF (5%) and RET (3%) in a mutually exclusive pattern. The chimeric proteins are constitutively active, stimulate oncogenic signalling pathways, are tumourigenic and are found in the entire biologic spectrum of spitzoid neoplasms, including 55% of Spitz naevi, 56% of atypical Spitz tumours and 39% of spitzoid melanomas. Kinase inhibitors suppress the oncogenic signalling of the fusion proteins in vitro. In summary, kinase fusions account for the majority of oncogenic aberrations in spitzoid neoplasms and may serve as therapeutic targets for metastatic spitzoid melanomas. Spitzoid neoplasms constitute a spectrum of melanocytic tumours, characterized by distinct clinical, pathological and genetic features. Here, Wiesner et al. show that kinase fusions represent the majority of oncogenic aberrations in spitzoid neoplasms and may serve as therapeutic targets for metastatic spitzoid melanoma.
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.
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
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
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863
Improved survival with vemurafenib in melanoma with BRAF V600E mutation
Chapman, P. B., Hauschild, A., Robert, C., Haanen, J. B., Ascierto, P., Larkin, J., Dummer, R., Garbe, C., Testori, A., Maio, M., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1103782 · Cited by 7,720
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
Druker, B. J., Talpaz, M., Resta, D. J., Peng, B., Buchdunger, E., Ford, J. M., Lydon, N. B., Kantarjian, H., Capdeville, R., Ohno-Jones, S., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200104053441401 · Cited by 5,243
Anaplastic Lymphoma Kinase Inhibition in Non–Small-Cell Lung Cancer
Kwak, E. L., Bang, Y.-J., Camidge, D. R., Shaw, A. T., Solomon, B., Maki, R. G., Ou, S.-H. I., Dezube, B. J., Jänne, P. A., Costa, D. B., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1006448 · Cited by 4,446
Global Survey of Phosphotyrosine Signaling Identifies Oncogenic Kinases in Lung Cancer
Rikova, K., Guo, A., Zeng, Q., Possemato, A., Yu, J., Haack, H., Nardone, J., Lee, K., Reeves, C., Li, Y., et al. (2007) · Cell · doi:10.1016/j.cell.2007.11.025 · Cited by 2,317
COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer
Forbes, S. A., Bindal, N., Bamford, S., Cole, C., Kok, C. Y., Beare, D., Jia, M., Shepherd, R., Leung, K., Menzies, A., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq929 · Cited by 2,278
ROS1 Rearrangements Define a Unique Molecular Class of Lung Cancers
Bergethon, K., Shaw, A. T., Ignatius Ou, S.-H., Katayama, R., Lovly, C. M., McDonald, N. T., Massion, P. P., Siwak-Tapp, C., Gonzalez, A., Fang, R., et al. (2012) · Journal of Clinical Oncology · doi:10.1200/jco.2011.35.6345 · Cited by 1,555
Cited by
Efficacy of Larotrectinib in TRK Fusion–Positive Cancers in Adults and Children
Drilon, A., Laetsch, T. W., Kummar, S., DuBois, S. G., Lassen, U. N., Demetri, G. D., Nathenson, M., Doebele, R. C., Farago, A. F., Pappo, A. S., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1714448 · Cited by 2,824
Mechanisms of receptor tyrosine kinase activation in cancer
Du, Z., & Lovly, C. M. (2018) · Molecular Cancer · doi:10.1186/s12943-018-0782-4 · Cited by 1,066
Long, G. V., Swetter, S. M., Menzies, A. M., Gershenwald, J. E., & Scolyer, R. A. (2023) · The Lancet · doi:10.1016/s0140-6736(23)00821-8 · Cited by 746
Acquired Resistance to the TRK Inhibitor Entrectinib in Colorectal Cancer
Russo, M., Misale, S., Wei, G., Siravegna, G., Crisafulli, G., Lazzari, L., Corti, G., Rospo, G., Novara, L., Mussolin, B., et al. (2016) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-0940 · Cited by 308
Targeting TRK family proteins in cancer
Khotskaya, Y. B., Holla, V. R., Farago, A. F., Mills Shaw, K. R., Meric-Bernstam, F., & Hong, D. S. (2017) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2017.02.006 · Cited by 292
Metadata
- Authors
- Wiesner, T., He, J., Yelensky, R., Esteve-Puig, R., Botton, T., Yeh, I., Lipson, D., Otto, G., Brennan, K., Murali, R., Garrido, M., Miller, V. A., Ross, J. S., Berger, M. F., Sparatta, A., Palmedo, G., Cerroni, L., Busam, K. J., Kutzner, H., Cronin, M. T., Stephens, P. J., & Bastian, B. C.
- Venue
- Nature Communications
- Published
- 2014-01-20
- Volume
- 5
- Issue
- 1
- Pages
- 3116-3116
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W1979188008
- Cited by
- 649
- References
- 41
- FWCI
- 25.28
- Type
- journal article
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Kinase fusions are frequent in Spitz tumours and spitzoid melanomas. https://app.cochat.ai/papers/10.1038/ncomms4116
- The paper
- Wiesner, T., He, J., Yelensky, R., Esteve-Puig, R., Botton, T., Yeh, I., Lipson, D., Otto, G., Brennan, K., Murali, R., Garrido, M., Miller, V. A., Ross, J. S., Berger, M. F., Sparatta, A., Palmedo, G., Cerroni, L., Busam, K. J., Kutzner, H., . . . Bastian, B. C. (2014). Kinase fusions are frequent in Spitz tumours and spitzoid melanomas. Nature Communications. https://doi.org/10.1038/ncomms4116
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
