The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Improving Melanoma Classification by Integrating Genetic and Morphologic Features
Open accessAbstract
BACKGROUND: In melanoma, morphology-based classification systems have not been able to provide relevant information for selecting treatments for patients whose tumors have metastasized. The recent identification of causative genetic alterations has revealed mutations in signaling pathways that offer targets for therapy. Identifying morphologic surrogates that can identify patients whose tumors express such alterations (or functionally equivalent alterations) would be clinically useful for therapy stratification and for retrospective analysis of clinical trial data. METHODOLOGY/PRINCIPAL FINDINGS: We defined and assessed a panel of histomorphologic measures and correlated them with the mutation status of the oncogenes BRAF and NRAS in a cohort of 302 archival tissues of primary cutaneous melanomas from an academic comprehensive cancer center. Melanomas with BRAF mutations showed distinct morphological features such as increased upward migration and nest formation of intraepidermal melanocytes, thickening of the involved epidermis, and sharper demarcation to the surrounding skin; and they had larger, rounder, and more pigmented tumor cells (all p-values below 0.0001). By contrast, melanomas with NRAS mutations could not be distinguished based on these morphological features. Using simple combinations of features, BRAF mutation status could be predicted with up to 90.8% accuracy in the entire cohort as well as within the categories of the current World Health Organization (WHO) classification. Among the variables routinely recorded in cancer registries, we identified age < 55 y as the single most predictive factor of BRAF mutation in our cohort. Using age < 55 y as a surrogate for BRAF mutation in an independent cohort of 4,785 patients of the Southern German Tumor Registry, we found a significant survival benefit (p < 0.0001) for patients who, based on their age, were predicted to have BRAF mutant melanomas in 69% of the cases. This group also showed a different pattern of metastasis, more frequently involving regional lymph nodes, compared to the patients predicted to have no BRAF mutation and who more frequently displayed satellite, in-transit metastasis, and visceral metastasis (p < 0.0001). CONCLUSIONS: Refined morphological classification of primary melanomas can be used to improve existing melanoma classifications by forming subgroups that are genetically more homogeneous and likely to differ in important clinical variables such as outcome and pattern of metastasis. We expect this information to improve classification and facilitate stratification for therapy as well as retrospective analysis of existing trial data.
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 Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
High frequency of BRAF mutations in nevi
Pollock, P. M., Harper, U. L., Hansen, K. S., Yudt, L. M., Stark, M., Robbins, C. M., Moses, T. Y., Hostetter, G., Wagner, U., Kakareka, J., et al. (2003) · Nature Genetics · doi:10.1038/ng1054 · Cited by 1,730
Garraway, L. A., Widlund, H. R., Rubin, M. A., Getz, G., Berger, A. J., Ramaswamy, S., Beroukhim, R., Milner, D. A., Granter, S. R., Du, J., et al. (2005) · Nature · doi:10.1038/nature03664 · Cited by 1,548
Determinants of BRAF Mutations in Primary Melanomas
Maldonado, J. L., Fridlyand, J., Patel, H., Jain, A. N., Busam, K., Kageshita, T., Ono, T., Albertson, D. G., Pinkel, D., & Bastian, B. C. (2003) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djg123 · Cited by 664 · cited 2×
“A strong association between patient age at diagnosis and BRAF mutation status has been reported previously by us and others [11,28,30,31].”
Self-citation
Cited by
A method for normalizing histology slides for quantitative analysis
Macenko, M., Niethammer, M., Marron, J. S., Borland, D., Woosley, J. T., Guan, X., Schmitt, C., & Thomas, N. E. (2009) · 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro · doi:10.1109/isbi.2009.5193250 · Cited by 1,482
Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma
Krauthammer, M., Kong, Y., Ha, B. H., Evans, P., Bacchiocchi, A., McCusker, J. P., Cheng, E., Davis, M. J., Goh, G., Choi, M., et al. (2012) · Nature Genetics · doi:10.1038/ng.2359 · Cited by 1,191
Kirkham, J. J., Dwan, K. M., Altman, D. G., Gamble, C., Dodd, S., Smyth, R., & Williamson, P. R. (2010) · BMJ · doi:10.1136/bmj.c365 · Cited by 1,133
Prognostic and Clinicopathologic Associations of Oncogenic BRAF in Metastatic Melanoma
Long, G. V., Menzies, A. M., Nagrial, A. M., Haydu, L. E., Hamilton, A. L., Mann, G. J., Hughes, T. M., Thompson, J. F., Scolyer, R. A., & Kefford, R. F. (2011) · Journal of Clinical Oncology · doi:10.1200/jco.2010.32.4327 · Cited by 1,042
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
Metadata
- Authors
- Viros, A., Fridlyand, J., Bauer, J., Lasithiotakis, K., Garbe, C., Pinkel, D., & Bastian, B. C.
- Venue
- PLoS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-06-03
- Volume
- 5
- Issue
- 6
- Pages
- e120
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- OpenAlex
- W2131819768
- Cited by
- 379
- References
- 6
- FWCI
- 11.17
- Type
- journal article
- Language
- en
- Open access
- gold
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: Improving Melanoma Classification by Integrating Genetic and Morphologic Features. https://app.cochat.ai/papers/10.1371/journal.pmed.0050120
- The paper
- Viros, A., Fridlyand, J., Bauer, J., Lasithiotakis, K., Garbe, C., Pinkel, D., & Bastian, B. C. (2008). Improving Melanoma Classification by Integrating Genetic and Morphologic Features. PLoS Medicine. https://doi.org/10.1371/journal.pmed.0050120
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.