The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets
Open accessAbstract
Triple negative breast cancers (TNBCs) have a relatively poor prognosis and cannot be effectively treated with current targeted therapies. We searched for genes that have the potential to be therapeutic targets by identifying genes consistently overexpressed when amplified. Fifty-six TNBCs were subjected to high-resolution microarray-based comparative genomic hybridization (aCGH), of which 24 were subjected to genome-wide gene expression analysis. TNBCs were genetically heterogeneous; no individual focal amplification was present at high frequency, although 78.6% of TNBCs harboured at least one focal amplification. Integration of aCGH and expression data revealed 40 genes significantly overexpressed when amplified, including the known oncogenes and potential therapeutic targets, FGFR2 (10q26.3), BUB3 (10q26.3), RAB20 (13q34), PKN1 (19p13.12) and NOTCH3 (19p13.12). We identified two TNBC cell lines with FGFR2 amplification, which both had constitutive activation of FGFR2. Amplified cell lines were highly sensitive to FGFR inhibitor PD173074, and to RNAi silencing of FGFR2. Treatment with PD173074 induced apoptosis resulting partly from inhibition of PI3K-AKT signalling. Independent validation using publicly available aCGH data sets revealed FGFR2 gene was amplified in 4% (6/165) of TNBC, but not in other subtypes (0/214, P=0.0065). Our analysis demonstrates that TNBCs are heterogeneous tumours with amplifications of FGFR2 in a subgroup of tumours.
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
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Chou, T.-C., & Talalay, P. (1984) · Advances in Enzyme Regulation · doi:10.1016/0065-2571(84)90007-4 · Cited by 7,178
Triple-negative breast cancer: clinical features and patterns of recurrence
Dent, R., Trudeau, M., Pritchard, K. I., Hanna, W. M., Kahn, H. K., Sawka, C. A., Lickley, L. A., Rawlinson, E., Sun, P., & Narod, S. A. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-3045 · Cited by 5,091
Patterns of somatic mutation in human cancer genomes
Greenman, C., Stephens, P., Smith, R., Dalgliesh, G. L., Hunter, C., Bignell, G., Davies, H., Teague, J., Butler, A., Stevens, C., et al. (2007) · Nature · doi:10.1038/nature05610 · Cited by 3,080
Genome-wide association study identifies novel breast cancer susceptibility loci
Easton, D. F., Pooley, K. A., Dunning, A. M., Pharoah, P. D. P., Thompson, D., Ballinger, D. G., Struewing, J. P., Morrison, J., Field, H., Luben, R., et al. (2007) · Nature · doi:10.1038/nature05887 · Cited by 2,319
The Triple Negative Paradox: Primary Tumor Chemosensitivity of Breast Cancer Subtypes
Carey, L. A., Dees, E. C., Sawyer, L., Gatti, L., Moore, D. T., Collichio, F., Ollila, D. W., Sartor, C. I., Graham, M. L., & Perou, C. M. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-1109 · Cited by 2,087
Hallmarks of 'BRCAness' in sporadic cancers
Turner, N., Tutt, A., & Ashworth, A. (2004) · Nature Reviews Cancer · doi:10.1038/nrc1457 · Cited by 1,657
Self-citationThe molecular portraits of breast tumors are conserved across microarray platforms
Hu, Z., Fan, C., Oh, D. S., Marron, J., He, X., Qaqish, B. F., Livasy, C., Carey, L. A., Reynolds, E., Dressler, L., et al. (2006) · BMC Genomics · doi:10.1186/1471-2164-7-96 · Cited by 1,491
Genomic and transcriptional aberrations linked to breast cancer pathophysiologies
Chin, K., DeVries, S., Fridlyand, J., Spellman, P. T., Roydasgupta, R., Kuo, W.-L., Lapuk, A., Neve, R. M., Qian, Z., Ryder, T., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.10.009 · Cited by 1,317
Maira, S.-M., Stauffer, F., Brueggen, J., Furet, P., Schnell, C., Fritsch, C., Brachmann, S., Chène, P., De Pover, A., Schoemaker, K., et al. (2008) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-08-0017 · Cited by 1,134
Cited by
The Fibroblast Growth Factor signaling pathway
Ornitz, D. M., & Itoh, N. (2015) · WIREs Developmental Biology · doi:10.1002/wdev.176 · Cited by 2,050
Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes
Gao, R., Bai, S., Henderson, Y. C., Lin, Y., Schalck, A., Yan, Y., Kumar, T., Hu, M., Sei, E., Davis, A., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-00795-2 · Cited by 917
Molecular alterations in triple-negative breast cancer—the road to new treatment strategies
Denkert, C., Liedtke, C., Tutt, A., & von Minckwitz, G. (2017) · The Lancet · doi:10.1016/s0140-6736(16)32454-0 · Cited by 872
FGFR1 Amplification Drives Endocrine Therapy Resistance and Is a Therapeutic Target in Breast Cancer
Turner, N., Pearson, A., Sharpe, R., Lambros, M., Geyer, F., Lopez-Garcia, M. A., Natrajan, R., Marchio, C., Iorns, E., Mackay, A., et al. (2010) · Cancer Research · doi:10.1158/0008-5472.can-09-3746 · Cited by 732
Self-citationPathogenesis of Triple-Negative Breast Cancer
Derakhshan, F., & Reis-Filho, J. S. (2022) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-042420-093238 · Cited by 714
Self-citation
Metadata
- Authors
- Turner, N., Lambros, M. B., Horlings, H. M., Pearson, A., Sharpe, R., Natrajan, R., Geyer, F. C., van Kouwenhove, M., Kreike, B., Mackay, A., Ashworth, A., van de Vijver, M. J., & Reis-Filho, J. S.
- Venue
- Oncogene
- Published
- 2010-01-18
- Volume
- 29
- Issue
- 14
- Pages
- 2013-2023
- ISSN
- 0950-9232 (ISSN-L)
- 1476-5594
- OpenAlex
- W2023297465
- Cited by
- 416
- References
- 46
- FWCI
- 11.02
- Type
- journal article
- Language
- en
- Open access
- green
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: Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets. https://app.cochat.ai/papers/10.1038/onc.2009.489
- The paper
- Turner, N., Lambros, M. B., Horlings, H. M., Pearson, A., Sharpe, R., Natrajan, R., Geyer, F. C., van Kouwenhove, M., Kreike, B., Mackay, A., Ashworth, A., van de Vijver, M. J., & Reis-Filho, J. S. (2010). Integrative molecular profiling of triple negative breast cancers identifies amplicon drivers and potential therapeutic targets. Oncogene. https://doi.org/10.1038/onc.2009.489
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.