The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis
Open accessAbstract
Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets. We have utilized WGCNA to identify 11 coregulated gene clusters across 2342 breast cancer samples from 13 microarray-based gene expression studies. A number of these transcriptional modules were found to be correlated to clinicopathological variables (e.g. tumor grade), survival endpoints for breast cancer as a whole (disease-free survival, distant disease-free survival and overall survival) and also its molecular subtypes (luminal A, luminal B, HER2+ and basal-like). Examples of findings arising from this work include the identification of a cluster of proliferation-related genes that when upregulated correlated to increased tumor grade and were associated with poor survival in general. The prognostic potential of novel genes, for example, ubiquitin-conjugating enzyme E2S (UBE2S) within this group was confirmed in an independent data set. In addition, gene clusters were also associated with survival for breast cancer molecular subtypes including a cluster of genes that was found to correlate with prognosis exclusively for basal-like breast cancer. The upregulation of several single genes within this coexpression cluster, for example, the potassium channel, subfamily K, member 5 (KCNK5) was associated with poor outcome for the basal-like molecular subtype. We have developed an online database to allow user-friendly access to the coexpression patterns and the survival analysis outputs uncovered in this study (available at http://glados.ucd.ie/Coexpression/).
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
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Molecular portraits of human breast tumours
Perou, C. M., Sørlie, T., Eisen, M. B., van de Rijn, M., Jeffrey, S. S., Rees, C. A., Pollack, J. R., Ross, D. T., Johnsen, H., Akslen, L. A., et al. (2000) · Nature · doi:10.1038/35021093 · Cited by 16,261
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
Exploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A. (2003) · Biostatistics · doi:10.1093/biostatistics/4.2.249 · Cited by 10,603
Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658
A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer
Paik, S., Shak, S., Tang, G., Kim, C., Baker, J., Cronin, M., Baehner, F. L., Walker, M. G., Watson, D., Park, T., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa041588 · Cited by 6,277
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., et al. (2012) · Nature · doi:10.1038/nature10983 · Cited by 6,097
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684
Repeated observation of breast tumor subtypes in independent gene expression data sets
Sørlie, T., Tibshirani, R., Parker, J., Hastie, T., Marron, J. S., Nobel, A., Deng, S., Johnsen, H., Pesich, R., Geisler, S., et al. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0932692100 · Cited by 5,429
Cited by
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Ping, L., Zhou, M., Yin, L., Higginbotham, L. A., Guajardo, A., White, B., Troncoso, J. C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0815-6 · Cited by 1,001
Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups
Rueda, O. M., Sammut, S.-J., Seoane, J. A., Chin, S.-F., Caswell-Jin, J. L., Callari, M., Batra, R., Pereira, B., Bruna, A., Ali, H. R., et al. (2019) · Nature · doi:10.1038/s41586-019-1007-8 · Cited by 417
Kogelman, L. J. A., Cirera, S., Zhernakova, D. V., Fredholm, M., Franke, L., & Kadarmideen, H. N. (2014) · BMC Medical Genomics · doi:10.1186/1755-8794-7-57 · Cited by 106
Oncosis and apoptosis induction by activation of an overexpressed ion channel in breast cancer cells
Peters, A. A., Jamaludin, S. Y. N., Yapa, K. T. D. S., Chalmers, S., Wiegmans, A. P., Lim, H. F., Milevskiy, M. J. G., Azimi, I., Davis, F. M., Northwood, K. S., et al. (2017) · Oncogene · doi:10.1038/onc.2017.234 · Cited by 85
Metadata
- Authors
- Clarke, C., Madden, S. F., Doolan, P., Aherne, S. T., Joyce, H., O’Driscoll, L., Gallagher, W. M., Hennessy, B. T., Moriarty, M., Crown, J., Kennedy, S., & Clynes, M.
- Venue
- Carcinogenesis
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-06-05
- Volume
- 34
- Issue
- 10
- Pages
- 2300-2308
- ISSN
- 0143-3334 (ISSN-L)
- 1460-2180
- OpenAlex
- W2111758831
- Cited by
- 849
- References
- 52
- FWCI
- 5.69
- 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: Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis. https://app.cochat.ai/papers/10.1093/carcin/bgt208
- The paper
- Clarke, C., Madden, S. F., Doolan, P., Aherne, S. T., Joyce, H., O’Driscoll, L., Gallagher, W. M., Hennessy, B. T., Moriarty, M., Crown, J., Kennedy, S., & Clynes, M. (2013). Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis. Carcinogenesis. https://doi.org/10.1093/carcin/bgt208
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.
