The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients
Open accessAbstract
Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained (n = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com . We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B, MKI67, CCND2, CCND3, CCNDE2, as well as CDKN1A, and TK2. We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The top 23 differentially expressed genes in CIN-high cells (referred to as CIN signature) predicted distant-metastasis-free survival (DMFS) in a meta-analysis16 as well as a validation cohort17 of patients with breast cancer, irrespective of tumor subtype, grade, or lymph node status”
From Chromosomal instability drives metastasis through a cytosolic DNA response (2018) · cites this paper as [16]
Experimental — accuracy not yet measured
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
Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-4380-9_25 · Cited by 45,239
Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1958) · Journal of the American Statistical Association · doi:10.1080/01621459.1958.10501452 · Cited by 39,158
A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer
Paik, S., Shak, S., Tang, G., Kim, C., Baker, J. B., Cronin, M. T., Baehner, F. L., Walker, M. G., Watson, D., Park, T., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa041588 · Cited by 6,321
affy—analysis of Affymetrix GeneChip data at the probe level
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg405 · Cited by 5,221
Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer
Wang, Y., Klijn, J. G. M., Zhang, Y., Sieuwerts, A. M., Look, M. P., Yang, F., Talantov, D., Timmermans, M. A. M., Gelder, M. E. M., Yu, J. X., et al. (2005) · The Lancet · doi:10.1016/s0140-6736(05)17947-1 · Cited by 2,831
Paik, S., Tang, G., Shak, S., Kim, C., Baker, J. B., Kim, W., Cronin, M. T., Baehner, F. L., Watson, D., Bryant, J., et al. (2006) · Journal of Clinical Oncology · doi:10.1200/jco.2005.04.7985 · Cited by 2,597
Harris, L. N., Fritsche, H. A., Mennel, R. G., Norton, L., Ravdin, P. M., Taube, S. E., Somerfield, M. R., Hayes, D. F., & Bast, R. C. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2007.14.2364 · Cited by 2,234
MAQC Consortium, Shi, L., Shi, L., Reid, L. H., Jones, W. D., Shippy, R., Warrington, J. A., Baker, S. C., Collins, P. J., de Longueville, F., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1239 · Cited by 2,126
Self-citationSotiriou, C. P., Wirapati, P., Loi, S., Harris, A. L., Fox, S., Smeds, J., Nordgren, H., Farmer, P. J., Praz, V., Haibe‐Kains, B., et al. (2006) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djj052 · Cited by 2,050
Genes that mediate breast cancer metastasis to the brain
Bos, P. D., Zhang, X. H.-F., Nadal, C., Shu, W., Gomis, R. R., Nguyen, D. X., Minn, A. J., van de Vijver, M. J., Gerald, W. L., Foekens, J. A., et al. (2009) · Nature · doi:10.1038/nature08021 · Cited by 1,863
Cited by
Sorted by citations
Items 1,001–1,007 of 1,007
Lin, T., Qiu, Y., Peng, W., & Peng, L. (2020) · BioMed Research International · doi:10.1155/2020/2148253 · Cited by 31
Glucose-sensitive acetylation of Seryl tRNA synthetase regulates lipid synthesis in breast cancer
Zhao, J., Bai, H., Li, X., Yan, J., Zou, G., Wang, L., Li, X., Liu, Z., Xiang, R., Yang, X.-L., et al. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00714-0 · Cited by 27
The pro- and anti-tumor roles of mesenchymal stem cells toward BRCA1-IRIS-overexpressing TNBC cells
Ryan, D., Paul, B. T., Koziol, J., & ElShamy, W. M. (2019) · Breast Cancer Research · doi:10.1186/s13058-019-1131-2 · Cited by 25
Ranzani, M., Annunziato, S., Calabria, A., Brasca, S., Benedicenti, F., Gallina, P., Naldini, L., & Montini, E. (2014) · Molecular Therapy · doi:10.1038/mt.2014.174 · Cited by 17
Choi, E., Jeon, K., Lee, H., Mun, G., Kim, J., Shin, J., Kwon, Y., Na, Y., & Lee, Y. (2024) · Cancer Science · doi:10.1111/cas.16174 · Cited by 15
BAUERSCHMITZ, G., HÜCHEL, S., GALLWAS, J., & GRÜNDKER, C. (2023) · Cancer Genomics - Proteomics · doi:10.21873/cgp.20403 · Cited by 11
The exostosin glycosyltransferase 1/STAT3 axis is a driver of breast cancer aggressiveness
Solaimuthu, B., Khatib, A., Tanna, M., Karmi, A., Hayashi, A., Abu Rmaileh, A., Lichtenstein, M., Takoe, S., Jolly, M. K., & Shaul, Y. D. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2316733121 · Cited by 8
Metadata
- Authors
- Györffy, B., Lanczky, A., Eklund, A. C., Denkert, C., Budczies, J., Li, Q., & Szallasi, Z.
- Affiliations
- Technical University of Denmark (DK)
- Charité – Universitätsmedizin Berlin (DE)
- Venue
- Breast Cancer Research and Treatment
- Published
- 2009-12-18
- Volume
- 123
- Issue
- 3
- Pages
- 725-731
- ISSN
- 0167-6806 (ISSN-L)
- 1573-7217
- OpenAlex
- W2085934079
- Cited by
- 4,169
- References
- 34
- Citations by year
- 2026: 52 · 2025: 53 · 2024: 119 · 2023: 203 · 2022: 723 · 2021: 1329 · 2020: 434 · 2019: 306 · 2018: 241 · 2017: 192 · 2016: 187 · 2015: 120 · 2014: 100 · 2013: 59 · 2012: 26
- FWCI
- 5.15
- Type
- journal article
- Language
- en
- Open access
- green
- hal.science
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Breast Cancer Research and Treatment (publishedVersion)
- PubMed (publishedVersion)
- Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
- Semmelweis University Repository (Semmelweis University) (submittedVersion)
- Trinity's Access to Research Output (TARA) (Trinity College Dublin) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- breast cancer prognosis, prognostic gene expression, gene expression microarrays, relapse-free survival, overall survival, distant metastasis, estrogen receptor status, endocrine therapy, TOP2A, TOP2B, MKI67, cell cycle genes, p21, thymidine kinase 2, biomarker validation
- MeSH terms
- Adult, Aged, Breast Neoplasms, Computer Graphics, Female, Genetic Markers, Humans, Lymphatic Metastasis, Middle Aged, Neoplasm Staging, Online Systems, Predictive Value of Tests, Prognosis, Receptors, Estrogen, Time Factors, Biomarkers, Tumor, Reproducibility of Results, Gene Expression Regulation, Neoplastic, Disease-Free Survival, Internet, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Kaplan-Meier Estimate
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
