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articleTop 10% cited

X-Tile

Clinical Cancer Research · 2004 · Vol. 10(21) · pp. 7252–7259

Abstract

The ability to parse tumors into subsets based on biomarker expression has many clinical applications; however, there is no global way to visualize the best cut-points for creating such divisions. We have developed a graphical method, the X-tile plot that illustrates the presence of substantial tumor subpopulations and shows the robustness of the relationship between a biomarker and outcome by construction of a two dimensional projection of every possible subpopulation. We validate X-tile plots by examining the expression of several established prognostic markers (human epidermal growth factor receptor-2, estrogen receptor, p53 expression, patient age, tumor size, and node number) in cohorts of breast cancer patients and show how X-tile plots of each marker predict population subsets rooted in the known biology of their expression.

Gene expression and cancer classificationHER2/EGFR in Cancer ResearchEstrogen and related hormone effectsTileBiomarkerEstrogen receptorBiologyPopulationEpidermal growth factor receptorBreast cancerRobustness (evolution)CancerOncology

MeSH terms

AdultAge FactorsAgedAged, 80 and overBreast NeoplasmsFemaleHumansImmunohistochemistryLymph NodesMiddle AgedPrognosisReceptors, EstrogenSoftwareBiomarkers, TumorCohort Studies
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References
Tissue Microarrays for Rapid Linking of Molecular Changes to Clinical Endpoints
American Journal Of Pathology · 2001 · 569 citations
Dangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors
JNCI Journal of the National Cancer Institute · 1994 · 1,124 citations
Cluster analysis and display of genome-wide expression patterns
Proceedings of the National Academy of Sciences · 1998 · 16,353 citations
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