X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization.
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.
Camp
Robert L
RL
Department of Pathology, Yale University, School of Medicine, New Haven, Connecticut 06520, USA. robert.camp@yale.edu
Dolled-Filhart
Marisa
M
Rimm
David L
DL
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000175:diagnosis / Q000378:metabolism / Q000473:pathology; D015331:Cohort Studies; D019295:Computational Biology / Q000379:methods*; D066246:ErbB Receptors / Q000096:biosynthesis; D005260:Female; D006801:Humans; D007150:Immunohistochemistry; D008198:Lymph Nodes / Q000473:pathology; D008875:Middle Aged; D011379:Prognosis; D011960:Receptors, Estrogen / Q000096:biosynthesis; D012984:Software; D016159:Tumor Suppressor Protein p53 / Q000096:biosynthesis
D014408:Biomarkers, Tumor; D011960:Receptors, Estrogen; D016159:Tumor Suppressor Protein p53; D066246:ErbB Receptors