| Title | "Stemness" genomics law governs clinical behavior of human cancer: implications for decision making in disease management. | | Author(s) | Glinsky GV | | Institution | Translational & Functional Genomics Laboratory, Ordway Research Institute, Ordway Cancer Center, Center for Medical Science, 150 New Scotland Ave, Albany, NY 12208, USA. gglinsky@ordwayresearch.org | | Source | J Clin Oncol 2008 Jun 10; 26(17):2846-53. | | MeSH | Algorithms
Breast Neoplasms
Decision Support Techniques
Drug Resistance, Neoplasm
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Silencing
Genetic Screening
Genotype
Humans
Lung Neoplasms
Male
Models, Genetic
Neoplasms
Neoplastic Stem Cells
Ovarian Neoplasms
Patient Selection
Pharmacogenetics
Phenotype
Prostatic Neoplasms
Repressor Proteins
Reproducibility of Results
| | Abstract | One of the most significant accomplishments of translational oncogenomics is a realistic promise of efficient diagnostic tests that would facilitate implementation of the concept of individualized cancer therapies. Recent discovery of the BMI1 pathway rule indicates that gene expression signatures (GESs) associated with the "stemness" state of a cell might be informative as molecular predictors of cancer therapy outcome. We illustrate a potential clinical utility of this concept using GESs derived from genomic analysis of embryonic stem cells (ESCs) during transition from self-renewing, pluripotent state to differentiated phenotypes. Signatures of multiple stemness pathways (signatures of BMI1, Nanog/Sox2/Oct4, EED, and Suz12 pathways; transposon exclusion zones and ESC pattern 3 signatures; signatures of Polycomb-bound and bivalent chromatin domain transcription factors) seem informative in stratification of cancer patients into low- and high-intensity treatment groups on the basis of prediction of the long-term therapy outcome. A stemness cancer therapy outcome predictor (CTOP) algorithm combining scores of nine stemness signatures outperforms individual signatures and demonstrates a superior prognostic accuracy in retrospective supervised analysis of large cohorts of breast, prostate, lung, and ovarian cancer patients. Our analysis suggests that stemness genomics law governs clinical behavior of human malignancies and defines epigenetic boundaries of therapy-resistant and -sensitive tumors within distinct stemness/differentiation programs. One of the main conclusions of our analysis is that near-term progress in practical implementation of the concept of personalized cancer therapies would depend on timely delivery to practicing physicians of relevant scientific information regarding the outcome of prospective trials validating prognostic performance of CTOP tests in a clinical setting. | | Language | eng | | Pub Type(s) | Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review
| | PubMed ID | 18539963 |
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