title: Stem cell-ness: a "magic marker" for cancer.
abstract: Transcriptional profiling of patient tumors is a much-heralded advancement in cancer therapy, as it provides the opportunity to identify patients who would benefit from more or less aggressive therapy and thus allows the development of individualized treatment. However, translation of this promise into patient benefit has proven challenging. In this issue of the JCI, Glinsky and colleagues used human and murine models to identify a potential stem cell mRNA signature, based on the hypothesis that tumors with stem cell-like characteristics are likely to have a poor prognosis. Remarkably, an 11-gene "expression signature" associated with "stem cell-ness" separated patients with different cancers into good- and poor-prognosis groups. Such a "magic marker" would, if validated, have a major impact on patient care. However, there remain challenges incumbent with creating and validating such signatures.
authors.affiliation: Department of Molecular Therapeutics, University of Texas M.D. Anderson Cancer Center, Houston, Texas 77030, USA.
authors.forename: John P
authors.initials: JP
authors.lastname: Lahad
authors.forename: Gordon B
authors.initials: GB
authors.lastname: Mills
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Coombes
mesh_terms: D000818:Animals; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D004195:Disease Models, Animal; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D051379:Mice; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000628:therapy; D014411:Neoplastic Stem Cells / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D012334:RNA, Neoplasm / Q000235:genetics* / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor; D012334:RNA, Neoplasm