title: Molecular staging for survival prediction of colorectal cancer patients.
abstract: OBJECTIVE
  The Dukes' staging system is the gold standard for predicting colorectal cancer prognosis; however, accurate classification of intermediate-stage cases is problematic. We hypothesized that molecular fingerprints could provide more accurate staging and potentially assist in directing adjuvant therapy.
  
  
  METHODS
  A 32,000 cDNA microarray was used to evaluate 78 human colon cancer specimens, and these results were correlated with survival. Molecular classifiers were produced to predict outcome.
  
  
  RESULTS
  Molecular staging, based on 43 core genes, was 90% accurate (93% sensitivity, 84% specificity) in predicting 36-month overall survival in 78 patients. This result was significantly better than Dukes' staging (P = .03878), discriminated patients into significantly different groups by survival time (P < .001, log-rank test), and was significantly different from chance (P < .001, 1,000 permutations). Furthermore, the classifier was able to discriminate a survival difference in an independent test set from Denmark. Molecular staging identifies patient prognosis (as represented by 36-month survival) more accurately than the traditional clinical staging, particularly for intermediate Dukes' stage B and C patients. The classifier was based on a core set of 43 genes, including osteopontin and neuregulin, which have biologic significance for this disease.
  
  
  CONCLUSIONS
  These data support further evaluation of molecular staging to discriminate good from poor prognosis patients, with the potential to direct adjuvant therapy.
authors.affiliation: Department of Surgery, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
authors.forename: Steven
authors.initials: S
authors.lastname: Eschrich
authors.forename: Ivana
authors.initials: I
authors.lastname: Yang
authors.forename: Greg
authors.initials: G
authors.lastname: Bloom
authors.forename: Ka Yin
authors.initials: KY
authors.lastname: Kwong
authors.forename: David
authors.initials: D
authors.lastname: Boulware
authors.forename: Alan
authors.initials: A
authors.lastname: Cantor
authors.forename: Domenico
authors.initials: D
authors.lastname: Coppola
authors.forename: Mogens
authors.initials: M
authors.lastname: Kruhøffer
authors.forename: Lauri
authors.initials: L
authors.lastname: Aaltonen
authors.forename: Torben F
authors.initials: TF
authors.lastname: Orntoft
authors.forename: John
authors.initials: J
authors.lastname: Quackenbush
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Yeatman
mesh_terms: D000328:Adult; D015331:Cohort Studies; D015179:Colorectal Neoplasms / Q000235:genetics* / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D003131:Combined Modality Therapy; D016172:DNA Fingerprinting; D018076:DNA, Complementary / Q000032:analysis*; D005260:Female; D016163:Genes, DCC; D049671:History, 18th Century; D006801:Humans; D008297:Male; D008875:Middle Aged; D008967:Molecular Biology; D009367:Neoplasm Staging / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D011336:Probability; D011379:Prognosis; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D016019:Survival Analysis; D025521:Tumor Suppressor Proteins / Q000235:genetics*
chemical_list: D018076:DNA, Complementary; D025521:Tumor Suppressor Proteins