title: A clinical-biological risk stratification model for resected gastric cancer: prognostic impact of Her2, Fhit, and APC expression status.
abstract: BACKGROUND
  To obtain a prognostic stratification model for resected gastric cancer patients.
  
  
  METHODS
  Clinicopathological and molecular data (expression of Cdx2, Apc, β-catenin, E-cadherin, Fhit, p53, and human epidermal growth factor receptor-2 (Her2); HER2 and TOPO2A gene copy number; PIK3CA mutations; microsatellite instability) were correlated to cancer-specific/overall survival (CSS/OS) using a Cox model. Individual patient probability (IPP) was estimated by logistic equation. A continuous score to identify risk-classes was derived according to the model ratios.
  
  
  RESULTS
  Two-hundred eight patients were studied (median follow-up 20 months). At multivariate analysis, sex, stage, margins, location, nodes, Apc, and Fhit were independent predictors for CSS; the same factors (and age and Her2, except Fhit) predicted OS. Multivariate model predicted IPP with high prognostic accuracy (0.90 for CSS; 0.91 for OS). A two-class model significantly separated low- and high-risk patients for CSS (23.4% and 85.6%, P < 0.0001) and OS (21.4% and 82.0%, P < 0.0001). A three-class model differentiated low-, intermediate-, and high-risk patients for CSS (6.3%, 35.3%, and 88.0%, P < 0.0001) and OS (6.1%, 34.6%, and 86.5%, P < 0.0001).
  
  
  CONCLUSIONS
  A risk classification system comprising the immunohistochemical expression of three proteins (Apc, Fhit, and Her2) and five clinicopathological parameters (stage, resected nodes, margins, location, and sex) accurately separates the resected gastric cancer patients into three classes of risk.
authors.affiliation: ARC-NET the Miriam Cherubini Loro, Applied Research on Cancer Center.
authors.forename: E
authors.initials: E
authors.lastname: Bria
authors.forename: G
authors.initials: G
authors.lastname: De Manzoni
authors.forename: S
authors.initials: S
authors.lastname: Beghelli
authors.forename: A
authors.initials: A
authors.lastname: Tomezzoli
authors.forename: S
authors.initials: S
authors.lastname: Barbi
authors.forename: C
authors.initials: C
authors.lastname: Di Gregorio
authors.forename: M
authors.initials: M
authors.lastname: Scardoni
authors.forename: E
authors.initials: E
authors.lastname: Amato
authors.forename: M
authors.initials: M
authors.lastname: Frizziero
authors.forename: I
authors.initials: I
authors.lastname: Sperduti
authors.forename: V
authors.initials: V
authors.lastname: Corbo
authors.forename: M
authors.initials: M
authors.lastname: Brunelli
authors.forename: S
authors.initials: S
authors.lastname: Bersani
authors.forename: G
authors.initials: G
authors.lastname: Tortora
authors.forename: A
authors.initials: A
authors.lastname: Scarpa
mesh_terms: D017766:Acid Anhydride Hydrolases / Q000378:metabolism*; D025601:Adenomatous Polyposis Coli Protein / Q000235:genetics / Q000378:metabolism*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D002277:Carcinoma / Q000378:metabolism* / Q000401:mortality / Q000556:secondary / Q000601:surgery; D004252:DNA Mutational Analysis; D005260:Female; D015870:Gene Expression; D006801:Humans; D053208:Kaplan-Meier Estimate; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009363:Neoplasm Proteins / Q000378:metabolism*; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000235:genetics / Q000378:metabolism*; D012189:Retrospective Studies; D013274:Stomach Neoplasms / Q000378:metabolism* / Q000401:mortality / Q000473:pathology / Q000601:surgery; D000099170:Bis(5'-adenosyl)triphosphatase
chemical_list: D017766:Acid Anhydride Hydrolases; D025601:Adenomatous Polyposis Coli Protein; D009363:Neoplasm Proteins; D018719:Erb-b2 Receptor Tyrosine Kinases; D000099170:Bis(5'-adenosyl)triphosphatase; C555337:APC protein, human; C508053:ERBB2 protein, human