title: Development of a serum biomarker panel predicting recurrence in stage I non-small cell lung cancer patients.
abstract: OBJECTIVE
  Molecular diagnostics capable of prognosticating disease recurrence in stage I non-small cell lung cancer (NSCLC) patients have implications for improving survival. The objective of the present study was to develop a multianalyte serum algorithm predictive of disease recurrence in stage I NSCLC patients.
  
  
  METHODS
  The Luminex immunobead platform was used to evaluate 43 biomarkers against 79 patients with resectable NSCLC, with the following cohorts represented: stage I (T(1)-T(2)N(0)M(0)) NSCLC without recurrence (n = 37), stage I (T(1)-T(2)N(0)M(0)) NSCLC with recurrence (n = 15), and node-positive (T(1)-T(2)N(1)-N(2)M(0)) NSCLC (n = 27). Peripheral blood was collected before surgery, with all patients undergoing anatomic resection. Univariate statistical methods (receiver operating characteristics curves and log-rank test) were used to evaluate each biomarker with respect to recurrence and outcome. Multivariate statistical methods were used to develop a prognostic classification panel for disease recurrence.
  
  
  RESULTS
  No relationship was found between recurrence and age, gender, smoking history, or histologic type. Analysis for all stage I patients revealed 28 biomarkers significant for recurrence. Of these, the log-rank test identified 10 biomarkers that were strongly (P < .01) prognostic for recurrence. The Random Forest algorithm created a 6-analyte panel for preoperative classification that accurately predicted recurrence in 77% of stage I patients tested, with a sensitivity of 74% and specificity of 79%.
  
  
  CONCLUSIONS
  We report the development of a serum biomarker algorithm capable of preoperatively predicting disease recurrence in stage I NSCLC patients. Refinement of this panel might stratify patients for adjuvant therapy or aggressive recurrence monitoring to improve survival.
authors.affiliation: Department of Thoracic Surgery, Rush University Medical Center, Chicago, Ill 60612, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Rinewalt
authors.forename: David D
authors.initials: DD
authors.lastname: Shersher
authors.forename: Shaun
authors.initials: S
authors.lastname: Daly
authors.forename: Cristina
authors.initials: C
authors.lastname: Fhied
authors.forename: Sanjib
authors.initials: S
authors.lastname: Basu
authors.forename: Brett
authors.initials: B
authors.lastname: Mahon
authors.forename: Edward
authors.initials: E
authors.lastname: Hong
authors.forename: Gary
authors.initials: G
authors.lastname: Chmielewski
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Liptay
authors.forename: Jeffrey A
authors.initials: JA
authors.lastname: Borgia
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D014408:Biomarkers, Tumor / Q000097:blood*; D002289:Carcinoma, Non-Small-Cell Lung / Q000097:blood* / Q000556:secondary / Q000601:surgery; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D007118:Immunoassay; D008175:Lung Neoplasms / Q000097:blood* / Q000473:pathology / Q000601:surgery; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009364:Neoplasm Recurrence, Local; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor