title: Salivary transcriptomic biomarkers for detection of resectable pancreatic cancer.
abstract: OBJECTIVE
  Lack of detection technology for early pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. New strategies and biomarkers for early detection are sorely needed. In this study, we have conducted a prospective sample collection and retrospective blinded validation to evaluate the performance and translational utilities of salivary transcriptomic biomarkers for the noninvasive detection of resectable pancreatic cancer.
  
  
  METHODS
  The Affymetrix HG U133 Plus 2.0 Array (Affymetrix, Santa Clara, CA) was used to profile transcriptomes and discover altered gene expression in saliva supernatant. Biomarkers discovered from the microarray study were subjected to clinical validation using an independent sample set of 30 pancreatic cancer patients, 30 chronic pancreatitis patients, and 30 healthy controls.
  
  
  RESULTS
  Twelve messenger RNA biomarkers were discovered and validated. The logistic regression model with the combination of 4 messenger RNA biomarkers (KRAS, MBD3L2, ACRV1, and DPM1) could differentiate pancreatic cancer patients from noncancer subjects (chronic pancreatitis and healthy control), yielding a receiver operating characteristic plot, area under the curve value of 0.971 with 90.0% sensitivity and 95.0% specificity.
  
  
  CONCLUSIONS
  The salivary biomarkers possess discriminatory power for the detection of resectable pancreatic cancer, with high specificity and sensitivity. This report provides the proof of concept of salivary biomarkers for the noninvasive detection of a systemic cancer and paves the way for prediction model validation study followed by pivotal clinical validation.
authors.affiliation: School of Dentistry and Dental Research Institute, University of California-Los Angeles, Los Angeles, California 90095, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Zhang
authors.forename: James J
authors.initials: JJ
authors.lastname: Farrell
authors.forename: Hui
authors.initials: H
authors.lastname: Zhou
authors.forename: David
authors.initials: D
authors.lastname: Elashoff
authors.forename: David
authors.initials: D
authors.lastname: Akin
authors.forename: No-Hee
authors.initials: NH
authors.lastname: Park
authors.forename: David
authors.initials: D
authors.lastname: Chia
authors.forename: David T
authors.initials: DT
authors.lastname: Wong
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000032:analysis*; D055088:Early Detection of Cancer; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D005820:Genetic Testing; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D010190:Pancreatic Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000601:surgery; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012333:RNA, Messenger / Q000032:analysis*; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012463:Saliva / Q000737:chemistry*; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D012333:RNA, Messenger