Volume 138, Issue 3, Pages 949-957.e7 (March 2010) Salivary Transcriptomic Biomarkers for Detection of Resectable Pancreatic Cancer  Lei Zhang, James J. Farrell, Hui Zhou, David Elashoff, David Akin, No–Hee Park, David Chia, David T. Wong  Gastroenterology  Volume 138, Issue 3, Pages 949-957.e7 (March 2010) DOI: 10.1053/j.gastro.2009.11.010 Copyright © 2010 AGA Institute Terms and Conditions

Figure 1 Schematic of the strategy used for the discovery and validation of salivary biomarkers. PC, pancreatic cancer; H, healthy control; CP, chronic pancreatitis. Gastroenterology 2010 138, 949-957.e7DOI: (10.1053/j.gastro.2009.11.010) Copyright © 2010 AGA Institute Terms and Conditions

Figure 2 Heat map of 35 qPCR verified genes (23 up-regulated and 12 down-regulated) based on the microarray data. Hierarchical clustering and gene function enrichment were performed using Euclidean distance metric and centroid linkage method (unsupervised clustering). Pancreatic cancer patients (n = 12) and healthy controls (n = 12) could be classified into distinct groups, indicating the discriminatory power of salivary mRNA biomarkers. The GEO database access number of all microarray experiments is GSE14245. Gastroenterology 2010 138, 949-957.e7DOI: (10.1053/j.gastro.2009.11.010) Copyright © 2010 AGA Institute Terms and Conditions

Figure 3 ROC curve and interactive dot diagram for the logistic regression model. (A) The logistic regression model using 4 biomarkers (KRAS, MBD3L2, ACRV1, and DPM1) yielded an AUC value of 0.971 (cutoff, 0.433). (B) Interactive dot diagram was based on the qPCR data of the noncancer group (n = 60) and cancer group (n = 30). Gastroenterology 2010 138, 949-957.e7DOI: (10.1053/j.gastro.2009.11.010) Copyright © 2010 AGA Institute Terms and Conditions

Gastroenterology 2010 138, 949-957. e7DOI: (10. 1053/j. gastro. 2009 Copyright © 2010 AGA Institute Terms and Conditions