R3 조 욱 Salivary Transcriptomic Biomarkers for Detection of Resectable Pancreatic Cancer Articles LEI ZHANG, JAMES J. FARRELL, HUI ZHOU, DAVID ELASHOFF,

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R3 조 욱 Salivary Transcriptomic Biomarkers for Detection of Resectable Pancreatic Cancer Articles LEI ZHANG, JAMES J. FARRELL, HUI ZHOU, DAVID ELASHOFF, DAVID AKIN, NO–HEE PARK, DAVID CHIA, and DAVID T. WONG GASTROENTEROLOGY 2010;138:949–957

BACKGROUND & AIMS Pancreatic cancer –second most frequent gastrointestinal malignancy –advanced stage of presentation Early detection of pancreatic cancer offers promise of improved mortality rates through surgical resection –Requirement of methods to identify potentially affected individuals Lack of highly specific pancreatic cancer biomarkers Current strategies for early detection of pancreatic cancer –confined to a small number of patients at greater risk –relying on invasive procedures –Lack sensitivity and specificity –Chronic pancreatitis has phenotypic overlap with early pancreatic cancer

Saliva –readily accessible noninvasively –mirror of the body –Salivary constituents (DNA, RNA, protein, and bacteria) extensively linked to forensic sciences, oral disease, and systemic disease Purpose of this study –to evaluate the performance and translational utilities of salivary transcriptomic biomarkers for noninvasive detection of resectable pancreatic cancer

METHODS Patients and Methods –Started in February 2006 / recruited from UCLA Medical Center –114 samples (42 pancreatic cancer /30 chronic pancreatitis /42 healthy control individuals) Inclusion criteria –confirmed diagnosis of pancreatic cancer confined to pancreas (either resectable or borderline resectable [because of superior mesenteric vein or portal vein involvement] ) –chronic pancreatitis Exclusion criteria –evidence of locally advanced cancer / metastatic pancreatic cancer –chemotherapy or radiation therapy prior to saliva collection –diagnosis of other malignancies within 5 years from saliva collection.

Study design

Salivary Transcriptomic Profiling –saliva supernatant 330 uL  RNA isolation  complementary DNA in vitro-transcribed and biotinylated  Chip hybridization and scanning  mRNA biomarkers selection  verified by quantitative PCR Verified biomarkers were then assayed by qPCR in the set of 90 independent samples * Wilcoxon test was used to compare biomarkers between groups Predictive Model Building and Evaluation –logistic regression method –receiver operating characteristic (ROC) curve / area under curve (AUC) Cross-Disease Comparison of Salivary mRNA Biomarkers (Microarray Studies)

Results Variation of Salivary Gene Expression Profiles Between Pancreatic Cancer Patients / Healthy Controls –no significant difference in total RNA quantity –all samples(n=24) contain transcripts of 4 genes (GAPDH, ANXA2, RPL37, and RPS16)  no significant differences in levels –Transcriptomic profiling 958 genes 2-fold up-regulation in pancreatic cancer (P<0.05)958 genes 2-fold up-regulation in pancreatic cancer (P<0.05) 691 genes 2-fold down-regulation in pancreatic cancer (P<0.05)691 genes 2-fold down-regulation in pancreatic cancer (P<0.05) 49 genes 4-fold up-regulation in pancreatic cancer (P<0.01)49 genes 4-fold up-regulation in pancreatic cancer (P<0.01) 21 genes 4-fold down-regulation in pancreatic cancer (P<0.01)21 genes 4-fold down-regulation in pancreatic cancer (P<0.01)

Identification and Validation of mRNA Biomarkers for Pancreatic Cancer –Quantitative PCR(qPCR) –relative RNA expression of 23 up-regulated and 12 down-regulated transcripts were consistent with microarray data A heat map of these 35 verified genes built based on microarray data –Pancreatic cancer patients (n12) and healthy controls (n12) could be classified into distinct groups, indicating the discriminatory power of salivary mRNA biomarkers

35 verified genes  validation by qPCR in an independent cohort of 30 pancreatic cancer / 30 healthy control/ 30 chronic pancreatitis patients –7 up-regulated and 5 down-regulated genes were validated

Prediction Models Using the Validated mRNA Biomarkers –Logistic regression models

Cross-Disease Comparisons of Salivary mRNA Biomarkers –specificity of 12 validated mRNA biomarkers against diverse cancers, including oral cancer, breast cancer, and lung cancer –none of 11 mRNAs/transcripts significantly altered in other cancer –*TK2 : significant variation in lung cancer

Conclusion salivary biomarkers –possess discriminatory power for 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.