Meta analysis of transcriptome data identifies a novel 5 gene pancreatic adenocarcinoma classifier
Purpose Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification. Experimental Design Optimized meta analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC specific expression of a 5 gene biomarker panel was measured by qRT PCR in microdissected patient derived FFPE tissues. Cell based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells. Results A 5 gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non tumor samples in four training sets and similar performance (sensitivity 94% specificity 89.6% in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC 0.83) other cancers (AUC 0.89) and non tumor from PDAC precursors (AUC 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1 Cre;LSL KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non tumor pancreas or pancreatitis. Notably, knock down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion. Conclusions This study identified and validated a highly accurate 5 gene PDAC classifier for discriminating PDAC and early precursor lesions from non malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets.
Oncotarget