Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier
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Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier
| Title: | Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier |
| Author: |
Bhasin, Manoj K.; Ndebele, Kenneth; Bucur, Octavian; Yee, Eric U.; Otu, Hasan H.; Plati, Jessica; Bullock, Andrea; Gu, Xuesong; Castan, Eduardo; Zhang, Peng; Najarian, Robert; Muraru, Maria S.; Miksad, Rebecca; Khosravi-Far, Roya; Libermann, Towia A.
Note: Order does not necessarily reflect citation order of authors. |
| Citation: | Bhasin, M. K., K. Ndebele, O. Bucur, E. U. Yee, H. H. Otu, J. Plati, A. Bullock, et al. 2016. “Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier.” Oncotarget 7 (17): 23263-23281. doi:10.18632/oncotarget.8139. http://dx.doi.org/10.18632/oncotarget.8139. |
| Full Text & Related Files: |
5029625.pdf (1.779Mb; PDF) 
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| Abstract: | 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. |
| Published Version: | doi:10.18632/oncotarget.8139 |
| Other Sources: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5029625/pdf/ |
| Terms of Use: | This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA |
| Citable link to this page: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:29407638 |
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