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Qualitative Transcriptional Signature for the Pathological Diagnosis of Pancreatic Cancer.


ABSTRACT: It is currently difficult for pathologists to diagnose pancreatic cancer (PC) using biopsy specimens because samples may have been from an incorrect site or contain an insufficient amount of tissue. Thus, there is a need to develop a platform-independent molecular classifier that accurately distinguishes benign pancreatic lesions from PC. Here, we developed a robust qualitative messenger RNA signature based on within-sample relative expression orderings (REOs) of genes to discriminate both PC tissues and cancer-adjacent normal tissues from non-PC pancreatitis and healthy pancreatic tissues. A signature comprising 12 gene pairs and 17 genes was built in the training datasets and validated in microarray and RNA-sequencing datasets from biopsy samples and surgically resected samples. Analysis of 1,007 PC tissues and 257 non-tumor samples from nine databases indicated that the geometric mean of sensitivity and specificity was 96.7%, and the area under receiver operating characteristic curve was 0.978 (95% confidence interval, 0.947-0.994). For 20 specimens obtained from endoscopic biopsy, the signature had a diagnostic accuracy of 100%. The REO-based signature described here can aid in the molecular diagnosis of PC and may facilitate objective differentiation between benign and malignant pancreatic lesions.

SUBMITTER: Zhou YJ 

PROVIDER: S-EPMC7538791 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Qualitative Transcriptional Signature for the Pathological Diagnosis of Pancreatic Cancer.

Zhou Yu-Jie YJ   Lu Xiao-Fan XF   Meng Jia-Lin JL   Wang Xin-Yuan XY   Ruan Xin-Jia XJ   Yang Chang-Jie CJ   Wang Qi-Wen QW   Chen Hui-Min HM   Gao Yun-Jie YJ   Yan Fang-Rong FR   Li Xiao-Bo XB  

Frontiers in molecular biosciences 20200923


It is currently difficult for pathologists to diagnose pancreatic cancer (PC) using biopsy specimens because samples may have been from an incorrect site or contain an insufficient amount of tissue. Thus, there is a need to develop a platform-independent molecular classifier that accurately distinguishes benign pancreatic lesions from PC. Here, we developed a robust qualitative messenger RNA signature based on within-sample relative expression orderings (REOs) of genes to discriminate both PC ti  ...[more]

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