PDAC-ANN: an artificial neural network to predict pancreatic ductal adenocarcinoma based on gene expression.

ABSTRACT:

Background

Although the pancreatic ductal adenocarcinoma (PDAC) presents high mortality and metastatic potential, there is a lack of effective therapies and a low survival rate for this disease. This PDAC scenario urges new strategies for diagnosis, drug targets, and treatment.

Methods

We performed a gene expression microarray meta-analysis of the tumor against normal tissues in order to identify differentially expressed genes (DEG) shared among all datasets, named core-genes (CG). We confirmed the CG protein expression in pancreatic tissue through The Human Protein Atlas. It was selected five genes with the highest area under the curve (AUC) among these proteins with expression confirmed in the tumor group to train an artificial neural network (ANN) to classify samples.

SUBMITTER: Almeida PP 

PROVIDER: S-EPMC6995241 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature