Superposition Analysis: A Method for Liver Disease Diagnosis and Prognostic Evaluation Related Gene Screening

To predict the types, stages and prognostic evaluation of liver diseases based on gene expression changes in liver tissues, the “superposition analysis method” was employed to screen mRNAs which were significant, differentially expressed, relevant, critical, and prognostically informative. Differential expression of candidate critical mRNAs in rat liver diseases was assessed using the t-test, and mRNAs with a p-value ≤ 0.01 were designated as prognostic mRNAs. The expression levels of the prognostic mRNAs were quantified by real-time PCR. The superposition analysis method was applied to calculate the weighted minimum Manhattan distance, which served as the basis for predicting the type of liver disease. 328 critical mRNAs were identified from the rat liver tissues with seven aforementioned liver diseases. Among them, six prognostic mRNAs, including ANXA2, AVPR1A, CLEC10A, FABP4, GSTP1 and RCN2, exhibited p-values ≤ 0.01. qPCR revealed that AVPR1A was downregulated in rat hepatocellular carcinoma (HCC), whereas others were upregulated. The superposition analysis method demonstrated prediction accuracies of 100% for hepatitis, advanced HCC, and terminal-stage HCC; 90% for hepatic fibrosis and early-stage HCC; 80% for cirrhosis; and 50% for intermediate-stage HCC, which described herein for predicting rat liver diseases exhibits considerable reliability and feasibility.