Abstract

Idiopathic pulmonary fibrosis (IPF) is a lung disease that is both chronic and progressive and is characterized by glycolysis. However, glycolysis's function and its clinical significance in IPF are still not well understood. We accessed the Gene Expression Omnibus database to retrieve mRNA expression information for lung tissue and other samples. We identified genes associated with glycolysis that had differential expression levels between IPF and controls. In this work, we conducted a comprehensive bioinformatic analysis to systematically examine the glycolysis-associated genes with differential expression and subsequently investigated the possible prognostic significance of these genes. Additionally, the expression profiles of the associated prognostic genes were further investigated via quantitative real-time polymerase chain reaction in our cohort. In this investigation, we found that the expression of 16 genes involved in glycolysis was differentially expressed. Among them, 12 were upregulated and 4 were downregulated. We found that 3 glycolysis-related genes (stanniocalcin 2, transketolase like 1, artemin) might serve as hub genes for anticipating patient prognosis. The data from these genes were used to generate the prognostic models. The findings confirmed that high-risk IPF patients recorded a shorter overall survival relative to low-risk patients. This prognostic model yielded 1-, 2-, and 3-year survival rates of 0.666, 0.651, and 0.717, correspondingly, based on the area under the curve of the survival-dependent receiver operating characteristic. The GSE27957 and GSE70866 cohorts validated these findings, indicating the model has a good predictive performance. All 3 glycolysis-associated genes were validated to be expressed in our cohort. Finally, we used mRNA levels from 3 genes to produce a nomogram to quantitatively predict the prognosis of IPF individuals. As possible indicators for the prognosis of IPF, the glycolysis-related genes stanniocalcin 2, transketolase like 1, and artemin were shown to be promising candidate markers.

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