A nomogram combining PPARγ expression profiles and clinical factors predicts survival in patients with hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with poor prognosis. Peroxisome proliferator-activated receptor γ (PPARγ) is involved in the development of various tumor types. However, its role in hepatocellular carcinoma (HCC) remains unclear. Multiple databases including The Cancer Genome Atlas, Gene Expression Omnibus and Kaplan-Meier plotter were used for bioinformatics analysis of the PPARγ gene or protein. Immunohistochemical labeling of tumor and adjacent normal tissues obtained from 125 patients with HCC was performed to analyze the relationship between PPARγ expression and overall survival (OS) rate. PPARγ was evaluated using functional enrichment analyses and Lasso regression was used to conduct a dimensionality reduction analysis of 43 clinical factors for HCC. An OS prognostic nomogram was then established using seven independent risk factors screened via Lasso regression. PPARγ expression in HCC tumor tissues was higher compared with that in normal liver tissues, and its high expression was associated with poor prognosis, as indicated by bioinformatics analysis. However, opposite results were obtained using the clinical specimens. Functional enrichment analysis indicated that PPARγ was enriched in the 'fatty acid metabolism' pathway. Lasso regression identified seven clinical factors associated with prognosis, including Tumor-Node-Metastasis stage, grade, vascular invasion, α fetoprotein, carbohydrate antigen 199, γ-glutamyl transpeptidase and the PPARγ protein. These seven clinical factors were to construct an OS prognostic nomogram. Overall, PPARγ was highly expressed in the livers of patients with HCC and can be included in an OS prognostic nomogram. However, the factors underlying the differential association of PPARγ expression with HCC prognosis in different datasets should be further investigated.