Risk prediction for Dermatomyositis-associated hepatocellular carcinoma

Abstract

Objective To explore dermatomyositis signature genes as potential biomarkers of hepatocellular carcinoma and their associated molecular regulatory mechanisms. Methods Based on the mRNA-Seq data of dermatomyositis and hepatocellular carcinoma in public databases, five dermatomyositis signature genes were screened by LASSO regression analysis and support vector machine (SVM) algorithm, and their biological functions in dermatomyositis with hepatocellular carcinoma were investigated, and a nomogram risk prediction model for hepatocellular carcinoma was constructed and its predictive efficiency was initially evaluated. The immune profile in hepatocellular carcinoma was examined based on the CIBERSORT and ssGSEA algorithms, and the correlation between five dermatomyositis signature genes and tumor immune cell infiltration and immune checkpoints in hepatocellular carcinoma was investigated. Results The expression levels of five dermatomyositis signature genes were significantly altered in hepatocellular carcinoma and showed good diagnostic efficacy for hepatocellular carcinoma, suggesting that they may be potential predictive targets for hepatocellular carcinoma, and the risk prediction model based on five dermatomyositis signature genes showed good risk prediction efficacy for hepatocellular carcinoma and has good potential for clinical application. In addition, we also found that the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through integrin-mediated activation, which in turn regulates the development and progression of hepatocellular carcinoma. Conclusion LY6E, IFITM1, GADD45A, MT1M, and SPP1 are potential predictive targets for new-onset hepatocellular carcinoma in patients with dermatomyositis, and the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through the mediation of integrins to promote the development and progression of hepatocellular carcinoma.