Risk prediction for dermatomyositis-associated hepatocellular carcinoma

Xusheng Zhang; Yongxin Ma; Kejun Liu; Long Chen; Lin Ding; Weihu Ma; Bendong Chen

doi:10.1186/s12859-023-05353-6

Risk prediction for dermatomyositis-associated hepatocellular carcinoma

BMC Bioinformatics. 2023 May 31;24(1):222. doi: 10.1186/s12859-023-05353-6.

Authors

Xusheng Zhang^#¹, Yongxin Ma^#¹, Kejun Liu^{1

2

3}, Long Chen¹, Lin Ding¹, Weihu Ma¹, Bendong Chen^{4

5}

Affiliations

¹ Ningxia Medical University, Yinchuan, 750004, China.
² Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
³ Ningxia Hepatobiliary and Pancreatic Surgical Diseases Clinical Medical Research Center, Yinchuan, 750004, China.
⁴ Ningxia Medical University, Yinchuan, 750004, China. chenbendong@nxmu.edu.cn.
⁵ Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan, 750004, China. chenbendong@nxmu.edu.cn.

^# Contributed equally.

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.

Keywords: Dermatomyositis; Hepatocellular carcinoma; PI3K/ART signaling pathway; SPP1; Support vector machine.

MeSH terms

Algorithms
Carcinoma, Hepatocellular* / genetics
Dermatomyositis* / complications
Dermatomyositis* / genetics
Humans
Liver Neoplasms* / genetics
Phosphatidylinositol 3-Kinases

Substances

Phosphatidylinositol 3-Kinases