Graphene therapy-related lncRNAs as prognostic and immune microenvironmental biomarkers in hepatocellular carcinoma

Weilong Ye; Hui Li; Juan Zhao; Deshuai Lu; Tao Tao; Xiao Zhu

doi:10.1016/j.tranon.2024.101915

Graphene therapy-related lncRNAs as prognostic and immune microenvironmental biomarkers in hepatocellular carcinoma

Transl Oncol. 2024 May:43:101915. doi: 10.1016/j.tranon.2024.101915. Epub 2024 Feb 17.

Authors

Weilong Ye¹, Hui Li², Juan Zhao³, Deshuai Lu¹, Tao Tao⁴, Xiao Zhu⁵

Affiliations

¹ Computational Medicine and Epidemiology Laboratory (CMEL), The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang, PR China.
² Department of Internal Medicine, Huadu District People's Hospital of Guangzhou (The Third School of Clinical Medicine, Southern Medical University), PR China.
³ Department of the Clinical Laboratory, Huadu District People's Hospital of Guangzhou (The Third School of Clinical Medicine, Southern Medical University), PR China.
⁴ Department of Gastroenterology, Zibo Central Hospital, Zibo, PR China. Electronic address: tao_tao79@163.com.
⁵ Computational Medicine and Epidemiology Laboratory (CMEL), The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang, PR China. Electronic address: xzhu@gdmu.edu.cn.

Abstract

Background: Graphene materials have the capacity to influence the tumor microenvironment and intracellular signaling responsiveness. However, the process of graphene-assisted liver cancer treatment still lacks specific biomarkers for assessing its efficacy.

Methods: We identified graphene therapy-related lncRNAs (GTLncRNAs) through gene analysis and correlation tests. Multivariate COX and LASSO regression analyses yielded significant lncRNAs for a risk score model. We evaluated clinicopathological factors and tumor microenvironment using ssGSEA. We scrutinized the pathways of immune function, the evasion of tumor immunity, and the potential for immunotherapy. GTLncRNAs with differential expression were subjected to GO/KEGG analysis, and prospective chemotherapy drugs were discerned utilizing the pRRophetic algorithm. The prognostic model was authenticated through the examination of the Imvigor210 cohort, and an analysis of mRNA stemness was executed.

Results: The researchers constructed a prognostic model based on 22 graphene therapy-related lncRNAs. Protective lncRNAs (AC010280.2, AL365361.1, and LINC01549) and negative lncRNAs (AC026412.3, AL031985.3, ELFN1-AS1, SNHG4, and EB2-AS1) were identified. Higher risk scores correlated with shorter survival. Low-risk immune pathways included Type_II_IFN_Reponse and cytolytic_activity. Subgroups differed significantly in TMB, TIDE, MDSC, exclusion, and dysfunction. Low TMB values correlated with longer survival. The high-risk subgroup showed increased sensitivity to screened compounds, and mRNAsi was higher in cancer tissue.

Conclusions: Our GTLncRNAs-based model accurately predicted survival of HCC patients and underscored the influence of graphene therapy-related genes on the tumor microenvironment. Potential treatment compounds were identified, and the mRNAsi index demonstrated prognostic value.

Keywords: Drug sensitivity; Graphene therapy-related lncRNAs (GTLncRNAs); Hepatocellular carcinoma (HCC); Prognosis; Tumor microenvironment.