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Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response.
Da, Bin-Bin; Luo, Shuai; Huang, Ming; Song, Fei; Ding, Rong; Xiao, Yao; Fu, Yang; Yang, Yin-Shan; Wang, Hai-Lei.
Afiliação
  • Da BB; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Luo S; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Huang M; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Song F; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Ding R; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Xiao Y; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Fu Y; CT Room, Kunming First People's Hospital, Kunming 650000, China.
  • Yang YS; Department of Minimally Invasive Interventional Medicine Yunnan Cancer Hospital, Kunming 650118, China.
  • Wang HL; Hepatobiliary Pancreatic Vascular Surgery, Kunming First People's Hospital, Kunming 650031, China.
Comput Math Methods Med ; 2022: 2415129, 2022.
Article em En | MEDLINE | ID: mdl-35035517
ABSTRACT
It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Comput Math Methods Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Comput Math Methods Med Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China