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Comprehensive evaluation of genes related to basement membrane in hepatocellular carcinoma.
Wu, Guojing; Li, Fei; Guo, Danyan; Xi, Kaiwen; Zheng, Dayong; Huang, Ruichao; Wu, Xiuqiong; Li, Aimin; Liu, Xinhui.
Afiliación
  • Wu G; Southern Medical University Hospital of Integrated Traditional Chinese and Western Medicine, Southern Medical University, Guangzhou 510315, China.
  • Li F; Cancer Center, Southern Medical University, Guangzhou 510315, China.
  • Guo D; Southern Medical University Hospital of Integrated Traditional Chinese and Western Medicine, Southern Medical University, Guangzhou 510315, China.
  • Xi K; Cancer Center, Southern Medical University, Guangzhou 510315, China.
  • Zheng D; Southern Medical University Hospital of Integrated Traditional Chinese and Western Medicine, Southern Medical University, Guangzhou 510315, China.
  • Huang R; Cancer Center, Southern Medical University, Guangzhou 510315, China.
  • Wu X; Southern Medical University Hospital of Integrated Traditional Chinese and Western Medicine, Southern Medical University, Guangzhou 510315, China.
  • Li A; Cancer Center, Southern Medical University, Guangzhou 510315, China.
  • Liu X; Southern Medical University Hospital of Integrated Traditional Chinese and Western Medicine, Southern Medical University, Guangzhou 510315, China.
Aging (Albany NY) ; 16(11): 10108-10131, 2024 06 12.
Article en En | MEDLINE | ID: mdl-38870261
ABSTRACT
In all mammals, the basement membrane serves as a pivotal extracellular matrix. Hepatocellular carcinoma (HCC) is a challenge among numerous cancer types shaped by basement membrane-related genes (BMGs). Our research established an innovative prognostic model that is highly accurate in its prediction of HCC prognoses and immunotherapy efficacy to summarize the crucial role of BMGs in HCC. We obtained HCC transcriptome analysis data and corresponding clinical data from The Cancer Genome Atlas (TCGA). To augment our dataset, we incorporated 222 differentially expressed BMGs identified from relevant literature. A weighted gene coexpression network analysis (WGCNA) of 10158 genes demonstrated four modules that were connected to HCC. Additionally, 66 genes that are found at the intersection of BMGs and HCC-related genes were designated as hub HCC-related BMGs. MMP1, ITGA2, P3H1, and CTSA comprise the novel model that was engineered using univariate and multivariate Cox regression analysis. Furthermore, the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) datasets encouraged the BMs model's validity. The overall survival (OS) of individuals with HCC may be precisely predicted in the TCGA and ICGC databases utilizing the BMs model. A nomogram based on the model was created in the TCGA database at similar time, and displayed a favorable discriminating ability for HCC. Particularly, when compared to the patients at an elevated risk, the patients with a low-risk profile presented different tumor microenvironment (TME) and hallmark pathways. Moreover, we discovered that a lower risk score of HCC patients would display a greater response to immunotherapy. Finally, quantitative real-time PCR (qRT-PCR) experiments were used to verify the expression patterns of BMs model. In summary, BMs model demonstrated efficacy in prognosticating the survival probability of HCC patients and their immunotherapeutic responsiveness.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Membrana Basal / Regulación Neoplásica de la Expresión Génica / Carcinoma Hepatocelular / Neoplasias Hepáticas Límite: Female / Humans / Male Idioma: En Revista: Aging (Albany NY) Asunto de la revista: GERIATRIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Membrana Basal / Regulación Neoplásica de la Expresión Génica / Carcinoma Hepatocelular / Neoplasias Hepáticas Límite: Female / Humans / Male Idioma: En Revista: Aging (Albany NY) Asunto de la revista: GERIATRIA Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos