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The novel immune-related genes predict the prognosis of patients with hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is one of the main causes of cancer deaths globally. Immunotherapy is becoming increasingly important in the cure of advanced HCC. Thus it is essential to identify biomarkers for treatment response and prognosis prediction. We searched publicly available databases and retrieved 465 samples of genes from The Cancer Genome Atlas (TCGA) database and 115 tumor samples from Gene Expression Omnibus (GEO). Meanwhile, we used the ImmPort database to determine the immune-related genes as well. Weighted gene correlation network analysis, Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to identify the key immune related genes (IRGs) which are closely related to prognosis. Gene set enrichment analysis (GSEA) was implemented to explore the difference of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway between Immune high- and low-risk score groups. Finally, we made a prognostic nomogram including Immune-Risk score and other clinicopathologic factors. A total of 318 genes from prognosis related modules were identified through weighted gene co-expression network analysis (WGCNA). 46 genes were strongly linked to prognosis after univariate Cox analysis. We constructed a seven genes prognostic signature which showed powerful prediction ability in both training cohort and testing cohort. 16 significant KEGG pathways were identified between high- and low- risk score groups using GSEA analysis. This study identified and verified seven immune-related prognostic biomarkers for the patients with HCC, which have potential value for immune modulatory and therapeutic targets.

SUBMITTER: Li L

PROVIDER: S-EPMC8139963 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most serious malignant tumors threatening human life with a high mortality rate. The liver regenerative capacity after hepatectomy in early-stage HCC patients is influenced by various factors, including surgical methods and energy metabolism. This study aims to provide a prognostic model based on genes related to liver regeneration that can predict the prognosis of non-tumor tissues in HCC patients.Patients and methodsA total of 584 non-tumor tissues from HCC patients were collected from three independent databases. Kaplan-Meier survival curves were used to identify prognostic liver-regeneration genes. Subsequently, a prognostic indicator, designated as the Liver Regeneration score (LR score), was determined using single-sample gene set enrichment analysis (ssGSEA). Independent cohorts were used to verify the relationship between LR score and prognosis in non-tumor tissues of HCC patients. Furthermore, a liver regeneration-related model was established to validate key genes identified through LASSO Cox regression analysis.ResultsWe constructed a gene set comprising 24 liver regeneration-related genes, and the LR score was utilized to predict the prognosis of HCC patients based on its levels in non-tumor tissues. In non-tumor tissues of HCC patients, higher LR scores were associated with improved prognosis. Higher LR scores in non-tumor tissues indicate improved liver metabolism in HCC patients, revealed by Enrichment analysis. LASSO Cox regression analysis identified two key genes, DHTKD1 (dehydrogenase E1 and transketolase domain containing 1) and PHYH (phytanoyl-CoA 2-hydroxylase), and higher expression levels of these genes in non-tumor tissues were correlated with better prognosis. The expression levels of these two genes also changed corresponding to the progression of liver regeneration.ConclusionIn summary, our study has introduced a novel LR gene signature for HCC patients, providing a predictive model for estimating clinical prognosis from non-tumor tissues. The LR score demonstrates promise as a reliable indicator for predicting overall survival in HCC.

Project description:BackgroundUnderstanding the interplay between disulfidptosis, ferroptosis, and hepatocellular carcinoma (HCC) could provide valuable insights into the pathogenesis of HCC and potentially identify novel therapeutic targets for the treatment of this deadly disease. This study aimed to identify a prognostic signature for HCC by examining the differential expression of genes related to disulfidptosis and ferroptosis (DRG-FRG), and to assess its clinical applicability.MethodsBy integrating 23 disulfidptosis and 259 ferroptosis related genes with HCC messenger RNA (mRNA) expression data from The Cancer Genome Atlas (TCGA), differentially expressed DRG-FRG genes were identified. From these, 11 DRG-FRG genes were selected to construct a risk signature model using least absolute shrinkage and selection operator regression analyses. The prognostic performance of this model was evaluated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) analysis. Subsequently, a nomogram was built by combining the signature with clinical variables. To further delve into the underlying mechanisms, we performed bioinformatics analysis using a variety of databases.ResultsA prognostic signature based on 11 DRG-FRG genes effectively categorized HCC patients into high- and low-risk groups, showing a significant survival difference. Even after considering clinical variables, this signature remained an independent prognostic factor. Furthermore, the signature played a role in various critical biological processes and pathways that drive HCC progression. Potential therapeutic benefits could be derived from small molecule drugs targeting NQO1 and SLC7A11. Interestingly, the high-risk group exhibited resistance to several chemotherapeutic drugs, yet showed sensitivity to others when contrasted with the low-risk group. Lastly, the DRG-FRG genes signature had a strong correlation with the tumor immune microenvironment, marked by an elevated expression of immune checkpoint molecules in the high-risk group.ConclusionsThe signature based on 11 DRG-FRG genes stands out as a promising prognostic biomarker for HCC. Beyond its predictive value, it sheds light on the intricate crosstalk between DRG-FRG genes and HCC. Importantly, these findings could pave the way for enhanced prognostic prediction, informed treatment decisions, and the advancement of immunotherapy for HCC patients.

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The novel immune-related genes predict the prognosis of patients with hepatocellular carcinoma.

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