Dataset Information

Integrated Bioinformatics Analysis Identifies Heat Shock Factor 2 as a Prognostic Biomarker Associated With Immune Cell Infiltration in Hepatocellular Carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies examining the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. In the present study, we found that HSF2 expression was significantly upregulated in HCC tissues compared with normal liver tissues using the TCGA, ICGC, GEO, UALCAN, HCCDB and HPA databases. High HSF2 expression was associated with shorter survival of patients with HCC. Cox regression analyses and nomogram were used to evaluate the association of HSF2 expression with the prognosis of patients with HCC. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and gene set enrichment analysis (GSEA) revealed that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells using the TIMER database and CIBERSORT algorithm. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC tissues. Knockdown of HSF2 significantly inhibited the proliferation, migration, invasion and colony formation ability of HCC cells. In summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

SUBMITTER: Fan Y

PROVIDER: S-EPMC8669829 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background: BTBD10 serves as an activator of Akt family members through decreasing the protein phosphatase 2A-mediated dephosphorylation. The present study attempted to investigate the prognostic value of BTBD10 in hepatocellular carcinoma (HCC), specially, its relationship with tumor-infiltrating lymphocytes (TILs). Methods: BTBD10 expression was evaluated in HCC using The Cancer Genome Atlas (TCGA) and Xijing Hospital database, and verified in HCC cell lines. Cox analyses were performed to analyze independent prognostic risk factors for HCC. The optimal cut-off value of BTBD10 was calculated, by which all patients were divided into two groups to compare the overall survival (OS). The signaling pathways were predicted, by which BTBD10 may affect the progression of HCC. To investigate the impact of BTBD10 on HCC immunotherapy, correlations between BTBD10 and TILs, immune checkpoints, m6A methylation-related genes and ferroptosis-related genes were assessed. The distribution of half-maximal inhibitory concentration (IC50) of diverse targeted drugs was observed based on the differential expression of BTBD10. Results: BTBD10 expression was higher in HCC tissues and cell lines than that of normal liver tissues and cells. The patients with high expression of BTBD10 showed a worse OS, as compared to that of BTBD10 low-expressing group. Cox analyses indicated that BTBD10 was an independent prognostic risk factor for HCC. Several molecular pathways of immune responses were activated in HCC patients with high-expressing of BTBD10. Furthermore, BTBD10 expression was demonstrated to be positively correlated with tumor-infiltrating B cells, T cells, macrophages, neutrophils and dendritic cells. Meanwhile, the expression of BTBD10 was synchronized with that of several m6A methylation-related genes, ferroptosis-related genes and immune checkpoints. The IC50 scores of Sorafenib, Navitoclax, Veliparib, Luminespib, and Imatinib were found to be lower in BTBD10 high-expressing HCC group. Conclusion: BTBD10 negatively regulates tumor immunity in HCC and exhibits adverse effect on the prognosis of HCC, which could be a potential target for immunotherapy.

Project description:The poliovirus receptor (PVR) is a member of the immunoglobulin superfamily (Ig SF) and is essential for the promotion of cancer cell proliferation and invasion. However, the correlation between PVR expression and prognosis as well as immune infiltration in hepatocellular carcinoma (HCC) remains unclear. The expression level of PVR was quantified using the Tumor and Tumor Immunity Evaluation Resource (TIMER) and Sangerbox. The Gene Expression Omnibus (GEO) database was used to validate the PVR expression. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of using PVR as a differentiating factor according to the area under curve (AUC) score. A PVR binding protein network was built using the STRING tool. An enrichment analysis using the R package clusterProfiler was used to explore the potential function of PVR. Immune infiltration analysis was calculated with ESTIMATE algorithms. We also assessed the correlation between PVR expression and immune infiltration by the single-sample Gene Set Enrichment Analysis (ssGSEA) method from the R package GSVA and TIMER database. The results showed that PVR was commonly overexpressed in multiple types of tumors including HCC. The data of GSE64041 confirmed the same result. The ROC curve suggested that PVR could be a potential diagnostic biomarker. Additionally, high mRNA expression of PVR in HCC was significantly correlated with poor overall survival (OS) and relapse free survival (RFS). Results also indicated correlations between PVR mRNA expression with the level of infiltration immune cells including B cells, CD8+ T cells, cytotoxic cells, DCs, CD56dim NK cells, pDCs, and Th2 cells. Furthermore, the PVR level was significantly correlated with immune markers for immunosuppressive cells in HCC. In conclusion, PVR might be an important regulator of tumor immune cell infiltration and a valuable prognostic biomarker in HCC. However, additional work is needed to fully elucidate the underlying mechanisms.

Project description:Rad51, a DNA-repair-related gene, has been reported to be involved in multiple cancers. However, its link with immune infiltration in liver cancer still unknown. Therefore, more research into the roles and activities of Rad51 in hepatocellular carcinoma (HCC) is required. The International Cancer Genome Consortium (ICGC) was used to identify the DNA repair gene Rad51, and has been proved to be overexpressed in HCC patients. We plotted the Kapan-Meier curve, demonstrating that patients with high expression of Rad51 have a poor prognosis. By analyzing the patient data, we discovered that high expression of Rad51 in HCC is linked to clinical stage, pathological T stage, grade, and age. Rad51 was found to be an independent prognostic factor for HCC patients using the multivariate cox model. Moreover, Rad51 expression was found to be associated with the infiltration of immune cells (B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells) and was intimately linked to the expression of immune cell markers in HCC. Through the analysis of differentially coexpressed genes (DCGs) of Rad51, GO and KEGG enrichment analyses suggested that the expression level of Rad51 might be relevant to neuroactive ligand-receptor interactions, the cell cycle, DNA replication, homologous recombination, oocyte meiosis, and the Fanconi anemia pathway. These findings indicated that Rad51 is a valuable biomarker for the prognosis of patients with liver cancer and that its expression has a significant correlation with immune infiltrations.Abbreviations: HCC: hepatocellular carcinoma; ICGC: International Cancer Genome Consortium TCGA: The Cancer Genome Atlas; TIMER: Tumor Immune Estimation Resource; CAF: Cancer-associated fibroblast; GEPIA: Gene Expression Profiling Interactive Analysis; GSEA: Gene set enrichment analysis; OS: overall survival; PFS: progression-free survival; RFS: relapse-free survival; DSS: disease-specific survival. Partial cor: partial correlation coefficient; HPA: Human Protein Atlas; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; CAF: Cancer-associated fibroblast; DCGs: differentially co-expressed genes.

Dataset Information

Integrated Bioinformatics Analysis Identifies Heat Shock Factor 2 as a Prognostic Biomarker Associated With Immune Cell Infiltration in Hepatocellular Carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets