Pan-Cancer Integrated Analysis of HSF2 Expression, Prognostic Value and Potential Implications for Cancer Immunity

Chen, Fei; Fan, Yumei; Liu, Xiaopeng; Zhang, Jianhua; Shang, Yanan; Zhang, Bo; Liu, Bing; Hou, Jiajie; Cao, Pengxiu; Tan, Karsoon

doi:10.3389/fmolb.2021.789703

Cited by 6 publications

(4 citation statements)

References 55 publications

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“…DNA methylation is a form of epigenetic modification that regulates gene expression, and hypermethylation may contribute to the inactivation of tumor suppressor genes [ 49 ]. Hence, the associations between DNA methylation and CD276 expression in different types of cancer were investigated, and the results obtained revealed that the DNA methylation level of CD276 was negatively correlated with CD276 expression in many types of cancer, including BLCA, BRCA, HNSC, KIRP, LUAD, LUSC and TGCT, whereas it was positively correlated with other cancer types, including PCPG.…”

Section: Resultsmentioning

confidence: 99%

Multi-omics analyses of CD276 in pan-cancer reveals its clinical prognostic value in glioblastoma and other major cancer types

et al. 2023

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Background CD276 (also known as B7-H3) is one of the most important immune checkpoints of the CD28 and B7 superfamily, and its abnormal expression is closely associated with various types of cancer. It has been shown that CD276 is able to inhibit the function of T cells, and that this gene may potentially be a promising immunotherapy target for different types of cancer. Methods Since few systematic studies have been published on the role of CD276 in cancer to date, the present study has employed single-cell sequencing and bioinformatics methods to analyze the expression patterns, clinical significance, prognostic value, epigenetic alterations, DNA methylation level, tumor immune cell infiltration and immune functions of CD276 in different types of cancer. In order to analyze the potential underlying mechanism of CD276 in glioblastoma (GBM) to assess its prognostic value, the LinkedOmics database was used to explore the biological function and co-expression pattern of CD276 in GBM, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. In addition, a simple validation of the above analyses was performed using reverse transcription-quantitative (RT-q)PCR assay. Results The results revealed that CD276 was highly expressed, and was often associated with poorer survival and prognosis, in the majority of different types of cancer. In addition, CD276 expression was found to be closely associated with T cell infiltration, immune checkpoint genes and immunoregulatory interactions between lymphoid and a non-lymphoid cell. It was also shown that the CD276 expression network exerts a wide influence on the immune activation of GBM. The expression of CD276 was found to be positively correlated with neutrophil-mediated immunity, although it was negatively correlated with the level of neurotransmitters, neurotransmitter transport and the regulation of neuropeptide signaling pathways in GBM. It is noteworthy that CD276 expression was found to be significantly higher in GBM compared with normal controls according to the RT-qPCR analysis, and the co-expression network, biological function and chemotherapeutic drug sensitivity of CD276 in GBM were further explored. In conclusion, the findings of the present study have revealed that CD276 is strongly expressed and associated with poor prognosis in most types of cancer, including GBM, and its expression is strongly associated with T-cell infiltration, immune checkpoint genes, and immunomodulatory interactions between lymphocytes and non-lymphoid cells. Conclusions Taken together, based on our systematic analysis, our findings have revealed important roles for CD276 in different types of cancers, especially GBM, and CD276 may potentially serve as a biomarker for cancer.

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Section: Resultsmentioning

confidence: 99%

Multi-omics analyses of CD276 in pan-cancer reveals its clinical prognostic value in glioblastoma and other major cancer types

et al. 2023

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“…As a Heat shock protein, it has been reported to be associated with cellular stress and aging in diverse cells, including mesenchymal stem cells, skeletal muscle, and T cells ( 49 – 51 ). Through various bioinformatics, it has been related to immune cell infiltration and tumor immune microenvironment across different cancer types ( 52 ). Finally, the autophagy-related gene ATG10 regulated the formation of autophagosomes and participated in the anti-virus immune response ( 53 ).…”

Section: Discussionmentioning

confidence: 99%

Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC

Shi

Liu

et al. 2023

Front. Immunol.

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ObjectivesThe exhausted CD8+T (Tex) cells are a unique cell population of activated T cells that emerges in response to persistent viral infection or tumor antigens. Tex cells showed the characteristics of aging cells, including weakened self-renewal ability, effector function inhibition, sustained high expression of inhibitory receptors including PD-1, TIGIT, TIM-3, and LAG-3, and always accompanied by metabolic and epigenetic reprogramming. Tex cells are getting more and more attention in researching immune-related diseases and tumor immunotherapy. However, studies on Tex-related models for tumor prognosis are still lacking. We hope to establish a risk model based on Tex-related genes for HCC prognosis.MethodsTex-related GEO datasets from different pathologic factors (chronic HBV, chronic HCV, and telomere shortening) were analyzed respectively to acquire differentially expressed genes (DEGs) by the ‘limma’ package of R. Genes with at least one intersection were incorporated into Tex-related gene set. GO, KEGG, and GSEA enrichment analyses were produced. Hub genes and the PPI network were established and visualized by the STRING website and Cytoscape software. Transcription factors and targeting small molecules were predicted by the TRUST and CLUE websites. The Tex-related HCC prognostic model was built by Cox regression and verified based on different datasets. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms tested immunotherapy sensitivity. Finally, qRT-PCR and Flow Cytometry was used to confirm the bioinformatic results.ResultsHub genes such as AKT1, CDC6, TNF and their upstream transcription factor ILF3, Regulatory factor X-associated protein, STAT3, JUN, and RELA/NFKB1 were identified as potential motivators for Tex. Tex-related genes SLC16A11, CACYBP, HSF2, and ATG10 built the HCC prognostic model and helped with Immunotherapy sensitivity prediction.ConclusionOur study demonstrated that Tex-related genes might provide accurate prediction for HCC patients in clinical decision-making, prognostic assessment, and immunotherapy. In addition, targeting the hub genes or transcription factors may help to reverse T cell function and enhance the effect of tumor immunotherapy.

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“…The correlations between the hub gene expression of the COADREAD dataset and the immune-related gene set were calculated using the “corr.test” function of Spearman’s algorithm ( https://rpubs.com/aaronsc32/spearman-rank-correlation ), and the correlation heatmap was drawn. The immune checkpoint genes reported by Chen et al ( 26 ) were used to calculate and plot the correlations between these genes and the hub genes in the COADREAD dataset.…”

Section: Methodsmentioning

confidence: 99%

Screening of key genes related to ferroptosis and a molecular interaction network analysis in colorectal cancer using machine learning and bioinformatics

Feng¹,

Jiang²,

Kou³

2023

J Gastrointest Oncol

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Background This study sought to identify the key genes and molecular interactions related to ferroptosis in colorectal cancer (CRC) using machine-learning and bioinformatics analyses. Methods The Gene Expression Omnibus (National Institutes of Health, US) datasets for CRC were downloaded from the National Center for Biotechnology Information (NCBI) ( https://www.ncbi.nlm.nih.gov/ ). The 291 ferroptosis genes were downloaded and screened from the FerrDb ( http://www.zhounan.org/ferrdb ) and GeneCards ( https://www.genecards.org/ ) databases. The least absolute shrinkage and selection operator regression model and support vector machine model were constructed to identify the different ferroptosis-related hub genes. The immune infiltrates were identified and a survival curve analysis was conducted. Results We identified 11 ferroptosis-related differentially expressed genes (DEGs) from the COADREAD (Colon and Rectal Cancer) dataset. We found that angiopoietin-related protein 7 ( ANGPTL7 ) gene expression was positively correlated to both the neuroglobin ( NGB ) (r=0.678) and ceruloplasmin (CP) (r=0.454) genes but was negatively correlated with transferrin receptor 2 ( TFR2 ) expression (r=–0.426). In addition, TFR2 gene expression was positively correlated with the arachidonate lipoxygenase 3 ( ALOXE3 ) (r=0.452) and carbonic anhydrase 9 ( CA9 ) (r=0.411) genes. A total of 4 hub genes were identified by the machine-learning analysis [i.e., NADPH oxidase 4 ( NOX4 ), TFR2, ALOXE3 , and CA9 ]. The expression of the NOX4 gene was significantly positively correlated with neutrophil (r=0.543) and M0 macrophage (r=0.422) infiltration. In addition, a positive correlation between ALOXE3 and activated natural-killer cells (r=0.356) was found. Conversely, the NOX4, TFR2 , and CA9 genes were negatively correlated with the resting mast cells. A strong negative correlation was observed between NOX4 and CD160 antigen ( CD160 ) expression; however, a significant positive correlation was observed between NOX4 and transforming growth factor beta receptor 1 ( TGFBR1 ) expression (r=0.397). The patients had a more favorable prognosis when the NOX4 expression levels were relatively low. Conclusions Our study identified 4 ferroptosis-related DEGs in CRC (i.e., NOX4, TFR2 , ALOXE3 , and CA9 ), and fur...

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Pan-Cancer Integrated Analysis of HSF2 Expression, Prognostic Value and Potential Implications for Cancer Immunity

Cited by 6 publications

References 55 publications

Multi-omics analyses of CD276 in pan-cancer reveals its clinical prognostic value in glioblastoma and other major cancer types

Multi-omics analyses of CD276 in pan-cancer reveals its clinical prognostic value in glioblastoma and other major cancer types

Establishment and validation of exhausted CD8+ T cell feature as a prognostic model of HCC

Screening of key genes related to ferroptosis and a molecular interaction network analysis in colorectal cancer using machine learning and bioinformatics

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