Project description:ObjectiveTriple negative breast cancer (TNBC) is a kind of cancer that endangers the lives of women all over the world in the 21st century. Heat shock protein member 8 (HSPA8) is the chaperone gene of the heat shock protein family. It is involved in many cellular functions. For example, it promotes the circulation between ATP and ADP, participates in protein folding, and can change the vitality of the cell and inhibit its growth. However, the abnormal expression of HSPA8 gene in TNBC and its diagnostic and prognostic significance still need to be further studied.MethodsFirst, we used related databases (such as TCGA, GEO, GTEx, ONCOMINE, TIMER2.0, UALCAN, HPA, STRING, CCLE, and Kaplan-Meier plotter databases) to analyze the relationship between HSPA8 and TNBC by bioinformatics. Then, the analysis using only a small part of the experimental work is used to explain our findings. For example, HSPA8 protein expression was evaluated by immunohistochemical method in TNBC tissues. Western blotting experiments were carried out to verify the results. Then, the clinicopathological characteristics of patients with TNBC were analyzed by R software and Cox regression analysis. On the basis, a nomogram is constructed to estimate the 1-, 3-, and 5-year overall survival (OS). The prognostic nomogram performance was calibrated and evaluated by the calibration curve and receiver operating characteristic (ROC) curve.ResultsIn the study, we analyzed the three GEO databases (including GSE86945, GSE106977, and GSE102088) and found that HSPA8 is one of the central genes of TNBC. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) researches indicated that HSPA8 was mainly involved in partner-mediated autophagy, mRNA catabolism, neutrophil activation, immune response, protein targeting, RNA splicing, RNA catabolism, and other biological processes. Next, we used bioinformatics technology to find that the expression level of HSPA8 in breast cancer (BC) and TNBC samples was significantly higher than that in normal breast tissues, which was determined by analyzing hospital patient samples and related experiments. In addition, the expression level of HSPA8 in BC and TNBC samples was significantly correlated with clinical indexes such as TNM stage. The Cox analysis revealed that the expression of HSPA8 in TNBC had significant clinical prognostic value. The results of nomogram and ROC test show that HSPA8 has significant predictive ability in TNBC. The results of immune infiltration of HSPA8 through the TIMER2.0 database showed that there was a significant correlation between HSPA8 and immune cell subsets.ConclusionsOur results show that the expression of HSPA8 in TNBC has important clinical diagnostic significance and clarify the potential molecular mechanism that promotes the evolution of TNBC. The high expression of HSPA8 may be related with the poor clinical outcome of TNBC. This helps to provide us with a new direction of TNBC targeted therapy.

Project description:Background: We have established a statistical approach on building a transcriptional regulatory network in silico at a global transcriptome scale. Here, we characterize clinical relevant gene activities regulated by a transcription factor-estrogen-related receptor gamma (ESRRG) via such approach. Methods: We measured gene expression relationship between ESRRG and its target gene via univariate coefficient of intrinsic dependence and Galton Pearson’s correlation coefficient. A few more bioinformatics tools were used for further investigation on ESRRG. Results: ESRRG is a negative determinant of lymphovascular invasion, lymph nodal category, stage, histological grade, nuclear pleomorphism and tubule formation in ER(+) infiltrating ductal carcinoma of breast. Interestingly, ESRRG was the only one in the final intersection of Venn Diagram analyses for determinants of those clinical indices. We established an ESRRG core network consisting of 118 probes. Both MYB and ARNT2 were up-regulated by ESRRG and in two ESRRG subnetworks (29 probes, 89 probes), respectively. We observed genes for tumor suppressive activities and responsiveness to anticancer treatments within ESRRG core network and a conserved protective role of ESRRG. Conclusions: ESRRG is a tumor suppressor typically for ER(+) breast cancer and up-regulates tumor suppressor genes mostly within ERα transcriptional regulatory network. An ESRRG core network reveals ESRRG to be a favorable marker and MYB to be the main partner for its cancer protective role during early tumor promotion. But, ARNT2 is an additional partner of ESRRG during early tumor progression. Impact: A core ESRRG transcriptional regulatory network indicates the major clinical impact of ESRRG. 181 surgical specimens of primary infiltrating ductal carcinoma (IDC) were obtained from patients who underwent surgery at National Taiwan University Hospital (NTUH) between 1998 and 2007. They include 90 ER(+) IDCs and 91 ER(-) IDCs. Tissue samples were excised, snap frozen in liquid nitrogen, and stored at -80℃. Breast cancer samples containing relatively pure cancer as defined by greater than 50% tumor cells per high-power field examined in an adjacent section of tumor sample were for this study (Lien HC, et al. Oncogene 2007; 26: 7859-71). Twenty five non-tumor samples were surgically taken from breast cancer patients in 181 IDC patients to generate 25 gene expression profiles as a control in this study. All patients had given informed consent according to the guidelines approved by the Institutional Review Board at NTUH. The matrix file linked to the bottom of this Series includes reanalyzed data from the 119 Samples of this Series and 87 Samples from Series GSE9309 and GSE17040.

Project description:Fas apoptosis inhibitory molecule 2 (FAIM2) is an important member of the transmembrane BAX inhibitor motif containing (TMBIM) family. However, the role of FAIM2 in tumor prognosis and immune infiltration has rarely been studied. Here, we conducted a pan-cancer analysis to explore the role of FAIM2 in various tumors and further verified the results in glioma through molecular biology experiment. FAIM2 expression and clinical stages in tumor samples and para-cancerous samples were analyzed by TIMER2 database, GEPIA database, and the TISIDB database. The role of FAIM2 on prognosis was analyzed via GEPIA2. We utilized the ESTIMATE algorithm to evaluate the ImmuneScore and StromalScore of various tumors. In addition, we explored the correlation between FAIM2 expression and tumor immune cell infiltration by the TIMER2 database. The immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methylation related to FAIM2 were analyzed based on the TCGA database. The correlation between FAIM2 expression with Copy number variations (CNV) and methylation is explored by GSCA database. Protein-Protein Interaction (PPI) analysis was obtained from the STRING database and the CellMiner database was used to explore the association between FAIM2 expression and drug response. FAIM2 co-expression genes were studied by the LinkedOmics database. Immunohistochemistry, Western Blotting Analysis, Cell Viability Assay, Colony Formation Assay, and Edu staining assay were used in the molecular biology experiments section. The FAIM2 expression was down-regulated in most tumors and highly expressed FAIM2 was associated with a better prognosis in several cancers. FAIM2 plays an essential role in the tumor microenvironment and is closely associated with immune Infiltration in various tumors. The expression of FAIM2 was closely correlated to TMB, MSI, MMR, CNV, and DNA methylation. Furthermore, FAIM2 related genes in the PPI network and its co-expression genes in glioma are involved in a large number of immune-related pathways. Molecular biology experiments verified a cancer suppressor role for FAIM2 in glioma. FAIM2 may serve as a potential pan-cancer biomarker for prognosis and immune infiltration, especially in glioma. Moreover, this study might provide a potential target for tumor immunotherapy.

Project description:Background: We have established a statistical approach on building a transcriptional regulatory network in silico at a global transcriptome scale. Here, we characterize clinical relevant gene activities regulated by a transcription factor-estrogen-related receptor gamma (ESRRG) via such approach. Methods: We measured gene expression relationship between ESRRG and its target gene via univariate coefficient of intrinsic dependence and Galton Pearson’s correlation coefficient. A few more bioinformatics tools were used for further investigation on ESRRG. Results: ESRRG is a negative determinant of lymphovascular invasion, lymph nodal category, stage, histological grade, nuclear pleomorphism and tubule formation in ER(+) infiltrating ductal carcinoma of breast. Interestingly, ESRRG was the only one in the final intersection of Venn Diagram analyses for determinants of those clinical indices. We established an ESRRG core network consisting of 118 probes. Both MYB and ARNT2 were up-regulated by ESRRG and in two ESRRG subnetworks (29 probes, 89 probes), respectively. We observed genes for tumor suppressive activities and responsiveness to anticancer treatments within ESRRG core network and a conserved protective role of ESRRG. Conclusions: ESRRG is a tumor suppressor typically for ER(+) breast cancer and up-regulates tumor suppressor genes mostly within ERα transcriptional regulatory network. An ESRRG core network reveals ESRRG to be a favorable marker and MYB to be the main partner for its cancer protective role during early tumor promotion. But, ARNT2 is an additional partner of ESRRG during early tumor progression. Impact: A core ESRRG transcriptional regulatory network indicates the major clinical impact of ESRRG. 181 surgical specimens of primary infiltrating ductal carcinoma (IDC) were obtained from patients who underwent surgery at National Taiwan University Hospital (NTUH) between 1998 and 2007. They include 90 ER(+) IDCs and 91 ER(-) IDCs. Tissue samples were excised, snap frozen in liquid nitrogen, and stored at -80℃. Breast cancer samples containing relatively pure cancer as defined by greater than 50% tumor cells per high-power field examined in an adjacent section of tumor sample were for this study (Lien HC, et al. Oncogene 2007; 26: 7859-71). Twenty five non-tumor samples were surgically taken from breast cancer patients in 181 IDC patients to generate 25 gene expression profiles as a control in this study. All patients had given informed consent according to the guidelines approved by the Institutional Review Board at NTUH. The matrix file linked to the bottom of this Series includes reanalyzed data from the 119 Samples of this Series and 87 Samples from Series GSE9309 and GSE17040.

Project description:Purpose: Breast cancer is a highly heterogeneous malignancy, seriously threatening female health worldwide and inducing higher mortalities. Few have the studies evaluated Fms-like TyrosineKinase-3 (FLT3) in prognostic risk, immunotherapy or any other treatment of breast cancer. Our study focused on investigating the function of FLT3 in breast cancer. Patients and methods: Based on transcriptome and methylation data mined from The Cancer Gene Atlas (TCGA), we explored the clinical features of FLT3 expression in 1079 breast cancer samples. RT-qPCR in cell lines and tissue samples was used to verify the expression difference of FLT3. Kaplan-Meier survival analysis and cox regression models were employed for screening of FLT3 with potential prognostic capacity. Subsequently, functional analysis of the co-expressed genes was conducted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene-set enrichment analysis (GSEA). The correlation between FLT3 expression and tumor immune infiltration was jointly analyzed with estimate, ssGSEA, TIMER, and TISIDB. Then we employed checkpoint-related molecules, immunophenoscore (IPS), and tumor mutation burden (TMB) to assess the efficacy of immuno-checkpoint inhibitors (ICIs). Pearson correlation coefficient was employed to exam the association between DNA methylation and FLT3 expression. Results: FLT3 displays an elevated expression in breast cancer than normal pairs and is significantly associated with multiple clinical characteristics like age, menopause status, histological type, pathological stage, and molecular subtype as well as increased overall survival (OS). Additionally, FLT3 is a favorable independent prognostic factor. GO, KEGG, and GSEA suggested that FLT3 was associated with diversified immune-related features. FLT3 expression is correlated with the abundance of various immune cells namely CD4+T cell, CD8+ T cell, myeloid dendritic cell, and neutrophil as well as immune inhibitors especially CTLA4, which is positively correlated with FLT3 expression. Moreover, TMB displayed a negative correlation with FLT3 expression while IPS showed adverse tendency. Ultimately, the methylation of FLT3 downregulates the gene expression and closely binds to a few clinical parameters. Conclusion: FLT3 can be used for prognostic prediction and is relevant to immune infiltration in breast cancer. FLT3 may pave the way for future novel immunotherapies.

Project description:ObjectiveThe morbidity of hepatocellular carcinoma (HCC) is increasing annually. The aim of this study is to investigate the molecular mechanisms of upregulated genes in HCC using bioinformatic methods, so as to identify new potential biological markers.MethodsThe Gene Expression Omnibus database (GEO database) was mined for HCC datasets, which were screened for hub genes and subjected to (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis. The hub genes were analyzed in terms of Receiver Operating Characteristic (ROC) and methylation levels. Validation of hub genes was completed through basic pathological alterations based on the protein and gene expression level of hub genes. The correlation of genes with immune infiltration in HCC was analyzed based on the database Timer 2.0, and the prognosis as well as survival of hub genes in HCC was analyzed using R studio software. Finally, we performed a gene combination drug analysis on the potential therapeutic targets in HCC.ResultsExpression-up-regulated genes were screened via differential analysis, which were mainly enriched in cell cycles and DNA replication pathways. Five hub genes, BRCA1 associated RING domain 1 (BARD1), Mismatch Repair Protein (MSH2), Recombinant H2A Histone Family, Member X (H2AFX), Recombinant H2A Histone Family, Member z (H2AFZ) and Chromosome 18 Open Reading Frame 54 (C18orf54) were identified using a Protein-Protein Interaction Networks (PPI). After a comprehensive analysis of ROC curves and methylation gene mutation sites, C18orf54 was localized followed by basic experiments, so as to verify the C18orf54 upregulated in HCC. Based on the online database Timer 2.0, the immune infiltration of C18orf54 gene in HCC was analyzed, which was found to be negatively correlated with CD4+ T cells and macrophages in HCC, meanwhile a further refinement of the immune checkpoint correlation analysis revealed that C18orf54 was mainly correlated with Hepatitis A virus cellular receptor 2 (HAVCR2), T cell immunoreceptor with Ig and ITIM domains (TIGIT) and Cytotoxic T lymphocyte associate protein-4 (CTLA4). The prognosis and survival of patients with HCC expressing C18orf54 were also analyzed, and it was found that such patients had a higher incidence of adjacent liver tissue inflammation, a higher child-Pugh grade score and a higher rate of residual tumor recurrence. Similarly, the prognosis was worse in the subset of patients with C18orf54. Finally, we performed a combined genetic analysis, which suggested that cyclosporine, quercetin, testosterone and calcitriol might be effective in reducing C18orf54 mRNA expression.ConclusionC18orf54 is involved in the immune infiltration and promotes the poor prognosis of HCC, which could be a candidate biomarker for HCC.

Dataset Information

CXCL9 Is a Potential Biomarker of Immune Infiltration Associated With Favorable Prognosis in ER-Negative Breast Cancer.

Publications

CXCL9 Is a Potential Biomarker of Immune Infiltration Associated With Favorable Prognosis in ER-Negative Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets