Heparanase is a novel biomarker for immune infiltration and prognosis in breast cancer.
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ABSTRACT:
SUBMITTER: Yang WJ
PROVIDER: S-EPMC8436937 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundBreast invasive cancer (BRCA) is the most common malignancy and the second leading cause of malignancy death among women. Signal transducers and activators of transcription (STAT) family played a vital role in regulating certain biological processes and could serve as biomarkers for many diseases or cancers.MethodsThe expression, prognostic value, and clinical functions of STAT family in BRCA were evaluated with several bioinformatics web portals.ResultsThe expression of STAT5A/5B were downregulated in BRCA in subgroup analyses based on race, age, gender, race, subclasses, tumor histology, menopause status, nodal metastasis status, and TP53 mutation. BRCA patients with high STAT5B expression had a better overall survival, relapse free survival, MDFS and post progression survival. STAT5B expression level can impact the prognosis in BRCA patients with positive PR status, negative Her2 status and wild type TP53. Moreover, STAT5B was positively correlated with immune cell infiltration and the level of immune biomarkers. Drug sensitivity revealed that low STAT5B expression was resistant to the many small molecules or drugs. Functional enrichment analysis revealed that STAT5B was involved in adaptive immune response, translational initiation, JAK-STAT signaling pathway, Ribosome, NF-kappa B signaling pathway and Cell adhesion molecules.ConclusionsSTAT5B was a biomarker associated with prognosis and immune infiltration in breast cancer.
| S-EPMC9981440 | biostudies-literature
Project description:Breast cancer is the malignant tumor with the highest incidence rate at present, and its incidence rate ranks first in the female population. COL11A1 is an important component of collagen XI and is considered to play an important role in a variety of connective tissue diseases. Recent studies have shown that COL11A1 is associated with the occurrence and development of many kinds of malignant tumors. However, its prognostic value in breast cancer and its correlation with immune cell infiltration in tumor tissue are not clear. In this paper, we reveal the prognostic value of COL11A1 in breast cancer and its tumor immune-related function through in-depth bioinformatics analysis. The expression of COL11A1 is abnormally upregulated in breast cancer and is significantly related to the poor prognosis of breast cancer. In the analysis of the clinical characteristics of the patients, we found that the expression level of COLL11A1 was closely related to lymph node metastasis, PAM50 (Prediction Analysis of Microarray 50) expression, clinical stage and so on. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) all suggest that COL11A1 is related to tumor immunity. Further study found that the COL11A1 expression was significantly correlated with the degree of immune infiltration and the expression of a variety of immune cell markers in tumor tissue. More importantly, COL11A1 can affect the prognosis of breast cancer patients by participating in the regulation of tumor immune infiltration. Therefore, we believe that COL11A1 is a very potential target for diagnosis and treatment of breast cancer.
| S-EPMC9500398 | biostudies-literature
Project description:Breast cancer is the most common malignancy in women, and there is evidence for the dual role of cell pyroptosis in tumor development. However, little is known about the relationship between cell pyroptosis and breast cancer and its prognostic value. We aimed to construct a prognostic model using cell-pyroptosis-related genes to provide innovative insights into the prognosis and treatment of breast cancer. We screened candidate genes for pyroptosis using public databases and identified 10 cell pyroptosis signature genes with the random forest method. Finally, a nomogram for predicting 1-, 3-, and 5-year survival probabilities was constructed. The differences in immune cell distributions between survival periods were similar across the breast cancer datasets. The 10 identified key pyroptosis factors showed a significant correlation with Her2, tumor-node-metastasis (TNM) stage, and survival of breast cancer. The risk scores correlated positively with the infiltration features of naive B cells, CD8+ T cells, atpdelnd mast cells, while they correlated negatively with those of M0 macrophages and dendritic cells. In conclusion, our findings confirm that cell pyroptosis is closely associated with breast cancer. Importantly, the prognostic complex values generated from the 10 cell-pyroptosis-related genes based on various clinical features may provide an important basis for future studies on the prognosis of breast cancer.
| S-EPMC9491236 | biostudies-literature
Project description:The chemokine CXCL9 (C-X-C motif chemokine ligand 9) has been reported to be required for antitumour immune responses following immune checkpoint blockade. In this study, we sought to investigate the potential value of CXCL9 according to immune responses in patients with breast cancer (BC). A variety of open-source databases and online tools were used to explore the expression features and prognostic significance of CXCL9 in BC and its correlation with immune-related biomarkers followed by subsequent verification with immunohistochemistry experiments. The CXCL9 mRNA level was found to be significantly higher in BC than in normal tissue and was associated with better survival outcomes in patients with ER-negative tumours. Moreover, CXCL9 is significantly correlated with immune cell infiltration and immune-related biomarkers, including CTLA4, GZMB, LAG3, PDCD1 and HAVCR2. Finally, we performed immunohistochemistry with breast cancer tissue samples and observed that CXCL9 is highly expressed in the ER-negative subgroup and positively correlated with the immune-related factors LAG3, PD1, PDL1 and CTLA4 to varying degrees. These findings suggest that CXCL9 is an underlying biomarker for predicting the status of immune infiltration in ER-negative breast cancer.
| S-EPMC8435794 | biostudies-literature
Project description:BackgroundCurrent studies on the role of ARHGAP39 mainly focused on its effect on neurodevelopment. However, there are few studies on the comprehensive analysis of ARHGAP39 in breast cancer.MethodsARHGAP39 expression level was analyzed based on the Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression Project (GTEx), and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database and validated by qPCR in various cell lines and tumor tissues. The prognostic value was analyzed using Kaplan-Meier curve analysis. CCK-8 and transwell assays were conducted to identify the biological function of ARHGAP39 in tumorigenesis. Signaling pathways related to ARHGAP39 expression were identified by the GO and KEGG enrichment analysis and gene set enrichment analysis (GSEA). The correlations between ARHGAP39 and cancer immune infiltrates were investigated via TIMER, CIBERSORT, ESTIMATE and tumor-immune system interactions database (TISIDB).ResultsARHGAP39 was overexpressed in breast cancer and associated with poor survival outcomes. In vitro experiments revealed that ARHGAP39 could facilitate the proliferation, migration, and invasion capability of breast cancer cells. GSEA analysis showed that the main enrichment pathways of ARHGAP39 was immunity-related pathways. Considering the immune infiltration level, ARHGAP39 was negatively associated with infiltrating levels of CD8 + T cell and macrophage, and positively associated with CD4 + T cell. Furthermore, ARHGAP39 was significantly negatively correlated with immune score, stromal score, and ESTIMATE score.ConclusionsOur findings suggested that ARHGAP39 can be used as a potential therapeutic target and prognostic biomarker in breast cancer. ARHGAP39 was indeed a determinant factor of immune infiltration.
| S-EPMC10184379 | biostudies-literature
Project description:Ferroptosis, a newly discovered way of cell death, has been proved to be involved in the oncogenesis and development of cancers, including colorectal cancer (CRC). Here, by identifying the differentially expressed genes (DEGs) from three CRC transcriptome microarray datasets (GSE20842, GSE23878, and GSE25070), we found that the expression of MT1G was significantly decreased in CRC tissues, and the patients with a high level of MT1G displayed a poor prognosis. Quantitative PCR (qPCR) further confirmed the downregulated MT1G in two CRC cells, HCT8 and HCT116. The colony-forming assay indicated that the MT1G overexpression exhibited a remarkable inhibition of cell proliferation in HCT8 and HCT116 cells. In addition, we explored the co-expressed genes of MT1G to gain a better understanding of its potential signaling pathways. Aberrantly expressed MT1G also affected the immune response of CRC patients. Collectively, these findings might deepen our comprehension on the potential biological implications of MT1G in CRC.
| S-EPMC9065264 | biostudies-literature
Project description:Breast cancer (BRCA) is a common malignancy worldwide that is associated with a high mortality rate. Despite recent improvements in diagnosis and treatment, there is an urgent need to investigate the processes underlying cancer progression and identify novel prognostic indicators. Anoikis, which plays a role in the development of human malignant tumors, has been gaining increasing interest from researchers. However, the potential role of anoikis-related genes (ANRGs) in the advancement of BRCA remains unknown. In this study, we aimed to assess the predictive value of ANRGs in BRCA, construct a prognostic model based on ANRGs, and explore the tumor microenvironment in different prognostic score groups. This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect clinical information and RNA sequencing data from patients with BRCA. Information on ANRGs was gathered from GeneCards and Harmonizome portals. A risk score model based on ANRGs was created using least absolute shrinkage and selection operator Cox (LASSO) regression analysis. Additionally, the study explored the tumor microenvironment and enriched pathways in different risk groups. Finally, a novel ANRG-based nomogram is developed. A total of 142 differentially expressed genes associated with survival were identified, of which 5 genes were selected to create the ANRG signature. The risk score based on this signature proved to be an independent prognostic factor. Further analysis revealed that different risk subgroups exhibited variations in the tumor microenvironment and drug sensitivities. Subsequently, a nomogram was developed using risk scores and clinicopathological factors. The decision curve analysis results suggest that patients with BRCA might derive clinical treatment benefits from utilizing this prognostic model. Based on the results of this study, the ANRG signature and nomograph established can be used for clinical decision-making in patients with BRCA.
| S-EPMC10615559 | biostudies-literature
Project description:BackgroundGlioma is the most common central nervous malignancy. Due to its poor survival outcomes, it is essential to identify novel individualized therapy. Oncolytic virus (OV) treatment is a key therapy regulating tumor microenvironment in malignant glioma. Herein, we aim to identify the key genes after OV infection and its role in glioma.MethodsPerforming an RNA-seq analysis, the differentially expressed genes (DEGs) between EV-A71-infection and mock group were screened with GFold values. DAVID online analysis was performed to identify the functional classification. Overall survival (OS) or disease-free survival (DFS) was evaluated to analyze the relation between PTBP1 expression levels and prognosis of glioma patients. Additionally, the ssGSEA and TIMER algorithms were applied for evaluating immune cell infiltration in glioma.ResultsFollowing EV-A71 infection in glioma cells, PTBP1, one of the downregulated DEGs, was found to be associated with multiple categories of GO and KEGG enrichment analysis. We observed elevated expression levels of PTBP1 across various tumor grades of glioma in comparison to normal brain samples. High PTBP1 expression had a notable impact on the OS of patients with low-grade glioma (LGG). Furthermore, we observed an obvious association between PTBP1 levels and immune cell infiltration in LGG. Notably, PTBP1 was regarded as an essential prognostic biomarker in immune cells of LGG.ConclusionOur research uncovered a critical role of PTBP1 in outcomes and immune cell infiltration of glioma patients, particularly in those with LGG.
| S-EPMC10556503 | biostudies-literature
Project description:Background: Pancreatic cancer (PC) is a malignant gastrointestinal tumor with a terrible prognosis. Cuproptosis is a recently discovered form of cell death. This study is intended to explore the relationship between cuproptosis-related lncRNAs (CRLncs) signature with the prognosis and the tumor microenvironment (TME) of PC. Methods: Transcript sequencing data of PC samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and LASSO regression analysis were employed to construct the prognostic signature based on CRLncs associated with PC survival. A nomogram was created according to this signature, and the signaling pathway enrichment was analyzed. Subsequently, we explored the link between this prognostic signature with the mutational landscape and TME. Eventually, drug sensitivity was predicted based on this signature. Results: Forty-six of 159 CRLncs were most significantly relevant to the prognosis of PC, and a 6-lncRNA prognostic signature was established. The expression level of signature lncRNAs were detected in PC cell lines. The AUC value of the ROC curve for this risk score predicting 5-year survival in PC was .944, which was an independent prognostic factor for PC. The risk score was tightly related to the mutational pattern of PC, especially the driver genes of PC. Single-sample gene set enrichment analysis (ssGSEA) demonstrated a significant correlation between signature with the TME of PC. Ultimately, compounds were measured for therapy in high-risk and low-risk PC patients, respectively. Conclusion: A prognostic signature of CRLncs for PC was established in the current study, which may serve as a promising marker for the outcomes of PC patients and has important forecasting roles for gene mutations, immune cell infiltration, and drug sensitivity in PC.
| S-EPMC9880288 | biostudies-literature
Project description:BACKGROUND Cervical cancer is one of the most common malignances among women globally. This study aimed to construct a novel immune-related signature to predict the prognosis and immune infiltration of cervical cancer. MATERIAL AND METHODS Transcriptomic profiles and corresponding clinical information of cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database and GEO database. The hub immune-related genes were screened and selected using Cox regression analysis and LASSO regression analysis. A novel signature was established based on the expression levels and corresponding coefficients of the selected hub immune-related genes. Kaplan-Meier survival curve and ROC curve illustrated the prognostic value of this novel signature in cervical cancer. The predictive accuracy and stability of this novel signature were confirmed in the validation cohort, internal testing set and external testing set. Then, a nomogram was constructed to predict individual survival probability of cervical cancer patient. The association between the risk scores of novel signature and immune infiltration was investigated through single-sample gene set enrichment analysis (ssGSEA). RESULTS Ten hub immune-related genes (TFRC, SPP1, CAMP, CSF2, TUBB3, ZAP70, CHIT1, LEPR, DLL4, and DES) were selected to construct a novel signature. The risk score of this novel signature could be an independent prognostic factor in cervical cancer, which divided patients into high-risk and low-risk groups. The patients in high-risk groups showed significantly worse overall survival rates than those in low-risk groups in all training and validation cohorts (all P<0.05). A nomogram model was constructed based on the risk score of the novel signature and other clinical characteristics, which achieved the highest clinical net benefit across the entire range of reasonable threshold probabilities (concordance index=0.813). Furthermore, gene enrichment analysis revealed that the novel signature was closely related with immunology. The novel signature was negatively correlated with the infiltration of most immune cell types, especially T cell subsets (P<0.001). CONCLUSIONS The novel signature could comprehensively predict the prognosis and immune infiltration of cervical cancer. It may provide new insights for the precise treatment in cervical cancer.
| S-EPMC10066621 | biostudies-literature