scholarly journals The Novel Methylation Biomarker NPY5R Sensitizes Breast Cancer Cells to Chemotherapy

2022 ◽  
Vol 9 ◽  
Author(s):  
Jiazhou Liu ◽  
Xiaoyu Wang ◽  
Jiazheng Sun ◽  
Yuru Chen ◽  
Jie Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ectopic Expression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Novel ◽  
Clinical Prognosis ◽  
Stat3 Signaling ◽  
Pathway Activation ◽  
Stat3 Signaling Pathway ◽  
Gene Modules

Breast cancer (BC) is the most common tumor in women, and the molecular mechanism underlying its pathogenesis remains unclear. In this study, we aimed to investigate gene modules related to the phenotypes of BC, and identify representative candidate biomarkers for clinical prognosis of BC patients. Using weighted gene co-expression network analysis, we here identified NPY5R as a hub gene in BC. We further found that NPY5R was frequently downregulated in BC tissues compared with adjacent tumor-matched control tissues, due to its aberrant promoter CpG methylation which was confirmed by methylation analysis and treatment with demethylation agent. Higher expression of NPY5R was closely associated with better prognosis for BC patients. Gene set enrichment analysis showed that transcriptome signatures concerning apoptosis and cell cycle were critically enriched in specimens with elevated NPY5R. Ectopic expression of NPY5R significantly curbed breast tumor cell growth, induced cell apoptosis and G2/M arrest. Moreover, NPY5R also promoted the sensitivity of BC cells to doxorubicin. Mechanistically, we found that NPY5R restricted STAT3 signaling pathway activation through interacting with IL6, which may be responsible for the antitumor activity of NPY5R. Collectively, our findings indicate that NPY5R functions as a tumor suppressor but was frequently downregulated in BC.

scholarly journals Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

2021 ◽  
Vol 27 ◽  
Author(s):  
Aoshuang Qi ◽  
Mingyi Ju ◽  
Yinfeng Liu ◽  
Jia Bi ◽  
Qian Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Antigen Processing ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Gene Set ◽  
Antigen Processing And Presentation

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC.Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis.Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) < 1), and HLA-F was risky (HR > 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC.Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

scholarly journals Enolase 1 Correlated With Cancer Progression and Immune-Infiltrating in Multiple Cancer Types: A Pan-Cancer Analysis

2021 ◽  
Vol 10 ◽  
Author(s):  
Wenhua Xu ◽  
Wenna Yang ◽  
Chunfeng Wu ◽  
Xiaocong Ma ◽  
Haoyu Li ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Stress Protein ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Multiple Cancer ◽  
Clinical Prognosis ◽  
Multiple Tumor ◽  
Normal Tissues

Enolase 1 (ENO1) is an oxidative stress protein expressed in endothelial cells. This study aimed to investigate the correlation of ENO1 with prognosis, tumor stage, and levels of tumor-infiltrating immune cells in multiple cancers. ENO1 expression and its influence on tumor stage and clinical prognosis were analyzed by UCSC Xena browser, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and GTEx Portal. The ENO1 mutation analysis was performed by cBio Portal, and demonstrated ENO1 mutation (1.8%) did not impact on tumor prognosis. The relationship between ENO1 expression and tumor immunity was analyzed by Tumor Immune Estimation Resource (TIMER) and GEPIA. The potential functions of ENO1 in pathways were investigated by Gene Set Enrichment Analysis. ENO1 expression was significantly different in tumor and corresponding normal tissues. ENO1 expression in multiple tumor tissues correlated with prognosis and stage. ENO1 showed correlation with immune infiltrates including B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells, and tumor purity. ENO1 was proved to be involved in DNA replication, cell cycle, apoptosis, glycolysis process, and other processes. These findings indicate that ENO1 is a potential prognostic biomarker that correlates with cancer progression immune infiltration.

scholarly journals Prognostic Significance of SQSTM1 in Breast Cancer: A Comprehensive Analysis

2020 ◽  
Author(s):  
Yang Liu ◽  
Qian Du ◽  
Dan Sun ◽  
Ruiying Han ◽  
Mengmeng Teng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Somatic Mutation ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Regulation Mechanism ◽  
Breast Cancer Patients ◽  
Gene Set ◽  
Multiple Datasets

Abstract Background: SQSTM1 (Sequestosome 1, p62) is degraded by activated autophagy and involved in the progression of in various types of cancers. However, the prognostic role and underlying regulation mechanism of SQSTM1 in the progression and development of breast cancer remain unclear.Methods: In this study, 1336 samples with available mRNA data from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database and 27 formalin fixation and paraffin embedding (FFPE) tissue samples from the First Affiliated Hospital of Xi’an Jiaotong University were collected to evaluate SQSTM1 expression in mRNA and protein levels. Kaplan–Meier and Cox regression were used for revealing prognostic value in three independent breast cancer independent datasets. Tumor Immune Estimation Resource (TIMER) database and Gene Set Variation Analysis (GSVA) was used to explore the relationship of SQSTM1 mRNA expression and immune infiltration level in breast cancer. Dysregulation mechanisms of SQSTM1 were also explored including copy number variation (CNV), somatic mutation, epigenetic alterations and other transcription and post-transcription level using multiple datasets. Finally, Gene Set Enrichment Analysis (GSEA) was constructed to elucidate functional regulating performance of SQSTM1 in breast cancer.Results: The results showed that mRNA and protein level of SQSTM1 were significantly elevated in breast cancer and receiver operating characteristic (ROC) curve showed that p62 may act as diagnostic biomarker. Lower expression of SQSTM1 predicted better outcome through multiple datasets. It was also found that SQSTM1 correlated with immune infiltrates in breast cancer. Moreover, CNV and methylation of SQSTM1 DNA was correlated with SQSTM1 dysregulation and act as prognostic factors for breast cancer patients. Yet, somatic mutation status of SQSTM1 didn’t show any prognostic relevance. We also identified diverse transcription factors that directly bound to SQSTM1 DNA and the miRNAs which may regulate SQSTM1 mRNA. Finally, functional enrichment analysis revealed that SQSTM1 is related to cell signal transduction, oxidative stress and autophagy in breast cancer.Conclusion: Our findings revealed that SQSTM1 plays a key role in the progression of breast cancer and might be a promising biomarker for the diagnosis and personalized treatment of breast cancer patients.

The Role of PAX2 in Breast Cancer: A Study Based on Bioinformatics Analysis and in Vitro Validation

2021 ◽  
Author(s):  
Shan Yang ◽  
Wei Gao ◽  
Haoqi Wang ◽  
Xi Zhang ◽  
Yunzhe Mi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Growth ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Migration And Invasion ◽  
Clinical Samples

Abstract Background: Breast cancer (BC) is the most frequently diagnosed cancer in women and is the second most common cancer among newly diagnosed cancers worldwide. Studies have shown that paired box 2 (PAX2) participates in the tumorigenesis of some cancer cells. However, the functions of PAX2 in the BC context are still unclear.Methods: Transcriptome expression profiles and clinicopathological information of BC were download from the TCGA database. Then the expression level and prognostic value in TCGA database were explored. Gene Set Enrichment Analysis (GSEA) and functional enrichment analysis were performed to investigate the functions and pathways of PAX2. Moreover, RT-qPCR was used to determine the expression of PAX2 in BC tissues, and the predictive value of PAX2 in clinical samples was assessed. CCK-8 assay was used to evaluate cell growth. The migration and invasion capacities of cells were assessed by wound healing assay and Transwell assay.Results: PAX2 was up-regulated in the TCGA-BC datasets. GSEA analysis suggested that PAX2 might be involved in the regulation of MAPK signaling pathways and so on. Moreover, PAX2 was overexpressed in BC tissues, and PAX2 expression was associated with menopause. PAX2 deficiency could inhibit the growth, migration, and invasion of BC cells.Conclusion: This study suggested that PAX2 was up-regulated in BC, which inhibited BC cell growth, migration, and invasion. Thus, PAX2 could be a potential therapeutic target for BC.

Immune-related gene based prognostic signature for the risk stratification analysis of breast cancer

2021 ◽  
Vol 16 ◽  
Author(s):  
Dongqing Su ◽  
Qianzi Lu ◽  
Yi Pan ◽  
Yao Yu ◽  
Shiyuan Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Breast Cancer Patients ◽  
Cox Regression Analysis ◽  
Score Model

Background: Breast cancer has plagued women for many years and caused many deaths around the world. Method: In this study, based on the weighted correlation network analysis, univariate Cox regression analysis and least absolute shrinkage and selection operator, 12 immune-related genes were selected to construct the risk score for breast cancer patients. The multivariable Cox regression analysis, gene set enrichment analysis and nomogram were also conducted in this study. Results: Good results were obtained in the survival analysis, enrichment analysis, multivariable Cox regression analysis and immune-related feature analysis. When the risk score model was applied in 22 breast cancer cohorts, the univariate Cox regression analysis demonstrated that the risk score model was significantly associated with overall survival in most of the breast cancer cohorts. Conclusion: Based on these results, we could conclude that the proposed risk score model may be a promising method, and may improve the treatment stratification of breast cancer patients in the future work.

scholarly journals Pathway Interactions Based on Drug-Induced Datasets

2019 ◽  
Vol 18 ◽  
pp. 117693511985151 ◽  
Author(s):  
Shinuk Kim
Keyword(s):  
Breast Cancer ◽  
Valproic Acid ◽  
Epithelial Cells ◽  
Sample Size ◽  
Drug Combination ◽  
Trichostatin A ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Drug Induced

In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. We found meaningful pathways using gene set enrichment analysis and identified intradrug and interdrug pathway interactions, which implied the influence of drug combination. Among the top 20 enrichment pathways that were wortmannin induced, there were a total of 37 intradrug pathway interactions via common genes. Thirty-seven pathway interactions were induced by valproic acid, 11 induced by trichostatin A, 20 induced by LY294002, and 59 induced by sirolimus, all via common genes. The number of interdrug-induced pathway interactions ranged from one pair of pathways to 23. The pair of ERBB_SIGNALING and INSULIN_SIGNALING pathways showed the highest score from a pair of 2 individual drugs. The highest number of pathway interactions was observed between the drugs 17-allylamino-geldanamycin and LY294002.

scholarly journals Epigenetic Silencing of Tumor Suppressor miR-124 Directly Supports STAT3 Activation in Cutaneous T-Cell Lymphoma

Cells ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2692
Author(s):  
Lidia García-Colmenero ◽  
Jéssica González ◽  
Juan Sandoval ◽  
Yolanda Guillén ◽  
Angel Diaz-Lagares ◽  
...  
Keyword(s):  
T Cell ◽  
Ectopic Expression ◽  
Tumor Stage ◽  
Stat3 Pathway ◽  
Stat3 Signaling ◽  
T Cell Lymphomas ◽  
Pathway Activation ◽  
Pathway Regulation ◽  
Genetic Signatures ◽  
Phosphorylated Stat3

Increasing evidence supports a potential role for STAT3 as a tumor driver in cutaneous T-cell lymphomas (CTCL). The mechanisms leading to STAT3 activation are not fully understood; however, we recently found that miR-124, a known STAT3 regulator, is robustly silenced in MF tumor-stage and CTCL cells. Objective: We studied here whether deregulation of miR-124 contributes to STAT3 pathway activation in CTCL. Methods: We measured the effect of ectopic mir-124 expression in active phosphorylated STAT3 (p-STAT3) levels and evaluated the transcriptional impact of miR-124-dependent STAT3 pathway regulation by expression microarray analysis. Results: We found that ectopic expression of miR-124 results in massive downregulation of activated STAT3 in different CTCL lines, which resulted in a significant alteration of genetic signatures related with gene transcription and proliferation such as MYC and E2F. Conclusions: Our study highlights the importance of the miR-124/STAT3 axis in CTCL and demonstrates that the STAT3 pathway is regulated through epigenetic mechanisms in these cells. Since deregulated STAT3 signaling has a major impact on CTCL initiation and progression, a better understanding of the molecular basis of the miR-124/STAT3 axis may provide useful information for future personalized therapies.

scholarly journals The G Protein-Coupled Estrogen Receptor (GPER) Expression Correlates with Pro-Metastatic Pathways in ER-Negative Breast Cancer: A Bioinformatics Analysis

Cells ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 622 ◽  
Author(s):  
Marianna Talia ◽  
Ernestina De Francesco ◽  
Damiano Rigiracciolo ◽  
Maria Muoio ◽  
Lucia Muglia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
Signaling Pathways ◽  
G Protein ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
G Protein Coupled

The G protein-coupled estrogen receptor (GPER, formerly known as GPR30) is a seven-transmembrane receptor that mediates estrogen signals in both normal and malignant cells. In particular, GPER has been involved in the activation of diverse signaling pathways toward transcriptional and biological responses that characterize the progression of breast cancer (BC). In this context, a correlation between GPER expression and worse clinical-pathological features of BC has been suggested, although controversial data have also been reported. In order to better assess the biological significance of GPER in the aggressive estrogen receptor (ER)-negative BC, we performed a bioinformatics analysis using the information provided by The Invasive Breast Cancer Cohort of The Cancer Genome Atlas (TCGA) project and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. Gene expression correlation and the statistical analysis were carried out with R studio base functions and the tidyverse package. Pathway enrichment analysis was evaluated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the Database for Annotation, Visualization and Integrated Discovery (DAVID) website, whereas gene set enrichment analysis (GSEA) was performed with the R package phenoTest. The survival analysis was determined with the R package survivALL. Analyzing the expression data of more than 2500 primary BC, we ascertained that GPER levels are associated with pro-migratory and metastatic genes belonging to cell adhesion molecules (CAMs), extracellular matrix (ECM)-receptor interaction, and focal adhesion (FA) signaling pathways. Thereafter, evaluating the disease-free interval (DFI) in ER-negative BC patients, we found that the subjects expressing high GPER levels exhibited a shorter DFI in respect to those exhibiting low GPER levels. Overall, our results may pave the way to further dissect the network triggered by GPER in the breast malignancies lacking ER toward a better assessment of its prognostic significance and the action elicited in mediating the aggressive features of the aforementioned BC subtype.

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