scholarly journals Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2220
Author(s):  
Chung-Chieh Chiao ◽  
Yen-Hsi Liu ◽  
Nam Nhut Phan ◽  
Nu Thuy An Ton ◽  
Hoang Dang Khoa Ta ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Messenger Rna ◽  
Genomic Analysis ◽  
Normal Breast ◽  
High Expression ◽  
Breast Cancer Patients ◽  
Expression Levels ◽  
Kaplan Meier ◽  
Novel Biomarkers ◽  
Cluster Of Differentiation

The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan–Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.

scholarly journals Expression and Prognostic Characteristics of m6 A RNA Methylation Regulators in Breast Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Bo Zhang ◽  
Yanlin Gu ◽  
Guoqin Jiang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
High Expression ◽  
Cancer Gene ◽  
Breast Cancer Patients ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Her 2 ◽  
Kaplan Meier Plotter

PurposeN6-methyladenosine (m6A) is the most prevalent modification in mRNA methylation which has a wide effect on biological functions. This study aims to figure out the efficacy of m6A RNA methylation regulator-based biomarkers with prognostic significance in breast cancer.Patients and MethodsThe 23 RNA methylation regulators were firstly analyzed through ONCOMINE, then relative RNA-seq transcriptome and clinical data of 1,096 breast cancer samples and 112 normal tissue samples were acquired from The Cancer Gene Atlas (TCGA) database. The expressive distinction was also showed by the Gene Expression Omnibus (GEO) database. The gene expression data of m6A RNA regulators in human tissues were acquired from the Genotype-Tissue Expression (GTEx) database. The R v3.5.1 and other online tools such as STRING, bc-GeneExminer v4.5, Kaplan-Meier Plotter were applied for bioinformatics analysis.ResultsResults from ONCOMINE, TCGA, and GEO databases showed distinctive expression and clinical correlations of m6A RNA methylation regulators in breast cancer patients. The high expression of YTHDF3, ZC3H13, LRPPRC, and METTL16 indicated poor survival rate in patients with breast cancer, while high expression of RBM15B pointed to a better survival rate. Both univariate and multivariate Cox regression analyses revealed that age and risk scores were related to overall survival (OS). Univariate analysis also delineated that stage, tumor (T) status, lymph node (N) status, and metastasis (M) status were associated with OS. From another perspective, Kaplan-Meier Plotter platform showed that the relatively high expression of YTHDF3 and LRPPRC and the relatively low expression of RBM15B, ZC3H13, and METTL16 in breast cancer patients had worse Relapse-Free Survival (RFS). Breast Cancer Gene-Expression Miner v4.5 showed that LRPPRC level was negatively associated with ER and PR expression, while METTL16, RBM15B, ZC3H13 level was positively linked with ER and PR expression. In HER-2 (+) breast cancer patients, the expression of LRPPRC, METTL16, RBM15B, and ZC3H13 were all lower than the HER-2 (−) group.ConclusionThe significant difference in expression levels and prognostic value of m6A RNA methylation regulators were analyzed and validated in this study. This signature revealed the potential therapeutic value of m6A RNA methylation regulators in breast cancer.

High Expression Levels of miR-21 and miR-210 Predict Unfavorable Survival in Breast Cancer: A Systemic Review and Meta-Analysis

2015 ◽  
Vol 30 (4) ◽  
pp. 347-358 ◽  
Author(s):  
Yiting Tang ◽  
Xifa Zhou ◽  
Jianfeng Ji ◽  
Ling Chen ◽  
Jianping Cao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Negative Impact ◽  
Meta Analysis ◽  
Survival Rates ◽  
Prognostic Biomarkers ◽  
High Expression ◽  
Systemic Review ◽  
Breast Cancer Patients ◽  
Expression Levels

Background MicroRNAs (miRNAs) have been emerging as valuable prognostic biomarkers of breast cancer. We therefore summarized recent research into miRNAs involved in human breast cancer and, further, completed a meta-analysis to predict the role of specific miRNAs in the survival of breast cancer patients. Methods Studies were identified by searching PubMed, Embase and Web of Science. Descriptive characteristics for studies were described, and an additional meta-analysis for specific miRNAs was performed. Pooled hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) were calculated. Results A total of 41 articles including 27 types of miRNAs were found regarding prognostic biomarkers for breast cancer survival, of which, micRNA-21 (miR-21) was the most-studied specific miRNA that appeared repeatedly among the selected classifiers. For the studies evaluating miR-21's association with clinical outcomes, the median HR in the studies was 2.32 (interquartile range [IQR] = 1.04-3.40), and the pooled HR suggested that high expression of miR-21 has a negative impact on overall survival (OS; HR = 1.46, 95% CI, 1.25-1.70; p<0.05) and disease/recurrence-free survival in breast cancer (HR = 1.49, 95% CI, 1.17-1.90; p<0.01). We also found that higher expression levels of miR-210 significantly predicted poorer outcome, with median HR in the reported studies of 4.07 (IQR = 1.54-4.43) and a pooled HR of 2.94 (95% CI, 2.08-4.17; p<0.05). Conclusions These results indicate that miRNAs show promising associations with prognosis in breast cancer. Moreover, specific miRNAs such as miR-21 and miR-210 can predict poor survival rates in breast cancer patients.

Solamargine induces apoptosis and enhances susceptibility to trastuzumab and epirubicin in breast cancer cells with low or high expression levels of HER2/neu

2008 ◽  
Vol 29 (1) ◽  
pp. 35-45 ◽  
Author(s):  
Li Yen Shiu ◽  
Chia Hua Liang ◽  
Li Ching Chang ◽  
Hamm Ming Sheu ◽  
Eing Mei Tsai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Breast Cancer Cells ◽  
Topoisomerase Ii ◽  
Growth Factor Receptor ◽  
High Expression ◽  
Breast Cancer Patients ◽  
Expression Levels ◽  
Topoisomerase Ii Α

Trastuzumab is used for breast cancer patients with high expression levels of HER2 (human epidermal growth factor receptor 2)/neu; however, it has no effect on cancers with low levels of HER2/neu. SM (solamargine), a major steroidal alkaloid glycoside purified from Solanum incanum, triggered apoptosis of breast cancer cells (MCF-7 and SK-BR-3 cells) and non-cancerous breast epithelial cells (HBL-100 cells) within 3 h. To extend the application of trastuzumab in breast cancer patients, the regulation of HER2/neu expression by SM was investigated. SM significantly up-regulates HER2/neu expression in breast cancer cells with low and high expression levels of HER2/neu, and synergistically enhanced the effect of trastuzumab in inhibiting cell proliferation. Additionally, HER2/neu and TOP2A [TopoII (topoisomerase II) α] genes share the same amplicon on an identical chromosome. Notably, SM co-regulates HER2/neu and TopoIIα expression markedly, and enhances TopoII inhibitor–EPI (epirubicin)-induced cytotoxicity to breast cancer cells.

scholarly journals CD300LG (Nepmucin) is differentially expressed in brain metastatic breast cancer.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Messenger Rna ◽  
Treatment Options ◽  
Metastatic Breast ◽  
Global Gene Expression ◽  
Normal Breast ◽  
Breast Cancer Patients ◽  
Primary Tumors ◽  
The Brain

Brain metastases affect up to 34% of breast cancer patients treated with trastuzumab (1). Limited treatment options are available for clinical control of brain metastatic breast cancer (2-4). We mined published microarray data (5, 6) to identify genes associated with metastasis to the brain in human breast cancer. This unbiased, global gene expression analysis identified differential expression of CD300LG as a transcriptional feature of brain metastasis in patients with breast cancer. Messenger RNA for CD300LG was present at significantly lower quantities in the brain metastatic tissues of patients with metastatic breast cancer. Additional microarray analysis revealed that CD300LG was also among the genes whose expression, transcriptome-wide, was most significantly different in primary tumors of the breast when compared to normal breast tissues. CD300LG is part of the transcriptional signature of human metastatic breast cancer.

scholarly journals Bioinformatic analysis of the expression and prognostic value of chromobox family proteins in human breast cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiaomin Li ◽  
Junhe Gou ◽  
Hongjiang Li ◽  
Xiaoqin Yang
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Prognostic Index ◽  
Bioinformatic Analysis ◽  
Tumor Stage ◽  
Normal Breast ◽  
Nottingham Prognostic Index ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Chromobox (CBX) family proteins control chromatin structure and gene expression. However, the functions of CBXs in cancer progression, especially breast cancer, are inadequately studied. We assessed the significance of eight CBX proteins in breast cancer. We performed immunohistochemistry and bioinformatic analysis of data from Oncomine, GEPIA Dataset, bcGenExMiner, Kaplan–Meier Plotter, and cBioPortal. We compared mRNA and protein expression levels of eight CBX proteins between breast tumor and normal tissue. The expression difference of CBX7 was the greatest, and CBX7 was downregulated in breast cancer tissues compared with normal breast tissues. The expression of CBX2 was strongly associated with tumor stage. We further analyzed the association between the eight CBX proteins and the following clinicopathological features: menopause age, estrogen receptor (ER), progesterone receptor (PR) and HER-2 receptor status, nodal status, P53 status, triple-negative status, and the Scarff–Bloom–Richardson grade (SBR) and Nottingham prognostic index (NPI). Survival analysis in the Kaplan–Meier Plotter database showed that the eight CBX proteins were significantly associated with prognosis. Moreover, CBX genes in breast cancer patients had a high net alteration frequency of 57%. There were significant co-expression correlations between the following CBX protein pairs: CBX4 positively with CBX8, CBX6 positively with CBX7, and CBX2 negatively with CBX7. We also analyzed the Gene Ontology enrichment of the CBX proteins, including biological processes, cellular components, and molecular functions. CBX 1/2/3/5/8 may be oncogenes for breast cancer, whereas CBX 6 and 7 may be tumor suppressors for breast cancer. All eight CBX proteins may be predictive for prognosis. Clinical trials are needed to confirm the significance of the eight CBX proteins in breast cancer.

Overexpressed FAM166B Predicts Favorable Prognosis and Associated With Metabolic Pathways and Tumor Immune Infiltrates in BRCA

2021 ◽  
Author(s):  
Yi Zhou ◽  
Huiqin Zhu ◽  
Gao He ◽  
Hongfei Zhang ◽  
Xuyu Cheng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Cell Metabolism ◽  
Immune Therapy ◽  
High Expression ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Protein Coding ◽  
Kaplan Meier ◽  
Cox Analysis

Abstract Background: Breast cancer is one of the most common and lethal cancer worldwide. Though surgery, chemotherapy, endocrine therapy and immune therapy have boost patients' survival rate, to establish more molecular biomarkers that can detect the early metastasis and shed a light on breast cancer treatment still requires efforts. Based on previous studies, adipose tissue had a metabolic crosstalk in breast cancer. FAM166B is a protein-coding gene which was reported to be found in adipose tissues. Yet whether FAM166B has a role in breast cancer had not been determined.Methods: In this study, 1109 BRCA patients and 113 adjacent cancer samples and clinical characteristics data were downloaded from TCGA data portal, R software and Strawberry Perl were used for all pre-processing processes. Kaplan-Meier plotter, univariate and multivariate Cox analysis were used to investigate FAM166B potential in BRCA prognosis. GSEA was performed to investigate the biological function of FAM166B. Furthermore, TIMER was utilized to identify the association between FAM166B and tumor-infiltrating immune cells.Results: We found out increased FAM166B expression correlates with better prognosis in BRCA. By conducting Multivariate Cox analysis, we draw a conclusion that FAM166B could be an independent prognosis factor. Moreover, the GSEA revealed that FAM166B could possibly restrain the cell metabolism and glucose converting pathways. Also, a high expression of FAM166B was correlated with increased immune infiltration levels like CD4+ T cells and decreased macrophages, especially in luminal and basal breast cancers. Conclusion: Our study illustrated that FAM166B is an independent prognostic factor in BRCA. A high expression of FAM166B indicates a better prognosis of breast cancer patients and it may restrain the tumor cell metabolism and likely play a role in immune cell infiltration.

Systemic analysis of the expression levels and prognosis of breast cancer-related cadherins

2021 ◽  
pp. 153537022110104
Author(s):  
Mingfei Xu ◽  
Chaoyue Liu ◽  
Lulan Pu ◽  
Jinrong Lai ◽  
Jingjia Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Patients ◽  
Relapse Free Survival ◽  
Free Survival ◽  
Expression Levels ◽  
Protein Levels ◽  
Kaplan Meier ◽  
Cancer Tissues ◽  
Breast Tissues ◽  
Kaplan Meier Plotter

Cadherins form connection between cells, facilitate communication, and serve as essential agents in the progression of multiple cancers. Over 100 cadherins have been identified and they are mainly divided into four groups: classical cadherins (CDHs), protocadherins (PCDHs), desmosomal (DSC), and cadherin-related proteins. Accumulating evidence has indicated that several members of the cadherins are involved in breast cancer development. Nevertheless, the expression profiles and corresponding prognostic outcomes of these breast cancer-related cadherins are yet to be analyzed. Here, we examined the expression levels and prognostic potential of these breast cancer-related cadherins from the specific databases viz. oncomine, gene expression profiling interactive analysis, human protein atlas, UALCAN, Kaplan–Meier Plotter, and cBioPortal. We found that the CDH2/11 levels were higher in breast cancer tissues, compared to healthy breast tissues, whereas with CDH3-5, PCDH8/10, and DSC3, the levels were lower in the former than in the latter. Additionally, for CDH1/6/13/17/23, PCDH7, and FAT4, trancript level alterations between breast cancer and healthy tissues varied across different databases. The CDH1 protein levels were elevated in breast cancer tissues versus healthy breast tissues, whereas the protein levels of CDH3/11 and PCDH8/10 were reduced in breast cancer, compared to healthy breast tissues. For CDH15 and CDH23, the expression levels paralleled tumor stage. Survival analysis, using the Kaplan–Meier Plotter database, demonstrated that elevated CDH1-3 levels correlated with diminished relapse-free survival in breast cancer patients. Alternately, enhanced CDH4-6/15/17/23, PCDH10, DSC3, and FAT4 levels estimated a rise in relapse-free survival of breast cancer patients. These data suggest CDH1-3 to be a promising target for breast cancer precision therapy and CDH4-6/15/17/23, PCDH10, DSC3, and FAT4 to be novel biomarkers for breast cancer prognosis.

scholarly journals DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Consensus Clustering ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

scholarly journals Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer

2021 ◽  
Vol 22 (2) ◽  
pp. 636
Author(s):  
Hsing-Ju Wu ◽  
Pei-Yi Chu
Keyword(s):  
Breast Cancer ◽  
Normal Breast ◽  
New Drugs ◽  
Cancer Type ◽  
Luminal A ◽  
Luminal B ◽  
Therapeutic Implications ◽  
Whole Cells ◽  
Diagnosis And Prognosis ◽  
Novel Biomarkers

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

scholarly journals Serum Long Non-Coding RNAs PVT1, HOTAIR, and NEAT1 as Potential Biomarkers in Egyptian Women with Breast Cancer

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 301
Author(s):  
Amal Ahmed Abd El-Fattah ◽  
Nermin Abdel Hamid Sadik ◽  
Olfat Gamil Shaker ◽  
Amal Mohamed Kamal ◽  
Nancy Nabil Shahin
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Cancer Patients ◽  
Breast Cancer Diagnosis ◽  
Serum Levels ◽  
Breast Cancer Patients ◽  
Multivariate Logistic Regression ◽  
Expression Levels ◽  
Non Coding Rnas ◽  
Pai 1

Long non-coding RNAs play an important role in tumor growth, angiogenesis, and metastasis in several types of cancer. However, the clinical significance of using lncRNAs as biomarkers for breast cancer diagnosis and prognosis is still poorly investigated. In this study, we analyzed the serum expression levels of lncRNAs PVT1, HOTAIR, NEAT1, and MALAT1, and their associated proteins, PAI-1, and OPN, in breast cancer patients compared to fibroadenoma patients and healthy subjects. Using quantitative real-time PCR (qRT-PCR), we compared the serum expression levels of the four circulating lncRNAs in patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The serum levels of PAI-1 and OPN were measured using ELISA. Receiveroperating-characteristic (ROC) analysis and multivariate logistic regression were used to evaluate the diagnostic value of the selected parameters. The serum levels of HOTAIR, PAI-1, and OPN were significantly higher in breast cancer patients compared to controls and fibroadenoma patients. The serum level of PVT1 was significantly higher in breast cancer patients than in the controls, while that of NEAT1 was significantly lower in breast cancer patients compared to controls and fibroadenoma patients. Both ROC and multivariate logistic regression analyses revealed that PAI-1 has the greatest power in discriminating breast cancer from the control, whereas HOTAIR, PAI-1, and OPN have the greatest power in discriminating breast cancer from fibroadenoma patients. In conclusion, our data suggest that the serum levels of PVT1, HOTAIR, NEAT1, PAI-1, and OPN could serve as promising diagnostic biomarkers for breast cancer.

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