scholarly journals Identification of ATFs in Human Breast Cancer by Integrated Bioinformatic Analysis

Author(s):  
chenchen Geng ◽  
Qian Pu ◽  
Shuxu Tian ◽  
Wenwen Geng ◽  
Haiyan Wang ◽  
...  

Abstract Background: To obtain a thorough comprehension of the profile and prognosis of activating transcription factor (ATF) family members in breast cancer.Method: We searched Oncomine, GEPIA, cBioPortal, Kaplan-Meier plotter, and CancerSEA databases to assess expression level, prognostic value, and functions of ATFs in breast cancer. Results: In breast cancer, we found that the expression levels of genes like ATF1, ATF5, and ATF6, were higher than in normal tissues. While the expression levels of ATF3, ATF4, ATF7 were lower in the former than in the latter. Similarly, the ATFs protein expressions were consistent with this in the Human Protein Atlas database. High expressions of ATF2, ATF4, and ATF6-7 were associated with good relapse-free survival. Increased expressions of ATF4 and ATF7 had high overall survival. Conversely, the mRNA expression of ATF1 was negatively correlated with distant metastasis-free survival. Similarly, high expression of ATF2 had reduced post-progression survival. Conclusions: ATF1 was a target of potential therapeutic interest for breast cancer, and ATF4 and ATF6-7 were potential prognostic factors in evaluating breast cancer.

2021 ◽  
Vol 11 ◽  
Author(s):  
Min Wu ◽  
Pan Zhang ◽  
Penghui Wang ◽  
Zhen Fang ◽  
Yaqin Zhu

ObjectiveThis study aims to identify the potential value of flap endonuclease 1 (FEN1) as a diagnostic and prognostic marker for breast cancer (BC).MethodsELISA was used to measure serum FEN1 levels and ECLIA for CA153 and CEA levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value. Oncomine and UALCAN databases were used to analyze the differences in FEN1 mRNA and protein expressions. Kaplan-Meier Plotter database was then used to assess the prognostic value.ResultsBioinformatics analysis showed that the FEN1 mRNA and protein levels were significantly higher in BC tissues than in normal tissues. FEN1 was detected in culture medium of BC cell lines and serum FEN1 concentrations were significantly increased in BC patients than in cancer-free individuals. Besides, FEN1 exhibited higher diagnostic accuracy (AUC values>0.800) than CA153 and CEA for distinguishing BC patients, especially early BC, from the healthy and benign groups, or individually. Additionally, serum FEN1 levels were significantly associated with the stage (P=0.001) and lymph invasion (P=0.016), and serum FEN1 levels were increased with the development of BC. Furthermore, serum FEN1 levels were significantly decreased in post-operative patients than in pre-operative patients (P=0.016). Based on the Kaplan-Meier Plotter database, the survival analysis indicated that FEN1 overexpression was associated with poor prognoses for overall survival (OS), relapse-free survival (RFS), and distant metastasis-free survival (DMFS) in BC patients.ConclusionFEN1 might be a novel diagnostic and prognostic marker for BC.


2021 ◽  
Author(s):  
Mingjie Li ◽  
Qianyun Wang ◽  
Qinqin Zheng ◽  
Lin Wu ◽  
Bin Zhao ◽  
...  

Aim: We aimed to evaluate the diagnostic and prognostic values of P4HAs in breast cancer (BC) patients. Materials & methods: Kaplan–Meier plotter was used to evaluate the prognostic values of P4HAs and correlations between their expression and clinical characteristics were assessed based on The Cancer Genome Atlas and the Human Protein Atlas. Results: The current study showed that P4HAs were highly expressed in BC patients with clinical stage I compared with nontumor control and elevated P4HAs were correlated with poor survival outcomes. Subtypes analysis revealed that P4HA1 and P4HA2 were most expressed in HER2+ subtypes patients. Univariate analysis displayed that elevated P4HA1 and P4HA3 correlated with unfavorable recurrence-free survival in mutated TP53 patients. Conclusion: This study indicated the diagnostic and prognostic roles of P4HAs members and broadened the biomarker fields of early diagnosis and prognostic monitoring of BC patients.


2021 ◽  
pp. 153537022110104
Author(s):  
Mingfei Xu ◽  
Chaoyue Liu ◽  
Lulan Pu ◽  
Jinrong Lai ◽  
Jingjia Li ◽  
...  

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinyu Liu ◽  
Ying Liu ◽  
Qiangshan Wang ◽  
Siqi Song ◽  
Lingjun Feng ◽  
...  

The minichromosome maintenance (MCM) protein family plays a key role in eukaryotic DNA replication and has been confirmed to be associated with the occurrence and progression of many tumors. However, the expression levels, functions, and prognostic values of MCMs in breast cancer (BC) have not been clearly and systematically explained. In this article, we studied the transcriptional levels of MCMs in BC based on the Oncomine database. Kaplan-Meier plotter was used to analyze prognostic value of MCMs in human BC patients. Furthermore, we constructed a MCM coexpression gene network and performed functional annotation analysis through DAVID to reveal the functions of MCMs and coexpressed genes. The data showed that the expression of MCM2–8 and MCM10 but not MCM1 and MCM9 was upregulated in BC. Kaplan-Meier plotter analysis revealed that high transcriptional levels of MCM2, MCM4–7, and MCM10 were significantly related to low relapse-free survival (RFS) in BC patients. In contrast, high levels of MCM1 and MCM9 predicted high RFS for BC patients. This study suggests that MCM2, MCM4–7, and MCM10 possess great potential to be valuable prognostic biomarkers for BC and that MCM1 and MCM9 may serve as potential treatment targets for BC patients.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12548-e12548
Author(s):  
Xianghou Xia ◽  
Wenjuan Yin ◽  
Jiefei Mao ◽  
Jiejie Hu ◽  
Dehong Zou ◽  
...  

e12548 Background: Pyroptosis is a type of inflammatory cell death mediated by gasdermins. Pyroptosis is critical for macrophage against pathogen infection. Recently growing evidences show that pyroptosis may affect development and progression of many cancers. We aim to explore the expression and related function of pyroptosis executioner Gasdermin D (GSDMD) in breast cancer. Methods: We investigated the expression level of GSDMD using TNM plotter and Breast Cancer landscape proteome with TCGA, GTEx and TARGET databases, and the prognostic value of GSDMD in invasive breast cancer using Kaplan-Meier plotter with TCGA, GEO and EGA databases. The treatment response prediction values of GSDMD in invasive breast were calculated using ROC-plotter with GEO database. Further validation of the prognostic value and chemotherapy response prediction value of GSDMD were carried out with immunohistochemical staining on tissues from 165 cases of breast cancer patients receiving neoadjuvant chemotherapy in our cancer center. Results: TNM plotter and breast cancer landscape proteome portal analysis shows that overall expression level of GSDMD in invasive breast cancer tissue is 1.67 folds higher than it is in breast normal tissues ( p=1.05*e-06). Expression of GSDMD in LuminalB subtype (p=0.019) and Her2 subtype(p=0.04) is significantly higher than it is in TNBC subtype. Calculations with Kaplan-Meier plotter show expression of GSDMD is negatively correlated with overall survival(OS), HR=0.61(0.4−0.95) p=0.027 and relapse free survival (RFS), HR =0.65(0.58−0.63), p=8.7*e-14 and distant metastasis free survival (DMFS) HR =0.75(0.61−0.91), p=0.0038 in breast cancer patients. ROC-plotter calculations show high GSDMD expression is a powerful endocrine therapy (AUC=0.731 p=6*e-09 ) and chemotherapy response (AUC=0.64 p=8*e-05 ) predictor based on 5-year RFS in overall breast cancer patients. Our IHC staining analysis shows consistent prognostic and chemotherapy prediction value of GSDMD expression in TNBC patients. Conclusions: In conclusion, our findings suggest that high expression of GSDMD is positively correlated with prognosis and therapeutic response in breast cancer. GSDMD is a promising prognostic marker and therapeutic response predictor in invasive breast cancer.


2020 ◽  
Vol 19 ◽  
pp. 153303382094582
Author(s):  
Jun Shen ◽  
Cong Chen ◽  
Zhaoqing Li ◽  
Shufang Hu

Objective: Breast cancer remains the most threatening triggers of cancer death in women. Drug resistance inevitably leads to the weakness of treatment for breast cancer. Macrophages, as one of the most abundant immune cells in tumor immune-infiltrating microenvironment, involves in cell survival, migration, and invasion of breast cancer. Methods: In this study, we compared the proportions of macrophages in patients with breast cancer with and without paclitaxel treatment, and investigated the targeted genes associated with macrophages for paclitaxel response. To explore the relationship between drug-related genes and breast cancer prognosis, survival analysis based on the drug-related genes were performed by website of Kaplan-Meier plotter with the threshold of significant P value < .05. Results: Compared to the normal samples, we revealed that paclitaxel significantly enhanced the ratio of macrophages in the tumor microenvironment. Furthermore, the expression of 3 drug-related genes (IFT46, PEX11A, and TMEM223) were significantly negatively associated with the proportions of macrophages. And it is worth to notice that PEX11A and TMEM223 were associated with better progression-free survival outcomes of patients with breast cancer. Moreover, PEX11A was associated with longer overall survival time of breast cancer. Conclusion: Taken all together, all the findings support to gain a better understanding to the development of more effective therapies targeted with paclitaxel.


2021 ◽  
Author(s):  
zhang jing ◽  
Fu xi feng

Abstract Background.The AMIGO2 extracellular domain has a leucine - rich repetitive domain (LRR) and encodes a type 1 transmembrane protein , and is a member of the AMIGO gene family .Although the abnormal expression of AMIGO2 is associated with multiple tumors , the relationship with pancreatic cancer is not clear .Methods.The expression of AMIGO2 mRNA and proteins in pancreatic cancer was analyzed using NCBI GEO database and GEPIA2、Human Protein Atlas database.The RNA sequencing data of pancreatic cancer and clinical data of pancreatic cancer patients in TCGA public database were retrospectively analyzed. AMIGO2 gene expression data and their corresponding clinical information in the sample were analyzed retrospectively. The diagnostic value of AMIGO2 expression in pancreatic cancer patients was determined by receiver operating characteristic (ROC) curve analysis. The effects of AMIGO2 expression differences on survival time of pancreatic cancer patients were analyzed by Kaplan-Meier Plotter database and GEPIA2 database.The correlation between AMIGO2 gene and TP53 mutation in pancreatic cancer was analyzed by UALCAN database and TIMER database. The similar genes of AMIGO2 in pancreatic cancer were analyzed by GEPIA2 database, and the biological behavior, cellular composition, molecular function enrichment analysis and protein interaction of similar genes were analyzed by DAVID database and Metascape database. enrichment analysis of AMIGO2 similar gene pathways using KEGG database. The MSIGDB cancer coexpression module in Harmonizome database and TIMER database were used to study the gene coexpression of AMIGO2 in pancreatic cancer. AMIGO2 transcription factors were predicted using the JASPER database. The pathway of AMIGO2 transcription factors and co-expression genes was studied by KEGG database.Results. The expression of AMIGO2 (GSE16515, GSE15471) in pancreatic cancer tissues was significantly higher than that in normal tissues (P < 0.05). The GEPIA2 database also confirmed that the expression of AMIGO2 in pancreatic cancer tissues was significantly higher than that in normal tissues. The expression level of AMIGO2 gene was correlated with lymph node metastasis and histological grade of pancreatic cancer (P<0.05). The high expression of AMIGO2 protein in pancreatic cancer was confirmed in Human Protein Atlas database. The overall survival rate and progression-free survival rate of pancreatic cancer patients with high expression of AMIGO2 were significantly shorter than those of patients with low expression of AMIGO2 in Kaplan-Meier Plotter database and GEPIA2 database. In the gene ontology analysis, it is found that AMIGO2 is involved in cell adhesion, proliferation, migration, apoptosis and other biological processes. KEGG analysis pathway is concentrated in the focal adhesion pathway, mitotic cell cycle changes, and the regulation of cell protein localization. Abnormal expression of AMIGO2 was found in pancreatic cancer caused by TP53 mutation in UALCAN and TIMER databases.In JASPAR database, we predicted that there are 10 transcription sites between AMIGO2 and transcription factor MYB. In addition, there are positive genes related to AMIGO2 in TIMER database and transcription factor MYB regulates tumor cell proliferation and apoptosis in PI3K-Akt signal transduction pathway and WNT signal pathway in pancreatic cancer.


2021 ◽  
Author(s):  
Xiangyu Sun ◽  
Meng Li ◽  
Mozhi Wang ◽  
Mengshen Wang ◽  
Haoran Dong ◽  
...  

Abstract Objective: To explore the expression pattern of long chain fatty acyl CoA synthetase 3 (ACSL3) in breast cancer, and evaluate the clinical significance of ACSL3 by analyzing potential function and prognostic value of ACSL3 in human breast carcinoma.Methods: The expression of ACSL3 in normal mammary tissues and breast tumor tissues was analyzed by GEPIA and Human Protein Atlas. The prognostic value of ACSL3 was evaluated by Kaplan–Meier plotter analysis. ACSL3 expression was analyzed by immunohistochemistry in 297 breast cancer patients from the First Hospital of China Medical University Furthermore, based on LinkedOmics database, analyses of GO and KEGG pathways were performed to identify the potential function of ACSL3. Tumor Immune Estimation Resource (TIMER) database was used to evaluate the association between ACSL3 and immune infiltration in breast cancer. Results: GEPIA and Human Protein Atlas indicated that ACSL3 was significantly upregulated in breast carcinomas. Kaplan-Meier plotter analysis showed that increased expression of ACSL3 mRNA was significantly associated with shorter overall survival (OS) and relapse-free survival (RFS) in breast cancer patients. Results from immunochemical staining showed that ACSL3 was obviously related to clinicopathological features of breast cancer, and ACSL3 was highly abundant in TNBC tumors. Moreover, survival analysis of breast cancer patients demonstrated that higher ACSL3 protein expression is unfavorable prognostic biomarker in breast cancer patients. Results from TIMER database indicated that ACSL3 expression was significantly correlated with infiltration level of multiple immune cells. Further studies are needed to explore underlying mechanism of the pro-tumor effects of ACSL3 expression.Conclusions: ACSL3 may not only serve as a reliable predictive biomarker of breast cancer but also have impact on the occurrence and progression of breast cancer. Thus, ACSL3 may be an emerging therapeutic target for the development of molecular-targeted therapeutic strategies for breast cancer.


2021 ◽  
Author(s):  
Qingfang Yue ◽  
Fei Wang ◽  
Fei Cao ◽  
Xianglong Duan ◽  
Jun Bai

Abstract Background: Breast invasive carcinoma (BRCA) is the primary cause of cancer-associated mortality worldwide. Platelet endothelial cell adhesion molecule 1 (PECAM-1) has been implicated in a number of important biological processes. However, the interrelation between PECAM-1 gene expression, tumor immunity, and prognosis of patients with BRCA is unclear. The current study is aimed to analyze the expression and clinical significance of PECAM-1 in breast cancer and the correlation between PECAM-1 and immune infiltrations. Methods: The differential expressions of PECAM-1 in breast cancer tissues and normal tissues were evaluated via exploring TIMER, Oncomine and UALCAN databases; the relationship within expression level of PECAM-1 and outcome of breast patients was evaluated via Kaplan-Meier plotter and PrognoScan; the methylation of PECAM-1 were investigated through the MethSurv platform; the correlation between PECAM-1 and tumor immune cell infiltration was further investigated by TIMER and GEPIA databases; the correlation between PECAM-1 and gene makers of immune infiltration were checked using TIMER and GEPIA. Results: There were significant differences in PECAM-1 expression levels between breast invasive carcinoma tissues and adjacent normal tissues. Low PECAM-1 expression was significantly related to poor overall survival, progression-free survival and distant metastasis free survival in patients with breast cancer. In DNA methylation level, PECAM-1 hypermethylation in three CpG sites (cg20830094, cg00427260 and cg00879592) showed poor survival in breast cancer. PECAM-1 expression exhibited significantly positive correlations with the levels of infiltrated B cell, CD4+T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells in breast cancer. Furthermore, PECAM-1 expression is positively correlated with multiple immune gene makers in breast cancer.Conclusion: The expression of PECAM-1 can serves as a prognostic biomarker in breast invasive carcinoma and is correlated with immune infiltrates.


2021 ◽  
Author(s):  
Gen Wu ◽  
Ziyuan Chen ◽  
Tong Wu ◽  
Jian Zhou ◽  
Qunyan Tian ◽  
...  

Abstract Background: GINS family was reported to be highly expressed in many tumors. However, the association of GINS family with human sarcoma remained unknown. This study was undertaken to explore the expression and prognostic value of GINS family in human sarcoma.Methods: In terms of the expression levels of mRNA for GINS family members, a particular contrast in various cancers, especially human sarcoma, was conducted through ONCOMINE and GEPIA and CCLE databases. Kaplan-Meier Plotter was used to identify the prognostic value of GINS family in sarcoma.Results: We discovered that the mRNA expression levels of GINS1, GINS2, GINS3, and GINS4 were all higher in the majority of tumor tissues than in normal samples, of course, including sarcoma. Through the Cancer Cell Line Encyclopedia (CCLE), all the four members (GINS1, GINS2, GINS3, GINS4) expression were observed in high levels in sarcoma cell lines. In Gene Expression Profiling Analysis (GEPIA) and Kaplan-Meier Plotter, our results indicated that the poor overall survival (OS), disease-free survival (DFS) and relapse free survival (RFS) were tightly associated with the increased expression of GINS genes. Conclusion: The four GINS family members are all the prognostic biomarkers for the prognosis of human sarcoma.


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