Co‑expression Network Analysis by WGCNA and Identify Potential Prognostic Markers Associated with Lung Metastasis in Breast Cancer

2021 ◽  
Author(s):  
xixun zhang
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Lung Metastasis ◽  
Prognostic Markers ◽  
Clinical Information ◽  
Preventive Treatment ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Breast Cancer Patients ◽  
Kaplan Meier

Abstract Backgroud: Breast cancer (BC) is an aggressive cancer with a high percentage recurrence and metastasis. As one of the most common distant metastasis organ in breast cancer, lung metastasis has a worse prognosis than that of liver and bone. Therefore, it’s important to explore some potential prognostic markers associated with the lung metastasis in breast cancer for preventive treatment. Methods: In our study, transcriptomic data and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. Co-expression modules was built by Weighted gene co-expression network analysis (WGCNA) to find out the royalbule modules which is significantly associated with lung metastasis in breast cancer. Then, co-expression genes were analyzed for functional enrichment. Furthermore, the prognostic value of these genes was assessed by GEPIA Database and Kaplan-Meier Plotter. Results: Results showed that the hub genes, LMNB and CDC20, were up-regulated in breast cancer and indicated worse survival. Therefore, we speculate that these two genes play crucial roles in the process of lung metastasis in breast cancer, and can be used as potential prognostic markers in lung metastasis of breast cancer. Conclusion: Collectively, our study identified two potential key genes in the lung metastasis of breast cancer, which might be applied as the prognostic markers of the precise treatment in breast cancer with lung metastasis.

Identification of potential prognostic markers associated with lung metastasis in breast cancer by coexpression network analysis

2021 ◽  
pp. 1-12
Author(s):  
Xixun Zhang
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Lung Metastasis ◽  
Prognostic Markers ◽  
Clinical Information ◽  
Preventive Treatment ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Breast cancer (BC) is an aggressive cancer with a high percentage recurrence and metastasis. As one of the most common distant metastasis organ in BC, lung metastasis has a worse prognosis than that of liver and bone. Therefore, it’s important to explore some potential prognostic markers associated with the lung metastasis in BC for preventive treatment. In this study, transcriptomic data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Co-expression modules constructed by weighted gene co-expression network analysis (WGCNA) found the royal blue module was significantly associated with lung metastasis in BC. Then, co-expression genes of this module were analyzed for functional enrichment. Furthermore, the prognostic value of these genes was assessed by GEPIA Database and Kaplan-Meier Plotter. Results showed that the hub genes, LMNB and CDC20, were up-regulated in BC and had a worse survival of the patients. Therefore, we speculate that these two genes play crucial roles in the process of lung metastasis in BC, which can be used as potential prognostic markers in lung metastasis of BC. Collectively, our study identified two potential key genes in the lung metastasis of BC, which might be applied as the prognostic markers of the precise treatment in breast cancer with lung metastasis.

scholarly journals Analysis of LAGEs Family Gene Signature and Prognostic Relevance in Breast Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 726
Author(s):  
Hoang Dang Khoa Ta ◽  
Wan-Chun Tang ◽  
Nam Nhut Phan ◽  
Gangga Anuraga ◽  
Sz-Ying Hou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Expression Profiles ◽  
Family Members ◽  
Gene Expression Profiles ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Breast Cancer Patients ◽  
Kaplan Meier

Breast cancer (BRCA) is one of the most complex diseases and involves several biological processes. Members of the L-antigen (LAGE) family participate in the development of various cancers, but their expressions and prognostic values in breast cancer remain to be clarified. High-throughput methods for exploring disease progression mechanisms might play a pivotal role in the improvement of novel therapeutics. Therefore, gene expression profiles and clinical data of LAGE family members were acquired from the cBioportal database, followed by verification using the Oncomine and The Cancer Genome Atlas (TCGA) databases. In addition, the Kaplan-Meier method was applied to explore correlations between expressions of LAGE family members and prognoses of breast cancer patients. MetaCore, GlueGo, and GluePedia were used to comprehensively study the transcript expression signatures of LAGEs and their co-expressed genes together with LAGE-related signal transduction pathways in BRCA. The result indicated that higher LAGE3 messenger (m)RNA expressions were observed in BRCA tissues than in normal tissues, and they were also associated with the stage of BRCA patients. Kaplan-Meier plots showed that overexpression of LAGE1, LAGE2A, LAGE2B, and LAGE3 were highly correlated to poor survival in most types of breast cancer. Significant associations of LAGE family genes were correlated with the cell cycle, focal adhesion, and extracellular matrix (ECM) receptor interactions as indicated by functional enrichment analyses. Collectively, LAGE family members’ gene expression levels were related to adverse clinicopathological factors and prognoses of BRCA patients; therefore, LAGEs have the potential to serve as prognosticators of BRCA patients.

scholarly journals Exosomal miR-1246 is Involved in Tumorigenesis by Targeting THRB in Breast Cancer

2021 ◽  
Author(s):  
Jie Zhu ◽  
Xiaoying Chen ◽  
Fengxiang Xi ◽  
Lei Zhao ◽  
Yichao Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Metastatic Breast ◽  
Functional Enrichment ◽  
Breast Cancer Patients ◽  
Invasion And Migration ◽  
Kaplan Meier ◽  
Exosomal Mirnas ◽  
And Migration

Abstract Background: Exosomal miRNAs have drawn increasing attention as tumor biomarkers involving in tumorigenesis due to their stability. The aim of this study was to analyze the role of exosomal miR-1246 in breast cancer.Methods: The differentially expressed (DE) miRNAs in exosomes from the serum of breast cancer patients and healthy controls were investigated using RNA-seq. The potential pathogenic target genes and functional enrichment of these miRNAs were explored using bioinformatics. Additionally, the role of miR-1246 in migration, invasion and proliferation were investigated in breast cancer cells. The expression of THRB were detected by QRT-PCR. Kaplan-Meier plotter was used to perform survival analysis.Results: The results showed that the level of exosomal miR-1246 was significantly higher in breast cancer than in the control. MiR-1246 mimic treatment promoted invasion and migration in MDA-MB-231 cells by targeting THRB. Kaplan-Meier survival curves showed that patients with high miR-1246 expression exhibited poor OS compared with patients with low miR-1246 expression, especially those with metastatic breast cancer.Conclusion: Our study provides a better understanding of exosomal miR-1246 in the process of breast cancer. Exosomal miR-1246 could be a potential prognostic biomarker for breast carcinoma.

scholarly journals Identification of Metastasis-Associated Genes in Triple-Negative Breast Cancer Using Weighted Gene Co-expression Network Analysis

2020 ◽  
Vol 16 ◽  
pp. 117693432095486
Author(s):  
Wenting Xie ◽  
Zhongshi Du ◽  
Yijie Chen ◽  
Naxiang Liu ◽  
Zhaoming Zhong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Candidate Genes ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Characteristic Curve ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Diagnosis And Prognosis

Triple-negative breast cancer (TNBC) is the most aggressive and fatal sub-type of breast cancer. This study aimed to identify metastasis-associated genes that could serve as biomarkers for TNBC diagnosis and prognosis. RNA-seq data and clinical information on TNBC from the Cancer Genome Atlas were used to conduct analyses. Expression data were used to establish co-expression modules using average linkage hierarchical clustering. We used weighted gene co-expression network analysis to explore the associations between gene sets and clinical features and to identify metastasis-associated candidate biomarkers. The K-M plotter website was used to explore the association between the expression of candidate biomarkers and patient survival. In addition, receiver operating characteristic curve analysis was used to illustrate the diagnostic performance of candidate genes. The pale turquoise module was significantly associated with the occurrence of metastasis. In this module, 64 genes were identified, and its functional enrichment analysis revealed that they were mainly associated with transcriptional misregulation in cancer, microRNAs in cancer, and negative regulation of angiogenesis. Further, 4 genes, IGSF10, RUNX1T1, XIST, and TSHZ2, which were negatively associated with relapse-free survival and have seldom been reported before in TNBC, were selected. In addition, the mRNA expression levels of the 4 candidate genes were significantly lower in TNBC tumor tissues compared with healthy tissues. Based on the K-M plotter, these 4 genes were correlated with poor prognosis of TNBC. The area under the curve of IGSF10, RUNX1T1, TSHZ2, and XIST was 0.918, 0.957, 0.977, and 0.749. These findings provide new insight into TNBC metastasis. IGSF10, RUNX1T1, TSHZ2, and XIST could be used as candidate biomarkers for the diagnosis and prognosis of TNBC metastasis.

scholarly journals Systematic analysis of the expression and prognosis relevance of FBXO family reveals the significance of FBXO1 in human breast cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yaqian Liu ◽  
Bo Pan ◽  
Weikun Qu ◽  
Yilong Cao ◽  
Jun Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Proliferation ◽  
Prognostic Factors ◽  
Cell Lines ◽  
Therapeutic Target ◽  
Molecular Typing ◽  
Functional Enrichment ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Breast cancer (BC) remains a prevalent and common form of cancer with high heterogeneity. Making efforts to explore novel molecular biomarkers and serve as potential disease indicators, which is essential to effectively enhance the prognosis and individualized treatment of BC. FBXO proteins act as the core component of E3 ubiquitin ligase, which play essential regulators roles in multiple cellular processes. Recently, research has indicated that FBXOs also play significant roles in cancer development. However, the molecular functions of these family members in BC have not been fully elucidated. Methods In this research, we investigated the expression data, survival relevance and mutation situation of 10 FBXO members (FBXO1, 2, 5, 6, 16, 17, 22, 28, 31 and 45) in patients with BC from the Oncomine, GEPIA, HPA, Kaplan–Meier Plotter, UALCAN and cBioPortal databases. The high transcriptional levels of FBXO1 in different subtypes of BC were verified by immunohistochemical staining and the specific mutations of FBXO1 were obtained from COSMIC database. Top 10 genes with the highest correlation to FBXO1 were identified through cBioPortal and COXPRESdb tools. Additionally, functional enrichment analysis, PPI network and survival relevance of FBXO1 and co-expressed genes in BC were obtained from DAVID, STRING, UCSC Xena, GEPIA, bc-GenExMiner and Kaplan–Meier Plotter databases. FBXO1 siRNAs were transfected into MCF-7 and MDA-MB-231 cell lines. Expression of FBXO1 in BC cell lines was detected by western-blot and RT-qPCR. Cell proliferation was detected by using CCK-8 kit and colony formation assay. Cell migration was detected by wound‐healing and transwell migration assay. Results We found that FBXO2, FBXO6, FBXO16 and FBXO17 were potential favorable prognostic factors for BC. FBXO1, FBXO5, FBXO22, FBXO28, FBXO31 and FBXO45 may be the independent poor prognostic factors for BC. All of them were correlated to clinicopathological staging. Moreover, knockdown of FBXO1 in MCF7 and MDA-MB-231 cell lines resulted in decreased cell proliferation and migration in vitro. We identified that FBXO1 was an excellent molecular biomarker and therapeutic target for different molecular typing of BC. Conclusion This study implies that FBXO1, FBXO2, FBXO5, FBXO6, FBXO16, FBXO17, FBXO22, FBXO28, FBXO31 and FBXO45 genes are potential clinical targets and prognostic biomarkers for patients with different molecular typing of BC. In addition, the overexpression of FBXO1 is always found in breast cancer and predicts disadvantageous prognosis, implicating it could as an appealing therapeutic target for breast cancer patients.

scholarly journals Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

2020 ◽  
Vol 10 ◽  
Author(s):  
Peng-Ju Gong ◽  
You-Cheng Shao ◽  
Si-Rui Huang ◽  
Yi-Fan Zeng ◽  
Xiao-Ning Yuan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cell ◽  
Prognostic Markers ◽  
Immune Cell ◽  
Tumor Hypoxia ◽  
Gene Expression Signature ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Patients ◽  
Related Gene ◽  
Primary Tumors

ObjectiveMany primary tumors have insufficient supply of molecular oxygen, called hypoxia. Hypoxia is one of the leading characteristics of solid tumors resulting in a higher risk of local failure and distant metastasis. It is quite necessary to investigate the hypoxia associated molecular hallmarks in breast cancer.Materials and MethodsAccording to the published studies, we selected 13 hypoxia related gene expression signature to define the hypoxia status of breast cancer using ConsensusClusterPlus package based on the data from The Cancer Genome Atlas (TCGA). Subsequently, we characterized the infiltration of 24 immune cell types under different hypoxic conditions. Furthermore, the differentially expressed hypoxia associated microRNAs, mRNAs and related signaling pathways were analyzed and depicted. On this basis, a series of prognostic markers related to hypoxia were identified and ceRNA co-expression networks were constructed.ResultsTwo subgroups (cluster1 and cluster2) were identified and the 13 hypoxia related gene signature were all up-regulated in cluster1. Thus, we defined the cluster1 as “hypoxic subgroup” compared with cluster2. The infiltration of CD8+ T cell and CD4+ T cell were lower in cluster1 while the nTreg cell and iTreg cell were higher, indicating that there was immunosuppressive status in cluster1. We observed widespread hypoxia-associated dysregulation of microRNAs and mRNAs. Next, a risk signature for predicting prognosis of breast cancer patients was established based on 12 dysregulated hypoxia associated prognostic genes. Two microRNAs, hsa-miR-210-3p and hsa-miR-190b, with the most significant absolute logFC value were related to unfavorable and better prognosis, respectively. Several long non-coding RNAs were predicted to be microRNA targets and positively correlated with two selected mRNAs, CPEB2 and BCL11A. Predictions based on the SNHG16-hsa-miR-210-3p-CPEB2 and LINC00899/PSMG3-AS1/PAXIP-AS1-hsa-miR-190b-BCL11A ceRNA regulation networks indicated that the two genes might act as tumor suppressor and oncogene, respectively.ConclusionHypoxia plays an important role in the initiation and progression of breast cancer. Our research provides potential mechanisms into molecular-level understanding of tumor hypoxia.

scholarly journals Comprehensive Transcriptomic Analysis Identifies ST8SIA1 as a Survival-Related Sialyltransferase Gene in Breast Cancer

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1436
Author(s):  
Jung-Yu Kan ◽  
Sin-Hua Moi ◽  
Wen-Chun Hung ◽  
Ming-Feng Hou ◽  
Fang-Ming Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Area Under The Curve ◽  
Disease Free Survival ◽  
Comprehensive Analysis ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Breast Cancer Patients ◽  
Clinical Database ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Hypersialylation caused by the overexpression of sialyltransferases (STs) is a common feature in cancer that is associated with several characteristics of tumorigenesis. Thus, identifying cancer-associated STs is critical for cancer therapy. However, ST screening has been frequently conducted in cell line models. In this study, we conducted a comprehensive analysis of STs in the clinical database and identified the STs related with the survival of breast cancer patients. RNA sequencing (RNA-Seq) data of 496 patients were obtained from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA). Of the eight mapped STs, ST3GAL5, and ST8SIA1 met the acceptable area under the curve (AUC) criteria for overall survival (OS). Using Kaplan–Meier methods, we determined that high expression of ST8SIA1 was associated with poor 10-year OS in all patients, triple-negative breast cancer (TNBC), and non-TNBC patients, and poor disease-free survival (DFS) rates particularly in TNBC. ST8SIA1 also had superior AUC values in terms of OS/DFS. High ST8SIA1 levels showed a higher risk for poor OS in different groups of patients and a higher risk for poor DFS particularly in TNBC. In summary, we conducted a comprehensive analysis of STs from the clinical database and identified ST8SIA1 as a crucial survival-related ST, which might be a potential therapeutic target for breast cancer and TNBC patients.

scholarly journals Gene and lncRNA co-expression network analysis reveals novel ceRNA network for triple-negative breast cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kehao Le ◽  
Hui Guo ◽  
Qiulei Zhang ◽  
Xiaojuan Huang ◽  
Ming Xu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Triple Negative Breast Cancer ◽  
Molecular Mechanisms ◽  
Triple Negative ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Protein Coding ◽  
Cerna Network

Abstract Breast cancer is the most frequently diagnosed malignancy among women, and triple-negative breast cancer (TNBC) is a highly aggressive subtype. Increasing evidence has shown that lncRNAs are involved in tumor growth, cell-cycle, and apoptosis through interactions with miRNAs or mRNAs. However, there is still limited data on ceRNAs involved in the molecular mechanisms underlying TNBC. In this study, we applied the weighted gene co-expression network analysis to the existing microarray mRNA and lncRNA expression data obtained from the breast tissues of TNBC patients to find the hub genes and lncRNAs involved in TNBC. Functional enrichment was performed on the module that correlated with Ki-67 status the most (Turquoise module). The hub genes in the Turquoise module were found to be associated with DNA repair, cell proliferation, and the p53 signaling pathway. We performed co-expression analysis of the protein-coding and lncRNA hub genes in the Turquoise module. Analysis of the RNA-seq data obtained from The Cancer Genome Atlas database revealed that the protein-coding genes and lncRNAs that were co-expressed were also differentially expressed in the TNBC tissues compared with the normal mammary tissues. On the basis of establishing the ceRNA network, two mRNAs (RAD51AP1 and TYMS) were found to be correlated with overall survival in TNBC. These results suggest that TNBC-specific mRNA and lncRNAs may participate in a complex ceRNA network, which represents a potential therapeutic target for the treatment of TNBC.

scholarly journals Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jian Qi ◽  
Yu Liu ◽  
Jiliang Hu ◽  
Li Lu ◽  
Zhen Dou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Tumor Stages ◽  
Immune Score

Although research into immunotherapy is growing, its use in the treatment of breast cancer remains limited. Thus, identification and evaluation of prognostic biomarkers of tissue microenvironments will reveal new immune-based therapeutic strategies for breast cancer. Using an in silico bioinformatic approach, we investigated the tumor microenvironmental and genetic factors related to breast cancer. We calculated the Immune score, Stromal score, Estimate score, Tumor purity, TMB (Tumor mutation burden), and MATH (Mutant-allele tumor heterogeneity) of Breast cancer patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and Maftools. Significant correlations between Immune/Stromal scores with breast cancer subtypes and tumor stages were established. Importantly, we found that the Immune score, but not the Stromal score, was significantly related to the patient's prognosis. Weighted correlation network analysis (WGCNA) identified a pattern of gene function associated with Immune score, and that almost all of these genes (388 genes) are significantly upregulated in the higher Immune score group. Protein-protein interaction (PPI) network analysis revealed the enrichment of immune checkpoint genes, predicting a good prognosis for breast cancer. Among all the upregulated genes, FPR3, a G protein-coupled receptor essential for neutrophil activation, is the sole factor that predicts poor prognosis. Gene set enrichment analysis analysis showed FRP3 upregulation synergizes with the activation of many pathways involved in carcinogenesis. In summary, this study identified FPR3 as a key immune-related biomarker predicting a poor prognosis for breast cancer, revealing it as a promising intervention target for immunotherapy.

scholarly journals Systematic analysis of the expression and prognosis relevance of FBXO family reveals the significance of FBXO1 in human breast cancer

2021 ◽  
Author(s):  
Yaqian Liu ◽  
Bo Pan ◽  
Weikun Qu ◽  
Yilong Cao ◽  
Jun Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Therapeutic Target ◽  
Molecular Typing ◽  
Functional Enrichment ◽  
Breast Cancer Patients ◽  
Systematic Analysis ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background: Breast cancer (BC) remains a prevalent and common form of cancer with high heterogeneity. Making efforts to explore novel molecular biomarkers and serve as potential disease indicators, which is essential to effectively enhance the prognosis and individualized treatment of BC. FBXO proteins act as the core component of E3 ubiquitin ligase, which play essential regulators roles in multiple cellular processes. Recently, research has indicated that FBXOs also play significant roles in cancer development. However, the molecular functions of these family members in BC have not been fully elucidated.Methods: In this research, we investigated the expression data, survival relevance and mutation situation of 10 FBXO members (FBXO1, 2, 5, 6, 16, 17, 22, 28, 31 and 45) in patients with BC from the Oncomine, GEPIA, HPA, Kaplan-Meier Plotter, UALCAN and cBioPortal databases. The high transcriptional levels of FBXO1 in different subtypes of BC were verified by immunohistochemical staining and the specific mutations of FBXO1 were obtained from COSMIC database. Top 10 genes with the highest correlation to FBXO1 were identified through cBioPortal and COXPRESdb tools. We also showed that knockdown of FBXO1 in MCF7 and MDA-MB-231 cell lines resulted in decreased cell proliferation and migration in vitro. Additionally, functional enrichment analysis, PPI network and survival relevance of FBXO1 and co-expressed genes in BC were obtained from DAVID, STRING, UCSC Xena, GEPIA, bc-GenExMiner and Kaplan-Meier Plotter databases. Results: We found that FBXO2, FBXO6, FBXO16 and FBXO17 were potential favorable prognostic factors for BC. FBXO1, FBXO5, FBXO22, FBXO28, FBXO31 and FBXO45 may be the independent poor prognostic factors for BC. All of them were correlated to clinicopathological staging. Moreover, we identified that FBXO1 was an excellent molecular biomarker and therapeutic target for different molecular typing of BC. Conclusion: This study implies that FBXO1, FBXO2, FBXO5, FBXO6, FBXO16, FBXO17, FBXO22, FBXO28, FBXO31 and FBXO45 genes are potential clinical targets and prognostic biomarkers for patients with different molecular typing of BC. In addition, the overexpression of FBXO1 is always found in breast cancer and predicts disadvantageous prognosis, implicating it could as an appealing therapeutic target for breast cancer patients.

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