scholarly journals Co‑expression network analysis of gene expression profiles of HER2+ breast cancer‑associated brain metastasis

2018 ◽  
Author(s):  
Feng Yuan ◽  
Wei Wang ◽  
Hongtao Cheng
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Network Analysis ◽  
Brain Metastasis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Her2 Breast Cancer

scholarly journals A novel immune subtype classification of ER-positive, PR-negative and HER2-negative breast cancer based on the genomic and transcriptomic landscape

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Peiling Xie ◽  
Rui An ◽  
Shibo Yu ◽  
Jianjun He ◽  
Huimin Zhang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Outcomes ◽  
Immune Escape ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Characteristics ◽  
Consensus Clustering ◽  
Breast Cancers ◽  
Her2 Breast Cancer

Abstract Background The diversity and plasticity behind ER+/PR−/HER2− breast cancer have not been widely explored. It is essential to identify heterogeneous microenvironment phenotypes and investigate specific genomic events driving the formation of these phenotypes. Methods Based on the immune-related gene expression profiles of 411 ER+/PR−/HER2− breast cancers in the METABRIC cohort, we used consensus clustering to identify heterogeneous immune subtypes and assessed their reproducibility in an independent meta-cohort including 135 patients collected from GEO database. We further analyzed the differences of cellular and molecular characteristics, and potential immune escape mechanism among immune subtypes. In addition, we constructed a transcriptional trajectory to visualize the distribution of individual patient. Results Our analysis identified and validated five reproducible immune subtypes with distinct cellular and molecular characteristics, potential immune escape mechanisms, genomic drivers, as well as clinical outcomes. An immune-cold subtype, with the least amount of lymphocyte infiltration, had a poorer prognosis. By contrast, an immune-hot subtype, which demonstrated the highest infiltration of CD8+ T cells, DCs and NK cells, and elevated IFN-γ response, had a comparatively favorable prognosis. Other subtypes showed more diverse gene expression and immune infiltration patterns with distinct clinical outcomes. Finally, our analysis revealed a complex immune landscape consisting of both discrete cluster and continuous spectrum. Conclusion Overall, this study revealed five heterogeneous immune subtypes among ER+/PR–/HER2− breast cancer, also provided important implications for clinical translations.

scholarly journals Prognostic Genes of Breast Cancer Identified by Gene Co-expression Network Analysis

2020 ◽  
Author(s):  
Jianing Tang ◽  
Yongwen Luo ◽  
Gaosong Wu
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Proliferation ◽  
Network Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Validation Dataset ◽  
Pcr Analysis ◽  
Normal Tissues

Abstract Background Breast cancer is the mostly diagnosed malignance in female worldwide. However, the mechanisms of its pathogenesis remain largely unknown. Methods In this study, we used weighted gene co-expression network analysis (WGCNA) to identify novel biomarkers associated with the prognosis of breast cancer. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Results A total of 5 modules were identified via the average linkage hierarchical clustering. And a module significantly with the pathological grade was screened out. 33 genes with high connectivity in the clinically significant module were identified as hub genes. Among them, CASC5 and RAD51 were negatively associated with the overall survival and disease-specific survival. Similar results were observed in the validation dataset. Protein levels of CACS5 and RAD51 were also significantly higher in tumor tissues compared with normal tissues based on the analysis of the Human Protein Atlas. Convincingly, qRT-PCR analysis of breast cancer tissues and matched paracancerous tissue demonstrated that CACS5 and RAD51 were significantly upregulated in in breast cancer compared to paracancerous tissues. Further cell proliferation assay indicated that CACS5 and RAD51 depletion decreased cell proliferation capability. Conclusion In conclusion, our findings suggested that CASC5 and RAD51 could serve as biomarkers related to the prognosis of breast cancer and may be helpful for revealing pathogenic mechanism and developing further research.

Network Analysis of Gene Expression Profiles in Breast Cancer Cell Lines

2011 ◽  
pp. 233-242
Author(s):  
T Dewey ◽  
Katie Streicher ◽  
Stephen Ethier ◽  
T Dewey ◽  
Katie Streicher ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Network Analysis ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines

scholarly journals A Supervised Network Analysis on Gene Expression Profiles of Breast Tumors Predicts a 41-Gene Prognostic Signature of the Transcription FactorMYBacross Molecular Subtypes

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Li-Yu D. Liu ◽  
Li-Yun Chang ◽  
Wen-Hung Kuo ◽  
Hsiao-Lin Hwa ◽  
King-Jen Chang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Essential Gene ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Prognostic Signature ◽  
Prognostic Features ◽  
Bioinformatic Tools ◽  
Prognostic Feature ◽  
Relevant Gene

Background. MYBis predicted to be a favorable prognostic predictor in a breast cancer population. We proposed to find the inferred mechanism(s) relevant to the prognostic features ofMYBvia a supervised network analysis.Methods. Both coefficient of intrinsic dependence (CID) and Galton Pierson’s correlation coefficient (GPCC) were combined and designated as CIDUGPCC. It is for the univariate network analysis. Multivariate CID is for the multivariate network analysis. Other analyses using bioinformatic tools and statistical methods are included.Results. ARNT2is predicted to be the essential gene partner ofMYB. We classified four prognostic relevant gene subpools in three breast cancer cohorts as feature types I–IV. Only the probes in feature type II are the potential prognostic feature ofMYB. Moreover, we further validated 41 prognosis relevant probes to be the favorable prognostic signature. Surprisingly, two additional family members ofMYBare elevated to promote poor prognosis when both levels ofMYBandARNT2decline. BothMYBL1andMYBL2may partially decrease the tumor suppressive activities that are predicted to be up-regulated byMYBandARNT2.Conclusions. The major prognostic feature ofMYBis predicted to be determined by theMYBsubnetwork (41 probes) that is relevant across subtypes.

Gene expression profiles in premenopausal women with HR+ HER2− early breast cancer

2020 ◽  
Vol 138 ◽  
pp. S76
Author(s):  
H. Ni ◽  
A. Kurt ◽  
J. Kumbrink ◽  
A. Seiler ◽  
D. Mayr ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Early Breast Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Premenopausal Women
Sign in / Sign up

Export Citation Format

Share Document