scholarly journals Olfactory receptors OR5B21 and OR6C76 are differentially expressed in humans with triple negative breast cancer.

2019 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Olfactory Receptor ◽  
Triple Negative ◽  
Olfactory Receptors ◽  
Differentially Expressed ◽  
Survival Outcomes ◽  
Whole Genome ◽  
Genome Profiling ◽  
Whole Genome Profiling

Whole genome profiling data of 226 patients with triple negative breast cancer (1) was stratified based on survival. When comparing the transcriptomes of 87 patients that expired versus 123 patients that survived, two olfactory receptors were among the genes whose expression was most different. We previously reported that genes of the olfactory receptor superfamily were differentially expressed in metastases in the HER2+ Balb-NeuT mouse model of breast cancer (2). The data here indicate that differential expression of OR5B21 and OR6C76 associates with survival outcomes in humans with triple negative breast cancer.

scholarly journals Differential expression of methyltransferase METTL1 associates with death in a cohort of patients with triple negative breast cancer.

2019 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Differentially Expressed Gene ◽  
Whole Genome ◽  
Disease Course ◽  
The Third ◽  
Genome Profiling ◽  
Whole Genome Profiling

Whole genome profiling data of 226 patients with triple negative breast cancer using a published dataset (1) was stratified based on survival. When comparing the transcriptomes of 87 patients that expired versus 123 patients that survived, the methyltransferase like 1 METTL1 was the third most differentially expressed gene in the entire transcriptome. METTL1 mediates 7-methylguanosine modification of microRNAs and tRNAs (2,3,4,5,6). Increased expression of METTL1 is an indication that the disease course will likely result in fatality in patients with triple negative breast cancer and should be treated accordingly.

scholarly journals Iterative Variable Selection for High-Dimensional Data: Prediction of Pathological Response in Triple-Negative Breast Cancer

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 222
Author(s):  
Juan C. Laria ◽  
M. Carmen Aguilera-Morillo ◽  
Enrique Álvarez ◽  
Rosa E. Lillo ◽  
Sara López-Taruella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Variable Selection ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
A Priori ◽  
Simulated Data ◽  
Point Of View ◽  
High Dimensional ◽  
Whole Genome ◽  
Genome Context

Over the last decade, regularized regression methods have offered alternatives for performing multi-marker analysis and feature selection in a whole genome context. The process of defining a list of genes that will characterize an expression profile remains unclear. It currently relies upon advanced statistics and can use an agnostic point of view or include some a priori knowledge, but overfitting remains a problem. This paper introduces a methodology to deal with the variable selection and model estimation problems in the high-dimensional set-up, which can be particularly useful in the whole genome context. Results are validated using simulated data and a real dataset from a triple-negative breast cancer study.

scholarly journals MiR-211 determines brain metastasis specificity through SOX11/NGN2 axis in triple-negative breast cancer

Oncogene ◽  
2021 ◽  
Author(s):  
Jhih-Kai Pan ◽  
Cheng-Han Lin ◽  
Yao-Lung Kuo ◽  
Luo-Ping Ger ◽  
Hui-Chuan Cheng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Metastasis ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Survival Outcomes ◽  
Poor Survival ◽  
Breast Cancer Brain Metastasis ◽  
High Level

AbstractBrian metastasis, which is diagnosed in 30% of triple-negative breast cancer (TNBC) patients with metastasis, causes poor survival outcomes. Growing evidence has characterized miRNAs involving in breast cancer brain metastasis; however, currently, there is a lack of prognostic plasma-based indicator for brain metastasis. In this study, high level of miR-211 can act as brain metastatic prognostic marker in vivo. High miR-211 drives early and specific brain colonization through enhancing trans-blood–brain barrier (BBB) migration, BBB adherence, and stemness properties of tumor cells and causes poor survival in vivo. SOX11 and NGN2 are the downstream targets of miR-211 and negatively regulate miR-211-mediated TNBC brain metastasis in vitro and in vivo. Most importantly, high miR-211 is correlated with poor survival and brain metastasis in TNBC patients. Our findings suggest that miR-211 may be used as an indicator for TNBC brain metastasis.

scholarly journals The Survival Outcomes of T1aN0M0 Triple-Negative Breast Cancer With Adjuvant Chemotherapy

2020 ◽  
Vol 10 ◽  
Author(s):  
Wen-Fen Fu ◽  
Qing-Xia Chen ◽  
Xiao-Xiao Wang ◽  
Jie Zhang ◽  
Chuan-Gui Song
Keyword(s):  
Breast Cancer ◽  
Adjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Survival Outcomes

scholarly journals Differential expression of cyclin A2 in triple negative breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Differential Expression ◽  
Tumor Cells ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Differentially Expressed ◽  
Primary Tumors ◽  
Ductal Cells ◽  
Cyclin A2

Women diagnosed with triple negative breast cancer can benefit neither from endocrine therapy nor from HER2-targeted therapies (1). We mined published microarray datasets (2, 3) to determine in an unbiased fashion and at the systems level genes most differentially expressed in the primary tumors of patients with breast cancer. We report here significant differential expression of the gene encoding cyclin A2, CCNA2, when comparing the tumor cells of patients with triple negative breast cancer to normal mammary ductal cells (2). CCNA2 was also differentially expressed in bulk tumor in human breast cancer (3). CCNA2 mRNA was present at significantly increased quantities in TNBC tumor cells relative to normal mammary ductal cells. Analysis of human survival data revealed that expression of CCNA2 in primary tumors of the breast was correlated with overall survival in patients with basal-like type cancer, while within triple negative breast cancer, primary tumor expression of CCNA2 was correlated with overall survival in patients with basal-like 1, basal-like 2, and mesenchymal subtype disease. CCNA2 may be of relevance to initiation, maintenance or progression of triple negative breast cancers.

scholarly journals Prognostic Biomarkers on a Competitive Endogenous RNA Network Reveals Overall Survival in Triple-Negative Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Wenxing Qin ◽  
Feng Qi ◽  
Jia Li ◽  
Ping Li ◽  
Yuan-Sheng Zang
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Triple Negative Breast Cancer ◽  
Prognostic Model ◽  
Triple Negative ◽  
Cox Regression ◽  
Critical Role ◽  
Differentially Expressed ◽  
Cerna Network ◽  
Competitive Endogenous Rna

The objective of this study was to construct a competitive endogenous RNA (ceRNA) regulatory network using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with triple-negative breast cancer (TNBC) and to construct a prognostic model for predicting overall survival (OS) in patients with TNBC. Differentially expressed lncRNAs, miRNAs, and mRNAs in TNBC patients from the TCGA and Metabric databases were examined. A prognostic model based on prognostic scores (PSs) was established for predicting OS in TNBC patients, and the performance of the model was assessed by a recipient that operated on a distinctive curve. A total of 874 differentially expressed RNAs (DERs) were screened, among which 6 lncRNAs, 295 miRNAs and 573 mRNAs were utilized to construct targeted and coexpression ceRNA regulatory networks. Eight differentially expressed genes (DEGs) associated with survival prognosis, DBX2, MYH7, TARDBP, POU4F1, ABCB11, LHFPL5, TRHDE and TIMP4, were identified by multivariate Cox regression and then used to establish a prognostic model. Our study shows that the ceRNA network has a critical role in maintaining the aggressiveness of TNBC and provides comprehensive molecular-level insight for predicting individual mortality hazards for TNBC patients. Our data suggest that these prognostic mRNAs from the ceRNA network are promising therapeutic targets for clinical intervention.

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