A common transition in multi-drug resistance gene and risk of breast cancer: A genetic association study with an in silico-analysis

2016 ◽  
Vol 9 (4) ◽  
pp. 643-652
Author(s):  
Davood Kheirkhah ◽  
Mohammad Karimian
Keyword(s):  
Breast Cancer ◽  
Drug Resistance ◽  
Association Study ◽  
Resistance Gene ◽  
In Silico ◽  
Genetic Association Study ◽  
In Silico Analysis ◽  
Multi Drug Resistance ◽  
Common Transition ◽  
Silico Analysis

scholarly journals The Expression of miR-513c and miR-3163 was Downregulated in Tumor Tissues Compared with Margin Tissues of Patients With Breast Cancer

2020 ◽  
Author(s):  
Soheila Delgir ◽  
Khandan Ilkhani ◽  
Asma Safi ◽  
Farhad Seif ◽  
Milad Bastami ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
In Silico ◽  
In Silico Analysis ◽  
Glutamine Metabolism ◽  
Expression Level ◽  
P Value ◽  
Biological Processes ◽  
Tumor Tissues ◽  
Silico Analysis

Abstract Background Breast cancer (BC) is the most common invasive cancer with different subtypes that its metabolism is unique compared with normal cells. Glutamine is considered a critical nutrition for tumor cell growth and therefore, targeting glutamine metabolism, especially Glutaminase, which catalyzed the conversion of glutamine to glutamate can be beneficial to design anti-cancer agents. Recently, evidence has shown that miRNAs with short length and single strand properties play a significant role in regulating the genes related to glutamine metabolism and may control the development of cancer.Methods Since, in-silico analysis confirmed that miR-513c and miR-3163 might be involved in glutamine metabolism, the expression level of these two miRNAs was evaluated in eighty BC tissues and margin tissues. The data were analyzed to evaluate the correlation between expression level of these miRNAs and patient’s characteristics such as abortion history, family history, and age. Furthermore, in-silico analysis was applied to predict the potential biological processes and molecular pathways of miR-513c and miR-3163 based on its gene targets.Results In-silico studies revealed the top categories of biological processes and pathways that play a critical role in cancer development were target genes for miR-513c and miR-3163. The current study showed that miR-513c (P-value = 0.02062 and fold change= -2.3801) and miR-3163 (P-value = 0.02034 and fold change= -2.3792) were downregulated in tumor tissues compared to margin tissues. Furthermore, the subgroup studies did not show any substantial relationship between expression levels of these two miRNAs and factors such as age, family history cancer, and abortion.Conclusion Based on our data, miR-513c and miR-3163 may be offered as a potential diagnosis and therapeutic targets for patients with BC.

The pharmacoepigenetics of drug metabolism and transport in breast cancer: review of the literature and in silico analysis

2016 ◽  
Vol 17 (14) ◽  
pp. 1573-1585 ◽  
Author(s):  
Rihab Nasr ◽  
Fatima Sleiman ◽  
Zeinab Awada ◽  
Natalie K Zgheib
Keyword(s):  
Breast Cancer ◽  
Drug Metabolism ◽  
In Silico ◽  
In Silico Analysis ◽  
Review Of The Literature ◽  
Cancer Review ◽  
Silico Analysis

scholarly journals Association between SPARC mRNA Expression, Prognosis and Response to Neoadjuvant Chemotherapy in Early Breast Cancer: A Pooled in-silico Analysis

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e62451 ◽  
Author(s):  
Hatem A. Azim ◽  
Sandeep Singhal ◽  
Michail Ignatiadis ◽  
Christine Desmedt ◽  
Debora Fumagalli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Mrna Expression ◽  
Early Breast Cancer ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis ◽  
Response To Neoadjuvant Chemotherapy

scholarly journals In Silico Analysis Guides Selection of BET Inhibitors for Triple-Negative Breast Cancer Treatment

2016 ◽  
Vol 15 (8) ◽  
pp. 1823-1833 ◽  
Author(s):  
Javier Pérez-Peña ◽  
Gemma Serrano-Heras ◽  
Juan Carlos Montero ◽  
Verónica Corrales-Sánchez ◽  
Atanasio Pandiella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Triple Negative Breast Cancer ◽  
In Silico ◽  
Triple Negative ◽  
In Silico Analysis ◽  
Breast Cancer Treatment ◽  
Bet Inhibitors ◽  
Silico Analysis ◽  
Selection Of

scholarly journals EGF Induces Cell Motility and Multi-Drug Resistance Gene Expression in Breast Cancer Cells

Cell Cycle ◽  
2006 ◽  
Vol 5 (23) ◽  
pp. 2820-2826 ◽  
Author(s):  
Ruben Garcia ◽  
Richard A. Franklin ◽  
James A. McCubrey
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Drug Resistance ◽  
Cell Motility ◽  
Cancer Cells ◽  
Resistance Gene ◽  
Breast Cancer Cells ◽  
Multi Drug Resistance ◽  
Drug Resistance Gene
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