Amplification of the Oncogene HER2 in Breast Cancer: Molecular Basis and Therapeutic Significance

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Francini Matos Lima Lin ◽  
Edmund Chada Baracat ◽  
Filomena Marino Carvalho
2018 ◽  
Author(s):  
Asim Pervaiz ◽  
Muhammad Shoaib Akhtar ◽  
Saqib Mahmood ◽  
Osheen Sajjad ◽  
Saba Khaliq ◽  
...  

2010 ◽  
Vol 2 ◽  
pp. BIC.S3793 ◽  
Author(s):  
Arvind D. Thakkar ◽  
Hemanth Raj ◽  
Debarshi Chakrabarti ◽  
Ravishankar ◽  
N. Saravanan ◽  
...  

A significant group of patient with estrogen receptor (ER) α positive breast tumors fails to appreciably respond to endocrine therapy. An increased understanding of the molecular basis of estrogen-mediated signal transduction and resultant gene expression may lead to novel strategies for treating breast cancer. In this study, we sought to identify the dysregulated genes in breast tumors related to ERα status. Microarray analyses of 31 tumor samples showed 108 genes differentially expressed in ERα (+) and ERα (–) primary breast tumors. Further analyses of gene lists indicated that a significant number of dysregulated genes were involved in mRNA transcription and cellular differentiation. The majority of these genes were found to have promoter-binding sites for E74-like factor 5 (ELF5; 54.6% genes), E2F transcription factor 1 (E2F1; 22.2% genes), and nuclear transcription factor Y alpha (NFYA; 32.4% genes). Six candidate genes ( NTN4, SLC7A8, MLPH, ENPP1, LAMB2, and PLAT) with differential expression were selected for further validation studies using RT-qPCR (76 clinical specimen) and immunohistochemistry (48 clinical specimen). Our studies indicate significant overexpression of all the six genes in ERα (+) breast tumors as compared to ERα (–) breast tumors. In vitro studies using T-47D breast cancer cell line confirmed the estrogen dependant expression of four of the above six genes ( SLC7A8, ENPP1, LAMB2, and PLAT). Collectively, our study provides further insights into the molecular basis of estrogen-dependent breast cancer and identifies “candidate biomarkers” that could be useful for predicting endocrine responsiveness.


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