Molecular Mechanisms of Breast Cancer Progression: Lessons from Mouse Mammary Cancer Models and Gene Expression Profiling

2004 ◽  
Vol 19 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Yumei Ye ◽  
Ting Hu Qiu ◽  
Claudine Kavanaugh ◽  
Jeffrey E. Green
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Cancer Progression ◽  
Expression Profiling ◽  
Mammary Cancer ◽  
Molecular Mechanisms ◽  
Breast Cancer Progression ◽  
Cancer Models

scholarly journals Gene expression profiling of tumour epithelial and stromal compartments during breast cancer progression

2012 ◽  
Vol 135 (1) ◽  
pp. 153-165 ◽  
Author(s):  
Ana Cristina Vargas ◽  
Amy E. McCart Reed ◽  
Nic Waddell ◽  
Annette Lane ◽  
Lynne E. Reid ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Cancer Progression ◽  
Expression Profiling ◽  
Breast Cancer Progression

scholarly journals Gene expression profiling of the tumor microenvironment during breast cancer progression

2009 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao-Jun Ma ◽  
Sonika Dahiya ◽  
Elizabeth Richardson ◽  
Mark Erlander ◽  
Dennis C Sgroi
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Tumor Microenvironment ◽  
Gene Expression Profiling ◽  
Cancer Progression ◽  
Expression Profiling ◽  
Breast Cancer Progression

Prediction of Docetaxel Response in Human Breast Cancer by Gene Expression Profiling

2005 ◽  
Vol 23 (3) ◽  
pp. 422-431 ◽  
Author(s):  
Kyoko Iwao-Koizumi ◽  
Ryo Matoba ◽  
Noriko Ueno ◽  
Seung Jin Kim ◽  
Akiko Ando ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Side Effects ◽  
Gene Expression Profiling ◽  
Clinical Response ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Redox System ◽  
Response To Therapy

Purpose Docetaxel is one of the most effective anticancer drugs available in the treatment of breast cancer. Nearly half of the treated patients, however, do not respond to chemotherapy and suffer from side effects. The ability to reliably predict a patient's response based on tumor gene expression will improve therapeutic decision making and save patients from unnecessary side effects. Patients and Methods A total of 44 breast tumor tissues were sampled by biopsy before treatment with docetaxel, and the response to therapy was clinically evaluated by the degree of reduction in tumor size. Gene expression profiling of the biopsy samples was performed with 2,453 genes using a high-throughput reverse transcriptase polymerase chain reaction technique. Using genes differentially expressed between responders and nonresponders, a diagnostic system based on the weighted-voting algorithm was constructed. Results This system predicted the clinical response of 26 previously unanalyzed samples with over 80% accuracy, a level promising for clinical applications. Diagnostic profiles in nonresponders were characterized by elevated expression of genes controlling the cellular redox environment (ie, redox genes, such as thioredoxin, glutathione-S-transferase, and peroxiredoxin). Overexpression of these genes protected cultured mammary tumor cells from docetaxel-induced cell death, suggesting that enhancement of the redox system plays a major role in docetaxel resistance. Conclusion These results suggest that the clinical response to docetaxel can be predicted by gene expression patterns in biopsy samples. The results also suggest that one of the molecular mechanisms of the resistance is activation of a group of redox genes.

scholarly journals Mammary Fat of Breast Cancer: Gene Expression Profiling and Functional Characterization

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109742 ◽  
Author(s):  
Fengliang Wang ◽  
Sheng Gao ◽  
Fei Chen ◽  
Ziyi Fu ◽  
Hong Yin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Functional Characterization ◽  
Cancer Gene ◽  
Breast Cancer Gene

scholarly journals Gene expression profiling and breast cancer care: What are the potential benefits and policy implications?

2005 ◽  
Vol 7 (6) ◽  
pp. 380-389 ◽  
Author(s):  
Nina Oestreicher ◽  
Scott D Ramsey ◽  
Hannah M Linden ◽  
Jeannine S McCune ◽  
Laura J van't Veer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Cancer Care ◽  
Expression Profiling ◽  
Policy Implications ◽  
Breast Cancer Care ◽  
Potential Benefits
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