c-kit: Identification of co-regulated genes by gene expression profiling and clinical relevance of two breast cancer subtypes with stem cell like features

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 622-622 ◽  
Author(s):  
A. Rody ◽  
U. Holtrich ◽  
V. Müller ◽  
R. Gaetje ◽  
R. Diallo ◽  
...  

622 Background: Expression of the proto-oncogene c-kit has been found in malignant tissue including a subset of breast cancers. c-Kit is also expressed in normal breast tissue and several authors found a loss of c-kit expression in breast carcinoma suggesting it might be involved in the growth control of mammary epithelium. Until now, only a few markers were described to be co-regulated with c-kit. To elucidate the possible role of c-kit in malignant transformation, we analyzed gene expression data of breast cancer patients. Methods: Tumor tissue of n=171 breast cancer patients were analyzed by gene expression profiling using Affymetrix Hg U133 Arrays (22,500 genes) and bioinformatic analyses. Tumor samples with high stromal and low epithelial cell content by gene expression profiling were excluded for further analysis. Validation was performed with n=100 independent samples. Results: A total of 10.5% of the tumors showed strong c-kit expression (2.5 fold above median). A careful dissection of global expression data revealed strong correlations of c-kit with the expression of a large cluster of genes containing several for whom c-kit coexpression was already described (HER1, CK-5/-17, PDGFR) as well as several members of the wnt signalling pathway, providing a possible novel link to mammary epithelial differentiation. Analysis of n=171 breast cancer samples according to this gene set allows the identification of putative “stem cell like” tumors (SCL) characterized by expression of several known stem cell markers. Surprisingly, a tight link of ER status and proliferation is restricted only to these SCL tumors but lost among non-SCL tumors. The clinical implications of our findings will be presented. Conclusions: For the first time these data bring together the description of two breast cancer subtypes identified by gene expression profiling with the actual stem cell model of the development of breast cancer. No significant financial relationships to disclose.

Cancer ◽  
2015 ◽  
Vol 121 (22) ◽  
pp. 4062-4070 ◽  
Author(s):  
Arnold L. Potosky ◽  
Suzanne C. O'Neill ◽  
Claudine Isaacs ◽  
Huei-Ting Tsai ◽  
Calvin Chao ◽  
...  

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22041-e22041
Author(s):  
C. Lih ◽  
Y. Li ◽  
L. Trinh ◽  
S. Chien ◽  
X. Wu ◽  
...  

e22041 Background: Microarrays have been used to monitor global genes expression and have aided the identification of novel biomarkers for patients stratification and drug response prediction . To date there has been limited application of microarray- based gene expression analysis to formalin fixed paraffin embedded tissues (FFPET). FFPE tissues are the most commonly available clinical samples with documented clinical information for retrospective clinical analysis. However, FFPET RNA has proven to be an obstacle for microarray analysis because of low yield and compromised RNA integrity. Methods: Using a novel RNA amplification method, Single Primer Isothermal Amplification (SPIA, NuGEN Inc, San Carlos, CA), we amplified FFPET RNA, hybridized amplified, and labeled cDNA onto Affymetrix HG U133plus2 GeneChips. Results: We found that SPIA amplification successfully overcomes the problems of poor quality of FFPET RNA, and produced informative biological data. Comparing the gene expression data from 5 different types of FFPET archival cancer samples (breast, lung, ovarian, colon, and melanoma), we demonstrated that gene expression signatures clearly distinguish the tissue of origin. Further, from an analysis of 91 FFPET samples comprised of ER+, HER2+, triple negative breast cancer patients, and normal breast tissue, we have identified a 103 gene signature that distinguishes the intrinsic sub-types of breast cancer. Finally, the accuracy of gene expression measured by microarray was verified by real time PCR quantitation of the ERBB2 gene, resulting in a significant correlation (R = 0.88). Conclusions: We have demonstrated the feasibility of global gene expression profiling using RNA extracted from FFPET and have shown that a gene expression signature can stratify patient samples into different subtypes of disease. This study paves the way to identify novel molecular biomarkers for disease stratification and therapy response from archival FFPET samples, leading to the goals of personalized medicine. No significant financial relationships to disclose.


2001 ◽  
Vol 195 (3) ◽  
pp. 312-320 ◽  
Author(s):  
Andr� Ahr ◽  
Uwe Holtrich ◽  
Christine Solbach ◽  
Anton Scharl ◽  
Klaus Strebhardt ◽  
...  

2010 ◽  
Vol 1 (3) ◽  
pp. 421-437 ◽  
Author(s):  
Michael R. Mallmann ◽  
Andrea Staratschek-Jox ◽  
Christian Rudlowski ◽  
Michael Braun ◽  
Andrea Gaarz ◽  
...  

The Lancet ◽  
2002 ◽  
Vol 359 (9301) ◽  
pp. 131-132 ◽  
Author(s):  
André Ahr ◽  
Thomas Karn ◽  
Christine Solbach ◽  
Tanja Seiter ◽  
Klaus Strebhardt ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document