scholarly journals Gene Expression Profiling Identifies Molecular Subtypes of Inflammatory Breast Cancer

2005 ◽  
Vol 65 (6) ◽  
pp. 2170-2178 ◽  
Author(s):  
François Bertucci ◽  
Pascal Finetti ◽  
Jacques Rougemont ◽  
Emmanuelle Charafe-Jauffret ◽  
Nathalie Cervera ◽  
...  
2006 ◽  
Vol 9 (1) ◽  
pp. 1-3
Author(s):  
P. E. Lønning

Citation of original article:F. Bertucci, P. Finetti, J. Rougemont, E. Charafe-Jauffret, N. Cervera, C. Tarpin,et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer.Cancer Research2005;65(6): 2170–8.Abstract of the original articleBreast cancer is a heterogeneous disease. Comprehensive gene expression profiles obtained using DNA microarrays have revealed previously indistinguishable subtypes of non-inflammatory breast cancer (NIBC) related to different features of mammary epithelial biology and significantly associated with survival. Inflammatory breast cancer (IBC) is a rare, particular, and aggressive form of disease. Here we have investigated whether the five molecular subtypes described for NIBC (luminal A and B, basal, ERBB2 overexpressing, and normal breast-like) were also present in IBC. We monitored the RNA expression of approximately 8,000 genes in 83 breast tissue samples including 37 IBC, 44 NIBC, and 2 normal breast samples. Hierarchical clustering identified the five subtypes of breast cancer in both NIBC and IBC samples. These subtypes were highly similar to those defined in previous studies and associated with similar histoclinical features. The robustness of this classification was confirmed by the use of both alternative gene set and analysis method, and the results were corroborated at the protein level. Furthermore, we show that the differences in gene expression between NIBC and IBC and between IBC with and without pathologic complete response that we have recently reported persist in each subtype. Our results show that the expression signatures defining molecular subtypes of NIBC are also present in IBC. Obtained using different patient series and different microarray platforms, they reinforce confidence in the expression-based molecular taxonomy but also give evidence for its universality in breast cancer, independently of a specific clinical form.


2005 ◽  
Vol 95 (3) ◽  
pp. 243-255 ◽  
Author(s):  
Steven J. Van Laere ◽  
Gert G. Van den Eynden ◽  
Ilse Van der Auwera ◽  
Melanie Vandenberghe ◽  
Peter van Dam ◽  
...  

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 2531-2531
Author(s):  
J. Hannemann ◽  
H. Halfwerk ◽  
A. Velds ◽  
C. Loo ◽  
E. J. Rutgers ◽  
...  

2531 Background: Preoperative chemotherapy is increasingly employed to treat primary breast cancer, allowing an ‘in vivo chemosensitivity test’. Markers which predict a pathological complete response are urgently needed to refine this strategy. This study was conducted to evaluate the use of gene expression profiling to predict response to neoadjuvant anthracycline- or taxane-based chemotherapy. Methods: Patients with operable or locally advanced HER2-negative breast cancer received preoperative chemotherapy: either dose- dense doxorubicin and cyclophosphamide (ddAC) or capecitabine and docetaxel (CD). Core needle biopsies were taken before treatment and gene expression profiling was performed using 35k oligo microarrays. Results: Gene expression profiles were obtained from pretreatment biopsies of 63 tumors. 27% of the patients achieved a (near) pathologic complete remission (pCR), 40% of the patients had a partial remission and 33% of the patients did not respond to chemotherapy. Based on the gene expression profiles, tumors were assigned to the previously identified “molecular subtypes” luminal, basal-like or ERBB2-like (Sorlie et al., PNAS 98: 10869, 2001). 13 out of 25 patients with a basal-like tumor (52%) achieved a complete remission, whereas for the luminal tumors a pCR was only obtained in 2 out of 29 patients. Using four published gene expression classifiers of response to chemotherapy, a reasonable separation between responders and non-responders could be observed for two of these. We also performed exploratory supervised classification analyses on our dataset to identify a novel classifier. This resulted in a classifier for response to therapy irrespective of the chemotherapy regimen used and a second classifier specifically associated with response to ddAC chemotherapy. We will perform validation of these classifiers in samples from patients that are currently being enrolled in the study. Conclusions: Basal-like tumors have a better response to neoadjuvant chemotherapy as compared to other tumor types. The identification of robust gene expression signatures for better response prediction may require larger patient groups and should probably be established separately for each of the molecular subtypes of breast cancer. No significant financial relationships to disclose.


2004 ◽  
Vol 64 (23) ◽  
pp. 8558-8565 ◽  
Author(s):  
François Bertucci ◽  
Pascal Finetti ◽  
Jacques Rougemont ◽  
Emmanuelle Charafe-Jauffret ◽  
Valéry Nasser ◽  
...  

Cancer ◽  
2010 ◽  
Vol 116 (S11) ◽  
pp. 2783-2793 ◽  
Author(s):  
François Bertucci ◽  
Pascal Finetti ◽  
Daniel Birnbaum ◽  
Patrice Viens

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109742 ◽  
Author(s):  
Fengliang Wang ◽  
Sheng Gao ◽  
Fei Chen ◽  
Ziyi Fu ◽  
Hong Yin ◽  
...  

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