scholarly journals Review of: Gene expression profiling identifies molecular subtypes of inflammatory breast cancer

2006 ◽  
Vol 9 (1) ◽  
pp. 1-3
Author(s):  
P. E. Lønning
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Inflammatory Breast Cancer ◽  
Expression Profiling ◽  
Molecular Subtypes ◽  
Expression Profiles ◽  
Molecular Taxonomy ◽  
Pathologic Complete Response ◽  
Normal Breast

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.

Prospective analysis of mRNA expression signatures as predictive tests in primary breast cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 2531-2531
Author(s):  
J. Hannemann ◽  
H. Halfwerk ◽  
A. Velds ◽  
C. Loo ◽  
E. J. Rutgers ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Complete Remission ◽  
Gene Expression Profiling ◽  
Preoperative Chemotherapy ◽  
Expression Profiling ◽  
Primary Breast Cancer ◽  
Molecular Subtypes ◽  
Expression Profiles ◽  
Gene Expression Profiles

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.

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 ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Inflammatory Breast Cancer ◽  
Expression Profiling ◽  
Molecular Subtypes

scholarly journals Identification of cell-of-origin breast tumor subtypes in inflammatory breast cancer by gene expression profiling

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 ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Inflammatory Breast Cancer ◽  
Expression Profiling ◽  
Breast Tumor ◽  
Cell Of Origin ◽  
Tumor Subtypes

Pharmacogenomic analysis of needle biopsies obtained before preoperative docetaxel/capecitabine/FEC (TX/FEC) chemotherapy for breast cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10595-10595 ◽  
Author(s):  
F. A. Holmes ◽  
J. A. O’Shaughnessy ◽  
B. Hellerstedt ◽  
J. Pippen ◽  
S. Vukelja ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Rna Extraction ◽  
Tumor Biology ◽  
Pathologic Complete Response ◽  
Research Network ◽  
Community Practice ◽  
Oncology Research

10595 Background: Our goal was to evaluate the feasibility of obtaining fine needle biopsies, for pharmacogenomic analysis, in community based oncology practices and develop gene expression-based predictors of pathologic complete response (pCR) to preoperative sequential docetaxel/capecitabine and 5-fluorouracil, epirubicin, cyclophosphamide chemotherapy. Methods: One hundred seventy-five patients were accrued at 29 sites in the US Oncology Research network. FNA specimens were mailed to a central laboratory (MDACC) and gene expression profiling was performed on Affymetrix U133A chips. Results: RNA extraction was started on 140 specimens, 112 of these (80%) yielded ≥1 μg total RNA, 69 were hybridized and 65 (94%) gene expression profiles have passed quality control as of abstract submission date. The analysis plan is to develop a multigene predictor of pCR from the first 80 cases and test its performance independently in the remaining cases. Conclusions: Collection of mandatory research FNA biopsies for pharmacogenomic research is feasible in community practice. Approximately 80% of biopsies yield sufficient RNA for gene expression profiling. In 20% of patients, either technical factors, which can be addressed, or tumor biology (necrotic, rapidly growing tumors) were limiting. Supported by Roche Laboratories, Inc., Nutley, NJ; Pfizer, New York, NY; and Precision Therapeutics, Pittsburgh, PA. [Table: see text]

scholarly journals Gene Expression Profiling for Molecular Characterization of Inflammatory Breast Cancer and Prediction of Response to Chemotherapy

2004 ◽  
Vol 64 (23) ◽  
pp. 8558-8565 ◽  
Author(s):  
François Bertucci ◽  
Pascal Finetti ◽  
Jacques Rougemont ◽  
Emmanuelle Charafe-Jauffret ◽  
Valéry Nasser ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Molecular Characterization ◽  
Inflammatory Breast Cancer ◽  
Expression Profiling ◽  
Prediction Of Response ◽  
Response To Chemotherapy

scholarly journals Microarrays in breast cancer research and clinical practice – the future lies ahead

2006 ◽  
Vol 13 (4) ◽  
pp. 1017-1031 ◽  
Author(s):  
Sofia K Gruvberger-Saal ◽  
Heather E Cunliffe ◽  
Kristen M Carr ◽  
Ingrid A Hedenfalk
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Human Breast Cancer ◽  
Expression Profiles ◽  
Single Gene ◽  
Molecular Profiling ◽  
Response To Treatment ◽  
Human Breast

Molecular profiling for classification and prognostic purposes has demonstrated that the genetic signatures of tumors contain information regarding biological properties as well as clinical behavior. This review highlights the progress that has been made in the field of gene expression profiling of human breast cancer. Breast cancer has become one of the most intensely studied human malignancies in the genomic era; several hundred papers over the last few years have investigated various clinical and biological aspects of human breast cancer using high-throughput molecular profiling techniques. Given the grossly heterogeneous nature of the disease and the lack of robust conventional markers for disease prediction, prognosis, and response to treatment, the notion that a transcriptional profile comprising multiple genes, rather than any single gene or other parameter, will be more predictive of tumor behavior is both appealing and reasonable. Promising results have emerged from these studies, correlating gene expression profiles with prognosis, recurrence, metastatic potential, therapeutic response, as well as biological and functional aspects of the disease. Clearly, the integration of genomic approaches into the clinic lies in the near future, but prospective studies based on larger patient cohorts representing the whole spectrum of breast cancer, oncogenic pathway-based studies, attendant care in bioinformatic analyses and validation studies are needed before the full promise of gene expression profiling can be realized in the clinical setting.

Gene expression profiling of inflammatory breast cancer

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