Project description:Background: Breast cancer is a complex disease, encompassed by different clinically and molecularly stratified entities. In 2000, Perou and colleagues demonstrated that tumor phenotypic diversity correlates with differences in global gene expression patterns, which in turn reflect aspects of the biological behavior of the tumors. Gene expression profiling has distinguished sporadic breast tumor sub-classes with genetic, histopathological and clinical differences, however, little is known about the molecular classification of hereditary breast tumors. It has been recently suggested that most tumors arising in BRCA1 mutation carriers display a basal-like phenotype, with the percentages reported in different studies ranging from 44 to almost 100%. In the present study we used expression profiling to produce a molecular classification of BRCA1-associated breast tumors and applied an integrative approach to examine biological dependencies or differences. Methods and Findings: We used frozen tumor tissue from fourteen patients all of which harbored germline pathological mutations in BRCA1. Total RNA extraction, amplification and labeling with Cy5 were performed using standard protocols. Universal Human Reference RNA (Stratagene) was used as a reference and labeled with Cy3. Each pair of Cy3/Cy5 samples was hybridized onto the CNIO human OncoChip V2, which consists of a spotted microarray with 11,675 cDNA clones from the I.M.A.G.E. Consortium. Two channel ratios (Cy5/Cy3) for each spot were generated and quantified using GenePix Pro 5.1 (Axon Instruments, Inc., Union City, CA, USA). Data were normalized and filtered and multiple statistical analyses were performed. The data are deposited in the GEO database under the accession number GSE12350. A tissue microarray (TMA) containing an independent series of 15 BRCA1 tumors was used to validate some of the results obtained. We have described molecular signatures that define BRCA1 subclasses depending on the expression of the gene encoding for Estrogen Receptor, ESR1. Signatures were found to be molecularly associated with different biological processes and transcriptional regulatory programs. The signature of ESR1-positive tumors was mainly linked to cell proliferation-related processes and, therefore, regulated by the estrogen receptor, while the signature of ESR1-negative tumors was mainly linked to the immune response and possibly regulated by transcription factors of the REL/NFκB family. These signatures were then verified in an independent series of hereditary and sporadic breast tumors, which revealed a possible prognostic value for each subclass. Over-expression of immune response genes appears to be a common feature of ER-negative sporadic and hereditary breast cancer and is associated with good prognosis. Interestingly, the ESR1-negative tumors were sub-stratified into two groups presenting light differences in the magnitude of the expression of immune response transcripts and REL/NFκB transcription factors, and this could be dependent on the type of germline alteration. In addition, analysis of the human protein-protein interaction network provides the wiring diagram of critical molecular associations in BRCA1 tumorigenesis and identifies close relationships between the different signatures. Conclusions: In summary, in the present study we have established the gene expression profiling of a series of BRCA1 tumors and found that there is a further degree of heterogeneity beyond the main classification by the expression of ESR1 and the presence or absence of a basal-like phenotype. We have identified specific signatures for ESR1-positive and ESR1-negative BRCA1 tumors, the latter characterized by the enrichment of immune response and cell cycle genes, and have found that slight differences in the level of expression of the immune response stratify the ESR1-negative BRCA1 tumors into two additional sub-groups (A and B) with possible prognostic differences. NFkB could be a major driver responsible for the levels of both immune response and apoptotic genes in this group of tumors, which could in turn be related to the type of germline mutation in BRCA1. This study reveals the molecular complexity of BRCA1 breast tumors, which are found to display similarities to sporadic tumors, and suggests possible prognostic implications. 14 samples (primary breast tumors containing a BRCA1 mutation) were hybridized to a cDNA microarray in order to investigate the possible heterogeneity within the BRCA1 group.

Project description:To better characterize group IE like human breast cancer based on the gene profiles of estrogen actions through estrogen receptor alpha (ER alpha), we identified an ER alpha transcriptional regulatory network for cell cycle in silico. We used two datasets from cell line (Data 1) and clinical samples (Data 2), respectively. Analyses on Data 1 via trajectory clustering and Pathway-Express confirmed the significant estrogen effect on up-regulating cell cycle activities. The gene expression relationships between ER alpha and cell cycle genes were re-identified in Data 2 by three statistical methods – Galton-Pearson’s correlation coefficient, Student’s t-test and the coefficient of intrinsic dependence. They were mostly (56.09%)(46/82) re-confirmed by literature search. E2F1 was found to be the major ER alpha target in regulating cell cycle gene expressions (83.72%)(36/43) via suppressive mode. However, enhanced cell cycle progression via up-regulating some cell cycle genes was predicted in silico possibly involving E2F2, in part. Both tumorigenic and tumor suppressing activities indicated by this network were predicted. This network clearly provides a robust way for uncovering estrogen actions in an ER(+) subtype specific manner. Experiment Overall Design: Two clinical datasets were used in this study. One, the 37 clinical arrays (abbreviated as 37A) consist of 26 A for patients positive in estrogen receptor alpha (ER) and in progesterone receptor (PR) immunohistochemical stain (IHC) and 11A for patients negative in ER IHC. This dataset was designated as Data 2. The 31 clinical arrays (31A) consist of 20A for patients positive in ER status but negative in PR status and 11A which are the same as in 37A. This dataset was used for data comparison. All the signals from the mRNA profile of each sample in the experiments were normalized using the internal control RNA- Stratagene's human common reference RNA via statistical method 'rank consistant lowess. Finally, those ratios were transformed by Log2.

Project description:Tumorigenic breast cancer cells characterized by CD44 expression and low or undetectable CD24 levels (CD44+/CD24-/low) may be resistant to chemotherapy and therefore responsible for cancer relapse. Paired breast cancer core biopsies before and after neoadjuvant chemotherapy or lapatinib were obtained and as single cell suspensions stained using antibodies against CD24, CD44, and lineage markers, and then analyzed by flow cytometry. Mammosphere (MS) formation in culture was compared before and after treatment. Global gene expression differences between cancer cells bearing CD44+/CD24-/low cells and all other sorted cells, and between cancer MS and the primary bulk invasive cancers were analyzed. We report that CD44+/CD24-/low tumorigenic breast cancer cells were intrinsically chemoresistant - chemotherapy led to increased CD44+/CD24-/low cells, increased self-renewal capacity on MS assays, and enhanced tumorigeneicity in immunocompromised SCID/Beige mice. Conversely, in patients with HER2 overexpressing tumors, the EGFR/HER2 tyrosine kinase inhibitor, lapatinib decreased CD44+/CD24-/low cells, with the majority of these patients after conventional therapy achieving pathologic complete response, a validated surrogate marker for long-term survival. Gene transcription pathways that underlie chemoresistant, MS-forming CD44+/CD24-/low cells involve genes belonging to stem cell self-renewal, Wnt signaling, and early development pathways. Experiment Overall Design: Cells from human breast tumors were grown as mammospheres (MS). Experiment Overall Design: Isolated single cell suspensions from primary breast cancers were plated onto non-adherent (polyhema-coated) plastic, counted with a hematocytometer, and 20,000 cells were then seeded into a 6-well ultra-low attachment plate supplemented with 2mL MEGM, with the addition of 2 mL of freshly unfrozen MEGM every 3-4 days. Gene expression profiles were taken of both MS and primary bulk tumors and compared with each other.

Project description:Background: Breast cancer is a complex disease, encompassed by different clinically and molecularly stratified entities. In 2000, Perou and colleagues demonstrated that tumor phenotypic diversity correlates with differences in global gene expression patterns, which in turn reflect aspects of the biological behavior of the tumors. Gene expression profiling has distinguished sporadic breast tumor sub-classes with genetic, histopathological and clinical differences, however, little is known about the molecular classification of hereditary breast tumors. It has been recently suggested that most tumors arising in BRCA1 mutation carriers display a basal-like phenotype, with the percentages reported in different studies ranging from 44 to almost 100%. In the present study we used expression profiling to produce a molecular classification of BRCA1-associated breast tumors and applied an integrative approach to examine biological dependencies or differences. Methods and Findings: We used frozen tumor tissue from fourteen patients all of which harbored germline pathological mutations in BRCA1. Total RNA extraction, amplification and labeling with Cy5 were performed using standard protocols. Universal Human Reference RNA (Stratagene) was used as a reference and labeled with Cy3. Each pair of Cy3/Cy5 samples was hybridized onto the CNIO human OncoChip V2, which consists of a spotted microarray with 11,675 cDNA clones from the I.M.A.G.E. Consortium. Two channel ratios (Cy5/Cy3) for each spot were generated and quantified using GenePix Pro 5.1 (Axon Instruments, Inc., Union City, CA, USA). Data were normalized and filtered and multiple statistical analyses were performed. The data are deposited in the GEO database under the accession number GSE12350. A tissue microarray (TMA) containing an independent series of 15 BRCA1 tumors was used to validate some of the results obtained. We have described molecular signatures that define BRCA1 subclasses depending on the expression of the gene encoding for Estrogen Receptor, ESR1. Signatures were found to be molecularly associated with different biological processes and transcriptional regulatory programs. The signature of ESR1-positive tumors was mainly linked to cell proliferation-related processes and, therefore, regulated by the estrogen receptor, while the signature of ESR1-negative tumors was mainly linked to the immune response and possibly regulated by transcription factors of the REL/NFκB family. These signatures were then verified in an independent series of hereditary and sporadic breast tumors, which revealed a possible prognostic value for each subclass. Over-expression of immune response genes appears to be a common feature of ER-negative sporadic and hereditary breast cancer and is associated with good prognosis. Interestingly, the ESR1-negative tumors were sub-stratified into two groups presenting light differences in the magnitude of the expression of immune response transcripts and REL/NFκB transcription factors, and this could be dependent on the type of germline alteration. In addition, analysis of the human protein-protein interaction network provides the wiring diagram of critical molecular associations in BRCA1 tumorigenesis and identifies close relationships between the different signatures. Conclusions: In summary, in the present study we have established the gene expression profiling of a series of BRCA1 tumors and found that there is a further degree of heterogeneity beyond the main classification by the expression of ESR1 and the presence or absence of a basal-like phenotype. We have identified specific signatures for ESR1-positive and ESR1-negative BRCA1 tumors, the latter characterized by the enrichment of immune response and cell cycle genes, and have found that slight differences in the level of expression of the immune response stratify the ESR1-negative BRCA1 tumors into two additional sub-groups (A and B) with possible prognostic differences. NFkB could be a major driver responsible for the levels of both immune response and apoptotic genes in this group of tumors, which could in turn be related to the type of germline mutation in BRCA1. This study reveals the molecular complexity of BRCA1 breast tumors, which are found to display similarities to sporadic tumors, and suggests possible prognostic implications.

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Transcription profiling of BRCA1 wild type and mutant human breast tumors to examine expression of ER-alpha

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