FOXA1 in breast cancer

2009 ◽  
Vol 11 ◽  
Author(s):  
Harikrishna Nakshatri ◽  
Sunil Badve
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Transcription Factor ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Signature ◽  
Specific Gene ◽  
Breast Cancers ◽  
Transcription Factor Network ◽  
Histopathological Classification

Breast cancer is a heterogeneous disease and classification is important for clinical management. At least five subtypes can be identified based on unique gene expression patterns; this subtype classification is distinct from the histopathological classification. The transcription factor network(s) required for the specific gene expression signature in each of these subtypes is currently being elucidated. The transcription factor network composed of the oestrogen (estrogen) receptor α (ERα), FOXA1 and GATA3 may control the gene expression pattern in luminal subtype A breast cancers. Breast cancers that are dependent on this network correspond to well-differentiated and hormone-therapy-responsive tumours with good prognosis. In this review, we discuss the interplay between these transcription factors with a particular emphasis on FOXA1 structure and function, and its ability to control ERα function. Additionally, we discuss modulators of FOXA1 function, ERα–FOXA1–GATA3 downstream targets, and potential therapeutic agents that may increase differentiation through FOXA1.

A gene expression signature of eventual brain metastases in patients with breast cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 1019-1019
Author(s):  
Y. Tham ◽  
C. Creighton ◽  
C. Gutierrez ◽  
C. K. Osborne ◽  
P. Brown ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Brain Metastases ◽  
Lung Metastases ◽  
Expression Patterns ◽  
Gene Expression Signature ◽  
Breast Cancers ◽  
Primary Tumors ◽  
Er Positive ◽  
Her 2

1019 Background: The incidence of brain metastases (BM) from breast cancer may be increasing, in part due to more effective systemic therapy. A metastatic signature of bone or lung metastases has been identified in mice but not for BM in human. We hypothesized that gene expression patterns of primary breast cancers may provide a specific metastatic signature for eventual BM. Methods: Core biopsies from primary breast cancers of 11 patients with BM and 12 patients who have other non-brain metastases were identified. Double- stranded cDNA was synthesized using an oligo-dT primer containing a T7 RNA polymerase promoter, followed by in vitro transcription with biotinylated ribonucleotides. The labeled cRNA was hybridized to Affymetrix U133-A chips. Results: Of the patients with BM, 55% were ER negative/HER-2 positive while 36% were ER positive/HER-2 negative. Of the patients with non brain metastases, 42% were ER negative/HER-2 positive and 50% were ER positive/HER-2 negative, with. A differential pattern of gene expression was seen in primary tumors of patients with BM when compared with those who had non-brain metastases. Many more genes were found elevated in patients with BM over what would be expected by chance (after correcting for multiple testing). Tumors that developed BM had expression of genes related to the neurological development pathways such as fetal Alzheimer antigen, MAD, neuropilin 1, and others. Several kinase pathways were involved such as protein kinase C and casein kinase substrate in neurons 2, and A kinase (PRKA) anchor protein 13. These genes will be validated in an independent set of patients with BM and non-brain metastases using real time PCR. Conclusions: The identification of genes that may predict for future development of brain metastases has many implications in terms of screening or prophylactic treatment. This would also help identify potential targets for the treatment of brain metastases. No significant financial relationships to disclose.

scholarly journals Identification of Gene Expression Signature in Estrogen Receptor Positive Breast Carcinoma

2010 ◽  
Vol 2 ◽  
pp. BIC.S3793 ◽  
Author(s):  
Arvind D. Thakkar ◽  
Hemanth Raj ◽  
Debarshi Chakrabarti ◽  
Ravishankar ◽  
N. Saravanan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Estrogen Receptor ◽  
Transcription Factor ◽  
Molecular Basis ◽  
Clinical Specimen ◽  
Gene Expression Signature ◽  
Breast Tumors ◽  
Significant Group ◽  
Six Genes

A significant group of patient with estrogen receptor (ER) α positive breast tumors fails to appreciably respond to endocrine therapy. An increased understanding of the molecular basis of estrogen-mediated signal transduction and resultant gene expression may lead to novel strategies for treating breast cancer. In this study, we sought to identify the dysregulated genes in breast tumors related to ERα status. Microarray analyses of 31 tumor samples showed 108 genes differentially expressed in ERα (+) and ERα (–) primary breast tumors. Further analyses of gene lists indicated that a significant number of dysregulated genes were involved in mRNA transcription and cellular differentiation. The majority of these genes were found to have promoter-binding sites for E74-like factor 5 (ELF5; 54.6% genes), E2F transcription factor 1 (E2F1; 22.2% genes), and nuclear transcription factor Y alpha (NFYA; 32.4% genes). Six candidate genes ( NTN4, SLC7A8, MLPH, ENPP1, LAMB2, and PLAT) with differential expression were selected for further validation studies using RT-qPCR (76 clinical specimen) and immunohistochemistry (48 clinical specimen). Our studies indicate significant overexpression of all the six genes in ERα (+) breast tumors as compared to ERα (–) breast tumors. In vitro studies using T-47D breast cancer cell line confirmed the estrogen dependant expression of four of the above six genes ( SLC7A8, ENPP1, LAMB2, and PLAT). Collectively, our study provides further insights into the molecular basis of estrogen-dependent breast cancer and identifies “candidate biomarkers” that could be useful for predicting endocrine responsiveness.

High level analysis of genomic data reveals complex predictors of response to trastuzumab (T) and chemotherapy for early stage breast cancer

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 544-544
Author(s):  
L. N. Harris ◽  
S. Carter ◽  
F. You ◽  
A. Eklund ◽  
S. Hilsenbeck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Expression Patterns ◽  
Rna Extraction ◽  
Pathologic Complete Response ◽  
Gene Expression Signature ◽  
Response To Therapy ◽  
Snp Analysis ◽  
Predictors Of Response ◽  
High Level

544 Background: Trastuzumab (T) with chemotherapy has been shown to improve survival in breast cancer patients but de novo resistance is common. Identifying predictors of response to T in primary cancers may lead to an understanding of mechanisms of resistance. We investigated whether combined microarray datasets from patients with early breast cancer treated with preoperative T and chemotherapy could predict for response to therapy. Methods: Two cohorts of patients with HER2 3+/FISH+, stage II-III breast cancer were included in this analysis: trial 1- T and docetaxel (n=38), trial 2 -T and vinorelbine (n=48), both for 12 weeks. Frozen tissue core biopsies were available and successfully amplified in 41 patients (trial 1: 20, trial 2: 21 patients), with standard sample processing, RNA extraction, amplification and hybridization to Affymetrix U133 chips. Differential expression of genes and chromosomal regions, (defined as >10 genes in a given chromosomal cytoband), between patients with pathologic complete response (pCR) vs. those with residual invasive disease were examined. A measure of total functional aneuploidy (tFA) was calculated by summing net deviation in expression of all chromosomal regions and a gene expression signature of genomic instability (CIN) was derived by the identification of genes showing a high level of correlation with tFA . Results: By unsupervised hierarchical analysis, both datasets interdigitated suggesting no inherent bias. Gene expression patterns of individual genes showed weak associations with pCR. However, distinct statistically significant chromosomal regions, Chr2p23 Chr6q24 Chr7q33 Chr2p2 Chr12q21.31 Chr14q32.2 Chr1p34.2 Chr8q21.3, were associated with pCR to T therapy (p<0.005), and were confirmed in more than 50% samples by SNP analysis. In addition, resistant tumors showed higher levels of the CIN signature (p<0.005). Conclusions: We have shown that gene expression data can be merged and used for discovery predictive chromosomal regions associated T response. In addition, chromosomal instability was associated with T resistance. If validated, these distinct dysregulated chromosomal regions may serve as predictive markers of response to trastuzumab therapy. [Table: see text]

Molecular Phenotype of Malignant CD34+ Hematopoietic Stem and Progenitor Cells in Chronic Myelogenous Leukemia.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2863-2863
Author(s):  
Ralf Kronenwett ◽  
Elena Diaz-Blanco ◽  
Thorsten Graef ◽  
Ulrich Steidl ◽  
Slawomir Kliszewski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fatty Acid ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Leukemic Cell ◽  
Differentially Expressed ◽  
Specific Gene ◽  
Hematopoietic Stem ◽  
Cd34 Cells

Abstract In this study, we examined gene expression profiles of immunomagnetically enriched CD34+ cells from bone marrow (BM) of 9 patients with untreated CML in chronic phase and from 8 healthy volunteers using Affymetrix GeneChips. Additionally, in 3 patients CD34+ from peripheral blood (PB) were compared with those from BM. Differential expression of 12 candidate genes was corroborated by quantitative real-time RT-PCR. Following hybridization of labelled cRNA to Affymetrix GeneChips covering 8793 genes we used the statistical scripting language “R” for data analysis. For normalization a method of variance stabilization transformations was used. To identify significantly differentially expressed genes we used the Significance Analysis of Microarrays (SAM) algorithm. The intraindividual comparison of CD34+ cells from BM and PB in CML showed no differentially expressed genes which is different to normal CD34+ cells which had distinct gene expression patterns comparing circulating and sedentary CD34+ cells (Steidl et al., Blood, 2002). Comparing malignant BM CD34+ cells from CML with normal BM CD34+ cells 792 genes were significantly differentially expressed (fold change: &gt;1.3; q-value: &lt;0.03). 735 genes had a higher and 57 genes a lower expression in CML. Gene expression patterns reflected BCR-ABL-induced functional alterations such as increased cell-cycle and proteasome activity as well as decreased apoptosis. Downregulation of several genes involved in DNA repair and detoxification in CML might be the basis for DNA instability and progression to blast crisis. An interesting finding was an upregulation of fetal hemoglobin (Hb) components such as Hb gamma A and G in leukemic progenitor cells whereas no difference in adult Hb expression was observed suggesting an induction of fetal Hb synthesis in CML. Looking at genes involved in stem cell maintenance we found an upregulation of GATA2 and a reduced expression of proteins from the Wnt signalling pathway suggesting an increased self-renewal of CML hematopoietic stem cells compared to the normal counterpart. Moreover, several genes playing a role in ubiquitin-dependent protein catabolism and in fatty acid biosynthesis such as fatty acid synthase (FAS) were stronger expressed in CML. The functional role of FAS for leukemic cell growth was assessed in cell culture experiments. Incubation of the leukemic cell line K562 with the FAS inhibitor cerulenin (10 μg/ml) for 3 days resulted in death of 99% of cells suggesting that survival of leukemic cells depends upon endogenous fatty acid synthesis. In an attempt to find a specific gene expression pattern associated with response to imatinib therapy we divided the patients included in this study into two groups: maximal reduction of BCR-ABL transcript level &lt;3-log vs. &gt;3-log (major molecular remission) during therapy. Comparing pretherapeutic gene expression profiles of both groups we could not identify a pattern predictive for major molecular response. In conclusion, malignant CD34+ cells in CML have a specific gene expression pattern which seems not to be predictive for response to imatinib therapy.

scholarly journals Identification of Gene Expression Pattern Related to Breast Cancer Survival Using Integrated TCGA Datasets and Genomic Tools

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenzhen Huang ◽  
Huilong Duan ◽  
Haomin Li
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
Expression Pattern ◽  
Clinical Data ◽  
Cancer Genomics ◽  
Expression Patterns ◽  
Gene List ◽  
Gene Expression Pattern ◽  
Cancer Development

Several large-scale human cancer genomics projects such as TCGA offered huge genomic and clinical data for researchers to obtain meaningful genomics alterations which intervene in the development and metastasis of the tumor. A web-based TCGA data analysis platform called TCGA4U was developed in this study. TCGA4U provides a visualization solution for this study to illustrate the relationship of these genomics alternations with clinical data. A whole genome screening of the survival related gene expression patterns in breast cancer was studied. The gene list that impacts the breast cancer patient survival was divided into two patterns. Gene list of each of these patterns was separately analyzed on DAVID. The result showed that mitochondrial ribosomes play a more crucial role in the cancer development. We also reported that breast cancer patients with low HSPA2 expression level had shorter overall survival time. This is widely different to findings of HSPA2 expression pattern in other cancer types. TCGA4U provided a new perspective for the TCGA datasets. We believe it can inspire more biomedical researchers to study and explain the genomic alterations in cancer development and discover more targeted therapies to help more cancer patients.

scholarly journals Topsentinol L Trisulfate, a Marine Natural Product That Targets Basal-like and Claudin-Low Breast Cancers

Marine Drugs ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 41
Author(s):  
Nader N. El-Chaar ◽  
Thomas E. Smith ◽  
Gajendra Shrestha ◽  
Stephen R. Piccolo ◽  
Mary Kay Harper ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cell Lines ◽  
Gene Expression Signature ◽  
Marine Natural Product ◽  
Breast Cancer Cell Lines ◽  
Breast Cancers ◽  
Expression Signature ◽  
Her2 Breast Cancer ◽  
Cancer Types

Patients diagnosed with basal-like breast cancer suffer from poor prognosis and limited treatment options. There is an urgent need to identify new targets that can benefit patients with basal-like and claudin-low (BL-CL) breast cancers. We screened fractions from our Marine Invertebrate Compound Library (MICL) to identify compounds that specifically target BL-CL breast cancers. We identified a previously unreported trisulfated sterol, i.e., topsentinol L trisulfate (TLT), which exhibited increased efficacy against BL-CL breast cancers relative to luminal/HER2+ breast cancer. Biochemical investigation of the effects of TLT on BL-CL cell lines revealed its ability to inhibit activation of AMP-activated protein kinase (AMPK) and checkpoint kinase 1 (CHK1) and to promote activation of p38. The importance of targeting AMPK and CHK1 in BL-CL cell lines was validated by treating a panel of breast cancer cell lines with known small molecule inhibitors of AMPK (dorsomorphin) and CHK1 (Ly2603618) and recording the increased effectiveness against BL-CL breast cancers as compared with luminal/HER2+ breast cancer. Finally, we generated a drug response gene-expression signature and projected it against a human tumor panel of 12 different cancer types to identify other cancer types sensitive to the compound. The TLT sensitivity gene-expression signature identified breast and bladder cancer as the most sensitive to TLT, while glioblastoma multiforme was the least sensitive.

Gene Regulation: A Genomic Perspective

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. SCI-10-SCI-10
Author(s):  
John Stamatoyannopoulos
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Conflicts Of Interest ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Gene Expression Patterns ◽  
Specific Gene ◽  
Regulatory Regions ◽  
Regulatory Pathways ◽  
Wide Range

Abstract Regulatory elements control the anatomic and cellular contexts, timing, and magnitude of gene expression patterns. Under the ENCODE and Roadmap Epigenomics Projects, human regulatory DNA has been mapped using a variety of approaches in over 300 cell and tissue types and developmental states. Collectively, the human genome encodes several million regulatory elements, most of which are located at some distance from promoters. The vast majority of these elements exhibit exquisite cell-and lineage-selective activation patterns, providing novel insights into the coordination of gene expression patterns. Genomic footprinting is a new and powerful technology that enables simultaneous profiling of the occupancy of hundreds of sequence-specific transcription factors within regulatory regions. These profiles in turn enable construction of transcription factor regulatory networks that are providing new insights into how cell-and lineage-specific gene expression programs arise. Hundreds of genetic variants associated with a wide range of hematological traits and disorders localize within regulatory regions. Many such variants disrupt specific transcription factor-DNA interactions, exposing pathophysiologically relevant transcriptional regulatory pathways. Disclosures: No relevant conflicts of interest to declare.

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