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More than 40% of patients with luminal breast cancer treated with endocrine therapy agent tamoxifen demonstrate resistance. Emerging evidence suggests tumor initiating cells (TICs) and aberrant activation of Src and Akt signaling drive tamoxifen resistance and relapse. We previously demonstrated that aryl hydrocarbon receptor ligand aminoflavone (AF) inhibits the expression of TIC gene α6-integrin and disrupts mammospheres derived from tamoxifen-sensitive breast cancer cells. In the current study, we hypothesize that tamoxifen-resistant (TamR) cells exhibit higher levels of α6-integrin than tamoxifen-sensitive cells and that AF inhibits the growth of TamR cells by suppressing α6-integrin-Src-Akt signaling. In support of our hypothesis, TamR cells and associated mammospheres were found to exhibit elevated α6-integrin expression compared with their tamoxifen-sensitive counterparts. Furthermore, tumor sections from patients who relapsed on tamoxifen showed enhanced α6-integrin expression. Gene expression profiling from the TCGA database further revealed that basal-like breast cancer samples, known to be largely unresponsive to tamoxifen, demonstrated higher α6-integrin levels than luminal breast cancer samples. Importantly, AF reduced TamR cell viability and disrupted TamR mammospheres while concomitantly reducing α6-integrin messenger RNA and protein levels. In addition, AF and small interfering RNA against α6-integrin blocked tamoxifen-stimulated proliferation of TamR MCF-7 cells and further sensitized these cells to tamoxifen. Moreover, AF reduced Src and Akt signaling activation in TamR MCF-7 cells. Our findings suggest elevated α6-integrin expression is associated with tamoxifen resistance and AF suppresses α6-integrin-Src-Akt signaling activation to confer activity against TamR breast cancer.
Pubmed ID: 30076704 RIS Download
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This monoclonal targets ITGA6
View all literature mentionsThis polyclonal targets
View all literature mentionsThis polyclonal targets Phospho-Src (Tyr527)
View all literature mentionsThis polyclonal targets Mouse IgG
View all literature mentionsThis polyclonal targets ITGA6
View all literature mentionsThis polyclonal secondary targets IgG
View all literature mentionsThis monoclonal targets β-Actin
View all literature mentionsThis monoclonal targets synthetic peptide corresponding to residues near the carboxy terminus of human Src.
View all literature mentionsThis polyclonal targets Phospho-Akt (Ser473)
View all literature mentionsStatistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.
View all literature mentionsProject exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
View all literature mentionsCell line BT-474 is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsCell line ZR-75-30 is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsCell line T-47D is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsThis polyclonal targets Phospho-Akt (Ser473)
View all literature mentionsThis monoclonal targets ITGA6
View all literature mentionsThis polyclonal targets
View all literature mentionsThis monoclonal targets ITGA6
View all literature mentionsCell line T-47D is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsThis polyclonal targets Phospho-Akt (Ser473)
View all literature mentionsThis polyclonal targets Phospho-Src (Tyr527)
View all literature mentionsCell line BT-474 is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsCell line ZR-75-30 is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsThis polyclonal secondary targets IgG
View all literature mentionsThis monoclonal targets synthetic peptide corresponding to residues near the carboxy terminus of human Src.
View all literature mentionsThis monoclonal targets β-Actin
View all literature mentionsProject exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
View all literature mentionsThis polyclonal targets ITGA6
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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