Project description:We constructed four single cell transcriptome (SCT) libraries from MCF-7 breast cancer cells and characterized their transcriptome profiles using the expression of 143 housekeeping genes as a control.
Project description:We constructed four single cell transcriptome (SCT) libraries from MCF-7 breast cancer cells and characterized their transcriptome profiles using the expression of 143 housekeeping genes as a control.
Project description:A comparison of different energetics based techniques for the characterization of two mammalian breast cell lines, MCF-7 a luminal A breast cancer cell line and MCF-10A a normal human breast cell line. The techniques of stability of proteins from rates of oxidation (SPROX), thermal proteome profiling (TPP), and conventional expression level analyses were compared and the relative advantages and disadvantages are discussed.
Project description:Human breast cancer cell line MCF-7 is usually sensitive to chemotherapy drug BMS-554417, an insulin receptor (IR) and insulin-like growth factor receptor (IGFR) inhibitor. However, through step-wise increase in BMS-554417 doses in culture media, we were able able to screen and select a single MCF-7 clone that is BMS-554417 resistant. It is cross resistant to BMS-536924. This new line of MCF-7 cells was named as MCF-7R4. The transcriptome profiling of both MCF-7 and MCF-7R4 was performed using Affymetrix HG-U133 plus2.0 GeneChip arrays.
Project description:Human breast cancer cell line MCF-7 is usually sensitive to chemotherapy drug BMS-554417, an insulin receptor (IR) and insulin-like growth factor receptor (IGFR) inhibitor. However, through step-wise increase in BMS-554417 doses in culture media, we were able able to screen and select a single MCF-7 clone that is BMS-554417 resistant. It is cross resistant to BMS-536924. This new line of MCF-7 cells was named as MCF-7R4. The transcriptome profiling of both MCF-7 and MCF-7R4 was performed using Affymetrix HG-U133 plus2.0 GeneChip arrays. Five replicates of MCF-7 and five replicates of MCF-7R4 were profiled.
Project description:We used microarrays to detail the global programme of gene expression for MCF-7 and MDA-MB-231 and revealed the correlation between the methylation state of various genomic components and gene expression level. The expression analyses of the two breast cancer cell lines are a part of the whole study. The summary of our study is as follows: We establish a technique, called modified methylation-specific digital karyotyping (MMSDK) based on methylation-specific digital karyotyping (MSDK) with a novel sequencing approach. Briefly, after a tandem digestion of genomic DNA with a methylation-sensitive mapping enzyme and a fragmenting enzyme, short sequence tags are obtained. These tags are amplified, followed by direct, massively parallel sequencing (Solexa 1G Genome Analyzer). This method allows high-throughput and low-cost genome-wide DNA methylation mapping. We applied this method to investigate global DNA methylation profiles for widely used breast cancer cell lines, MCF-7 and MDA-MB-231, which are representatives for luminal-like and mesenchymal-like cancer types, respectively. By comparison, a highly similar overall DNA methylation pattern was revealed for the two cell lines. However a cohort of individual genomic loci with significantly different DNA methylation profile between two cell lines was identified. Furthermore, we revealed a genome-wide significant correlation between gene expression and the methylation status of gene promoters with CpG islands (CGIs) in the two cancer cell lines, and a correlation of gene expression and the methylation status of promoters without CGIs in MCF-7 cells. Experiment Overall Design: Breast cancer cell lines, MCF-7 and MDA-MB-231, were selected for the study of the impact of DNA methylation on gene expression regulation. Total RNA extraction was performed for both cell lines and hybridization was carried out using Affymetrix microarrays. We developed a modified methylation-specific digital karyotyping (MSDK) to obtain DNA methylation profiling genome wide. Then, we combined the analysis of DNA methylation data and gene expression data to reveal a correlation between epigenetic and transcriptional features genome wide.