Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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A Preclinical Model for ERÎ±-Positive Breast Cancer Points to the Epithelial Microenvironment as Determinant of Luminal Phenotype and Hormone Response [MCF7]

ABSTRACT: A high percentage of potential oncology drugs fail in clinical trials, partly because preclinical models used to test them are inadequate. Breast cancer is the leading cause of cancer-related death among women worldwide but we lack appropriate in vivo models for the ER+ subtypes, which represent more than 75% of all cases. We address these issues by xenografting tumor cells to their site of origin, the milk ducts. All ER+ cell lines and patient-derived xenografts grow mimicking their clinical counterparts. Disease progresses with invasion and metastasis, which become amenable to study. The action of hormones, important in breast carcinogenesis, can now be studied in a relevant context. Importantly, these open opportunities for development and evaluation of therapies. Eight- to twelve-week-old female SCID Beige mice (Charles River) were injected with 2x10e5 MCF7-DsRed/luc2 cells (n=3) either into the mammary fat pad or 5x10e4 MCF7-DsRed/luc2 cells intraductally (n=3). Xenografted MCF7 were FACS sorting based on DsRed expression; total RNA was extracted using Trizol Reagent (Invitrogen), purified with the miRNeasy Mini Kit (Qiagen), quantity and quality were assessed by NanoDropÂ®ND-1000 spectrophotometer and RNA 6000 NanoChips with the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, USA). Only samples with RIN score >7.0 were included. For each sample, 300 ng of total RNA were amplified using the message amp II enhanced kit (AM1791, Ambion). 12.5 Î¼g of biotin-labelled cRNA were chemically fragmented. Affymetrix GeneChip Human Genome U133A 2.0 Arrays (Affymetrix, Santa Clara, CA, USA) were hybridized with 11Î¼g of fragmented target, at 45Â°C for 17 hours, washed and stained according to Affymetrix GeneChipÂ® Expression Analysis Manual (Fluidics protocol FS450_0007). Arrays were scanned using the GeneChip Scanner 3000 7G (Affymetrix) and raw data was extracted from the scanned images and analyzed with the Affymetrix Power Tools software package (Affymetrix). All statistical analyses were performed using R and Bioconductor packages (http://www.Bioconductor.org). Hybridization quality was assessed using the Expression Console software (Affymetrix). Normalized expression signals were calculated from Affymetrix CEL files using RMA. Differential hybridized features were identified using Bioconductor package âlimmaâ that implements linear models for microarray data (Smyth, 2004). P values were adjusted for multiple testing with Benjamini and Hochbergâs method to control false discovery rate (FDR) (Benjamini et al., 2001). Probe sets showing â¥2-fold change and a FDR â¤0.05 were considered significant.

ORGANISM(S): Homo sapiens

SUBMITTER: George Sflomos

PROVIDER: E-GEOD-68694 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:A high percentage of potential oncology drugs fail in clinical trials, partly because preclinical models used to test them are inadequate. Breast cancer is the leading cause of cancer-related death among women worldwide but we lack appropriate in vivo models for the ER+ subtypes, which represent more than 75% of all cases. We address these issues by xenografting tumor cells to their site of origin, the milk ducts. All ER+ cell lines and patient-derived xenografts grow mimicking their clinical counterparts. Disease progresses with invasion and metastasis, which become amenable to study. The action of hormones, important in breast carcinogenesis, can now be studied in a relevant context. Importantly, these open opportunities for development and evaluation of therapies. Eight- to twelve-week-old female SCID Beige mice (Charles River) were injected with 5x10e5 BT20-GFP/luc2 cells (n=3) or 5x10e5 HCC1806-GFP/luc2 cells (n=3) either into the mammary fat pad or 2x10e5 BT20-GFP/luc2 cells (n=3) or 2x10e5 HCC1806-GFP/luc2 cells intraductally (n=3). Xenografted BT20 and HCC1806 basal breast cancer cells were sorted by FACS based on GFP expression; total RNA was extracted using Trizol Reagent (Invitrogen), purified with the miRNeasy Mini Kit (Qiagen), quantity and quality were assessed by NanoDropÂ®ND-1000 spectrophotometer and RNA 6000 NanoChips with the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, USA). Only samples with RIN score >7.0 were included. For each sample, 300 ng of total RNA were amplified using the message amp II enhanced kit (AM1791, Ambion). 12.5 Î¼g of biotin-labelled cRNA were chemically fragmented. Affymetrix GeneChip Human Genome U133A 2.0 Arrays (Affymetrix, Santa Clara, CA, USA) were hybridized with 11Î¼g of fragmented target, at 45Â°C for 17 hours, washed and stained according to Affymetrix GeneChipÂ® Expression Analysis Manual (Fluidics protocol FS450_0007). Arrays were scanned using the GeneChipÂ® Scanner 3000 7G (Affymetrix) and raw data was extracted from the scanned images and analyzed with the Affymetrix Power Tools software package (Affymetrix). All statistical analyses were performed using R and Bioconductor packages (http://www.Bioconductor.org). Hybridization quality was assessed using the Expression Console software (Affymetrix). Normalized expression signals were calculated from Affymetrix CEL files using RMA. Differential hybridized features were identified using Bioconductor package â??limmaâ?? that implements linear models for microarray data (Smyth, 2004). P values were adjusted for multiple testing with Benjamini and Hochbergâ??s method to control false discovery rate (FDR) (Benjamini et al., 2001). Probe sets showing â?¥2-fold change and a FDR â?¤0.05 were considered significant.

Project description:A time series of whole-genome transcription profiling of E. coli K-12 W3110 was performed to study the dynamic physiological response of E. coli K-12 W3110 to limited carbon conditions. cDNA from eight time intervals after glucose limitation, representing different stages of glucose depletion, along with cDNA of an unrestricted growth were hybridized to whole-genome microarrays of E. coli K-12. Glucose concentrations were gradually reduced in a fed-batch cultivation process with constant feeding rate in a bioreactor. Major focus was put on the dynamic changes in the transcription level of genes involved in the central carbon metabolism (glycolysis, pentose phosphate pathway, TCA cycle and glyoxylate shunt), high-affinity glucose transport systems, movement, growth, and stress response. In total, 40 microarrays were hybridized. The data were statistically analysed using the software R (R, 2005) and the Limma package included (Smyth, 2005). The data were normalized â??print-tip-loessâ??. â??Multiple hypothesis testingâ?? correction was performed with the method of Benjamini and Hochberg (Benjamini and Hochberg, 1995), which controls the â??false discovery rateâ?? (fdr). Genes were regarded as differentially expressed when the â??adjusted p valuesâ?? were < 0.05, therefore nominally controlling the expected fdr to less than 0.05. The reproducibility of dye swap experiments as well as biological replicates was estimated by calculating â??Pearsonâ??s correlation coefficientsâ??. A high correlation was observed for the dye swap pairs (with averaged Pearsonâ??s correlation coefficients of 0.89 Â± 0.06 for the reference samples and of 0.87 Â± 0.08 for the different points of time) as well as for biological replicates (with averaged Pearsonâ??s correlation coefficients of 0.86 Â± 0.04 for the red channel (Cy5) and 0.80 Â± 0.09 for the green channel (Cy3)). Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc B 57, 289-300. Smyth, G.K. (2005). Limma: Linear models for microarray data. In Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, Carrey, V., Dudoit, S., Irizzary, I., Huber, W., ed. (New York, Springer), pp. 397-420. R (2005). R: A language and environment for statistical computing. (R Development Core Team). Supplementary files: Data_table_A: TabelleA_Signifikante.txt Description: Data table with coefficients of the linear model for every gene which was differentially expressed for at least one point in time according to the reference sample. The statistical analysis was performed as described in Series section (GSE10307) based on the normalized log2(test/ref) ratios in the Sample records' VALUE columns. Data_table_B1: Tabelle_B1; /E. coli/, unlimited growth via glucose limitation (glucose concentration < 0.05 gL-1) Data_table_B2: Tabelle_B2; /E. coli/, unlimited growth via glucose limitation, acetate concentration = 0.35 gL-1 Data_table_B3: Tabelle_B3; /E. coli/, unlimited growth via glucose limitation, 30 min after depletion of extracellular acetate Data_table_B4: Tabelle_B4; /E. coli/, unlimited growth via glucose limitation, 50 min after depletion of extracellular acetate Data_table_B5: Tabelle_B5; /E. coli/, unlimited growth via glucose limitation, 110 min after depletion of extracellular acetate Data_table_B6: Tabelle_B6; /E. coli/, unlimited growth via glucose limitation, 170 min after depletion of extracellular acetate Data_table_B7: Tabelle_B7; /E. coli/, unlimited growth via glucose limitation, 230 min after depletion of extracellular acetate Data_table_B8: Tabelle_B8; /E. coli/, unlimited growth via glucose limitation, 350 min after depletion of extracellular acetate Description: Data_tables_B1-B8 report statistical values (A: average intensity value (1/2log2(test*ref)); M: average expression value (log2(test/ref)), t and P.value ('adjusted P.value')) for every point in time (studied conditions are described above for the corresponding table). Every differentially expressed gene of the corresponding point in time according to the reference sample is listed. Genes were regarded as differentially expressed when their 'adjusted P.values' were < 0.05, therefore nominally controlling the expected fdr to less than 0.05. The data are based on maximal three biological replicates (three independent fed-batch cultivations). RT-PCR_results_7genes.txt and RT-PCR_protocol.PDF Keywords: Time course, stress response Hybridization involved the hybridization of a common reference (unlimited growth, batch phase) on all arrays together with each sample of interest. This allowed the direct comparison of the transcripts of a time series taken during fed-batch cultivation with the unlimited reference sample. All samples were taken in duplicates and the experiments were performed as dye swap experiments. The first four samples of the time series (T1 - T4) were taken from three individual fed-batch cultivations (three biological replicates), the subsequent four samples (T5 - T8) were taken only from two individual fed-batch cultivations. On each array, the genes were spotted in duplicates. Therefore, twelve replicates (duplicates on dye swaps for three cultivations) were analyzed for T1 â?? T4 and eight replicates (duplicates on dye swaps for two cultivations) were analyzed for T5 â?? T8.

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A Preclinical Model for ERÎ±-Positive Breast Cancer Points to the Epithelial Microenvironment as Determinant of Luminal Phenotype and Hormone Response [MCF7]

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