Dataset Information

Integrative analysis reveals extensive association between microRNA expression and mRNA-protein translation [mRNA]

ABSTRACT: Transcription signatures have been used to stratify breast cancer patients into clinically distinct subgroups. However, transcription alone does not determine protein expression. Of potentially equal importance for determining the tumor phenotype is the rate at which transcripts are translated to form protein. Protein translation is controlled to a major degree by miRNA, and cancer cells may deregulate the expression of key genes by altering the activity of relevant miRNAs. The importance of miRNA deregulation and the extent to which multiple miRNAs coordinately deregulate key proteins in breast cancer is only partly understood. To gain such insight, we analyzed genome-wide miRNA expression and mRNA/protein expression for a panel of 105 selected cancer related genes in breast carcinomas from 283 patients. The miRNA-mRNA-protein interactome for the selected genes was constructed by modeling protein expression as a joint function of mRNA and miRNA expression, considering the effect of both one miRNA at a time, and all studied miRNAs simultaneously. The interactome represents a map of the global effects of miRNAs on protein expression, capturing direct as well as indirect effects. The results reveal extensive association between miRNA and protein expression as well as coordinated effects of multiple miRNAs on individual proteins. Applying the model onto two other independent primary breast cancer cohorts confirmed the generalizability of key aspects of the interactome map. The mRNA expression profiling of 283 breast cancer samples was performed using the SurePrint G3 Human GE 8x60K one-color microarrays from Agilent (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer’s protocol (One-Color Microarray-Based Gene Expression Analysis, Low Input Quick Amp Labeling, v.6.5, May 2010). For each sample, 100 ng of RNA was amplified and hybridized on the array. Scanning was performed with Agilent Scanner G2565A, using AgilentG3_GX_1Color as profile. Signals were extracted using FE v.10.7.3.1 and protocol GE1_107_Sep09 (Agilent Technologies). Arrays were log2-transformed, quantile normalized and hospital-adjusted by subtracting from each probe value the mean probe value among samples from the same hospital. The Oslo Breast Cancer Consortium (OSBREAC)

ORGANISM(S): Homo sapiens

SUBMITTER: Aure Miriam

PROVIDER: S-ECPF-GEOD-58212 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Transcription signatures have been used to stratify breast cancer patients into clinically distinct subgroups. However, transcription alone does not determine protein expression. Of potentially equal importance for determining the tumor phenotype is the rate at which transcripts are translated to form protein. Protein translation is controlled to a major degree by miRNA, and cancer cells may deregulate the expression of key genes by altering the activity of relevant miRNAs. The importance of miRNA deregulation and the extent to which multiple miRNAs coordinately deregulate key proteins in breast cancer is only partly understood. To gain such insight, we analyzed genome-wide miRNA expression and mRNA/protein expression for a panel of 105 selected cancer related genes in breast carcinomas from 283 patients. The miRNA-mRNA-protein interactome for the selected genes was constructed by modeling protein expression as a joint function of mRNA and miRNA expression, considering the effect of both one miRNA at a time, and all studied miRNAs simultaneously. The interactome represents a map of the global effects of miRNAs on protein expression, capturing direct as well as indirect effects. The results reveal extensive association between miRNA and protein expression as well as coordinated effects of multiple miRNAs on individual proteins. Applying the model onto two other independent primary breast cancer cohorts confirmed the generalizability of key aspects of the interactome map. The mRNA expression profiling of 283 breast cancer samples was performed using the SurePrint G3 Human GE 8x60K one-color microarrays from Agilent (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer’s protocol (One-Color Microarray-Based Gene Expression Analysis, Low Input Quick Amp Labeling, v.6.5, May 2010). For each sample, 100 ng of RNA was amplified and hybridized on the array. Scanning was performed with Agilent Scanner G2565A, using AgilentG3_GX_1Color as profile. Signals were extracted using FE v.10.7.3.1 and protocol GE1_107_Sep09 (Agilent Technologies). Arrays were log2-transformed, quantile normalized and hospital-adjusted by subtracting from each probe value the mean probe value among samples from the same hospital. The Oslo Breast Cancer Consortium (OSBREAC)

Project description:Transcription signatures have been used to stratify breast cancer patients into clinically distinct subgroups. However, transcription alone does not determine protein expression. Of potentially equal importance for determining the tumor phenotype is the rate at which transcripts are translated to form protein. Protein translation is controlled to a major degree by miRNA, and cancer cells may deregulate the expression of key genes by altering the activity of relevant miRNAs. The importance of miRNA deregulation and the extent to which multiple miRNAs coordinately deregulate key proteins in breast cancer is only partly understood. To gain such insight, we analyzed genome-wide miRNA expression and mRNA/protein expression for a panel of 105 selected cancer related genes in breast carcinomas from 283 patients. The miRNA-mRNA-protein interactome for the selected genes was constructed by modeling protein expression as a joint function of mRNA and miRNA expression, considering the effect of both one miRNA at a time, and all studied miRNAs simultaneously. The interactome represents a map of the global effects of miRNAs on protein expression, capturing direct as well as indirect effects. The results reveal extensive association between miRNA and protein expression as well as coordinated effects of multiple miRNAs on individual proteins. Applying the model onto two other independent primary breast cancer cohorts confirmed the generalizability of key aspects of the interactome map. The miRNA expression profiling of 283 breast cancer samples was performed using the 8x15k “Human miRNA Microarray Kit release 14.0 (V2)” with design id 029297 from Agilent (Agilent Technologies, Santa Clara, CA, USA). In brief, 100 ng total RNA was dephosphorylated, labeled and hybridized for 20 hours, following the manufacturer’s protocol. Scanning was performed on Agilent Scanner G2565A, signals were extracted using Feature Extraction v10.7.3.1 and the subsequent data processing was performed using the GeneSpring software v11.0 (Agilent Technologies). In brief, the miRNA signal intensities were log2-transformed and normalized to the 90th percentile, and miRNAs that were detected in less than 10% of the samples were excluded. This resulted in 421 unique mature miRNAs. The Oslo Breast Cancer Consortium (OSBREAC)

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Integrative analysis reveals extensive association between microRNA expression and mRNA-protein translation [mRNA]

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