Unknown,Transcriptomics,Genomics,Proteomics

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

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 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)

ORGANISM(S): Homo sapiens

SUBMITTER: Miriam Aure

PROVIDER: E-GEOD-58210 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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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:Background: The global effect of copy number and epigenetic alterations on miRNA expression in cancer is poorly understood. In the present study, we integrate genome-wide copy number, DNA methylation and miRNA expression and identify genetic mechanisms underlying miRNA dysregulation in breast cancer. Results: We identify 70 miRNAs whose expression was associated with aberrations in copy number or methylation, or both. Among these, five miRNA families are represented. Interestingly, the members of these families are encoded on different chromosomes and are complementarily altered by gain or hypomethylation across the patients. In an independent breast cancer cohort of 123 patients, 41 of the 70 miRNAs were confirmed with respect to aberration pattern and association to expression. In vitro functional experiments were performed in breast cancer cell lines with miRNA mimics to evaluate the phenotype of the replicated miRNAs. let-7e-3p, which in tumors is found associated with hypermethylation, is shown to induce apoptosis and reduce cell viability, and low let-7e-3p expression is associated with poorer prognosis. The overexpression of three other miRNAs associated with copy number gain, miR-21-3p, miR-148b-3p and miR-151a-5p, increases proliferation of breast cancer cell lines. In addition, miR-151a-5p enhances the levels of phosphorylated AKT protein. Conclusions: Our data provide novel evidence of the mechanisms behind miRNA dysregulation in breast cancer. The study contributes to the understanding of how methylation and copy number aberrations influence miRNA expression, emphasizing miRNA functionality through redundant encoding, and suggests novel miRNAs important in breast cancer. The miRNA expression profiling of 149 breast cancer samples was performed using the 8x15k “Human miRNA Microarray Kit (V2)” with design id 019118 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 v9.5 and the subsequent data processing was performed using the GeneSpring software v12.0 (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 448 unique mature miRNAs.

Project description:MicroRNAs (miRNAs) are known to be deregulated in human breast cancer (BC). The purpose of the current study was to investigate the expression of miRNAs in different stages of BC to assess their biological value in BC progression. MiRNA expression was assessed in a series of BC patients (n=7) with distinct stages of tumour progression (Normal, in-situ (DCIS), primary invasive BC and nodal metastases) to evaluate miRNA differential expression. We used an Agilent miRNA microarray based platform which uses miRBase 16 to screen for 1205 Homo sapiens (hsa) and 144 human viral miRNA candidates. To validate the microarray data, the expression of two deregulated miRNAs was measured by TaqMan quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). This study was conducted Formalin Fixed and Paraffin Embedded (FFPE) specimens from 7 female patients. Twenty M-NM-<m thick FFPE sections were cut and mounted on PALM Membrane Slides. Under direct microscopic visualization, tissues of interest were micro-dissected using PALM non-contact Laser catapulsion instrument (P.A.L.M. Microlaser Technologies, Carl Zeiss Ltd). Total RNA, including miRNAs, was extracted with the TRIzol reagent (Invitrogen, supplied by Fisher Scientific UK Ltd) according to the manufacturerM-bM-^@M-^Ys instructions. Total RNA was quantified with Quant-iT RiboGreen RNA Quantitation Kit (Fisher Scientific UK Ltd), which is an accurate method of measuring total RNA with a detection limit of 0.001-1ng/M-BM-5l. RNA purity and RNA integrity number (RIN) were determined on an Agilent 2100 Bioanalyzer and RNA 6000 NanoLabChip Kits (both Agilent Technologies, Santa Clara, USA), and the RIN of all the samples was >2 but <3. This is expected for FFPE breast samples and is acceptable by Agilent Technologies, Santa Clara, USA, for FFPE samples to undergo miRNA microarray analysis. MiRNAs extracted from laser microdissected tissue components were profiled using Agilent microRNA microarray profiling system (Agilent Technologies, Santa Clara, USA). Total RNA samples were spiked using the MicroRNA Spike-In Kit (Agilent Technologies, Santa Clara, USA) to evaluate efficiencies of labelling and hybridisation. Total RNA was treated with Calf Intestinal Alkaline Phosphatase (CIP), and then 100 ng of total RNA was used per sample to initiate a labelling reaction. Ligation master mix for T4 RNA ligase, which includes Cyanine 3-Cytidine biphosphate (Cyanine 3-pCp) (Complete miRNA Labelling and Hyb Kit, Agilent Technologies, Santa Clara, USA) was used to label the dephosphorylated RNA. Cyanine-3-labelled miRNA samples were hybridised to human miRNA microarrays (Release 16.0, 8x60K) (Agilent Technologies, Santa Clara, USA) at 55M-BM-0C for 20 hrs. Microarray slides were washed with increasing stringency (Gene Expression Wash Buffers, Agilent Technologies, Santa Clara), and subsequently dried with acetonitrile (Sigma-Aldrich, St. Louis, USA). Fluorescent signal intensities were detected on an Agilent Microarray Scanner (Agilent Technologies, Santa Clara, USA) using the Scan Control A.8.4.1 Software (Agilent Technologies, Santa Clara, USA) and extracted from the images with the Feature Extraction 10.7.3.1 Software (Agilent Technologies, Santa Clara, USA).

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

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