Project description:Introduction: microRNAs (miRNAs) are short non-coding RNAs that negatively regulate gene expression and may play a causal role in invasive breast cancer. Since many genetic aberrations of invasive disease are detectable in earlier stages, we hypothesized that miRNA expression dysregulation and the predicted changes in gene expression would also be found in early breast neoplasias. Methods: Expression profiling of 365 miRNAs by RT-qPCR was combined with laser-capture microdissection to obtain an epithelial specific miRNA expression signature of normal breast epithelium (n=9) and of paired samples of histologically normal epithelium (HN) and ductal carcinoma in situ (DCIS) (n=16). To determine how miRNAs may control the expression of co-dysregulated mRNAs we also performed gene expression microarray analysis in the same paired HN and DCIS samples and integrated this with miRNA-target prediction. We further validated several target pairs by modulating the expression levels of miRNAs in MCF7 cells and measured the expression of target mRNAs and proteins. Results: Thirty-five miRNAs were aberrantly expressed between RM, HN and DCIS. Twenty-nine miRNAs and 420 mRNAs were aberrantly expressed between HN and DCIS. Combining these two datasets with miRNA-target prediction we identified two established target pairs (miR-195:CCND1 and miR-21:NFIB) and tested several novel miRNA:mRNA target pairs. Over-expression of the putative tumor-suppressor miR-125b, under-expressed in DCIS, repressed the expression of MEMO1, which is required for ErbB2-driven cell motility (also a target of miR-125b); and NRIP1/RIP140, which modulates the transcriptional activity of the estrogen receptor. Knockdown of the putative oncogenic miRNAs miR-182 and miR-183, both highly over-expressed in DCIS, increased the expression of CBX7 (which regulates E-cadherin expression), DOK4, NMT2, and EGR1. Augmentation of CBX7 by knockdown of miR-182 expression, in turn, positively regulated the expression of E-cadherin, a key protein involved in maintaining normal epithelial cell morphology which is commonly lost during neoplastic progression. Conclusions: These data provide the first miRNA expression profile of normal breast epithelium and of pre-invasive breast carcinoma. Further, we demonstrate that altered miRNA expression can modulate gene expression changes that characterize these early cancers. We conclude that miRNA dysregulation likely plays a substantial role in early breast cancer development. Two total samples were analyzed via Affymetrix U133A. Case numbers correspond to individual patients. Each sample is identified by case number, histologic lesion and corresponding microarray ID.

Project description:Introduction: microRNAs (miRNAs) are short non-coding RNAs that negatively regulate gene expression and may play a causal role in invasive breast cancer. Since many genetic aberrations of invasive disease are detectable in earlier stages, we hypothesized that miRNA expression dysregulation and the predicted changes in gene expression would also be found in early breast neoplasias. Methods: Expression profiling of 365 miRNAs by RT-qPCR was combined with laser-capture microdissection to obtain an epithelial specific miRNA expression signature of normal breast epithelium (n=9) and of paired samples of histologically normal epithelium (HN) and ductal carcinoma in situ (DCIS) (n=16). To determine how miRNAs may control the expression of co-dysregulated mRNAs we also performed gene expression microarray analysis in the same paired HN and DCIS samples and integrated this with miRNA-target prediction. We further validated several target pairs by modulating the expression levels of miRNAs in MCF7 cells and measured the expression of target mRNAs and proteins. Results: Thirty-five miRNAs were aberrantly expressed between RM, HN and DCIS. Twenty-nine miRNAs and 420 mRNAs were aberrantly expressed between HN and DCIS. Combining these two datasets with miRNA-target prediction we identified two established target pairs (miR-195:CCND1 and miR-21:NFIB) and tested several novel miRNA:mRNA target pairs. Over-expression of the putative tumor-suppressor miR-125b, under-expressed in DCIS, repressed the expression of MEMO1, which is required for ErbB2-driven cell motility (also a target of miR-125b); and NRIP1/RIP140, which modulates the transcriptional activity of the estrogen receptor. Knockdown of the putative oncogenic miRNAs miR-182 and miR-183, both highly over-expressed in DCIS, increased the expression of CBX7 (which regulates E-cadherin expression), DOK4, NMT2, and EGR1. Augmentation of CBX7 by knockdown of miR-182 expression, in turn, positively regulated the expression of E-cadherin, a key protein involved in maintaining normal epithelial cell morphology which is commonly lost during neoplastic progression. Conclusions: These data provide the first miRNA expression profile of normal breast epithelium and of pre-invasive breast carcinoma. Further, we demonstrate that altered miRNA expression can modulate gene expression changes that characterize these early cancers. We conclude that miRNA dysregulation likely plays a substantial role in early breast cancer development.

Project description:Schmitz2014 - RNA triplex formation The model is parameterized using the parameters for gene CCDC3 from Supplementary Table S1. The two miRNAs which form the triplex together with CCDC3 are miR-551b and miR-138. This model is described in the article: Cooperative gene regulation by microRNA pairs and their identification using a computational workflow. Schmitz U, Lai X, Winter F, Wolkenhauer O, Vera J, Gupta SK. Nucleic Acids Res. 2014 Jul; 42(12): 7539-7552 Abstract: MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/. This model is hosted on BioModels Database and identified by: BIOMD0000000530. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir1_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Nature Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110000. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir181_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110001. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir378_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110002. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir143_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110003. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Expression of microRNAs and their gene targets are dysregulated in pre-invasive breast cancer (microRNA)

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