Project description:Dataset containing micro-RNA expression profiles of breast cancers at the time of endocrine resistance. It has been used to correlate micro-RNA and mRNA expressions and to identify two distinctive phenotypes with different expression of micro-RNA gens. Please note that the tumor samples are clinically quite homogeneous: all are post-menopausal ER+ve breast cancers, endocrine treated and growing on treatment. The main purpose of collecting these data was not to compare transcriptional profiles with clinical parameters, but rather to use the micro-RNA expression profiles of these clinically homogeneous tumours for (i) identifying intrinsic subgroups within endocrine resistance and (ii) for relating micro-RNA and mRNA expressions. However, the relevant clinical data was also provided as Series supplementary file (ClinicalData_AL28Jan2014.xlsx).
Project description:Expression data from B. japonicum bll2758::aphII strain (7414) grown micro-oxically. This study includes also the expression data of a fixK2 and a fixJ mutant grown in free-living micro-oxic condition (samples GSM313721 to GSM313734 in GEO record number GSE12491) and the wild type strain grown micro-oxically (samples GSM210246 to GSM210268 in GEO record number GSE8478).
Project description:Rationale: Overstretching of lung parenchyma may lead to tissue injury, especially during mechanical ventilation. There are no specific biomarkers of lung stretch. Objectives: To identify transcriptomic signatures of micro-RNAs and genes specifically related to lung stretch and validate them in preclinical models. Methods: Data on micro-RNA expression in response to stretch in experimental models were systematically pooled. Signatures were identified as those micro-RNAs or genes with differential expression in samples from stretched cells, and optimized using a greedy algorithm. Transcriptomic scores were calculated as the difference of geometric means in expression of up- and down-regulated features, and compared among different magnitudes of stretch. The accuracy of these scores was validated in animal models of lung injury, ex vivo mechanically ventilated human lungs and in bronchoalveolar lavage fluid (BALF) from patients under different ventilatory conditions. Measurements and main results: Eight micro-RNAs were differentially expressed in stretched cell cultures (n=24). Amongst the genes regulated by these micro-RNAs, a 180-gene signature was identified in ex vivo models (n=106) and refined using data from animal models (n=143) to obtain a 4-gene signature. The corresponding scores were significantly higher in samples submitted to stretch or injurious mechanical ventilation. The microRNA signatures were validated in human tissue and BALF, with areas under the ROC curve between 0.89 and 1 respectively to identify lung overdistention. Conclusions: Lung cell stretch induces the expression of specific micro-RNA and genes. These signatures may be used to obtain an index of lung overstretching that can be measured at the bedside.
Project description:Rationale: Overstretching of lung parenchyma may lead to tissue injury, especially during mechanical ventilation. There are no specific biomarkers of lung stretch. Objectives: To identify transcriptomic signatures of micro-RNAs and genes specifically related to lung stretch and validate them in preclinical models. Methods: Data on micro-RNA expression in response to stretch in experimental models were systematically pooled. Signatures were identified as those micro-RNAs or genes with differential expression in samples from stretched cells, and optimized using a greedy algorithm. Transcriptomic scores were calculated as the difference of geometric means in expression of up- and down-regulated features, and compared among different magnitudes of stretch. The accuracy of these scores was validated in animal models of lung injury, ex vivo mechanically ventilated human lungs and in bronchoalveolar lavage fluid (BALF) from patients under different ventilatory conditions. Measurements and main results: Eight micro-RNAs were differentially expressed in stretched cell cultures (n=24). Amongst the genes regulated by these micro-RNAs, a 180-gene signature was identified in ex vivo models (n=106) and refined using data from animal models (n=143) to obtain a 4-gene signature. The corresponding scores were significantly higher in samples submitted to stretch or injurious mechanical ventilation. The microRNA signatures were validated in human tissue and BALF, with areas under the ROC curve between 0.89 and 1 respectively to identify lung overdistention. Conclusions: Lung cell stretch induces the expression of specific micro-RNA and genes. These signatures may be used to obtain an index of lung overstretching that can be measured at the bedside.