RESUMEN
We performed a meta-analysis of the transcription profiles of type 1, type 2 and gestational diabetes to evaluate similarities and dissimilarities among these diabetes types. cRNA samples obtained from peripheral blood lymphomononuclear cells (PBMC) of 56 diabetes mellitus patients (type 1 = 19; type 2 = 20; gestational = 17) were hybridized to the same whole human genome oligomicroarray platform, encompassing 44,000 transcripts. The GeneSpring software was used to perform analysis and hierarchical clustering, and the DAVID database was used for gene ontology. The gene expression profiles showed more similarity between gestational and type 1 diabetes rather than between type 2 and gestational diabetes, a finding that was not influenced by patient gender and age. The meta-analysis of the three types of diabetes disclosed 3,747 differentially and significantly expressed genes. A total of 486 genes were characteristic of gestational diabetes, 202 genes of type 1, and 651 genes of type 2 diabetes. 19 known genes were shared by type 1, type 2 and gestational diabetes, highlighting EGF, FAM46C, HBEGF, ID1, SH3BGRL2, VEPH1, and TMEM158 genes. The meta-analysis of PBMC transcription profiles characterized each type of diabetes revealing that gestational and type 1 diabetes were transcriptionally related.
Asunto(s)
Diabetes Mellitus Tipo 1/metabolismo , Diabetes Mellitus Tipo 2/metabolismo , Diabetes Gestacional/metabolismo , Leucocitos Mononucleares/metabolismo , Adulto , Anciano , Análisis por Conglomerados , Diabetes Gestacional/clasificación , Femenino , Perfilación de la Expresión Génica , Humanos , Masculino , Análisis por Micromatrices , Persona de Mediana Edad , Embarazo , ARN Complementario/genéticaRESUMEN
Cediranib, a pan-tyrosine kinase inhibitor is showing promising results for the treatment of several solid tumours. In breast cancer, its effects remain unclear, and there are no predictive biomarkers. Several studies have examined the expression profiles of microRNAs (miRNAs) in response to different chemotherapy treatments and found that the expression patterns may be associated with the treatment response. Therefore, our aim was to evaluate the cellular behaviour and differential expression profiles of miRNAs in breast cancer cell lines exposed to cediranib. The biological effect of this drug was measured by viability, migration, invasion and cell death in in vitro assays. Signaling pathways were assessed using a human phospho-receptor tyrosine kinase array. Furthermore, using a miRNA array and quantitative real-time PCR (qRTPCR), we assessed the relative expression of miRNAs following cediranib treatment. The breast cancer cell lines exhibited a distinct cytotoxic response to cediranib treatment. Cediranib exposure resulted in a decrease in the cell migration and invasion of all the breast cancer cell lines. Treatment with cediranib appeared to be able to modulate the activation of several RTKs that are targets of cediranib such as EGFR and a new potential target ROR2. Furthermore, this drug was able to modulate the expression profile of different microRNAs such as miR-494, miR-923, miR-449a, miR-449b and miR-886-3 in breast cancer cell lines. These miRNAs are reported to regulate genes involved in important molecular processes, according to bioinformatics prediction tools.