Adriane F. Evangelista

Identifying common and specific microRNAs expressed in peripheral blood mononuclear cell of type 1, type 2, and gestational diabetes mellitus patients

BackgroundRegardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics.ResultsThe use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis.ConclusionsThese results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.

MicroRNA expression profiling and functional annotation analysis of their targets in patients with type 1 diabetes mellitus.

Type 1 diabetes mellitus (T1DM) results from an autoimmune attack against the insulin-producing pancreatic β-cells, leading to elimination of insulin production. The exact cause of this disorder is still unclear. Although the differential expression of microRNAs (miRNAs), small non-coding RNAs that control gene expression in a post-transcriptional manner, has been identified in many diseases, including T1DM, only scarce information exists concerning miRNA expression profile in T1DM. Thus, we employed the microarray technology to examine the miRNA expression profiles displayed by peripheral blood mononuclear cells (PBMCs) from T1DM patients compared with healthy subjects. Total RNA extracted from PBMCs from 11 T1DM patients and nine healthy subjects was hybridized onto Agilent human miRNA microarray slides (V3), 8x15K, and expression data were analyzed on R statistical environment. After applying the rank products statistical test, the receiver-operating characteristic (ROC) curves were generated and the areas under the ROC curves (AUC) were calculated. To examine the functions of the differentially expressed (p-value<0.01, percentage of false-positives <0.05) miRNAs that passed the AUC cutoff value ≥ 0.90, the database miRWalk was used to predict their potential targets, which were afterwards submitted to the functional annotation tool provided by the Database for Annotation, Visualization, and Integrated Discovery (DAVID), version 6.7, using annotations from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We found 57 probes, corresponding to 44 different miRNAs (35 up-regulated and 9 down-regulated), that were differentially expressed in T1DM and passed the AUC threshold of 0.90. The hierarchical clustering analysis indicated the discriminatory power of those miRNAs, since they were able to clearly distinguish T1DM patients from healthy individuals. Target prediction indicated that 47 candidate genes for T1DM are potentially regulated by the differentially expressed miRNAs. After performing functional annotation analysis of the predicted targets, we observed 22 and 12 annotated KEGG pathways for the induced and repressed miRNAs, respectively. Interestingly, many pathways were enriched for the targets of both up- and down-regulated miRNAs and the majority of those pathways have been previously associated with T1DM, including many cancer-related pathways. In conclusion, our study indicated miRNAs that may be potential biomarkers of T1DM as well as provided new insights into the molecular mechanisms involved in this disorder.

MicroRNA expression as risk biomarker of breast cancer metastasis: a pilot retrospective case-cohort study

BackgroundMicroRNAs (miRNAs) are small, non-coding RNA molecules involved in post-transcriptional gene regulation and have recently been shown to play a role in cancer metastasis. In solid tumors, especially breast cancer, alterations in miRNA expression contribute to cancer pathogenesis, including metastasis. Considering the emerging role of miRNAs in metastasis, the identification of predictive markers is necessary to further the understanding of stage-specific breast cancer development. This is a retrospective analysis that aimed to identify molecular biomarkers related to distant breast cancer metastasis development.MethodsA retrospective case cohort study was performed in 64 breast cancer patients treated during the period from 1998–2001. The case group (n = 29) consisted of patients with a poor prognosis who presented with breast cancer recurrence or metastasis during follow up. The control group (n = 35) consisted of patients with a good prognosis who did not develop breast cancer recurrence or metastasis. These patient groups were stratified according to TNM clinical stage (CS) I, II and III, and the main clinical features of the patients were homogeneous. MicroRNA profiling was performed and biomarkers related to metastatic were identified independent of clinical stage. Finally, a hazard risk analysis of these biomarkers was performed to evaluate their relation to metastatic potential.ResultsMiRNA expression profiling identified several miRNAs that were both specific and shared across all clinical stages (p ≤ 0.05). Among these, we identified miRNAs previously associated with cell motility (let-7 family) and distant metastasis (hsa-miR-21). In addition, hsa-miR-494 and hsa-miR-21 were deregulated in metastatic cases of CSI and CSII. Furthermore, metastatic miRNAs shared across all clinical stages did not present high sensitivity and specificity when compared to specific-CS miRNAs. Between them, hsa-miR-183 was the most significative of CSII, which miRNAs combination for CSII (hsa-miR-494, hsa-miR-183 and hsa-miR-21) was significant and were a more effective risk marker compared to the single miRNAs.ConclusionsWomen with metastatic breast cancer, especially CSII, presented up-regulated levels of miR-183, miR-494 and miR-21, which were associated with a poor prognosis. These miRNAs therefore represent new risk biomarkers of breast cancer metastasis and may be useful for future targeted therapies.

Autoimmune regulator (Aire) controls the expression of microRNAs in medullary thymic epithelial cells

The autoimmune regulator (Aire) is a transcription factor that controls the ectopic expression of a large set of peripheral tissue antigen (PTA) genes in medullary thymic epithelial cells (mTECs). Recent evidence has demonstrated that Aire releases stalled RNA polymerase II (RNA Pol II) from blockage at the promoter region of its target genes. Given that, in addition to messenger RNAs (mRNA), RNA Pol II also transcribes microRNAs (miRNAs), we raised the hypothesis that Aire might play a role as an upstream controller of miRNA transcription. To test this, we initially analyzed the expression profiles of 662 miRNAs in control and Aire-silenced (siRNA) murine mTEC 3.10 cells using microarrays. The bioinformatics programs SAM and Cluster-TreeView were then used to identify the differentially expressed miRNAs and their profiles, respectively. Thirty Aire-dependent miRNAs were identified in the Aire-silenced mTECs, of which 18 were up- and 12 were down-regulated. The down-regulated miR-376 family was the focus of this study because its members (miR-376a, miR-376b and miR-376c) are located in the genome within the Gm2922 open-reading frame (ORF) gene segment on the chromosome 12F1. The T-boxes (TTATTA) and G-boxes (GATTGG), which represent putative RNA Pol II promoter motifs, were located in a portion spanning 10 kb upstream of the ATG codon of Gm2922. Moreover, we found that Gm2922 encodes an mRNA, which was also down-regulated in Aire-silenced mTECs. These results represent the first evidence that Aire can play a role as a controller of transcription of miRNAs located within genomic regions encompassing ORF and/or mRNA genes.

Gene expression profiles displayed by peripheral blood mononuclear cells from patients with type 2 diabetes mellitus focusing on biological processes implicated on the pathogenesis of the disease

Patients with type 2 diabetes mellitus (T2DM) exhibit insulin resistance associated with obesity and inflammatory response, besides an increased level of oxidative DNA damage as a consequence of the hyperglycemic condition and the generation of reactive oxygen species (ROS). In order to provide information on the mechanisms involved in the pathophysiology of T2DM, we analyzed the transcriptional expression patterns exhibited by peripheral blood mononuclear cells (PBMCs) from patients with T2DM compared to non-diabetic subjects, by investigating several biological processes: inflammatory and immune responses, responses to oxidative stress and hypoxia, fatty acid processing, and DNA repair. PBMCs were obtained from 20 T2DM patients and eight non-diabetic subjects. Total RNA was hybridized to Agilent whole human genome 4×44K one-color oligo-microarray. Microarray data were analyzed using the GeneSpring GX 11.0 software (Agilent). We used BRB-ArrayTools software (gene set analysis - GSA) to investigate significant gene sets and the Genomica tool to study a possible influence of clinical features on gene expression profiles. We showed that PBMCs from T2DM patients presented significant changes in gene expression, exhibiting 1320 differentially expressed genes compared to the control group. A great number of genes were involved in biological processes implicated in the pathogenesis of T2DM. Among the genes with high fold-change values, the up-regulated ones were associated with fatty acid metabolism and protection against lipid-induced oxidative stress, while the down-regulated ones were implicated in the suppression of pro-inflammatory cytokines production and DNA repair. Moreover, we identified two significant signaling pathways: adipocytokine, related to insulin resistance; and ceramide, related to oxidative stress and induction of apoptosis. In addition, expression profiles were not influenced by patient features, such as age, gender, obesity, pre/post-menopause age, neuropathy, glycemia, and HbA(1c) percentage. Hence, by studying expression profiles of PBMCs, we provided quantitative and qualitative differences and similarities between T2DM patients and non-diabetic individuals, contributing with new perspectives for a better understanding of the disease.

Expression of genes related to apoptosis, cell cycle and signaling pathways are independent of TP53 status in urinary bladder cancer cells

Urinary bladder cancer is the fourth most common malignancy in the Western world. Transitional cell carcinoma (TCC) is the most common subtype, accounting for about 90% of all bladder cancers. The TP53 gene plays an essential role in the regulation of the cell cycle and apoptosis and therefore contributes to cellular transformation and malignancy; however, little is known about the differential gene expression patterns in human tumors that present with the wild-type or mutated TP53 gene. Therefore, because gene profiling can provide new insights into the molecular biology of bladder cancer, the present study aimed to compare the molecular profiles of bladder cancer cell lines with different TP53 alleles, including the wild type (RT4) and two mutants (5637, with mutations in codons 280 and 72; and T24, a TP53 allele encoding an in-frame deletion of tyrosine 126). Unsupervised hierarchical clustering and gene networks were constructed based on data generated by cDNA microarrays using mRNA from the three cell lines. Differentially expressed genes related to the cell cycle, cell division, cell death, and cell proliferation were observed in the three cell lines. However, the cDNA microarray data did not cluster cell lines based on their TP53 allele. The gene profiles of the RT4 cells were more similar to those of T24 than to those of the 5637 cells. While the deregulation of both the cell cycle and the apoptotic pathways was particularly related to TCC, these alterations were not associated with the TP53 status.

Evidence for a network transcriptional control of promiscuous gene expression in medullary thymic epithelial cells

The expression of peripheral tissue antigens (PTAs) in the thymus by medullary thymic epithelial cells (mTECs) is essential for the central self-tolerance in the generation of the T cell repertoire. Due to heterogeneity of autoantigen representation, this phenomenon has been termed promiscuous gene expression (PGE), in which the autoimmune regulator (Aire) gene plays a key role as a transcription factor in part of these genes. Here we used a microarray strategy to access PGE in cultured murine CD80(+) 3.10 mTEC line. Hierarchical clustering of the data allowed observation that PTA genes were differentially expressed being possible to found their respective induced or repressed mRNAs. To further investigate the control of PGE, we tested the hypothesis that genes involved in this phenomenon might also be modulated by transcriptional network. We then reconstructed such network based on the microarray expression data, featuring the guanylate cyclase 2d (Gucy2d) gene as a main node. In such condition, we established 167 positive and negative interactions with downstream PTA genes. Silencing Aire by RNA interference, Gucy2d while down regulated established a larger number (355) of interactions with PTA genes. T- and G-boxes corresponding to AIRE protein binding sites located upstream to ATG codon of Gucy2d supports this effect. These findings provide evidence that Aire plays a role in association with Gucy2d, which is connected to several PTA genes and establishes a cascade-like transcriptional control of promiscuous gene expression in mTEC cells.

Accuracy of microRNAs as markers for the detection of neck lymph node metastases in patients with head and neck squamous cell carcinoma

BackgroundThe presence of metastatic disease in cervical lymph nodes of head and neck squamous cell carcinoma (HNSCC) patients is a very important determinant in therapy choice and prognosis, with great impact in overall survival. Frequently, routine lymph node staging cannot detect occult metastases and the post-surgical histologic evaluation of resected lymph nodes is not sensitive in detecting small metastatic deposits. Molecular markers based on tissue-specific microRNA expression are alternative accurate diagnostic markers. Herein, we evaluated the feasibility of using the expression of microRNAs to detect metastatic cells in formalin-fixed paraffin-embedded (FFPE) lymph nodes and in fine-needle aspiration (FNA) biopsies of HNSCC patients.MethodsAn initial screening compared the expression of 667 microRNAs in a discovery set comprised by metastatic and non-metastatic lymph nodes from HNSCC patients. The most differentially expressed microRNAs were validated by qRT-PCR in two independent cohorts: i) 48 FFPE lymph node samples, and ii) 113 FNA lymph node biopsies. The accuracy of the markers in identifying metastatic samples was assessed through the analysis of sensitivity, specificity, accuracy, negative predictive value, positive predictive value, and area under the curve values.ResultsSeven microRNAs highly expressed in metastatic lymph nodes from the discovery set were validated in FFPE lymph node samples. MiR-203 and miR-205 identified all metastatic samples, regardless of the size of the metastatic deposit. Additionally, these markers also showed high accuracy when FNA samples were examined.ConclusionsThe high accuracy of miR-203 and miR-205 warrant these microRNAs as diagnostic markers of neck metastases in HNSCC. These can be evaluated in entire lymph nodes and in FNA biopsies collected at different time-points such as pre-treatment samples, intraoperative sentinel node biopsy, and during patient follow-up. These markers can be useful in a clinical setting in the management of HNSCC patients from initial disease staging and therapy planning to patient surveillance.

Integrative analysis of the transcriptome profiles observed in type 1, type 2 and gestational diabetes mellitus reveals the role of inflammation

BackgroundType 1 diabetes (T1D) is an autoimmune disease, while type 2 (T2D) and gestational diabetes (GDM) are considered metabolic disturbances. In a previous study evaluating the transcript profiling of peripheral mononuclear blood cells obtained from T1D, T2D and GDM patients we showed that the gene profile of T1D patients was closer to GDM than to T2D. To understand the influence of demographical, clinical, laboratory, pathogenetic and treatment features on the diabetes transcript profiling, we performed an analysis integrating these features with the gene expression profiles of the annotated genes included in databases containing information regarding GWAS and immune cell expression signatures.MethodsSamples from 56 (19 T1D, 20 T2D, and 17 GDM) patients were hybridized to whole genome one-color Agilent 4x44k microarrays. Non-informative genes were filtered by partitioning, and differentially expressed genes were obtained by rank product analysis. Functional analyses were carried out using the DAVID database, and module maps were constructed using the Genomica tool.ResultsThe functional analyses were able to discriminate between T1D and GDM patients based on genes involved in inflammation. Module maps of differentially expressed genes revealed that modulated genes: i) exhibited transcription profiles typical of macrophage and dendritic cells; ii) had been previously associated with diabetic complications by association and by meta-analysis studies, and iii) were influenced by disease duration, obesity, number of gestations, glucose serum levels and the use of medications, such as metformin.ConclusionThis is the first module map study to show the influence of epidemiological, clinical, laboratory, immunopathogenic and treatment features on the transcription profiles of T1D, T2D and GDM patients.

Assessment of DNA damage and mRNA/miRNA transcriptional expression profiles in hyperglycemic versus non-hyperglycemic patients with type 2 diabetes mellitus

The development of type 2 diabetes mellitus (T2D) is associated with a number of genetic and environmental factors. Hyperglycemia, a T2D hallmark, is related to several metabolic complications, comorbidities and increased DNA damage. However, the molecular alterations of a proper glucose control are still unclarified. In this study, we aimed to evaluate DNA damage (comet assay), as well as to compare the transcriptional expression (mRNA and miRNA analyzed by the microarray technique) displayed by peripheral blood mononuclear cells (PBMCs) from three distinct groups: hyperglycemic T2D patients (T2D-H, n=14), non-hyperglycemic T2D patients (T2D-N, n=15), and healthy non-diabetic individuals (n=16). The comet assay revealed significantly (p<0.05) higher levels of DNA damage in T2D-H group compared to both T2D-N and control groups, while a significant difference was not observed between the control and T2D-N groups. After bioinformatics analysis, the differentially expressed mRNAs were subjected to functional enrichment analysis (DAVID) and inflammatory response was among the enriched terms found when comparing T2D-N with controls and T2D-H with T2D-N. Concerning the gene set enrichment and gene set analyses, among the differentially expressed gene sets, three were of interest: regulation of DNA repair (T2D-H versus T2D-N), superoxide response (T2D-H versus control group), and response to endoplasmic reticulum stress (T2D-H versus control group). We also identified miRNAs related with T2D and hyperglycemia not yet associated with these conditions in the literature. Some of the differentially expressed mRNAs were among the predicted targets of the differentially expressed miRNAs. Our results showed the association of hyperglycemia with increased DNA damage and aberrant expression of miRNAs and genes related to several biological processes, such as inflammation, DNA repair, ROS production and antioxidant defense, highlighting the importance of proper glycemic control. Moreover, the transcriptional expression of miRNAs provided novel information for understanding the regulatory mechanisms involved in the T2D progression.