BRAF, TERT and HLA-G Status in the Papillary Thyroid Carcinoma: A Clinicopathological Association Study.

As BRAF, TERT, HLA-G, and microRNAs have been individually associated with papillary thyroid carcinoma (PTC), we aimed to evaluate the individual and collaborative role of these markers in PTC in the same patient cohort. HLA-G and BRAF tumor expression was evaluated by immunohistochemistry. Using molecular methods, BRAFV600E and TERT promoter mutations were evaluated in thyroid fine needle aspirates. MicroRNA tumor profiling was investigated using massively parallel sequencing. We observed strong HLA-G (67.96%) while BRAF (62.43%) staining was observed in PTC specimens. BRAF overexpression was associated with poor response to therapy. The BRAFV600E (52.9%) and TERTC228T (13%) mutations were associated with extrathyroidal extension, advanced-age, and advanced-stage cancer. The TERT rs2853669 CC+TC genotypes (38%) were overrepresented in metastatic tumors. Nine modulated microRNAs targeting the BRAF, TERT, and/or HLA-G genes were observed in PTC and involved with cancer-related signaling pathways. The markers were individually associated with PTC features, emphasizing the synergistic effect of BRAFV600E and TERTC228T; however, their collaborative role on PTC outcome was not fully demonstrated. The differentially expressed miRNAs targeting the BRAF and/or HLA-G genes may explain their increased expression in the tumor milieu.

Transcript Expression Profiles and MicroRNA Regulation Indicate an Upregulation of Processes Linked to Oxidative Stress, DNA Repair, Cell Death, and Inflammation in Type 1 Diabetes Mellitus Patients.

Type 1 diabetes (T1D) arises from autoimmune-mediated destruction of insulin-producing ß-cells leading to impaired insulin secretion and hyperglycemia. T1D is accompanied by DNA damage, oxidative stress, and inflammation, although there is still scarce information about the oxidative stress response and DNA repair in T1D pathogenesis. We used the microarray method to assess mRNA expression profiles in peripheral blood mononuclear cells (PBMCs) of 19 T1D patients compared to 11 controls and identify mRNA targets of microRNAs that were previously reported for T1D patients. We found 277 differentially expressed genes (220 upregulated and 57 downregulated) in T1D patients compared to controls. Analysis by gene sets (GSA and GSEA) showed an upregulation of processes linked to ROS generation, oxidative stress, inflammation, cell death, ER stress, and DNA repair in T1D patients. Besides, genes related to oxidative stress responses and DNA repair (PTGS2, ATF3, FOSB, DUSP1, and TNFAIP3) were found to be targets of four microRNAs (hsa-miR-101, hsa-miR148a, hsa-miR-27b, and hsa-miR-424). The expression levels of these mRNAs and microRNAs were confirmed by qRT-PCR. Therefore, the present study on differential expression profiles indicates relevant biological functions related to oxidative stress response, DNA repair, inflammation, and apoptosis in PBMCs of T1D patients relative to controls. We also report new insights regarding microRNA-mRNA interactions, which may play important roles in the T1D pathogenesis.

Peripheral spectrum neurological disorder after arbovirus infection is associated with HLA-F variants among Northeastern Brazilians.

INTRODUCTION: Non-classical class I human leukocyte antigens (HLA) molecules are known to modulate the function of cytotoxic cells (NK and T CD8+) during viral infection by interacting with inhibitory/activating receptors. However, little is known about the HLA-E/-F genetic variability on arbovirus infections. METHODS: We evaluated by massive parallel sequencing the full HLA-E/-F genetic diversity among patients infected during the arbovirus (ZIKV, DENV, and CHIKV) outbreak leading to a broad range of neurological complications in the Brazilian State of Pernambuco. In parallel, healthy blood donors from the same area were also studied. Plink and R software were used for genetic association study. To limit the false-positive results and enhance the reliability of the results, we adopted P-values <0.01 as significant levels. RESULTS: Compared to controls, the HLA-F alleles: -1610 C (rs17875375), +1383 G (rs17178385), and +3537 A (rs17875384), all in complete linkage disequilibrium with each other (r2 = 1), were overrepresented in patients presenting peripheral spectrum disorders (PSD). The HLA-F*Distal-D haplotype that harbored the -1610 C allele exhibited a trend increase in PSD group. No associations were found for HLA-E. CONCLUSIONS: Our findings showed that the HLA-F genetic background seems to be more important than HLA-E on the susceptibility to PSD complications.

HLA-G variability and haplotypes detected by massively parallel sequencing procedures in the geographicaly distinct population samples of Brazil and Cyprus.

The HLA-G molecule presents immunomodulatory properties that might inhibit immune responses when interacting with specific Natural Killer and T cell receptors, such as KIR2DL4, ILT2 and ILT4. Thus, HLA-G might influence the outcome of situations in which fine immune system modulation is required, such as autoimmune diseases, transplants, cancer and pregnancy. The majority of the studies regarding the HLA-G gene variability so far was restricted to a specific gene segment (i.e., promoter, coding or 3' untranslated region), and was performed by using Sanger sequencing and probabilistic models to infer haplotypes. Here we propose a massively parallel sequencing (NGS) with a bioinformatics strategy to evaluate the entire HLA-G regulatory and coding segments, with haplotypes inferred relying more on the straightforward haplotyping capabilities of NGS, and less on probabilistic models. Then, HLA-G variability was surveyed in two admixed population samples of distinct geographical regions and demographic backgrounds, Cyprus and Brazil. Most haplotypes (promoters, coding, 3'UTR and extended ones) were detected both in Brazil and Cyprus and were identical to the ones already described by probabilistic models, indicating that these haplotypes are quite old and may be present worldwide.

HLA-E coding and 3' untranslated region variability determined by next-generation sequencing in two West-African population samples.

HLA-E is a non-classical Human Leucocyte Antigen class I gene with immunomodulatory properties. Whereas HLA-E expression usually occurs at low levels, it is widely distributed amongst human tissues, has the ability to bind self and non-self antigens and to interact with NK cells and T lymphocytes, being important for immunosurveillance and also for fighting against infections. HLA-E is usually the most conserved locus among all class I genes. However, most of the previous studies evaluating HLA-E variability sequenced only a few exons or genotyped known polymorphisms. Here we report a strategy to evaluate HLA-E variability by next-generation sequencing (NGS) that might be used to other HLA loci and present the HLA-E haplotype diversity considering the segment encoding the entire HLA-E mRNA (including 5'UTR, introns and the 3'UTR) in two African population samples, Susu from Guinea-Conakry and Lobi from Burkina Faso. Our results indicate that (a) the HLA-E gene is indeed conserved, encoding mainly two different protein molecules; (b) Africans do present several unknown HLA-E alleles presenting synonymous mutations; (c) the HLA-E 3'UTR is quite polymorphic and (d) haplotypes in the HLA-E 3'UTR are in close association with HLA-E coding alleles. NGS has proved to be an important tool on data generation for future studies evaluating variability in non-classical MHC genes.

The Role of HLA-G Molecule and HLA-G Gene Polymorphisms in Tumors, Viral Hepatitis, and Parasitic Diseases.

Considering that the non-classical HLA-G molecule has well-recognized tolerogenic properties, HLA-G expression is expected to be deleterious when present in tumor cells and in cells chronically infected by viruses, whereas HLA-G expression is expected to be advantageous in autoimmune disorders. The expression of HLA-G on tissue or peripheral blood cells, the levels of soluble HLA-G and polymorphic sites along the gene have been studied in several disorders. In this study, we revised the role of the molecule and polymorphic sites along the HLA-G gene in tumors, viral hepatitis, and parasitic disorders. Overall, several lines of evidence clearly show that the induction of HLA-G expression in tumors has been associated with worse disease outcome and disease spread. In addition, the few studies conducted on hepatitis and parasitic disorders indicate that HLA-G may contribute to disease pathogenesis. Few isolated polymorphic sites, primarily located at the coding or 3' untranslated HLA-G region, have been evaluated in these disorders, and a complete HLA-G typing together with the study of gene regulatory elements may further help on the understanding of the influence of the genetic background on disease susceptibility.

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

BACKGROUND: Type 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. METHODS: Samples 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. RESULTS: The 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. CONCLUSION: This 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.

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 ß-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.

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

BACKGROUND: Regardless 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. RESULTS: The 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. CONCLUSIONS: These 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.