An improved in silico selection of phenotype affecting polymorphisms in SLC6A4, HTR1A and HTR2A genes

Computational Analysis of Single Nucleotide Polymorphisms in Human HIC1 Gene

Background A putative tumor suppressor gene called HIC1 (hypermethylated in cancer) is situated at 17p13.3, a locus where the allelic loss occurs often in human malignancies, including breast cancer. Hypermethylated in cancer 1 protein is a protein that in humans is encoded by the HIC1 gene and it's a Homo sapiens (Human). This gene functions as a growth regulatory and tumor repressor gene. The molecular function of HIC1 gene includes DNA-binding transcription factor activity, sequence-specific DNA binding, DNA binding, histone deacetylase binding, protein binding, metal ion binding, nucleic acid binding, DNA-binding transcription repressor activity, RNA polymerase II-specific, DNA-binding transcription factor activity, RNA polymerase II-specific. The biological process of HIC1 gene includes multicellular organism development, negative regulation of Wnt signaling pathway, positive regulation of DNA damage response, signal transduction by p53 class mediator regulation of transcription, DNA-templated, negative regulation of transcription by RNA polymerase II, Wnt signaling pathway, transcription, DNA-templated, intrinsic apoptotic signaling pathway in response to DNA damage, cellular response to DNA damage stimulus. The study aimed to predict the stability and structure of the protein that will arise from single nucleotide polymorphisms (SNPs) in the human HIC1 gene. Methodology To investigate the possible negative effects associated with these SNPs, bioinformatic analysis is typically essential. The following tools were employed for forecasting harmful SNPs: scale-invariant feature transform (SIFT), Protein Analysis Through Evolutionary Relationships (PANTHER), nonsynonymous SNP by Protein Variation Effect Analyzer (PROVEAN), and nonsynonymous SNP by Single Nucleotide Polymorphism Annotation Platform (SNAP). Results The present study identified a total of 36 SNPs using the SIFT approach, which were shown to have functional significance. Twenty-six were determined to be tolerable, whereas 10 were shown to be detrimental. Out of 20 SNPs, seven (P370A, P646S, R654P, A476T, S400S, D666N, D7V) SNPs were predicted as "Possibly damaging" and seven (L9F, G468R, G490R, L482R, S12W, G489D, S12P) were identified as "probably benign", and six (R725G, G620S, A56V, E463D, D394N, L338V) were identified as "probably damaging" according to the predictions made by PANTHER tools. The majority of the pixels on the strip were red, indicating that the gene changes may have dangerous consequences. These results highlight the need for more research to fully comprehend how these mutations affect the hic1 protein's function, which is essential for the emergence of different types of cancer. Conclusion The current research has provided us with essential information about how SNPs might be used as a diagnostic marker for cancer, given that SNPs may be candidates for cellular changes caused by mutations linked to cancer.

Emerging Biomarkers in Bladder Cancer Identified by Network Analysis of Transcriptomic Data

Bladder cancer is a very common malignancy. Although new treatment strategies have been developed, the identification of new therapeutic targets and reliable diagnostic/prognostic biomarkers for bladder cancer remains a priority. Generally, they are found among differentially expressed genes between patients and healthy subjects or among patients with different tumor stages. However, the classical approach includes processing these data taking into consideration only the expression of each single gene regardless of the expression of other genes. These complex gene interaction networks can be revealed by a recently developed systems biology approach called Weighted Gene Co-expression Network Analysis (WGCNA). It takes into account the expression of all genes assessed in an experiment in order to reveal the clusters of co-expressed genes (modules) that, very probably, are also co-regulated. If some genes are co-expressed in controls but not in pathological samples, it can be hypothesized that a regulatory mechanism was altered and that it could be the cause or the effect of the disease. Therefore, genes within these modules could play a role in cancer and thus be considered as potential therapeutic targets or diagnostic/prognostic biomarkers. Here, we have reviewed all the studies where WGCNA has been applied to gene expression data from bladder cancer patients. We have shown the importance of this new approach in identifying candidate biomarkers and therapeutic targets. They include both genes and miRNAs and some of them have already been identified in the literature to have a role in bladder cancer initiation, progression, metastasis, and patient survival.

Exploring Small Extracellular Vesicles for Precision Medicine in Prostate Cancer

Tumor microenvironment constitutes a complex network in which tumor cells communicate among them and with stromal and immune cells. It has been shown that cancer cells are able to exchange genetic materials through small extracellular vesicles (EVs), a heterogeneous group of vesicles with different size and shape, cargo content, and function. The importance to investigate populations of circulating EVs would be of great importance as prostate cancer (PCa) biomarkers. In several neoplasms as well as in PCa, nanometer-sized EVs of endosomal origin are implicated in supporting tumor growth and metastatic spread by both altering local stroma cells and creating a protumor environment that favors the formation of pre-metastatic niches. Several techniques are applicable for the isolation and analysis of PCa-derived small EVs and are illustrated in this article. Due to the high sensitivity and specificity of these techniques, small EVs have become ideal candidates for early diagnosis. Moreover, we discuss the role of small EVs during PCa carcinogenesis, as well as in modulating the development of drug resistance to hormonal therapy and chemotherapy, thus underlining the potential of EV-tailored strategies in PCa patients.

A germline missense mutation in exon 3 of the MSH2 gene in a Lynch syndrome family: correlation with phenotype and localization assay

Lynch syndrome is caused by germline mutations in any of the MisMatch Repair (MMR) genes. About 37% of MSH2 variants are missense variants causing single amino-acid substitutions. Whether missense variants affect the normal function of MMR proteins is crucial both to provide affected families a more accurate risk assessment and to offer predictive testing to family members. Here we report one family, fulfilling both Amsterdam I and II criteria and Bethesda guidelines, referred to our center for genetic counselling. The proband and some of her relatives have been investigated for microsatellite instability (MSI), immunohistochemical MMR protein staining, direct sequencing and Multiplex Ligation-dependent Probe Amplification (MLPA). Also Subcellular Localization Assay and Splice site predictions analyses were used. A germline missense variant of uncertain significance (exon 3, p.Val161Asp) was found in MSH2 gene in proband and in some relatives. The variant was associated with lack of expression of MSH2 protein (DMMR) and MSI-High status in tumour tissues. The localization assay of the MSH2 protein showed an abnormal subcellular localization pattern of the corresponding protein. Finally, splice-site prediction analysis ruled out a potential role of new splice sites as the cause behind the lack of expression of MSH2 protein and we suppose a potential correlation with other forms of post-transcriptional regulation (circular RNAs). The variant here reported shows a high correlation with phenotype and is located in an evolutionary conserved domain. The localization assay also suggest a potential pathogenic role, thus supporting further research on this matter.

Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysis

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a dismal prognosis which is, among others, due to a lack of suitable biomarkers and therapeutic targets. Previously, basic gene expression analysis methods have been used for their identification, but recently new algorithms have been developed allowing more comprehensive data analyses. Among them, weighted gene co-expression network analysis (WGCNA) has already been applied to several cancer types with promising results.

METHODS

We applied WGCNA to miRNA expression data from PDAC patients. Specifically, we processed microarray-based expression data of 2555 miRNAs in serum from 100 PDAC patients and 150 healthy subjects. We identified network modules of co-expressed miRNAs in the healthy subject dataset and verified their preservation in the PDAC dataset. In the non-preserved modules, we selected key miRNAs and carried out functional enrichment analyses of their experimentally known target genes. Finally, we tested their prognostic significance using overall survival analyses.

RESULTS

Through WGCNA we identified several miRNAs that discriminate healthy subjects from PDAC patients and that, therefore, may play critical roles in PDAC development. At a functional level, we found that they regulate p53, FoxO and ErbB associated cellular signalling pathways, as well as cell cycle progression and various genes known to be involved in PDAC development. Some miRNAs were also found to serve as novel prognostic biomarkers, whereas others have previously already been proposed as such, thereby validating the WGCNA approach. In addition, we found that these novel data may explain at least some of our previous PDAC gene expression analysis results.

CONCLUSIONS

We identified several miRNAs critical for PDAC development using WGCNA. These miRNAs may serve as biomarkers for PDAC diagnosis/prognosis and patient stratification, and as putative novel therapeutic targets.

Computational analysis of the mutations in BAP1, PBRM1 and SETD2 genes reveals the impaired molecular processes in renal cell carcinoma

Clear cell Renal Cell Carcinoma (ccRCC) is due to loss of von Hippel-Lindau (VHL) gene and at least one out of three chromatin regulating genes BRCA1-associated protein-1 (BAP1), Polybromo-1 (PBRM1) and Set domain-containing 2 (SETD2). More than 350, 700 and 500 mutations are known respectively for BAP1, PBRM1 and SETD2 genes. Each variation damages these genes with different severity levels. Unfortunately for most of these mutations the molecular effect is unknown, so precluding a severity classification. Moreover, the huge number of these gene mutations does not allow to perform experimental assays for each of them. By bioinformatic tools, we performed predictions of the molecular effects of all mutations lying in BAP1, PBRM1 and SETD2 genes. Our results allow to distinguish whether a mutation alters protein function directly or by splicing pattern destruction and how much severely. This classification could be useful to reveal correlation with patients' outcome, to guide experiments, to select the variations that are worth to be included in translational/association studies, and to direct gene therapies.

How much do we know about the coupling of G-proteins to serotonin receptors?

Serotonin receptors are G-protein-coupled receptors (GPCRs) involved in a variety of psychiatric disorders. G-proteins, heterotrimeric complexes that couple to multiple receptors, are activated when their receptor is bound by the appropriate ligand. Activation triggers a cascade of further signalling events that ultimately result in cell function changes. Each of the several known G-protein types can activate multiple pathways. Interestingly, since several G-proteins can couple to the same serotonin receptor type, receptor activation can result in induction of different pathways. To reach a better understanding of the role, interactions and expression of G-proteins a literature search was performed in order to list all the known heterotrimeric combinations and serotonin receptor complexes. Public databases were analysed to collect transcript and protein expression data relating to G-proteins in neural tissues. Only a very small number of heterotrimeric combinations and G-protein-receptor complexes out of the possible thousands suggested by expression data analysis have been examined experimentally. In addition this has mostly been obtained using insect, hamster, rat and, to a lesser extent, human cell lines. Besides highlighting which interactions have not been explored, our findings suggest additional possible interactions that should be examined based on our expression data analysis.

MicroRNA 135 is essential for chronic stress resiliency, antidepressant efficacy, and intact serotonergic activity

The link between dysregulated serotonergic activity and depression and anxiety disorders is well established, yet the molecular mechanisms underlying these psychopathologies are not fully understood. Here, we explore the role of microRNAs in regulating serotonergic (5HT) neuron activity. To this end, we determined the specific microRNA "fingerprint" of 5HT neurons and identified a strong microRNA-target interaction between microRNA 135 (miR135), and both serotonin transporter and serotonin receptor-1a transcripts. Intriguingly, miR135a levels were upregulated after administration of antidepressants. Genetically modified mouse models, expressing higher or lower levels of miR135, demonstrated major alterations in anxiety- and depression-like behaviors, 5HT levels, and behavioral response to antidepressant treatment. Finally, miR135a levels in blood and brain of depressed human patients were significantly lower. The current results suggest a potential role for miR135 as an endogenous antidepressant and provide a venue for potential treatment and insights into the onset, susceptibility, and heterogeneity of stress-related psychopathologies.

Insights into the influence of 5-HT2c aminoacidic variants with the inhibitory action of serotonin inverse agonists and antagonists

Specific modulation of serotonin 5-HT(2C) G protein-coupled receptors may be therapeutic for obesity and neuropsychiatric disorders. The different efficacy of drugs targeting these receptors are due to the presence of genetic variants in population and this variability is still hard to predict. Therefore, in order to administer the more suitable drug, taking into account patient genotype, it is necessary to know the molecular effects of its gene nucleotide variations. In this work, starting from an accurate 3D model of 5-HT(2C), we focus on the prediction of the possible effect of some single nucleotide polymorphisms (SNPs) producing amino acidic changes in proximity of the 5-HT(2C) ligand binding site. Particularly we chose a set of 5-HT(2C) inverse agonists and antagonists which have high inhibitory activity. After prediction of the structures of the receptor-ligand complexes using molecular docking tools, we performed full atom molecular dynamics simulations in explicit lipid bilayer monitoring the interactions between ligands and trans-membrane helices of the receptor, trying to infer relations with their biological activity. Serotonin, as the natural ligand was chosen as reference compound to advance a hypothesis able to explain the receptor inhibition mechanism. Indeed we observed a different behavior between the antagonists and inverse agonist with respect to serotonin or unbounded receptor, which could be responsible, even if not directly, of receptor's inactivation. Furthermore, we analyzed five aminoacidic variants of 5HT(2C) receptor observing alterations in the interactions between ligands and receptor which give rise to changes of free energy values for every complex considered.

Role of 5-HTTLPR polymorphism in the development of the inward/outward personality organization: a genetic association study

Reciprocity with primary caregivers affects subjects' adaptive abilities toward the construction of the most useful personal meaning organization (PMO) with respect to their developmental environment. Within cognitive theory the post-rationalist approach has outlined two basic categories of identity construction and of regulation of cognitive and emotional processes: the Outward and the Inward PMO. The presence of different, consistent clinical patterns in Inward and Outward subjects is paralleled by differences in cerebral activation during emotional tasks on fMRI and by different expression of some polymorphisms in serotonin pathways. Since several lines of evidence support a role for the 5-HTTLPR polymorphism in mediating individual susceptibility to environmental emotional stimuli, this study was conducted to investigate its influence in the development of the Inward/Outward PMO.

PMO was assessed and the 5-HTTLPR polymorphism investigated in 124 healthy subjects who were subdivided into an Inward (n = 52) and an Outward (n = 72) group.

Case-control comparisons of short allele (S) frequencies showed significant differences between Inwards and Outwards (p = 0.036, χ2 test; p = 0.026, exact test). Genotype frequencies were not significantly different although values slightly exceeded p≤0.05 (p = 0.056, χ2 test; p = 0.059, exact test). Analysis of the 5-HTTLPR genotypes according to the recessive inheritance model showed that the S/S genotype increased the likelihood of developing an Outward PMO (p = 0.0178, χ2 test; p = 0.0143, exact test; OR = 3.43, CI (95%) = 1.188–9.925). A logistic regression analysis confirmed the association between short allele and S/S genotypes with the Outward PMO also when gender and age were considered. However none of the differences remained significant after correction for multiple testing, even though using the recessive model they approach significance.

Overall our data seem to suggest a putative genetic basis for interindividual differences in PMO development.

Family-based study of HTR2A in suicide attempts: observed gene, gene × environment and parent-of-origin associations

While suicidal behavior is frequently accompanied by serotonergic system alterations, specific associations with genetic variation in the serotonin 2A receptor (HTR2A) gene have been inconsistent. Using a family-based study design of 660 offspring who have made a suicide attempt (SA) and both parents, we conducted an association and linkage analysis using single-nucleotide polymorphisms (SNPs) with extensive gene coverage, and included the study of parent-of-origin (POE) and gene-environment interaction (G × E), also using previously unstudied exposures. The main finding was a G × E between the exon 1 SNP rs6313 and exposure to cumulative types of lifetime stressful life events (SLEs), driven by overtransmission of CT and undertransmission of TT, both in relation to other genotypes. Further exploratory analysis revealed a significant POE in this G × E in female subjects, which followed a polar overdominant inheritance pattern. In addition, rs6310 and rs6305 were found to significantly associate with SA in the total sample. A G × E in female subjects (rs7322347 × physical assault in childhood/adolescence) confirmed features of a previously observed association with SA. Other potentially interesting nominally significant findings were observed, but like the G × E of rs7322347 did not pass a false-discovery rate cutoff. Taken together, this study found multiple associations of HTR2A SNPs on SA, with strongest statistical evidence for a G × E involving rs6313, and further suggested the importance of taking into account different inheritance patterns and G × Es with regard to HTR2A.

SpliceAid 2: a database of human splicing factors expression data and RNA target motifs

Splicing is the most frequently altered biological process by mutations within gene regions. Information for splicing is recognized by several factors that bind pre-mRNA sequence and, through coordinated interaction, yield mature transcripts. Some in silico methods have been developed to predict if a mutation leads to aberrant splicing patterns. We previously created SpliceAid tool that is able to minimize false positive predictions because it adopts strictly experimental RNA target motifs bound by splicing proteins in humans. In order to improve prediction accuracy and better understand the splicing outcome, the tissue specificity of each splicing regulatory factor has to be taken into account. Here, we have developed SpliceAid 2 by adding the expression data related to the splicing factors extracted from the main proteomic and transcriptomic databases, true 5' and 3' splice sites, polypyrimidine tracts, and branch point sequences. The new version collects 2,220 target sites of 62 human splicing proteins and their expression data in 320 tissues per cell. SpliceAid 2 can be useful to foresee the splicing pattern alteration, to guide the identification of the molecular effect due to the mutations and to understand the tissue-specific alternative splicing. SpliceAid 2 is freely accessible at www.introni.it/spliceaid.html.

Pilot study on HTR2A promoter polymorphism, -1438G/A (rs6311) and a nearby copy number variation showed association with onset and severity in early onset obsessive-compulsive disorder

A previous study showed that a single nucleotide polymorphism (SNP), -1438G/A (rs6311), found in the transcriptional control region of the gene that encodes the serotonin-receptor 2A (HTR2A) was associated with obsessive-compulsive disorder (OCD) in a sample of children and adolescents. In this study, we reanalyzed the association of this SNP with OCD in an enlarged population of 136 cases (55 previous + 81 new cases) and compared them to 106 newly recruited, healthy, age-matched controls. We also investigated whether this SNP or its copy number variations (CNV) was associated with OCD severity and age of onset. The CNV was analyzed in a DNA region located near rs6311. The results confirmed the association between the A-allele and early onset OCD in children and adolescents, with an odds ratio (OR) of 1.69 [95% CI (1.17, 2.46); p = 0.005]. Strikingly, we found that carriers of one copy (deletion) of the CNV were associated with a very early onset OCD (2.5 years earlier than the typical onset), and they had increased CY-BOCS scores (8.7 points higher compared to "normal" CNV and duplications); which is related to increased severity of OCD symptoms (p = 0.031; p = 0.004, respectively). Compared to the normal CNV and duplications, the association between the deletion and OCD showed an OR of 7.56 [95% CI (1.32, 142.84); p = 0.020]. These results pointed to the functional importance of this promoter region of HTR2A; it influenced the occurrence, the onset, and the severity of OCD.

Bioinformatic analyses to select phenotype affecting polymorphisms in HTR2C gene

OBJECTIVE

Single nucleotide polymorphisms (SNPs) in serotonin related genes influence mental disorders, responses to pharmacological and psychotherapeutic treatments. In planning association studies, researchers that want to investigate new SNPs have to select some among a large number of candidates. Our aim is to guide researchers in the selection of the most likely phenotype affecting polymorphisms. Here, we studied serotonin receptor 2C (HTR2C) SNPs because, till now, only relatively few of about 2000 are investigated.

METHODS

We used the most updated and assessed bioinformatic tools to predict which variations can give rise to biological effects among 2450 HTR2C SNPs.

RESULTS

We suggest 48 SNPs that are worth considering in future association studies in the field of psychiatry, psychology and pharmacogenomics. Moreover, our analyses point out the biological level probably affected, such as transcription, splicing, miRNA regulation and protein structure, thus allowing to suggest future molecular investigations.

CONCLUSIONS

Although few association studies are available in literature, their results are in agreement with our predictions, showing that our selection methods can help to guide future association studies.