Andigoni Malousi

Targeted KRAS Mutation Assessment on Patient Tumor Histologic Material in Real Time Diagnostics

Background Testing for tumor specific mutations on routine formalin-fixed paraffin-embedded (FFPE) tissues may predict response to treatment in Medical Oncology and has already entered diagnostics, with KRAS mutation assessment as a paradigm. The highly sensitive real time PCR (Q-PCR) methods developed for this purpose are usually standardized under optimal template conditions. In routine diagnostics, however, suboptimal templates pose the challenge. Herein, we addressed the applicability of sequencing and two Q-PCR methods on prospectively assessed diagnostic cases for KRAS mutations. Methodology/Principal Findings Tumor FFPE-DNA from 135 diagnostic and 75 low-quality control samples was obtained upon macrodissection, tested for fragmentation and assessed for KRAS mutations with dideoxy-sequencing and with two Q-PCR methods (Taqman-minor-groove-binder [TMGB] probes and DxS-KRAS-IVD). Samples with relatively well preserved DNA could be accurately analyzed with sequencing, while Q-PCR methods yielded informative results even in cases with very fragmented DNA (p<0.0001) with 100% sensitivity and specificity vs each other. However, Q-PCR efficiency (Ct values) also depended on DNA-fragmentation (p<0.0001). Q-PCR methods were sensitive to detect ≤1% mutant cells, provided that samples yielded cycle thresholds (Ct) <29, but this condition was met in only 38.5% of diagnostic samples. In comparison, FFPE samples (>99%) could accurately be analyzed at a sensitivity level of 10% (external validation of TMGB results). DNA quality and tumor cell content were the main reasons for discrepant sequencing/Q-PCR results (1.5%). Conclusions/Significance Diagnostic targeted mutation assessment on FFPE-DNA is very efficient with Q-PCR methods in comparison to dideoxy-sequencing. However, DNA fragmentation/amplification capacity and tumor DNA content must be considered for the interpretation of Q-PCR results in order to provide accurate information for clinical decision making.

Human epigenome data reveal increased CpG methylation in alternatively spliced sites and putative exonic splicing enhancers.

The role of gene body methylation, which represents a major part of methylation in DNA, remains mostly unknown. Evidence based on the CpG distribution associates its presence with nucleosome positioning and alternative splicing. Recently, it was also shown that cytosine methylation influences splicing. However, to date, there is no methylation-based data on the association of methylation with alternative splicing and the distribution in exonic splicing enhancers (ESEs). We presently report that, based on the computational analysis of the Human Epigenome Project data, CpG hypermethylation (>80%) is frequent in alternatively spliced sites (particularly in noncanonical) but not in alternate promoters. The methylation frequency increases in sequences containing multiple putative ESEs. However, significant differences in the extent of methylation are observed among different ESEs. Specifically, moderate levels of methylation, ranging from 20% to 80%, are frequent in SRp55-binding elements, which are associated with response to extracellular conditions, but not in SF2/ASF, primarily responsible for alternative splicing, or in CpG islands. Finally, methylation is more frequent in the presence of AT repeats and CpGs separated by 10 nucleotides and lower in adjacent CpGs, probably indicating its dependence on helical formations and on the presence of nucleosome positioning-related sequences. In conclusion, our results show the regulation of methylation in ESEs and support its involvement in alternative splicing.

A Personalized Framework for Medication Treatment Management in Chronic Care

The ongoing efforts toward continuity of care and the recent advances in information and communication technologies have led to a number of successful personal health systems for the management of chronic care. These systems are mostly focused on monitoring efficiently the patients medical status at home. This paper aims at extending home care services delivery by introducing a novel framework for monitoring the patients condition and safety with respect to the medication treatment administered. For this purpose, considering a body area network (BAN) with advanced sensors and a mobile base unit as the central communication hub from the one side, and the clinical environment from the other side, an architecture was developed, offering monitoring patterns definition for the detection of possible adverse drug events and the assessment of medication response, supported by mechanisms enabling bidirectional communication between the BAN and the clinical site. Particular emphasis was given on communication and information flow aspects that have been addressed by defining/adopting appropriate formal information structures as well as the service-oriented architecture paradigm. The proposed framework is illustrated via an application scenario concerning hypertension management.

Intronic CpG content and alternative splicing in human genes containing a single cassette exon

Clinical data provide evidence for the association of missplicing with methyl-binding protein mutations and inhibition of methylation. In this study, we analyzed a 373 human gene database containing a single alternatively spliced exon (cassette) and 1,039 constitutive introns, and showed that CpG frequencies are higher in alternative compared to constitutive introns, particularly in donors preceding cassette exons (p

Synonymous Polymorphisms at Splicing Regulatory Sites are Associated with CpGs in Neurodegenerative Disease-Related Genes

Neuronal plasticity is associated with alternative splicing and epigenetic modulation. Recent evidence reveals the association of cytosine methylation with alternative splicing and splicing regulatory mechanisms. Single nucleotide polymorphisms (SNPs) are generally less frequent in conserved coding regions and probably in splice sites, compared to non-coding regions. CpG polymorphisms in coding regions and splice sites and their association with splicing regulatory elements have not been investigated till presently. We currently analyzed the CpG variability in 28 genes (361 constitutive and 105 alternative exons and the corresponding splice sites) associated with neurodegenerative diseases (ND). CpG polymorphisms in the splice sites of these genes are particularly frequent when compared to those at AG sequences. Moreover, in both constitutive and alternative exons, polymorphisms in CpGs are more frequent than in AG, GT sequences. On the contrary, in the polypyrimidine acceptor sequence C/T conservation is prominent indicating that in this locus the sequence of cytosines and thymines is preserved. Bioinformatic analysis of the splicing-associated regulatory elements in these exons and splice sites reveals that 18 out of a total of 39 SNPs which could strongly affect splicing (>1.5 score difference) contain CpG sequences. Cytosines are considerably more frequent and variable than expected at the position preceding the GT splice donors, while sites of epigenetic modification are absent from acceptors. The high CpG frequency in polymorphic splicing-associated sites implicates the involvement of epigenetic mechanisms in splicing selection decisions regulated by these sites, and indicates the complexity of genetic studies involving these, tentatively critical, polymorphisms in ND.

Li-Fraumeni and Li-Fraumeni-like syndrome mutations in p53 are associated with exonic methylation and splicing regulatory elements.

Mutations in codon 133 of p53, which cause the loss of the Δ133 isoform(s) expression, are very frequent in the Li–Fraumeni (LF) and Li–Fraumeni‐like (LFL) syndromes. In sporadic cancers, silent p53 mutations are correlated with exonic splicing enhancers (ESEs) and exonic methylated sites. The present study shows that mutations in splice sites are also very frequent in LF/LFL syndromes, while missense mutations are less common compared to other familial or sporadic cancers (P = 0 in both cases). Furthermore, it is shown that the codons at which LF/LFL germline missense mutations occur, correlate with CpG‐containing ESEs (r = 0.181, P = 0.014) which are all methylated in p53. While both silent and LF/LFL missense mutations correlate with SC35 motifs, only the latter are associated with SRp55. On the contrary, only silent mutations in sporadic cancers correlate with SF2/ASF motifs in p53. Moreover, 12.1% of LF/LFL missense mutations involve the formation of potential splice sites of considerable splicing scores. Finally, mutations that are not at, or adjacent to CpGs (±1 codon, 34% of all LF/LFL mutated sites), introduce considerable changes of the ESE scores (>1.3 score change). The above data verify that LF/LFL missense mutations probably result also in splicing deregulation, in addition to any changes of the protein function and are mostly associated with alterations of the exonic methylation landscape. Some of the ESEs affected in LF/LFL syndromes are also genetically unstable in sporadic cancers but non‐CpG cytosine instability, which is predominantly associated with specific ESEs, is only common in sporadic cancers. Mol. Carcinog.

SpliceIT: A hybrid method for splice signal identification based on probabilistic and biological inference

Splice sites define the boundaries of exonic regions and dictate protein synthesis and function. The splicing mechanism involves complex interactions among positional and compositional features of different lengths. Computational modeling of the underlying constructive information is especially challenging, in order to decipher splicing-inducing elements and alternative splicing factors. SpliceIT (Splice Identification Technique) introduces a hybrid method for splice site prediction that couples probabilistic modeling with discriminative computational or experimental features inferred from published studies in two subsequent classification steps. The first step is undertaken by a Gaussian support vector machine (SVM) trained on the probabilistic profile that is extracted using two alternative position-dependent feature selection methods. In the second step, the extracted predictions are combined with known species-specific regulatory elements, in order to induce a tree-based modeling. The performance evaluation on human and Arabidopsis thaliana splice site datasets shows that SpliceIT is highly accurate compared to current state-of-the-art predictors in terms of the maximum sensitivity, specificity tradeoff without compromising space complexity and in a time-effective way. The source code and supplementary material are available at: http://www.med.auth.gr/research/spliceit/.

GREMET: An integrative tool for the prediction of mutation effects on gene regulation

The identification of thousands of mutations yearly has put new challenges to researchers who are interested in fast and effective annotation as well as the prediction of potential implications to the gene regulation mechanisms. This work presents an integrative tool, called GREMET, for the prediction of alterations in gene splicing regulation inferred by mutations of the human genome. GREMET supports the characterization of mutations either single-point or indels with respect to their effect on the splicing potential of the neighboring sequences and the binding strength of auxiliary cis-acting splicing enhancers. In addition, GREMET identifies possible consequences of mutations on the DNA methylation through the disruption or creation of CpG sequences. Besides locus-specific mutations, GREMET performs the analyses on newly identified mutations and provides an easy-to-use Web interface helping researchers to save time in routine mutation analyses. GREMET is freely accessible at: http://kedip.med.auth.gr/biotools/gremet/.

Engineering agent-mediated integration of bioinformatics analysis tools

The availability of massive amounts of biological data, distributed in various data sources, in conjunction with the need to understand the underlying biological processes of life, has prompted the development of a wide range of data analysis tools, most of which are publicly available through the Internet. However, due to the heterogeneity and complexity of the domain, performing a specific analysis by combining tools is complicated. In this paper, we argue that the software agent metaphor constitutes a flexible approach that efficiently addresses integration of bioinformatics analysis tools and dynamic composition-execution of data analysis workflows. To substantiate this assertion, a scalable engineering methodology is presented, aiming to address horizontal and/or vertical integration, through functionally related multiagent systems. The proposed approach is mediator-oriented, relying primarily on agent coordination strategies and semantic domain descriptions. The applicability and virtue of the proposed systems are illustrated through test cases addressing integration of computational gene finders.

Performing Ontology-Driven Gene Prediction Queries in a Multi-agent Environment

Gene prediction is one of the most challenging problems in Computational Biology. Motivated by the strengths and limitations of the currently available Web-based gene predictors, a Knowledge Base was constructed that conceptualizes the functionalities and requirements of each tool, following an ontology-based approach. According to this classification, a Multi-Agent System was developed that exploits the potential of the underlying semantic representation, in order to provide transparent and efficient query services based on user-implied criteria. Given a query, a broker agent searches for matches in the Knowledge Base, and coordinates correspondingly the submission/retrieval tasks via a set of wrapper agents. This approach is intended to enable efficient query processing in a resource-sharing environment by embodying a meta-search mechanism that maps queries to the appropriate gene prediction tools and obtains the overall prediction outcome.