A systems biology approach to investigate the mechanism of action of trabectedin in a model of myelomonocytic leukemia.

This study was designed to investigate the mode of action of trabectedin in myelomonocytic leukemia cells by applying systems biology approaches to mine gene expression profiling data and pharmacological assessment of the cellular effects. Significant enrichment was found in regulons of target genes inferred for specific transcription factors, among which MAFB was the most upregulated after treatment and was central in the transcriptional network likely to be relevant for the specific therapeutic effects of trabectedin against myelomonocytic cells. Using the Connectivity Map, similarity among transcriptional signatures elicited by treatment with different compounds was investigated, showing a high degree of similarity between transcriptional signatures of trabectedin and those of the topoisomerase I inhibitor, irinotecan, and an anti-dopaminergic antagonist, thioridazine. The study highlights the potential importance of systems biology approaches to generate new hypotheses that are experimentally testable to define the specificity of the mechanism of action of drugs.

Network-guided modeling allows tumor-type independent prediction of sensitivity to all-trans-retinoic acid.

Background: All-trans-retinoic acid (ATRA) is a differentiating agent used in the treatment of acute-promyelocytic-leukemia (APL) and it is under-exploited in other malignancies despite its low systemic toxicity. A rational/personalized use of ATRA requires the development of predictive tools allowing identification of sensitive cancer types and responsive individuals. Materials and methods: RNA-sequencing data for 10 080 patients and 33 different tumor types were derived from the TCGA and Leucegene datasets and completely re-processed. The study was carried out using machine learning methods and network analysis. Results: We profiled a large panel of breast-cancer cell-lines for in vitro sensitivity to ATRA and exploited the associated basal gene-expression data to initially generate a model predicting ATRA-sensitivity in this disease. Starting from these results and using a network-guided approach, we developed a generalized model (ATRA-21) whose validity extends to tumor types other than breast cancer. ATRA-21 predictions correlate with experimentally determined sensitivity in a large panel of cell-lines representative of numerous tumor types. In patients, ATRA-21 correctly identifies APL as the most sensitive acute-myelogenous-leukemia subtype and indicates that uveal-melanoma and low-grade glioma are top-ranking diseases as for average predicted responsiveness to ATRA. There is a consistent number of tumor types for which higher ATRA-21 predictions are associated with better outcomes. Conclusions: In summary, we generated a tumor-type independent ATRA-sensitivity predictor which consists of a restricted number of genes and has the potential to be applied in the clinics. Identification of the tumor types that are likely to be generally sensitive to the action of ATRA paves the way to the design of clinical studies in the context of these diseases. In addition, ATRA-21 may represent an important diagnostic tool for the selection of individual patients who may benefit from ATRA-based therapeutic strategies also in tumors characterized by lower average sensitivity.

Association between SNAP-25 gene polymorphisms and cognition in autism: functional consequences and potential therapeutic strategies.

Synaptosomal-associated protein of 25 kDa (SNAP-25) is involved in different neuropsychiatric disorders, including schizophrenia and attention-deficit/hyperactivity disorder. Consistently, SNAP-25 polymorphisms in humans are associated with hyperactivity and/or with low cognitive scores. We analysed five SNAP-25 gene polymorphisms (rs363050, rs363039, rs363043, rs3746544 and rs1051312) in 46 autistic children trying to correlate them with Childhood Autism Rating Scale and electroencephalogram (EEG) abnormalities. The functional effects of rs363050 single-nucleotide polymorphism (SNP) on the gene transcriptional activity, by means of the luciferase reporter gene, were evaluated. To investigate the functional consequences that SNAP-25 reduction may have in children, the behaviour and EEG of SNAP-25(+/-) adolescent mice (SNAP-25(+/+)) were studied. Significant association of SNAP-25 polymorphism with decreasing cognitive scores was observed. Analysis of transcriptional activity revealed that SNP rs363050 encompasses a regulatory element, leading to protein expression decrease. Reduction of SNAP-25 levels in adolescent mice was associated with hyperactivity, cognitive and social impairment and an abnormal EEG, characterized by the occurrence of frequent spikes. Both EEG abnormalities and behavioural deficits were rescued by repeated exposure for 21 days to sodium salt valproate (VLP). A partial recovery of SNAP-25 expression content in SNAP-25(+/-) hippocampi was also observed by means of western blotting. A reduced expression of SNAP-25 is responsible for the cognitive deficits in children affected by autism spectrum disorders, as presumably occurring in the presence of rs363050(G) allele, and for behavioural and EEG alterations in adolescent mice. VLP treatment could result in novel therapeutic strategies.

MassUntangler: a novel alignment tool for label-free liquid chromatography-mass spectrometry proteomic data.

Liquid chromatography-mass spectrometry (LC-MS) has become an important analytical tool for quantitative proteomics and biomarker discovery. In the label-free differential LC-MS approach computational methods are required for an accurate alignment of peaks extrapolated from the experimental raw data accounting for retention time and m/z signals intensity, which are strongly affected by sample matrix and instrumental performance. A novel procedure "MassUntangler" for pairwise alignment has been developed, relying on a pattern-based matching algorithm integrated with filtering algorithms in a multi-step approach. The procedure has been optimized employing a two-step approach. Firstly, low-complexity LC-MS data derived from the enzymatic digestion of two standard proteins have been analyzed. Then, the algorithm's performance has been evaluated by comparing the results with other achieved using state-of-the-art alignment tools. In the second step, our algorithm has been used for the alignment of high-complexity LC-MS data consisting of peptides obtained by an Escherichia coli lysate available from a public repository previously used for the comparison of other alignment tools. MassUntangler gave excellent results in terms of precision scores (from 80% to 93%) and recall scores (from 68% to 89%), showing performances similar and even better than the previous developed tools. Considering the mass spectrometry sensitivity and accuracy, this approach allows the identification and quantification of peptides present in a biological sample at femtomole level with high confidence. The procedure's capability of aligning LC-MS data previously corrected for distortion in retention time has been studied through a hybrid approach, in which MassUntangler was interfaced with the OpenMS TOPP tool MapAligner. The hybrid aligner yielded better results, showing that an integration of different bioinformatic approaches for accurate label-free LC-MS data alignment should be used.

Application of the Ramanujan Fourier Transform for the analysis of secondary structure content in amino acid sequences.

OBJECTIVE: A novel method is presented for the investigation of protein properties of sequences using Ramanujan Fourier Transform (RFT). METHODS: The new methodology involves the preprocessing of protein sequence data by numerically encoding it and then applying the RFT. The RFT is based on projecting the obtained numerical series on a set of basis functions constituted by Ramanujan sums (RS). In RS components, periodicities of finite integer length, rather than frequency, (as in classical harmonic analysis) are considered. RESULTS: The potential of the new approach is documented by a few examples in the analysis of hydrophobic profiles of proteins in two classes including abundance of alpha-helices (group A) or beta-strands (group B). Different patterns are provided as evidence. CONCLUSIONS: RFT can be used to characterize the structural properties of proteins and integrate complementary information provided by other signal processing transforms.

Hydrophobicity analysis of protein primary structures to identify helical regions.

OBJECTIVES: A wavelet based approach for the hydrophobicity analysis of protein primary structures is proposed to predict the presence of alpha helices in the secondary structure. METHODS: The information about hydropathy profile periodicity content together with a score of probability of occurrence of a single amino acid allows the localization of alpha helices. RESULTS: The accuracy is comparable to other consolidated predictors based on different techniques (i.e.: neural networks, hidden markov models). CONCLUSION: This method is particularly suitable to capture the amphiphilic character of the helical structures.

Single sweep analysis of event related auditory potentials for the monitoring of sedation in cardiac surgery patients.

Event-related potentials (ERPs) from the auditory system were investigated in 28 post-operative cardiac patients in order to assess their relevance in the monitoring of patient sedation level. Midazolam (17 patients) and propofol (11 patients) were the sedative agents used. The auditory ERP components of N100 (HAB100) and mismatch negativity (MMN) were considered. A single sweep method based on the AutoRegressive with eXogenous input (ARX) model, which is able to enhance the evoked responses to each single stimulus, was used to process each sweep and to compute traditional parameters on a sweep-by-sweep basis. Differences in the measured parameters were related to variations in the patient sedation levels classified through Ramsay score. Significant differences (P<0.05) in both MMN and HAB100 parameters were found between light sedation (LS) and deep sedation (DS) levels.