RESUMEN
The 'structure assessment' web server is a one-stop shop for interactive evaluation and benchmarking of structural models of macromolecular complexes including proteins and nucleic acids. A user-friendly web dashboard links sequence with structure information and results from a variety of state-of-the-art tools, which facilitates the visual exploration and evaluation of structure models. The dashboard integrates stereochemistry information, secondary structure information, global and local model quality assessment of the tertiary structure of comparative protein models, as well as prediction of membrane location. In addition, a benchmarking mode is available where a model can be compared to a reference structure, providing easy access to scores that have been used in recent CASP experiments and CAMEO. The structure assessment web server is available at https://swissmodel.expasy.org/assess.
Asunto(s)
Internet , Modelos Moleculares , Programas Informáticos , Proteínas/química , Benchmarking , Conformación ProteicaRESUMEN
A PI3Kα-selective inhibitor has recently been approved for use in breast tumors harboring mutations in PIK3CA, the gene encoding p110α. Preclinical studies have suggested that the PI3K/AKT/mTOR signaling pathway influences stemness, a dedifferentiation-related cellular phenotype associated with aggressive cancer. However, to date, no direct evidence for such a correlation has been demonstrated in human tumors. In two independent human breast cancer cohorts, encompassing nearly 3,000 tumor samples, transcriptional footprint-based analysis uncovered a positive linear association between transcriptionally-inferred PI3K/AKT/mTOR signaling scores and stemness scores. Unexpectedly, stratification of tumors according to PIK3CA genotype revealed a "biphasic" relationship of mutant PIK3CA allele dosage with these scores. Relative to tumor samples without PIK3CA mutations, the presence of a single copy of a hotspot PIK3CA variant was associated with lower PI3K/AKT/mTOR signaling and stemness scores, whereas the presence of multiple copies of PIK3CA hotspot mutations correlated with higher PI3K/AKT/mTOR signaling and stemness scores. This observation was recapitulated in a human cell model of heterozygous and homozygous PIK3CAH1047R expression. Collectively, our analysis (1) provides evidence for a signaling strength-dependent PI3K-stemness relationship in human breast cancer; (2) supports evaluation of the potential benefit of patient stratification based on a combination of conventional PI3K pathway genetic information with transcriptomic indices of PI3K signaling activation.
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Neoplasias de la Mama/patología , Fosfatidilinositol 3-Quinasa Clase I/metabolismo , Células Madre Neoplásicas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Transducción de Señal , Serina-Treonina Quinasas TOR/metabolismo , Transcriptoma , Neoplasias de la Mama/metabolismo , Femenino , Genotipo , HumanosRESUMEN
CASP15 introduced a new category, ligand prediction, where participants were provided with a protein or nucleic acid sequence, SMILES line notation, and stoichiometry for ligands and tasked with generating computational models for the three-dimensional structure of the corresponding protein-ligand complex. These models were subsequently compared with experimental structures determined by x-ray crystallography or cryoEM. To assess these predictions, two novel scores were developed. The Binding-Site Superposed, Symmetry-Corrected Pose Root Mean Square Deviation (BiSyRMSD) evaluated the absolute deviations of the models from the experimental structures. At the same time, the Local Distance Difference Test for Protein-Ligand Interactions (lDDT-PLI) assessed the ability of models to reproduce the protein-ligand interactions in the experimental structures. The ligands evaluated in this challenge range from single-atom ions to large flexible organic molecules. More than 1800 submissions were evaluated for their ability to predict 23 different protein-ligand complexes. Overall, the best models could faithfully reproduce the geometries of more than half of the prediction targets. The ligands' size and flexibility were the primary factors influencing the predictions' quality. Small ions and organic molecules with limited flexibility were predicted with high fidelity, while reproducing the binding poses of larger, flexible ligands proved more challenging.
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Modelos Moleculares , Humanos , Ligandos , Sitios de Unión , Iones , Unión Proteica , Cristalografía por Rayos XRESUMEN
The prediction of protein-ligand complexes (PLC), using both experimental and predicted structures, is an active and important area of research, underscored by the inclusion of the Protein-Ligand Interaction category in the latest round of the Critical Assessment of Protein Structure Prediction experiment CASP15. The prediction task in CASP15 consisted of predicting both the three-dimensional structure of the receptor protein as well as the position and conformation of the ligand. This paper addresses the challenges and proposed solutions for devising automated benchmarking techniques for PLC prediction. The reliability of experimentally solved PLC as ground truth reference structures is assessed using various validation criteria. Similarity of PLC to previously released complexes are employed to judge PLC diversity and the difficulty of a PLC as a prediction target. We show that the commonly used PDBBind time-split test-set is inappropriate for comprehensive PLC evaluation, with state-of-the-art tools showing conflicting results on a more representative and high quality dataset constructed for benchmarking purposes. We also show that redocking on crystal structures is a much simpler task than docking into predicted protein models, demonstrated by the two PLC-prediction-specific scoring metrics created. Finally, we introduce a fully automated pipeline that predicts PLC and evaluates the accuracy of the protein structure, ligand pose, and protein-ligand interactions.
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Benchmarking , Proteínas , Sitios de Unión , Unión Proteica , Ligandos , Reproducibilidad de los Resultados , Simulación del Acoplamiento Molecular , Proteínas/química , Conformación ProteicaRESUMEN
Prediction categories in the Critical Assessment of Structure Prediction (CASP) experiments change with the need to address specific problems in structure modeling. In CASP15, four new prediction categories were introduced: RNA structure, ligand-protein complexes, accuracy of oligomeric structures and their interfaces, and ensembles of alternative conformations. This paper lists technical specifications for these categories and describes their integration in the CASP data management system.
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Biología Computacional , Proteínas , Conformación Proteica , Proteínas/química , Modelos Moleculares , LigandosRESUMEN
The Continuous Automated Model EvaluatiOn (CAMEO) platform complements the biennial CASP experiment by conducting fully automated blind evaluations of three-dimensional protein prediction servers based on the weekly prerelease of sequences of those structures, which are going to be published in the upcoming release of the Protein Data Bank. While in CASP14, significant success was observed in predicting the structures of individual protein chains with high accuracy, significant challenges remain in correctly predicting the structures of complexes. By implementing fully automated evaluation of predictions for protein-protein complexes, as well as for proteins in complex with ligands, peptides, nucleic acids, or proteins containing noncanonical amino acid residues, CAMEO will assist new developments in those challenging areas of active research.
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Biología Computacional/métodos , Bases de Datos de Proteínas , Conformación Proteica , Análisis de Secuencia de Proteína , Programas Informáticos , Benchmarking , Análisis por Conglomerados , Modelos Moleculares , Proteínas/química , Proteínas/genéticaRESUMEN
Lectins, and related receptors such as adhesins and toxins, are glycan-binding proteins from all origins that decipher the glycocode, i.e. the structural information encoded in the conformation of complex carbohydrates present on the surface of all cells. Lectins are still poorly classified and annotated, but since their functions are based on ligand recognition, their 3D-structures provide a solid foundation for characterization. UniLectin3D is a curated database that classifies lectins on origin and fold, with cross-links to literature, other databases in glycosciences and functional data such as known specificity. The database provides detailed information on lectins, their bound glycan ligands, and features their interactions using the Protein-Ligand Interaction Profiler (PLIP) server. Special care was devoted to the description of the bound glycan ligands with the use of simple graphical representation and numerical format for cross-linking to other databases in glycoscience. We conceived the design of the database architecture and the navigation tools to account for all organisms, as well as to search for oligosaccharide epitopes complexed within specified binding sites. UniLectin3D is accessible at https://www.unilectin.eu/unilectin3D.
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Biología Computacional/métodos , Bases de Datos de Proteínas , Conformación Proteica , Receptores de Superficie Celular/química , Sitios de Unión , Humanos , Internet , Lectinas/química , Lectinas/metabolismo , Ligandos , Modelos Moleculares , Polisacáridos/química , Polisacáridos/metabolismo , Unión Proteica , Receptores de Superficie Celular/metabolismoRESUMEN
Cell migration is a central biological process that requires fine coordination of molecular events in time and space. A deregulation of the migratory phenotype is also associated with pathological conditions including cancer where cell motility has a causal role in tumor spreading and metastasis formation. Thus cell migration is of critical and strategic importance across the complex disease spectrum as well as for the basic understanding of cell phenotype. Experimental studies of the migration of cells in monolayers are often conducted with 'wound healing' assays. Analysis of these assays has traditionally relied on how the wound area changes over time. However this method does not take into account the shape of the wound. Given the many options for creating a wound healing assay and the fact that wound shape invariably changes as cells migrate this is a significant flaw. Here we present a novel software package for analyzing concerted cell velocity in wound healing assays. Our method encompasses a wound detection algorithm based on cell confluency thresholding and employs a Bayesian approach in order to estimate concerted cell velocity with an associated likelihood. We have applied this method to study the effect of siRNA knockdown on the migration of a breast cancer cell line and demonstrate that cell velocity can track wound healing independently of wound shape and provides a more robust quantification with significantly higher signal to noise ratios than conventional analyses of wound area. The software presented here will enable other researchers in any field of cell biology to quantitatively analyze and track live cell migratory processes and is therefore expected to have a significant impact on the study of cell migration, including cancer relevant processes. Installation instructions, documentation and source code can be found at http://bowhead.lindinglab.science licensed under GPLv3.
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Neoplasias de la Mama/genética , Movimiento Celular , Regulación Neoplásica de la Expresión Génica , Algoritmos , Teorema de Bayes , Proteínas de Ciclo Celular/metabolismo , Línea Celular Tumoral , Biología Computacional , Femenino , Humanos , Proteínas Motoras Moleculares/metabolismo , Cadenas Pesadas de Miosina/metabolismo , Distribución Normal , Factor 3 de Transcripción de Unión a Octámeros/metabolismo , Fenotipo , Proteínas Serina-Treonina Quinasas/metabolismo , Proteínas Proto-Oncogénicas/metabolismo , ARN Interferente Pequeño/metabolismo , Relación Señal-Ruido , Factores de Tiempo , Cicatrización de Heridas , Quinasa Tipo Polo 1RESUMEN
BACKGROUND & AIMS: Algorithms for diagnosis of malignant common bile duct (CBD) stenoses are complex and lack accuracy. Malignant tumors secrete large numbers of extracellular vesicles (EVs) into surrounding fluids; EVs might therefore serve as biomarkers for diagnosis. We investigated whether concentrations of EVs in bile could discriminate malignant from nonmalignant CBD stenoses. METHODS: We collected bile and blood samples from 50 patients undergoing therapeutic endoscopic retrograde cholangiopancreatography at university hospitals in Europe for CBD stenosis of malignant (pancreatic cancer, n = 20 or cholangiocarcinoma, n = 5) or nonmalignant (chronic pancreatitis [CP], n = 15) origin. Ten patients with CBD obstruction due to biliary stones were included as controls. EV concentrations in samples were determined by nanoparticle tracking analyses. The discovery cohort comprised the first 10 patients with a diagnosis of pancreatic cancer, based on tissue analysis, and 10 consecutive controls. Using samples from these subjects, we identified a threshold concentration of bile EVs that could best discriminate between patients with pancreatic cancer from controls. We verified the diagnostic performance of bile EV concentration by analyzing samples from the 30 consecutive patients with a diagnosis of malignant (pancreatic cancer or cholangiocarcinoma, n = 15) or nonmalignant (CP, n = 15) CBD stenosis. Samples were compared using the Mann-Whitney test and nonparametric Spearman correlation analysis. Receiver operating characteristic area under the curve was used to determine diagnostic accuracy. RESULTS: In both cohorts, the median concentration of EVs was significantly higher in bile samples from patients with malignant CBD stenoses than controls or nonmalignant CBD stenoses (2.41 × 1015 vs 1.60 × 1014 nanoparticles/L in the discovery cohort; P < .0001 and 4.00 × 1015 vs 1.26 × 1014 nanoparticles/L in the verification cohort; P < .0001). A threshold of 9.46 × 1014 nanoparticles/L in bile best distinguished patients with malignant CBD from controls in the discovery cohort. In the verification cohort, this threshold discriminated malignant from nonmalignant CBD stenoses with 100% accuracy. Serum concentration of EVs distinguished patients with malignant vs patients with nonmalignant CBD stenoses with 63.3% diagnostic accuracy. CONCLUSIONS: Concentration of EVs in bile samples discriminates between patients with malignant vs nonmalignant CBD stenosis with 100% accuracy. Further studies are needed to confirm these findings. Clinical Trial registration no: ISRCTN66835592.
Asunto(s)
Neoplasias de los Conductos Biliares/complicaciones , Bilis , Colestasis/etiología , Vesículas Extracelulares , Neoplasias Pancreáticas/complicaciones , Adulto , Anciano , Anciano de 80 o más Años , Neoplasias de los Conductos Biliares/diagnóstico , Biomarcadores de Tumor/análisis , Colangiocarcinoma/complicaciones , Colangiocarcinoma/diagnóstico , Colestasis/diagnóstico , Europa (Continente) , Femenino , Cálculos Biliares/diagnóstico , Humanos , Masculino , Persona de Mediana Edad , Neoplasias Pancreáticas/diagnóstico , Pancreatitis Crónica/complicaciones , Pancreatitis Crónica/diagnóstico , Estudios Prospectivos , Curva ROCRESUMEN
Sweat is one of the less employed biofluids for discovery of markers in spite of its increased application in medicine for detection of drugs or for diagnostic of cystic fibrosis. In this research, human sweat was used as clinical sample to develop a screening tool for lung cancer, which is the carcinogenic disease with the highest mortality rate owing to the advanced stage at which it is usually detected. In this context, a method based on the metabolite analysis of sweat to discriminate between patients with lung cancer versus smokers as control individuals is proposed. The capability of the metabolites identified in sweat to discriminate between both groups of individuals was studied and, among them, a trisaccharide phosphate presented the best independent performance in terms of the specificity/sensitivity pair (80 and 72.7%, respectively). Additionally, two panels of metabolites were configured using the PanelomiX tool as an attempt to reduce false negatives (at least 80% specificity) and false positives (at least 80% sensitivity). The first panel (80% specificity and 69% sensitivity) was composed by suberic acid, a tetrahexose, and a trihexose, while the second panel (69% specificity and 80% sensitivity) included nonanedioic acid, a trihexose, and the monoglyceride MG(22:2). Thus, the combination of the five metabolites led to a single panel providing 80% specificity and 79% sensitivity, reducing the false positive and negative rates to almost 20%. The method was validated by estimation of within-day and between-days variability of the quantitative analysis of the five metabolites.
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Neoplasias Pulmonares/diagnóstico , Metabolómica/métodos , Sudor/química , Espectrometría de Masas en Tándem/métodos , Anciano , Cromatografía Liquida , Estudios de Cohortes , Femenino , Humanos , Neoplasias Pulmonares/química , Masculino , Persona de Mediana Edad , Análisis Multivariante , Curva ROCRESUMEN
Human African trypanosomiasis, or sleeping sickness, is a parasitic disease endemic in sub-Saharan Africa, transmitted to humans through the bite of a tsetse fly. The first or hemolymphatic stage of the disease is associated with presence of parasites in the bloodstream, lymphatic system, and body tissues. If patients are left untreated, parasites cross the blood-brain barrier and invade the cerebrospinal fluid and the brain parenchyma, giving rise to the second or meningoencephalitic stage. Stage determination is a crucial step in guiding the choice of treatment, as drugs used for S2 are potentially dangerous. Current staging methods, based on counting white blood cells and demonstrating trypanosomes in cerebrospinal fluid, lack specificity and/or sensitivity. In the present study, we used several proteomic strategies to discover new markers with potential for staging human African trypanosomiasis. Cerebrospinal fluid (CSF) samples were collected from patients infected with Trypanosoma brucei gambiense in the Democratic Republic of Congo. The stage was determined following the guidelines of the national control program. The proteome of the samples was analyzed by two-dimensional gel electrophoresis (n = 9), and by sixplex tandem mass tag (TMT) isobaric labeling (n = 6) quantitative mass spectrometry. Overall, 73 proteins were overexpressed in patients presenting the second stage of the disease. Two of these, osteopontin and ß-2-microglobulin, were confirmed to be potential markers for staging human African trypanosomiasis (HAT) by Western blot and ELISA. The two proteins significantly discriminated between S1 and S2 patients with high sensitivity (68% and 78%, respectively) for 100% specificity, and a combination of both improved the sensitivity to 91%. The levels of osteopontin and ß-2-microglobulin in CSF of S2 patients (µg/ml range), as well as the fold increased concentration in S2 compared with S1 (3.8 and 5.5 respectively) make the two markers good candidates for the development of a test for staging HAT patients.
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Biomarcadores/metabolismo , Osteopontina/metabolismo , Tripanosomiasis Africana/metabolismo , Microglobulina beta-2/metabolismo , Western Blotting , Electroforesis en Gel Bidimensional , Ensayo de Inmunoadsorción Enzimática , Femenino , Humanos , Masculino , Espectrometría de Masa por Ionización de Electrospray , Espectrometría de Masa por Láser de Matriz Asistida de Ionización Desorción , Tripanosomiasis Africana/patologíaRESUMEN
BACKGROUND: Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. RESULTS: With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. CONCLUSIONS: pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.
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Biología Computacional/métodos , Interpretación Estadística de Datos , Curva ROC , Programas Informáticos , Biomarcadores/análisis , Intervalos de Confianza , Humanos , Lenguajes de ProgramaciónRESUMEN
OBJECTIVES: A critical step before treatment of human African trypanosomiasis (HAT) is the correct staging of the disease. As late stage is established when trypanosomes cross the blood-brain barrier and invade the central nervous system, we hypothesized that matrix metalloproteinases and cell adhesion molecules could indicate, alone or in combination, the disease progression from the first to the second stage of HAT. METHODS: We measured the levels of MMP-2, MMP-9, ICAM-1, VCAM-1 and E-selectin in the cerebrospinal fluid (CSF) of 63 Trypanosoma brucei gambiense-infected patients (15 stage 1 and 48 stage 2). Staging was based on counting of white blood cells (WBC) and/or parasite detection in CSF. Concentrations were obtained either by ELISA or multiplex bead suspension assays, and results were compared with three known HAT staging markers (CXCL10, CXCL8 and H-FABP). RESULTS: ICAM-1 and MMP-9 accurately discriminated between stage 1 and stage 2 patients with HAT with 95% sensitivity (SE) for 100% specificity (SP), which was better than CXCL10 (93% SE for 100% SP), one of the most promising known markers. Combination of ICAM-1 and MMP-9 with H-FABP provided a panel that resulted in 100% of SE and SP for staging HAT. CONCLUSIONS: ICAM-1 and MMP-9, alone or in combination, appeared as powerful CSF staging markers of HAT. Final validation of all newly discovered staging markers on a large multi-centric cohort including both forms of the disease as well as patients with others infections should be performed.
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Molécula 1 de Adhesión Intercelular/líquido cefalorraquídeo , Metaloproteinasa 9 de la Matriz/líquido cefalorraquídeo , Tripanosomiasis Africana/diagnóstico , Adolescente , Adulto , Anciano , Biomarcadores/líquido cefalorraquídeo , Moléculas de Adhesión Celular/líquido cefalorraquídeo , Infecciones Protozoarias del Sistema Nervioso Central/líquido cefalorraquídeo , Quimiocinas/líquido cefalorraquídeo , Progresión de la Enfermedad , Métodos Epidemiológicos , Femenino , Humanos , Masculino , Persona de Mediana Edad , Trypanosoma brucei gambiense/aislamiento & purificación , Tripanosomiasis Africana/líquido cefalorraquídeo , Adulto JovenRESUMEN
It is well known that the development of drug resistance in cancer cells can lead to changes in cell morphology. Here, we describe the use of deep neural networks to analyze this relationship, demonstrating that complex cell morphologies can encode states of signaling networks and unravel cellular mechanisms hidden to conventional approaches. We perform high-content screening of 17 cancer cell lines, generating more than 500 billion data points from â¼850 million cells. We analyze these data using a deep learning model, resulting in the identification of a continuous 27-dimension space describing all of the observed cell morphologies. From its morphology alone, we could thus predict whether a cell was resistant to ErbB-family drugs, with an accuracy of 74%, and predict the potential mechanism of resistance, subsequently validating the role of MET and insulin-like growth factor 1 receptor (IGF1R) as drivers of cetuximab resistance in in vitro models of lung and head/neck cancer.
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Aprendizaje Profundo/normas , Resistencia a Antineoplásicos/fisiología , Receptores ErbB/metabolismo , Aprendizaje Automático/normas , Humanos , Redes Neurales de la Computación , Transducción de SeñalRESUMEN
Activating PIK3CA mutations are known 'drivers' of human cancer and developmental overgrowth syndromes. We recently demonstrated that the 'hotspot' PIK3CAH1047R variant exerts unexpected allele dose-dependent effects on stemness in human pluripotent stem cells (hPSCs). In this study, we combine high-depth transcriptomics, total proteomics and reverse-phase protein arrays to reveal potentially disease-related alterations in heterozygous cells, and to assess the contribution of activated TGFß signalling to the stemness phenotype of homozygous PIK3CAH1047R cells. We demonstrate signalling rewiring as a function of oncogenic PI3K signalling strength, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFß signalling. A significant transcriptomic signature of TGFß pathway activation in heterozygous PIK3CAH1047R was observed but was modest and was not associated with the stemness phenotype seen in homozygous mutants. Notably, the stemness gene expression in homozygous PIK3CAH1047R hPSCs was reversed by pharmacological inhibition of NODAL/TGFß signalling, but not by pharmacological PI3Kα pathway inhibition. Altogether, this provides the first in-depth analysis of PI3K signalling in hPSCs and directly links strong PI3K activation to developmental NODAL/TGFß signalling. This work illustrates the importance of allele dosage and expression when artificial systems are used to model human genetic disease caused by activating PIK3CA mutations. This article has an associated First Person interview with the first author of the paper.
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Fosfatidilinositol 3-Quinasas , Células Madre Pluripotentes , Fosfatidilinositol 3-Quinasa Clase I/genética , Fosfatidilinositol 3-Quinasa Clase I/metabolismo , Humanos , Mutación/genética , Fosfatidilinositol 3-Quinasas/metabolismo , Células Madre Pluripotentes/metabolismo , Transducción de Señal , Factor de Crecimiento Transformador betaRESUMEN
A large number of biomarkers have been discovered over the past few years using proteomics techniques. Unfortunately, most of them are neither specific nor sensitive enough to be translated into in vitro diagnostics and routine clinical practice. From this observation, the idea of combining several markers into panels to improve clinical performances has emerged. In this article, we present a discussion of the bioinformatics aspects of biomarker panels and the concomitant challenges, including high dimensionality and low patient number and reproducibility.
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Biomarcadores/análisis , Biología Computacional/métodos , Proteínas/metabolismo , Algoritmos , Humanos , Modelos EstadísticosRESUMEN
Proteomics has allowed the discovery and validation of a massive number of biomarkers. However most of them suffer from insufficient specificity and sensitivity and therefore didn't translate to clinical practice. Combining biomarkers with different properties into panels can be an efficient way to bypass these limitations and facilitate the translation of biomarkers into clinical practice.
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Biomarcadores , Biología Computacional/métodos , Proteómica , Programas Informáticos , Interpretación Estadística de Datos , Proteómica/métodos , Curva ROC , Interfaz Usuario-Computador , Navegador WebRESUMEN
Bioinformatics tools may assist scientists in all steps of a typical 2-DE gel analysis workflow, that is, from the description of the sample preparation protocols, going through the gel image analysis and protein identification, to the publication of Internet-ready 2-DE gel databases. This short communication highlights in a single and summarised view, this workflow and the current bioinformatics solutions developed by the Proteome Informatics Group at the Swiss Institute of Bioinformatics.
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Biología Computacional/instrumentación , Electroforesis en Gel Bidimensional , Revisión de la Investigación por ParesRESUMEN
The outcome after severe traumatic brain injury (TBI) is largely unfavorable, with approximately two thirds of patients suffering from severe disabilities or dying during the first 6 months. Existing predictive models displayed only limited utility for outcome prediction in individual patients. Time courses of heart-fatty acidic binding protein (H-FABP) and their association with outcome were investigated and compared with S100b. Forty-nine consecutive patients with severe TBI (sTBI; Head component of the Abbreviated Injury Scale [HAIS] >3) with mono and multiple trauma were enrolled in this study. Enzyme-linked immunosorbent assay measured blood concentrations of H-FABP and S100b at 6, 12, 24, and 48 h after TBI. Outcome measures were conscious state at 14 days (Glasgow Coma Scale), disability (Glasgow Outcome Scale Extended; GOSE), and mortality at 3 months. Univariate logistic regression analysis and receiver operating characteristic curves analysis were carried out. Maximal H-FABP and S100b concentrations were observed at 6 h after TBI (34.4±34.0 and 0.64±0.99 ng/mL, respectively). Patients with multi-trauma had significantly higher H-FABP concentrations at 24 and 48 h (22.6±25.6 and 12.4±18.2 ng/mL, respectively), compared to patients with mono trauma (6.9±5.1 and 3.7±4.2 ng/mL, respectively). In the first 48 h, H-FABP and S100b were inversely correlated with the GOSE at 3 months; H-FABP at 48 h predicted mortality with 75% sensitivity and 93% specificity. Early blood levels of H-FABP after sTBI have prognostic significance for survival and disability.