Biomedical subjects

Andreas Hildebrandt

Publications and source records attributed to Andreas Hildebrandt.

6 recordsLinked to original sources

PubMed2006

A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors.

BACKGROUND: The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinformatics. Our approach uses statistical learning techniques applied to multiple antigen tumor antigen markers utilizing the immune system as a very sensitive marker of molecular pathological processes. For validation purposes we choose the intracranial meningioma tumors as model system since they occur very frequently, are mostly benign, and are genetically stable. RESULTS: A total of 183 blood samples from 93 meningioma patients (WHO stages I-III) and 90 healthy controls were screened for seroreactivity with a set of 57 meningioma-associated antigens. We tested several established statistical learning methods on the resulting reactivity patterns using 10-fold cross validation. The best performance was achieved by Naïve Bayes Classifiers. With this classification method, our framework, called Minimally Invasive Multiple Marker (MIMM) approach, yielded a specificity of 96.2%, a sensitivity of 84.5%, and an accuracy of 90.3%, the respective area under the ROC curve was 0.957. Detailed analysis revealed that prediction performs particularly well on low-grade (WHO I) tumors, consistent with our goal of early stage tumor detection. For these tumors the best classification result with a specificity of 97.5%, a sensitivity of 91.3%, an accuracy of 95.6%, and an area under the ROC curve of 0.971 was achieved using a set of 12 antigen markers only. This antigen set was detected by a subset selection method based on Mutual Information. Remarkably, our study proves that the inclusion of non-specific antigens, detected not only in tumor but also in normal sera, increases the performance significantly, since non-specific antigens contribute additional diagnostic information. CONCLUSION: Our approach offers the possibility to screen members of risk groups as a matter of routine such that tumors hopefully can be diagnosed immediately after their genesis. The early detection will finally result in a higher cure- and lower morbidity-rate.

Algorithms↗

PubMed2006

BALLView: an object-oriented molecular visualization and modeling framework.

We present BALLView, an extensible tool for visualizing and modeling bio-molecular structures. It provides a variety of different models for bio-molecular visualization, e.g. ball-and-stick models, molecular surfaces, or ribbon models. In contrast to most existing visualization tools, BALLView also offers rich functionality for molecular modeling and simulation, including molecular mechanics methods (AMBER and CHARMM force fields), continuum electrostatics methods employing a Finite-Difference Poisson Boltzmann solver, and secondary structure calculation. Results of these computations can be exported as publication quality images or as movies. Even unexperienced users have direct access to this functionality through an intuitive graphical user interface, which makes BALLView particularly useful for teaching. For more advanced users, BALLView is extensible in different ways. Owing to its framework design, extension on the level of C per thousand+ per thousand per thousand+ code is very convenient. In addition, an interface to the scripting language Python allows the interactive rapid prototyping of new methods. BALLView is portable and runs on all major platforms (Windows, MacOS X, Linux, most Unix flavors). It is available free of charge under the GNU Public License (GPL) from our website http://www.ballview.org.

Computer Graphics↗

PubMed2006

Glycosylation patterns of human chorionic gonadotropin revealed by liquid chromatography-mass spectrometry and bioinformatics.

Due to their extensive structural heterogeneity, the elucidation of glycosylation patterns in glycoproteins such as the subunits of human chorionic gonadotropin (hCG), hCG-alpha, and hCG-beta, remains one of the most challenging problems in the proteomic analysis of post-translational modifications. In consequence, glycosylation is usually studied after decomposition of the intact proteins to the proteolytic peptide level. However, by this approach all information about the combination of the different glycopeptides in the intact protein is lost. In this study we have, therefore, attempted to combine the results of glycan identification after tryptic digestion with molecular mass measurements on the native starting material of the new first WHO Reference Reagents (RR) for hCG-alpha (99/720) and hCG-beta (99/650). Despite the extremely high number of possible combinations of the glycans identified in the tryptic peptides by HPLC-MS (>1000 for hCG-alpha and >10 000 for hCG-beta), the mass spectra of intact hCG-alpha and hCG-beta revealed only a limited number of glycoforms present in hCG preparations from pools of pregnancy urines. Peak annotations for hCG-alpha were performed with the help of a bioinformatic algorithm that generated a database containing all possible modifications of the proteins, including modifications possibly introduced during sample preparation such as oxidation or truncation, for subsequent searches for combinations fitting the mass difference between the polypeptide backbone and the measured molecular masses. Fourteen different glycoforms of hCG-alpha, containing biantennary, partly sialylized hybrid-type glycans, including methionine-oxidized and N-terminally truncated forms, were identified. Mass spectra of high quality were also obtained for hCG-beta, however, a database search mass accuracy of +/-5 Da was insufficient to unambiguously assign the possible combinations of post-translational modifications. In summary, mass spectrometric fingerprints of intact molecules were shown to be highly useful for the characterization of glycosylation patterns of different hCG preparations such as the new first WHO RR for immunoassays and could be the first step in establishing biophysical reference methods for hCG and related molecules.

Chorionic Gonadotropin↗

PubMed2006

High-accuracy peak picking of proteomics data using wavelet techniques.

A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented. It is independent of the underlying machine or ionization method, and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detecting the mass peaks in the wavelet-transformed signal before a given asymmetric peak function is fitted to the raw data. In an optional third stage, the resulting fit can be further improved using techniques from nonlinear optimization. In contrast to currently established techniques (e.g. SNAP, Apex) our algorithm is able to separate overlapping peaks of multiply charged peptides in ESI-MS data of low resolution. Its improved accuracy with respect to peak positions makes it a valuable preprocessing method for MS-based identification and quantification experiments. The method has been validated on a number of different annotated test cases, where it compares favorably in both runtime and accuracy with currently established techniques. An implementation of the algorithm is freely available in our open source framework OpenMS.

Algorithms↗

PubMed2005

BALLView: a tool for research and education in molecular modeling.

We present BALLView, a molecular viewer and modeling tool. It combines state-of-the-art visualization capabilities with powerful modeling functionality including implementations of force field methods and continuum electrostatics models. BALLView is a versatile and extensible tool for research in structural bioinformatics and molecular modeling. Furthermore, the convenient and intuitive graphical user interface offers novice users direct access to the full functionality, rendering it ideal for teaching. Through an interface to the object-oriented scripting language Python it is easily extensible.

Computer Graphics↗

PubMed2005

Complex humoral immune response against a benign tumor: frequent antibody response against specific antigens as diagnostic targets.

There are numerous studies on the immune response against malignant human tumors. This study was aimed to address the complexity and specificity of humoral immune response against a benign human tumor. We assembled a panel of 62 meningioma-expressed antigens that show reactivity with serum antibodies of meningioma patients, including 41 previously uncharacterized antigens by screening of a fetal brain expression library. We tested the panel for reactivity with 48 sera, including sera of patients with common-type, atypical, and anaplastic meningioma, respectively. Meningioma sera detected an average of 14.6 antigens per serum and normal sera an average of 7.8 antigens per serum (P = 0.0001). We found a decline of seroreactivity with malignancy with a statistical significant difference between common-type and anaplastic meningioma (P < 0.05). We detected 17 antigens exclusively with patient sera, including 12 sera that were reactive against KIAA1344, 9 against natural killer tumor recognition (NKTR), and 7 against SRY (sex determining region Y)-box2 (SOX2). More than 80% of meningioma patients had antibodies against at least one of the antigens KIAA1344, SC65, SOX2, and C6orf153. Our results show a highly complex but specific humoral immune response against a benign tumor with a distinct serum reactivity pattern and a decline of complexity with malignancy. The frequent antibody response against specific antigens offers new diagnostic and therapeutic targets for meningioma. We developed a statistical learning method to differentiate sera of meningioma patients from sera of healthy donors.

Antibodies, Neoplasm↗