Hans-Peter Lenhof

Bio: Hans-Peter Lenhof is an academic researcher from Saarland University. The author has contributed to research in topics: Macromolecular docking & Autoantibody. The author has an hindex of 44, co-authored 164 publications receiving 6046 citations. Previous affiliations of Hans-Peter Lenhof include Max Planck Society.

A different view on DNA amplifications indicates frequent, highly complex, and stable amplicons on 12q13-21 in glioma.

Abstract: To further understand the biological significance of amplifications for glioma development and recurrencies, we characterized amplicon frequency and size in low-grade glioma and amplicon stability in vivo in recurring glioblastoma. We developed a 12q13-21 amplicon-specific genomic microarray and a bioinformatics amplification prediction tool to analyze amplicon frequency, size, and maintenance in 40 glioma samples including 16 glioblastoma, 10 anaplastic astrocytoma, 7 astrocytoma WHO grade 2, and 7 pilocytic astrocytoma. Whereas previous studies reported two amplified subregions, we found a more complex situation with many amplified subregions. Analyzing 40 glioma, we found that all analyzed glioblastoma and the majority of pilocytic astrocytoma, grade 2 astrocytoma, and anaplastic astrocytoma showed at least one amplified subregion, indicating a much higher amplification frequency than previously suggested. Amplifications in low-grade glioma were smaller in size and displayed clearly different distribution patterns than amplifications in glioblastoma. One glioblastoma and its recurrencies revealed an amplified subregion of 5 Mb that was stable for 6 years. Expression analysis of the amplified region revealed 10 overexpressed genes (i.e., KUB3, CTDSP2, CDK4, OS-9, DCTN2, RAB3IP, FRS2, GAS41, MDM2, and RAP1B) that were consistently overexpressed in all cases that carried this amplification. Our data indicate that amplifications on 12q13-21 (a) are more frequent than previously thought and present in low-grade tumors and (b) are maintained as extended regions over long periods of time.

Identification of lung cancer with high sensitivity and specificity by blood testing.

Abstract: Background: Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. Methods: We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. Results: The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%. Conclusion: We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.

Multiple sequence alignment with arbitrary gap costs: computing an optimal solution using polyhedral combinatorics.

Abstract: Multiple sequence alignment is one of the dominant problems in computational molecular biology. Numerous scoring functions and methods have been proposed, most of which result in NP-hard problems. In this paper we propose for the first time a general formulation for multiple alignment with arbitrary gap-costs based on an integer linear program (ILP). In addition we describe a branch-and-cut algorithm to effectively solve the ILP to optimality. We evaluate the performances of our approach in terms of running time and quality of the alignments using the BAliBase database of reference alignments. The results show that our implementation ranks amongst the best programs developed so far.

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

Abstract: 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.

Toward an early diagnosis of lung cancer: an autoantibody signature for squamous cell lung carcinoma.

Abstract: Serum-based diagnosis offers the prospect of early lung carcinoma detection and of differentiation between benign and malignant nodules identified by CT. One major challenge toward a future blood-based diagnostic consists in showing that seroreactivity patterns allow for discriminating lung cancer patients not only from normal controls but also from patients with non-tumor lung pathologies. We addressed this question for squamous cell lung cancer, one of the most common lung tumor types. Using a panel of 82 phage-peptide clones, which express potential autoantigens, we performed serological spot assay. We screened 108 sera, including 39 sera from squamous cell lung cancer patients, 29 sera from patients with other non-tumor lung pathologies, and 40 sera from volunteers without known disease. To classify the serum groups, we employed the standard Naive Bayesian method combined with a subset selection approach. We were able to separate squamous cell lung carcinoma and normal sera with an accuracy of 93%. Low-grade squamous cell lung carcinoma were separated from normal sera with an accuracy of 92.9%. We were able to distinguish squamous cell lung carcinoma from non-tumor lung pathologies with an accuracy of 83%. Three phage-peptide clones with sequence homology to ROCK1, PRKCB1 and KIAA0376 reacted with more than 15% of the cancer sera, but neither with normal nor with non-tumor lung pathology sera. Our study demonstrates that seroreactivity profiles combined with statistical classification methods have great potential for discriminating patients with squamous cell lung carcinoma not only from normal controls but also from patients with non-tumor lung pathologies.

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

Abstract: New evidence and consensus has led to further revision of the McDonald Criteria for diagnosis of multiple sclerosis. The use of imaging for demonstration of dissemination of central nervous system lesions in space and time has been simplified, and in some circumstances dissemination in space and time can be established by a single scan. These revisions simplify the Criteria, preserve their diagnostic sensitivity and specificity, address their applicability across populations, and may allow earlier diagnosis and more uniform and widespread use.

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Abstract: A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Abstract: Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.