Radioimmunotherapy in Non-Hodgkin's Lymphoma: Retrospective Adverse Event Profiling of Zevalin and Bexxar.

The development of monoclonal antibodies has dramatically changed the outcome of patients with non-Hodgkin's lymphoma (NHL), the most common hematological malignancy. However, despite the satisfying results of monoclonal antibody treatment, only few NHL patients are permanently cured with single-agent therapies. In this context, radioimmunotherapy, the administration of radionuclides conjugated to monoclonal antibodies, is aimed to augment the single-agent efficacy of immunotherapy in order to deliver targeted radiation to tumors, particularly CD20+ B-cell lymphomas. Based on evidence from several trials in NHL, the radiolabeled antibodies 90Y-ibritumomab tiuxetan (Zevalin, Spectrum Pharmaceuticals) and 131I-tositumomab (Bexxar, GlaxoSmithKline) received FDA approval in 2002 and 2003, respectively. However, none of the two radioimmunotherapeutic agents has been broadly applied in clinical practice. The main reason for the under-utilization of radioimmunotherapy includes economic and logistic considerations. However, concerns about potential side effects have also been raised. Driven by these developments, we performed retrospective analysis of adverse events reporting Zevalin or Bexxar, extracted from the FDA's Adverse Event Reporting System (FAERS) and the World Health Organization's VigiBase repository. Our results indicate that the two radioimmunotherapeutic agents have both related and distinct side effect profiles and confirm their known toxicological considerations. Our work also suggests that computational analysis of real-world post-marketing data can provide informative clinical insights. While more prospective studies are necessary to fully characterize the efficacy and safety of radioimmunotherapy, we expect that it has not yet reached its full therapeutic potential in modern hematological oncology

Arena3D: visualization of biological networks in 3D

<p>Abstract</p> <p>Background</p> <p>Complexity is a key problem when visualizing biological networks; as the number of entities increases, most graphical views become incomprehensible. Our goal is to enable many thousands of entities to be visualized meaningfully and with high performance.</p> <p>Results</p> <p>We present a new visualization tool, Arena3D, which introduces a new concept of staggered layers in 3D space. Related data – such as proteins, chemicals, or pathways – can be grouped onto separate layers and arranged via layout algorithms, such as Fruchterman-Reingold, distance geometry, and a novel hierarchical layout. Data on a layer can be clustered via k-means, affinity propagation, Markov clustering, neighbor joining, tree clustering, or UPGMA ('unweighted pair-group method with arithmetic mean'). A simple input format defines the name and URL for each node, and defines connections or similarity scores between pairs of nodes. The use of Arena3D is illustrated with datasets related to Huntington's disease.</p> <p>Conclusion</p> <p>Arena3D is a user friendly visualization tool that is able to visualize biological or any other network in 3D space. It is free for academic use and runs on any platform. It can be downloaded or lunched directly from <url>http://arena3d.org</url>. Java3D library and Java 1.5 need to be pre-installed for the software to run.</p

A reference guide for tree analysis and visualization

The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics, are becoming vast. Sequencing technologies become cheaper and easier to use and, thus, large-scale evolutionary studies towards the origins of life for all species and their evolution becomes more and more challenging. Databases holding information about how data are related and how they are hierarchically organized expand rapidly. Clustering analysis is becoming more and more difficult to be applied on very large amounts of data since the results of these algorithms cannot be efficiently visualized. Most of the available visualization tools that are able to represent such hierarchies, project data in 2D and are lacking often the necessary user friendliness and interactivity. For example, the current phylogenetic tree visualization tools are not able to display easy to understand large scale trees with more than a few thousand nodes. In this study, we review tools that are currently available for the visualization of biological trees and analysis, mainly developed during the last decade. We describe the uniform and standard computer readable formats to represent tree hierarchies and we comment on the functionality and the limitations of these tools. We also discuss on how these tools can be developed further and should become integrated with various data sources. Here we focus on freely available software that offers to the users various tree-representation methodologies for biological data analysis

Martini: using literature keywords to compare gene sets

Life scientists are often interested to compare two gene sets to gain insight into differences between two distinct, but related, phenotypes or conditions. Several tools have been developed for comparing gene sets, most of which find Gene Ontology (GO) terms that are significantly over-represented in one gene set. However, such tools often return GO terms that are too generic or too few to be informative. Here, we present Martini, an easy-to-use tool for comparing gene sets. Martini is based, not on GO, but on keywords extracted from Medline abstracts; Martini also supports a much wider range of species than comparable tools. To evaluate Martini we created a benchmark based on the human cell cycle, and we tested several comparable tools (CoPub, FatiGO, Marmite and ProfCom). Martini had the best benchmark performance, delivering a more detailed and accurate description of function. Martini also gave best or equal performance with three other datasets (related to Arabidopsis, melanoma and ovarian cancer), suggesting that Martini represents an advance in the automated comparison of gene sets. In agreement with previous studies, our results further suggest that literature-derived keywords are a richer source of gene-function information than GO annotations. Martini is freely available at http://martini.embl.de

LAITOR - Literature Assistant for Identification of Terms co-Occurrences and Relationships

<p>Abstract</p> <p>Background</p> <p>Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context.</p> <p>Results</p> <p>We created a text mining system (LAITOR: <it><b>L</b>iterature <b>A</b>ssistant for <b>I</b>dentification of <b>T</b>erms co-<b>O</b>ccurrences and <b>R</b>elationships</it>) that analyses co-occurrences of bioentities, biointeractions, and other biological terms in MEDLINE abstracts. The method accounts for the position of the co-occurring terms within sentences or abstracts. The system detected abstracts mentioning protein-protein interactions in a standard test (BioCreative II IAS test data) with a precision of 0.82-0.89 and a recall of 0.48-0.70. We illustrate the application of LAITOR to the detection of plant response genes in a dataset of 1000 abstracts relevant to the topic.</p> <p>Conclusions</p> <p>Text mining tools combining the extraction of interacting bioentities and biological concepts with network displays can be helpful in developing reasonable hypotheses in different scientific backgrounds.</p

Caipirini: using gene sets to rank literature

<p>Abstract</p> <p>Background</p> <p>Keeping up-to-date with bioscience literature is becoming increasingly challenging. Several recent methods help meet this challenge by allowing literature search to be launched based on lists of abstracts that the user judges to be 'interesting'. Some methods go further by allowing the user to provide a second input set of 'uninteresting' abstracts; these two input sets are then used to search and rank literature by relevance. In this work we present the service 'Caipirini' (<url>http://caipirini.org</url>) that also allows two input sets, but takes the novel approach of allowing ranking of literature based on one or more sets of genes.</p> <p>Results</p> <p>To evaluate the usefulness of Caipirini, we used two test cases, one related to the human cell cycle, and a second related to disease defense mechanisms in <it>Arabidopsis thaliana</it>. In both cases, the new method achieved high precision in finding literature related to the biological mechanisms underlying the input data sets.</p> <p>Conclusions</p> <p>To our knowledge Caipirini is the first service enabling literature search directly based on biological relevance to gene sets; thus, Caipirini gives the research community a new way to unlock hidden knowledge from gene sets derived via high-throughput experiments.</p

Using graph theory to analyze biological networks

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system

Retrospective Side Effect Profiling of the Metastatic Melanoma Combination Therapy Ipilimumab-Nivolumab Using Adverse Event Data

Recent studies suggest that combining nivolumab with ipilimumab is a more effective treatment for melanoma patients, compared to using ipilimumab or nivolumab alone. However, treatment with these immunotherapeutic agents is frequently associated with increased risk of toxicity, and (auto-) immune-related adverse events. The precise pathophysiologic mechanisms of these events are not yet clear, and evidence from clinical trials and translational studies remains limited. Our retrospective analysis of ~7700 metastatic melanoma patients treated with ipilimumab and/or nivolumab from the FDA Adverse Event Reporting System (FAERS) demonstrates that the identified immune-related reactions are specific to ipilimumab and/or nivolumab, and that when the two agents are administered together, their safety profile combines reactions from each drug alone. While more prospective studies are needed to characterize the safety of ipilimumab and nivolumab, the present work constitutes perhaps the first effort to examine the safety of these drugs and their combination based on computational evidence from real world post marketing data

The role of ultrasonography in the neuromonitoring of patients with severe head injury

Background: Elevated intracranial pressure (ICP) is a common manifestation of severe brain injury, that requires rapid diagnosis and therapeutic intervention. The use of an intracranial catheter remains the gold-standard method for diagnosing intracranial hypertension, however this modality is not always feasible and/or available. As a result, non-invasive techniques for the evaluation of the ICP have been developed and are frequently used in the clinical practice. The optic nerve sheath diameter (ONSD) has been reported to be increased in patients with intracranial hypertension. Direct measurement of the ONSD is possible by means of optic nerve sonography. Brain death (BD) is defined as the irreversible cessation of all hemispheric, cerebellar and brain stem functions. Since cerebral circulatory arrest (CCA) is an imperative feature of BD, cerebral blood flow tests are widely advocated to confirm the findings of the clinical examination. Angiography has been considered the gold standard in the diagnosis of BD, but is invasive. Transcranial Doppler sonography (TCD) offers a non-invasive means to assess cerebral hemodynamics, however its application may limited by a bilateral absence of bone windows, which precludes the evaluation of the anterior cerebral circulation, thereby rendering confirmation of CCA unfeasible. In such cases, CCA could be confirmed by means of transorbital Doppler sonography (TOD) of the internal carotid arteries (ICAs). Providing the family with a realistic understanding of the patient’s condition is considered a demanding and important part of intensive care unit (ICU) practice. A satisfactory explanation of BD may help relatives accept the death of their relative, promote the grieving process, and possibly ease the decision for organ donation. Reporting the results of ancillary tests could improve the relatives’ comprehension and satisfaction with the medical information. Objective: The purposes of this study were to evaluate whether a) optic nerve sonography can provide accurate detection of intracranial hypertension and/or ICP monitoring in brain-injured patients b) TCD offers accurate confirmation of CCA in patients with clinical diagnosis of BD c) the addition of TOD of the ICAs improves the efficacy of the TCD protocol in confirming CCA d) reporting the angiographic and sonographic confirmation of CCA to relatives of brain-dead patients improves their comprehension and satisfaction with the medical information. Materials and methods: From the 197 ICU patients who were included in the study, 106 suffered from brain injury, whereas 67 had no intracranial pathology and served as control individuals. Initially, brain-injured patients were evaluated clinically (Glasgow Coma Scale) and using a semiquantitative (I to VI) neuroimaging scale (Marshall Scale). Thereafter, the patients were divided into those with moderate (Marshall Scale = I and Glasgow Coma Scale > 8 [n = 35]) and severe (Marshall Scale = II to VI and Glasgow Coma Scale ≤ 8 [n = 71]) brain injury. Upon admission, all patients underwent non-invasive measurement of the ICP (estimated ICP, eICP) by TCD, and synchronous ONSD measurements by optic nerve sonography, whereas invasive ICP measurement using an intraparenchymal catheter was performed in 32 patients with severe brain injury. In patients with severe brain injury, the above measurement were repeated twice during their hospitalization. Forty-six clinically brain-dead patients underwent four-vessel angiography, TCD of the basilar and middle cerebral arteries, and TOD of the ICAs. Relatives were randomly allocated to 23 in whom BD was presented as a clinical diagnosis (group I) and to 23 in whom BD was presented as a clinical diagnosis confirmed by TCD and angiography (group II). Comprehension and satisfaction of the relatives were assessed using an interview and a questionnaire. Results: ONSD and eICP were both significantly increased (6.2 ± 0.7 mm and 27.5 ± 6.9 mmHg, respectively; P < 0.0001) in patients with severe brain injury as compared with patients with moderate brain injury (4.2 ± 0.9 mm and 12.2 ± 3.7 mmHg) and compared with control individuals (3.5 ± 0.8 mm and 9.9 ± 3.7 mmHg). In patients with severe brain injury, the correlation between the ONSD measurements and the neuroimaging scale results was strong upon admission (r = 0.82), and in the second (r = 0.76) and third (r = 0.77) evaluation (P < 0.001). In the same subjects, the correlation between the ONSD measurements and the eICP was strong upon admission (r = 0.80), weak in the second (r = 0.53) and relatively strong in the third (r = 0.65) evaluation (P < 0.001). In the patients with severe brain injury who underwent invasive measurement of the ICP, the latter correlated with the ONSD measurements (r = 0.68, P = 0.002). The best cut-off value of ONSD for predicting elevated ICP was 5.7 mm (sensitivity = 74.1% and specificity = 100%). Both angiography and TCD verified CCA in all cases (k = 1). In 7 patients with failure of the transtemporal approach, CCA was confirmed by the transorbital recordings. The addition of TOD enabled 15.5% more cases of CCA to be diagnosed by TCD. Group II exhibited improved comprehension and satisfaction rates (P < 0.05). Conclusions: ONSD measurements correlate with non-invasive and invasive measurements of the ICP, and with head computed tomography scan findings in brain-injured adults. Hence, optic nerve sonography may serve as an additional diagnostic tool that could alert clinicians to the presence of elevated ICP, whenever invasive ICP evaluation is contraindicated and/or is not available. Alterations in ONSD strongly correlated with neuroimaging results among patients with severe brain injury. The addition of TOD increases the efficacy of TCD in confirming CCA in BD. Reporting confirmation of CCA to families of brain-dead patients may improve their comprehension and satisfaction with the provided medical information