Data integration between clinical research and patient care: A framework for context-depending data sharing and in silico predictions.

The transfer of new insights from basic or clinical research into clinical routine is usually a lengthy and time-consuming process. Conversely, there are still many barriers to directly provide and use routine data in the context of basic and clinical research. In particular, no coherent software solution is available that allows a convenient and immediate bidirectional transfer of data between concrete treatment contexts and research settings. Here, we present a generic framework that integrates health data (e.g., clinical, molecular) and computational analytics (e.g., model predictions, statistical evaluations, visualizations) into a clinical software solution which simultaneously supports both patient-specific healthcare decisions and research efforts, while also adhering to the requirements for data protection and data quality. Specifically, our work is based on a recently established generic data management concept, for which we designed and implemented a web-based software framework that integrates data analysis, visualization as well as computer simulation and model prediction with audit trail functionality and a regulation-compliant pseudonymization service. Within the front-end application, we established two tailored views: a clinical (i.e., treatment context) perspective focusing on patient-specific data visualization, analysis and outcome prediction and a research perspective focusing on the exploration of pseudonymized data. We illustrate the application of our generic framework by two use-cases from the field of haematology/oncology. Our implementation demonstrates the feasibility of an integrated generation and backward propagation of data analysis results and model predictions at an individual patient level into clinical decision-making processes while enabling seamless integration into a clinical information system or an electronic health record.

A Novel, Broad-Acting Peptide Inhibitor of Double-Stranded DNA Virus Gene Expression and Replication.

Viral infections are a global disease burden with only a limited number of antiviral agents available. Due to newly emerging viral pathogens and increasing occurrence of drug resistance, there is a continuous need for additional therapeutic options, preferably with extended target range. In the present study, we describe a novel antiviral peptide with broad activity against several double-stranded DNA viruses. The 22-mer peptide TAT-I24 potently neutralized viruses such as herpes simplex viruses, adenovirus type 5, cytomegalovirus, vaccinia virus, and simian virus 40 in cell culture models, while being less active against RNA viruses. The peptide TAT-I24 therefore represents a novel and promising drug candidate for use against double-stranded DNA viruses.

Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology.

BACKGROUND: Individualization and patient-specific optimization of treatment is a major goal of modern health care. One way to achieve this goal is the application of high-resolution diagnostics together with the application of targeted therapies. However, the rising number of different treatment modalities also induces new challenges: Whereas randomized clinical trials focus on proving average treatment effects in specific groups of patients, direct conclusions at the individual patient level are problematic. Thus, the identification of the best patient-specific treatment options remains an open question. Systems medicine, specifically mechanistic mathematical models, can substantially support individual treatment optimization. In addition to providing a better general understanding of disease mechanisms and treatment effects, these models allow for an identification of patient-specific parameterizations and, therefore, provide individualized predictions for the effect of different treatment modalities. RESULTS: In the following we describe a software framework that facilitates the integration of mathematical models and computer simulations into routine clinical processes to support decision-making. This is achieved by combining standard data management and data exploration tools, with the generation and visualization of mathematical model predictions for treatment options at an individual patient level. CONCLUSIONS: By integrating model results in an audit trail compatible manner into established clinical workflows, our framework has the potential to foster the use of systems-medical approaches in clinical practice. We illustrate the framework application by two use cases from the field of haematological oncology.

Selective Engagement of FcγRIV by a M2e-Specific Single Domain Antibody Construct Protects Against Influenza A Virus Infection.

Lower respiratory tract infections, such as infections caused by influenza A viruses, are a constant threat for public health. Antivirals are indispensable to control disease caused by epidemic as well as pandemic influenza A. We developed a novel anti-influenza A virus approach based on an engineered single-domain antibody (VHH) construct that can selectively recruit innate immune cells to the sites of virus replication. This protective construct comprises two VHHs. One VHH binds with nanomolar affinity to the conserved influenza A matrix protein 2 (M2) ectodomain (M2e). Co-crystal structure analysis revealed that the complementarity determining regions 2 and 3 of this VHH embrace M2e. The second selected VHH specifically binds to the mouse Fcγ Receptor IV (FcγRIV) and was genetically fused to the M2e-specific VHH, which resulted in a bi-specific VHH-based construct that could be efficiently expressed in Pichia pastoris. In the presence of M2 expressing or influenza A virus-infected target cells, this single domain antibody construct selectively activated the mouse FcγRIV. Moreover, intranasal delivery of this bispecific FcγRIV-engaging VHH construct protected wild type but not FcγRIV-/- mice against challenge with an H3N2 influenza virus. These results provide proof of concept that VHHs directed against a surface exposed viral antigen can be readily armed with effector functions that trigger protective antiviral activity beyond direct virus neutralization.

CMV-encoded Fcγ receptors: modulators at the interface of innate and adaptive immunity.

The constant region of IgG antibodies mediates antiviral activities upon engaging host Fcγ receptors (FcγRs) expressed by a variety of immune cells, such as antibody-dependent cellullar cytotoxcity (ADCC) executed by natural killer (NK)cells. Human cytomegalovirus (HCMV) is unique among viruses by encoding also an array of several Fcγ-binding glycoproteins with cell surface disposition and concomitant incorporation into the virion. Evidence is increasing that the virus-encoded Fcγ receptors differ in their Fcγ binding mode but effectively operate as adversaries of host FcγRs since they are able to prevent IgG-mediated triggering of activating host FcγRs, i.e., FcγRI, FcγRIIA, and FcγRIIIA. Here we discuss virus-encoded FcγRs as the first known HCMV inhibitors of IgG-mediated immunity which could account for the limited efficacy of HCMV hyperimmune globulin in clinical settings. A better understanding of their molecular mode of action opens up new perspectives for improving IgG therapies against HCMV disease.

Lymphangiogenesis occurs in upper tract urothelial carcinoma and correlates with lymphatic tumour dissemination and poor prognosis.

OBJECTIVE: To describe the lymphatic vessel density and to determine the functional and prognostic significance of tumoral lymphatic vessels in upper tract urothelial carcinoma (UTUC). PATIENTS AND METHODS: The study included 65 patients who had a radical nephroureterectomy (RNU) for UTUC between 1997 and 2004. All pathological slides were re-evaluated by one reference pathologist and clinical data were reviewed. Lymphatic endothelial cells (LECs) were stained immunohistochemically using D2-40. The lymphatic vessel density (LVD) was described in representative intratumoral (ITLVD), peritumoral (PTLVD) and non-tumoral (NTLVD) areas. Random samples were selected for double-immunostaining with D2-40 and CD-34 (to distinguish blood and lymphatic vessels) and the proliferation marker Ki-67 to detect lymphangiogenesis. The primary outcome measures were disease-specific survival (DSS) and disease recurrence (urothelial and/or distant). RESULTS: The median (interquartile range) PTLVD was 4.0 (3.0-6.3), and significantly higher than that for ITLVD, of 0.3 (0-1.7) (P < 0.001), and NTLVD, of 3 (2.0-3.7) (P < 0.001). Both a higher ITLVD and PTLVD, the presence of lymphovascular invasion (LVI) (each P < 0.001) and a high tumour grade (P = 0.004) were associated with reduced DSS on univariate analysis. A higher PTLVD (P = 0.028) and the presence of LVI (P = 0.020) independently predicted reduced DSS on multivariate analysis. IT and PT lymphatic vessels showed proliferating LECs in all analysed samples. CONCLUSION: Lymphangiogenesis is present in UTUC, as shown by a significantly increased PTLVD and proliferating LECs. Our findings suggest functional relevance of PT lymphatic vessels during lymphatic tumour spread. PTLVD is a potential novel prognostic factor for DSS in UTUC, and further prospective studies will be needed to determine the effect of its routine evaluation on clinical outcomes of this malignancy.