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Mainz, Germany

Van Der Burg S.H.,Leiden University | Kalos M.,University of Pennsylvania | Gouttefangeas C.,University of Tubingen | Janetzki S.,ZellNet Consulting Inc. | And 6 more authors.
Science Translational Medicine | Year: 2011

Assays that measure a patient's immune response play an increasingly important role in the development of immunotherapies. The inherent complexity of these assays and independent protocol development between laboratories result in high data variability and poor reproducibility. Quality control through harmonization - based on integration of laboratory-specific protocols with standard operating procedures and assay performance benchmarks - is one way to overcome these limitations. Harmonization guidelines can be widely implemented to address assay performance variables. This process enables objective interpretation and comparison of data across clinical trial sites and also facilitates the identification of relevant immune biomarkers, guiding the development of new therapies. Source

Hoos A.,Formerly Cancer Vaccine Consortium of the Cancer Research Institute | Britten C.M.,Association for Immunotherapy of Cancer | Britten C.M.,Ribological GmbH
OncoImmunology | Year: 2012

Developers of cancer immunotherapy have struggled for decades to achieve clinical success in using the patient's immune system to treat cancer. In the absence of a defined development paradigm for immunotherapies, conventional criteria established for chemotherapy were applied to these agents. This article summarizes the recent lessons for development of agents in the immunotherapy space, describes the systematic creation of a new clinical development paradigm for cancer immunotherapies and integrates this paradigm with the emerging methodological framework for a new clinical sub-specialty of immuno-oncology, which was driven by the collaborative work between the Cancer Immunotherapy Consortium (CIC) of the Cancer Research Institute in the US and the Association for Cancer Immunotherapy (CIMT) in Europe. This new framework provides a better defined development path and a foundation for more reproducible success of future therapies. © 2012 Landes Bioscience. Source

Lower M.,Johannes Gutenberg University Mainz | Renard B.Y.,Johannes Gutenberg University Mainz | Renard B.Y.,Robert Koch Institute | de Graaf J.,Johannes Gutenberg University Mainz | And 10 more authors.
PLoS Computational Biology | Year: 2012

Next generation sequencing (NGS) has enabled high throughput discovery of somatic mutations. Detection depends on experimental design, lab platforms, parameters and analysis algorithms. However, NGS-based somatic mutation detection is prone to erroneous calls, with reported validation rates near 54% and congruence between algorithms less than 50%. Here, we developed an algorithm to assign a single statistic, a false discovery rate (FDR), to each somatic mutation identified by NGS. This FDR confidence value accurately discriminates true mutations from erroneous calls. Using sequencing data generated from triplicate exome profiling of C57BL/6 mice and B16-F10 melanoma cells, we used the existing algorithms GATK, SAMtools and SomaticSNiPer to identify somatic mutations. For each identified mutation, our algorithm assigned an FDR. We selected 139 mutations for validation, including 50 somatic mutations assigned a low FDR (high confidence) and 44 mutations assigned a high FDR (low confidence). All of the high confidence somatic mutations validated (50 of 50), none of the 44 low confidence somatic mutations validated, and 15 of 45 mutations with an intermediate FDR validated. Furthermore, the assignment of a single FDR to individual mutations enables statistical comparisons of lab and computation methodologies, including ROC curves and AUC metrics. Using the HiSeq 2000, single end 50 nt reads from replicates generate the highest confidence somatic mutation call set. © 2012 Löwer et al. Source

Reusch U.,Affimed Therapeutics | Burkhardt C.,Affimed Therapeutics | Fucek I.,Affimed Therapeutics | Le Gall F.,Affimed Therapeutics | And 10 more authors.
mAbs | Year: 2014

To improve recruitment and activation of natural killer (NK) cells to lyse tumor cells, we isolated a human anti-CD16A antibody with similar affinity for the CD16A 158F/V allotypes, but no binding to the CD16B isoform. Using CD16A-targeting Fv domains, we constructed a tetravalent bispecific CD30/CD16A tandem diabody (TandAb®) consisting solely of Fv domains. This TandAb has two binding sites for CD16A and two for CD30, the antigen identifying Hodgkin lymphoma cells. The binding and cytotoxicity of the TandAb were compared with antibodies with identical anti-CD30 domains: (1) a native IgG, (2) an IgG optimized for binding to Fc receptors, and (3) a bivalent bispecific CD30/CD16A diabody. Due to its CD16A-bivalency and reduced koff, the TandAb was retained longer on the surface of NK cells than the IgGs or the diabody. This contributed to the higher potency and efficacy of the TandAb relative to those of the other anti-CD30 antibodies. TandAb cytotoxicity was independent of the CD16A allotype, whereas the anti-CD30 IgGs were substantially less cytotoxic when NK cells with low affinity CD16A allotype were employed. TandAb activation of NK cells was strictly dependent on the presence of CD30+ target cells. Therefore, the CD30/CD16A TandAb may represent a promising therapeutic for the treatment of Hodgkin's lymphoma; further, anti-CD16A TandAbs may function as potent immunotherapeutics that specifically recruit NK cells to destroy cancer cells. © 2014 Landes Bioscience. Source

Boisguerin V.,Johannes Gutenberg University Mainz | Boisguerin V.,BioNTech AG | Castle J.C.,Johannes Gutenberg University Mainz | Loewer M.,Johannes Gutenberg University Mainz | And 11 more authors.
British Journal of Cancer | Year: 2014

Cancer is a disease caused by DNA mutations. Cancer therapies targeting defined functional mutations have shown clinical benefit. However, as 95% of the mutations in a tumour are unique to that single patient and only a small number of mutations are shared between patients, the addressed medical need is modest. A rapidly determined patient-specific tumour mutation pattern combined with a flexible mutation-targeting drug platform could generate a mutation-targeting individualised therapy, which would benefit each single patient. Next-generation sequencing enables the rapid identification of somatic mutations in individual tumours (the mutanome). Immunoinformatics enables predictions of mutation immunogenicity. Mutation-targeting RNA-based vaccines can be rapidly and affordably synthesised as custom GMP drug products. Integration of these cutting-edge technologies into a clinically applicable process holds the promise of a disruptive innovation benefiting cancer patients. Here, we describe our translation of the individualised RNA-based cancer vaccine concept into clinic trials. © 2014 Cancer Research UK. All rights reserved. Source

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