Promoting collaboration
Translational groups
Translational groups are working groups that develop preclinical models from experimental results in order to prepare clinical studies or to validate hypotheses from basic science results using patient samples/patient data.
Reichert translation group
Project title: LEGACY - DeLinEatinG the tumorAl and Clinical evolution of hereditarY pancreatic cancer
Main applicant: Prof. Dr. Maximilian Reichert (TUM Klinikum München)
Participating sites: University Hospital Augsburg, LMU Hospital Munich, University Hospital Regensburg, University Hospital Würzburg
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer that is usually diagnosed late. The LEGACY project focuses on investigating the clinical and molecular development of hereditary pancreatic cancer (HPC) by studying individuals at high risk of developing PDAC (high-risk individuals, HRI) as well as patients with HPC due to genetic or familial predispositions. LEGACY plans to utilize a data integration system (DIS) already established within the Pancreatic Cancer Alliance Bavaria (PCAB), which will enable the recruitment of HRI and HPC patients and the collection of comprehensive clinical and molecular data. Using this platform, we propose to establish a prospective, BZKF-wide registry of HRIs with detailed longitudinal clinical phenotyping (LEGACYrisk). Within the BZKF network, we will generate a comprehensive collection of HPC samples to perform molecular characterization at the single cell level and spatially resolved to define the cellular and molecular ecosystem of HPC (LEGACYtumor). In addition, we will develop and use advanced patient-derived models such as complex organoid systems to study the mechanisms of disease progression (LEGACYmodel).
The project is uniquely positioned to make significant contributions to the understanding of PDAC due to its comprehensive approach and use of state-of-the-art technology. By integrating clinical data, tissue resources and advanced modeling systems, LEGACY aims to improve the diagnosis and treatment of pancreatic cancer and ultimately lead to better outcomes for patients at risk of this devastating disease.
Translation group Prante
Project title: Translational Radiopharmaceutical Research
Main applicant: Prof. Dr. Olaf Prante (University Hospital Erlangen)
Participating locations: University Hospital Augsburg, FAU Erlangen-Nuremberg, University Hospital Regensburg
The Translational Radiopharmaceutical Research Group (BZKF-TRAFO) aims to make new theranostics available for clinical trials very quickly as predictive and therapeutic markers that are developed in the partners' medicinal chemistry research laboratories. The TRAFO platform is based on existing preclinical developments in the field of new theranostics for breast and pancreatic cancer, develops these further and provides validated procedures for their drug-compliant production. This makes it possible to use the theranostics for patients at the respective BZKF site even before the start of clinical trials. By linking BZKF-TRAFO to the BZKF Theranostics lighthouse, the availability of newly developed theranostics for clinical trials is also to be sustainably strengthened. This involves the chemical optimization of potential theranostics and their evaluation in animal models using preclinical tumor imaging and in therapy studies. BZKF-TRAFO is also developing an innovative biomarker that can visualize the migration of T cells into tumours with the aim of enabling early detection of the response to immunotherapy. The development of new predictive imaging probes for tumor diagnostics and for the prediction of therapy response as well as the successful establishment of their drug-compliant production by BZKF-TRAFO should enable an acceleration of their application and create all the prerequisites for their integration into future clinical studies at the BZKF sites.
Poster Translational Group TRAFO
Translational group Krause
Project title: Determination of residual disease in AML using automated AI-supported analysis of flow cytometry data
Main applicant: Prof. Dr. Stefan Krause, University Hospital Erlangen
Participating sites: University Hospital Augsburg, FAU Erlangen-Nuremberg, LMU Klinikum München, TUM Klinikum München
The assessment of measurable residual disease (MRD) after the start of therapy is of central importance for the prognosis and treatment management of patients with acute myeloid leukemia (AML). In addition to molecular methods, which are only available with sufficient sensitivity for a few changes, flow cytometry (FCM) is used for this purpose. However, this method is not standardized and depends to a large extent on the personal experience of the individual diagnostician. In the proposed project, an "artificial intelligence" (AI)-supported, fully automated pipeline for FCM-based quantification of MRD in AML patients is to be developed, optimized and validated, which works independently of the examiner and should achieve better discriminatory power compared to manual evaluation due to the analysis directly in the n-dimensional space of the data sets. Preliminary work has shown that both the pre-selection of relevant cell populations (i.e. immature cells) and the detection of atypical (i.e. leukemia) cells work in principle. However, several aspects of the methods still need to be optimized and brought together in a pipeline. This would be an important milestone in being able to offer FCM-based MRD diagnostics for all AML patients in a standardized and rapid manner and thus better monitor and control the therapy.
Reichert translation group
Project title: LEGACY - DeLinEatinG the tumorAl and Clinical evolution of hereditarY pancreatic cancer
Main applicant: Prof. Dr. Maximilian Reichert (TUM Klinikum München)
Participating sites: University Hospital Augsburg, LMU Hospital Munich, University Hospital Regensburg, University Hospital Würzburg
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer that is usually diagnosed late. The LEGACY project focuses on investigating the clinical and molecular development of hereditary pancreatic cancer (HPC) by studying individuals at high risk of developing PDAC (high-risk individuals, HRI) as well as patients with HPC due to genetic or familial predispositions. LEGACY plans to utilize a data integration system (DIS) already established within the Pancreatic Cancer Alliance Bavaria (PCAB), which will enable the recruitment of HRI and HPC patients and the collection of comprehensive clinical and molecular data. Using this platform, we propose to establish a prospective, BZKF-wide registry of HRIs with detailed longitudinal clinical phenotyping (LEGACYrisk). Within the BZKF network, we will generate a comprehensive collection of HPC samples to perform molecular characterization at the single cell level and spatially resolved to define the cellular and molecular ecosystem of HPC (LEGACYtumor). In addition, we will develop and use advanced patient-derived models such as complex organoid systems to study the mechanisms of disease progression (LEGACYmodel).
The project is uniquely positioned to make significant contributions to the understanding of PDAC due to its comprehensive approach and use of state-of-the-art technology. By integrating clinical data, tissue resources and advanced modeling systems, LEGACY aims to improve the diagnosis and treatment of pancreatic cancer and ultimately lead to better outcomes for patients at risk of this devastating disease.
Translation group Prante
Project title: Translational Radiopharmaceutical Research
Main applicant: Prof. Dr. Olaf Prante (University Hospital Erlangen)
Participating locations: University Hospital Augsburg, FAU Erlangen-Nuremberg, University Hospital Regensburg
The Translational Radiopharmaceutical Research Group (BZKF-TRAFO) aims to make new theranostics available for clinical trials very quickly as predictive and therapeutic markers that are developed in the partners' medicinal chemistry research laboratories. The TRAFO platform is based on existing preclinical developments in the field of new theranostics for breast and pancreatic cancer, develops these further and provides validated procedures for their drug-compliant production. This makes it possible to use the theranostics for patients at the respective BZKF site even before the start of clinical trials. By linking BZKF-TRAFO to the BZKF Theranostics lighthouse, the availability of newly developed theranostics for clinical trials is also to be sustainably strengthened. This involves the chemical optimization of potential theranostics and their evaluation in animal models using preclinical tumor imaging and in therapy studies. BZKF-TRAFO is also developing an innovative biomarker that can visualize the migration of T cells into tumours with the aim of enabling early detection of the response to immunotherapy. The development of new predictive imaging probes for tumor diagnostics and for the prediction of therapy response as well as the successful establishment of their drug-compliant production by BZKF-TRAFO should enable an acceleration of their application and create all the prerequisites for their integration into future clinical studies at the BZKF sites.
Poster Translational Group TRAFO
Translational group Krause
Project title: Determination of residual disease in AML using automated AI-supported analysis of flow cytometry data
Main applicant: Prof. Dr. Stefan Krause, University Hospital Erlangen
Participating sites: University Hospital Augsburg, FAU Erlangen-Nuremberg, LMU Klinikum München, TUM Klinikum München
The assessment of measurable residual disease (MRD) after the start of therapy is of central importance for the prognosis and treatment management of patients with acute myeloid leukemia (AML). In addition to molecular methods, which are only available with sufficient sensitivity for a few changes, flow cytometry (FCM) is used for this purpose. However, this method is not standardized and depends to a large extent on the personal experience of the individual diagnostician. In the proposed project, an "artificial intelligence" (AI)-supported, fully automated pipeline for FCM-based quantification of MRD in AML patients is to be developed, optimized and validated, which works independently of the examiner and should achieve better discriminatory power compared to manual evaluation due to the analysis directly in the n-dimensional space of the data sets. Preliminary work has shown that both the pre-selection of relevant cell populations (i.e. immature cells) and the detection of atypical (i.e. leukemia) cells work in principle. However, several aspects of the methods still need to be optimized and brought together in a pipeline. This would be an important milestone in being able to offer FCM-based MRD diagnostics for all AML patients in a standardized and rapid manner and thus better monitor and control the therapy.
Landwehr translation group
Project title: CAR T Control - Understanding and Addressing Toxicities of CAR T-Cell Therapy
Applicant: Dr. Laura-Sophie Landwehr (University Hospital Würzburg)
Participating sites: University Hospital Augsburg, LMU Clinic Munich
Chimeric antigen receptor (CAR) T cell therapy is an innovative form of immunotherapy in which the body's own T cells are modified in such a way that they direct a specific immune response against tumors. Such therapies have already been approved for hematological neoplasms and are also being tested for solid tumors, among others. An essential prerequisite for the development of effective
therapies is the elucidation of suitable target structures on tumor cells. In order to apply this form of cancer therapy in rare (neuro-)endocrine tumors with a poor prognosis - adrenocortical carcinomas (ACC), pheochromocytomas/paragangliomas (PPGL), neuroendocrine neoplasias (NEN) and radioiodine-refractory thyroid carcinomas (TC) - the highly specialized reference centers for endocrine oncology and cellular immunotherapy at the University Hospitals of Würzburg, Munich and Augsburg will work together. The aim of this research project is to develop one or more optimized cell products for the treatment of adult and paediatric (neuro-)endocrine tumors. First, we will evaluate tumor-specific target structures and analyze the effects of the tumor microenvironment. Based on these findings, potential cell products will be developed and optimized with regard to the requirements of the different tumors in order to ensure a targeted anti-tumor immune response. Against the background of this unique scientific and infrastructural strength, this research project has great potential for a translational trajectory.
