The Laboratory module develops approaches to achieve comprehensive, highly efficient, AI-supported, and partially automated characterization of tumor biopsies and resections. The aim is to characterize and quantify the heterogeneity of the disease so that subsequent therapy can be optimized and tailored to the individual lesion. This includes the acceleration, completion, and systematic examination of all potentially clinically relevant tissue parameters from biopsies and resections, as well as the automated collection, evaluation, and digitization of data as additional information for the tumor board by means of a complete pathological examination of human tissue, including specialist medical findings and complete digitization of the data. This is supplemented by state-of-the-art methods of multiplex immunohistochemistry mass spectrometry imaging for the fine tissue characterization of malignant lesions and their evaluation and validation for routine clinical use in the context of a clinical study.
Mass spectrometry enables rapid tissue classification within interventional radiology and tumor (sub)classification for targeted therapy decisions. Optimally adapted antibodies are also being developed for this purpose to cover the clinically relevant spectrum of applications. On the other hand, conventional pathological diagnosis is further supplemented by novel methods of tissue preparation, optical imaging, and automated AI-based image analysis to obtain representative insights into the density distribution of tumor cells. For this purpose, the samples are examined as a whole in order to investigate cell stratification and the distribution of relevant parameters within the lesion and to develop a solid database on how many tissue sections are required for a solid pathological diagnosis. In addition, the laboratory module also researches tumor-specific nuclear medicine diagnostics and therapy options as well as their automation, which are available for endoradiotherapy of the lesions if they match the profile of the tumor lesions.
In the routine clinical context of pathological diagnosis, human tissue taken from the patient is characterized using standard procedures in accordance with guidelines within one week, the findings are compiled, and then made available to the tumor board. The analyses include individual, selected parameters to be examined, the relevance of which has already been proven in studies. Within the framework of the M²OLIE closed-loop process, however, the specialist findings should be available within hours of sampling, and the analysis and evaluation should include as many potentially relevant parameters as possible, allowing for a better assessment of the disease/individual lesion in order to make an optimally tailored therapy decision for the individual patient.The scientific and technical objectives therefore include, on the one hand, the highly efficient and partially automated characterization of the biopsies obtained, including parameters that go well beyond those usually examined, with the aim of comprehensively and thus completely characterizing the individual lesions. As in other areas of the research campus, this aims to address tumor heterogeneity, which is the basis for controlling oligometastatic tumor disease. Likewise, the automated collection, evaluation, and digitization of data is being developed as additional information for the tumor board by means of complete pathological examination of human tissue, including specialist medical evaluation and digitization of the data.
To support pathological diagnosis, the extent of tumor heterogeneity in M²OLIE-relevant lesions is evaluated. To this end, novel methods of tissue preparation, optical imaging, and automated AI-based image analysis are being developed and used to obtain representative insights into the density distribution of tumor cells. It is crucial that the tissue samples remain intact as a whole so that cell stratification and the distribution of tumor foci with high division activity become visible. Among other things, this allows us to determine the minimum number of regular tissue sections required for a solid pathological diagnosis. This increases diagnostic reliability and, where appropriate, reduces the amount of work and time associated with conventional diagnosis while maintaining the same diagnostic quality.
In the field of molecular medicine, imaging and mass spectrometry techniques are being used in collaboration with our corporate partner PROGEN Biotechnik to research the use of multiplex immunohistochemistry mass spectrometry for the tissue characterization of malignant lesions and to evaluate and validate its routine clinical use in a clinical study. This has two implications for the M²OLIE closed-loop process. On the one hand, a targeted therapy decision can be made on the basis of tumor (sub)classification to improve patient care. For this purpose, multiplex immunohistochemistry mass spectrometry is used to simultaneously read out a large number of biomarkers on a single tissue section after biopsy, provided that suitable antibodies are available, and to analyze and interpret their co-localization in the tissue. On the other hand, the approach can be used as a diagnostic tool in molecular medicine to enable rapid tissue classification within interventional radiology. This serves to characterize the targets of theranostic ligands, which could subsequently be used as targeted, tumor-specific therapeutics. This means that in the future, the M²OLIE Clinic will have one of the most modern biomedical analysis methods for tissue diagnostics at its disposal.
Currently, there are insufficient numbers of optimally adapted tumor-specific radiopharmaceuticals available for the sensitive and specific imaging of target lesions using PET and their highly efficient targeted therapy using endoradiotherapeutics. Ideally, these theranostic radiopharmaceuticals should also be able to address and overcome the heterogeneity of tumor disease. As part of this work, new radiopharmaceuticals for the complete and highly sensitive imaging and characterization of tumor foci are therefore being researched, and the findings are being applied to the development of endoradiotherapeutics adapted to the disease (in particular α-emitters based on antibodies, their fragments, and nanoparticulate systems) adapted to the disease, and, in collaboration with the company partner Elysia, their GMP-compliant automated production for clinical application is being researched.
