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Advanced Clinician Scientists in Oncology

Supporting experienced physician–scientists in leading innovative cancer research

Advanced Clinician Scientists are experienced physician–scientists who have already established a strong research profile and aim to further develop their independence in academic medicine. The program provides extended protected research time and targeted support for building independent research groups and securing competitive funding.

At UCCSH, Advanced Clinician Scientists play a key role in bridging clinical practice and innovative cancer research. Their work contributes to strengthening translational approaches and advancing precision oncology across the campuses of Kiel and Lübeck.

Below, all Advanced Clinician Scientists currently active at UCCSH are presented with their respective research projects and descriptions.

PD Dr. med. Rüdiger Braun

PD Dr. med. Rüdiger Braun

Klinik für Chirurgie
Funktionsoberarzt, Viszeralchirurgie/ Studierendenbeauftragter

Advanced Clinician Scientist Program: Advanced Clinician Scientist Program at the University of Lübeck

Intratumoral heterogeneity and treatment response in gastrointestinal carcinomas

I am a senior resident in the Department of Surgery at the Lübeck Campus. My research focuses on the intratumoral heterogeneity of gastrointestinal tumors, particularly pancreatic cancer, and its influence on treatment response. Recent high-resolution imaging techniques have shown in recent years that most tumors consist of highly heterogeneous populations of tumor cells. During my two-year research fellowship as a German Cancer Aid grantee at the National Cancer Institute in Bethesda, USA, I was able to demonstrate that different cell clones within a tumor respond differently to therapies and that defined, clonal aberrations can be detected that are associated with response to therapy. As part of the current project, we are working on establishing organotypic slice cultures as a preclinical model for the individualized modification of multimodal therapeutic approaches. This model allows for the cultivation of the heterogeneous tumor in a tissue context and the direct testing of therapies ex vivo. Using transcriptomic and proteomic analyses of these cultures, the aim is to identify molecular targets that enable targeted modifications to treatment. In the long term, this system could make it possible to predict how individual patients will respond to various therapies. This would allow for the development of new, targeted therapies tailored to each patient’s tumor.

Dr. med. Lorenz Bastian

Dr. med. Lorenz Bastian

Klinik für Innere Medizin II mit den Schwerpunkten Hämatologie und Onkologie
Leitung Molekulares Tumorboard, Oberarzt, Advanced Clinician Scientist
Tel. Kiel: 0431 500-22555

Advanced Clinician Scientist Program: Advanced Clinician Scientist Program at Kiel University

Developmental Origins of Acute Lymphoblastic Leukemia—The “Cell of Origin” as a Therapeutic Target

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. It also occurs in adults with a significantly poorer prognosis and remains a challenge for all age groups when it recurs. In my project, it serves as a model for understanding the mechanisms of malignant transformation in the context of B-cell development. Based on the identification of new disease drivers in ALL (Bastian L et al. Leukemia 2019 and 2022), we were able to create a comprehensive reference for gene expression in ALL and its molecular subtypes (Beder T, [...], Bastian L. HemaSphere 2023). Comparison with normal B-cell development revealed overarching patterns that identified different developmental stages as the origin of the disease. We were able to show that in BCR::ABL1-driven ALL, earlier developmental origins, together with genomic alterations, define four prognostically relevant disease subtypes (Bastian L et al. Blood 2024), two of which are characterized by the fact that the BCR::ABL1 driver fusion was also detectable outside the B-cell lineage in various hematopoietic lineages.

Crossing lineage boundaries poses a risk of failure for modern immunotherapies, whose efficacy relies on targeting lineage-specific surface markers of leukemia.

The current focus is, on the one hand, to more precisely characterize the interaction between normal and leukemic hematopoiesis in the context of ALL and its driver subtypes. To this end, we are employing new methods of single-cell sequencing, the results of which we can relate to extensive, age-spanning reference cohorts of ALL. In addition, we aim to specifically reconstruct mechanisms of leukemogenesis with different genetic drivers in models of B-cell development, thereby contributing to a deeper understanding of the underlying regulatory processes and identifying critical signaling dependencies as potential therapeutic targets.  In close collaboration with the Hematology Laboratory in Kiel and the GMALL study group, we are translating findings from molecular analysis of ALL into routine diagnostic care.

PD Dr. med. Niclas Christian Blessin

Niclas Christian Blessin

Institut für Pathologie
Senior Resident, Advanced Clinician Scientist

Advanced Clinician Scientist Program: Funding is provided by external grants and by Prof. Röcken and Prof. Konukiewitz

Identification, understanding, and automated assessment of spatial (immune) prognostic biomarkers for implementation in routine clinical pathology

Prognostic biomarkers in routine clinical practice for various tumor types either have significant limitations, do not incorporate the immune system, or are evaluated using non-spatial RNA-based multigene panels that are sensitive to fluctuations in tumor homogeneity. To develop immunological prognostic biomarker panels for gastric cancer and other tumor types, we will utilize our recently developed >20+1-marker BLEACH&STAIN multiplex fluorescence immunohistochemistry method to search for strong prognostic biomarkers in the tumor’s immunological microenvironment. We have expanded this method so that we can now perform AI-based analysis of spatial proteo-transcriptomics. In addition, a detailed analysis of the spatial orchestration of immune cell subpopulations will be conducted using a framework comprising multiple convolutional neural networks (U-Net and DeepLab3+).