A5054327361- CAR-T cell therapy research
- Immunotherapy and Immune Responses
- Cell Image Analysis Techniques
- Nanowire Synthesis and Applications
- Nanoplatforms for cancer theranostics
- Image Processing Techniques and Applications
- Virus-based gene therapy research
- Immune Cell Function and Interaction
- AI in cancer detection
University of Cologne
2022
Miltenyi Biotec (Germany)
2020-2022
Solid tumors consist of malignant and nonmalignant cells that together create the local tumor microenvironment (TME). Additionally, TME is characterized by expression numerous soluble factors such as TGF-β. TGF-β plays an important role in suppressing T cell effector function promoting invasiveness. Up to now CAR exclusively target tumor-associated antigens (TAA) located on membrane. Thus, strategies exploit targets within are needed. This study demonstrates a novel approach using Adapter...
CAR T cell research in solid tumors often lacks spatiotemporal information and therefore, there is a need for molecular tomography to facilitate high-throughput preclinical monitoring of cells.Furthermore, gap exists between macro-and microlevel imaging data better assess intratumor infiltration therapeutic cells.We addressed this challenge by combining 3D µComputer bioluminescence (µCT/BLT), light-sheet fluorescence microscopy (LSFM) cyclic immunofluorescence (IF) staining.Methods: NSG mice...
<h3>Background</h3> The adoptive cell transfer (ACT) of tumor-infiltrating T lymphocytes (TILs) has shown remarkable results in patients with different cancer types. antitumor effect this therapy is mainly attributed to a small fraction tumor-reactive (TRLs) that recognize mutated peptides as well overexpressed self-antigens. Therefore, the enrichment and expansion TRLs constitutes promising immunotherapy approach. However, specific targeting individual antigens represents daunting challenge...
Multiplexed immunofluorescence microscopy gives deep insights into biological samples, like cancer tissues.The image intensities reflect the expression of immunological markers on surfaces cells that make up tissue.Typical tasks in analyzing such images are segmenting and quantifying their cell surface markers.Novel methods generate large datasets with hundreds per sample.The analysis can only be performed using automation, nowadays by machine learning.However, training models for...