Identification of CD318, TSPAN8 and CD66c as target candidates for CAR T cell based immunotherapy of pancreatic adenocarcinoma.

A major roadblock prohibiting effective cellular immunotherapy of pancreatic ductal adenocarcinoma (PDAC) is the lack of suitable tumor-specific antigens. To address this challenge, here we combine flow cytometry screenings, bioinformatic expression analyses and a cyclic immunofluorescence platform. We identify CLA, CD66c, CD318 and TSPAN8 as target candidates among 371 antigens and generate 32 CARs specific for these molecules. CAR T cell activity is evaluated in vitro based on target cell lysis, T cell activation and cytokine release. Promising constructs are evaluated in vivo. CAR T cells specific for CD66c, CD318 and TSPAN8 demonstrate efficacies ranging from stabilized disease to complete tumor eradication with CD318 followed by TSPAN8 being the most promising candidates for clinical translation based on functionality and predicted safety profiles. This study reveals potential target candidates for CAR T cell based immunotherapy of PDAC together with a functional set of CAR constructs specific for these molecules.

A preclinical micro-computed tomography database including 3D whole body organ segmentations.

The gold-standard of preclinical micro-computed tomography (µCT) data processing is still manual delineation of complete organs or regions by specialists. However, this method is time-consuming, error-prone, has limited reproducibility, and therefore is not suitable for large-scale data analysis. Unfortunately, robust and accurate automated whole body segmentation algorithms are still missing. In this publication, we introduce a database containing 225 murine 3D whole body µCT scans along with manual organ segmentation of most important organs including heart, liver, lung, trachea, spleen, kidneys, stomach, intestine, bladder, thigh muscle, bone, as well as subcutaneous tumors. The database includes native and contrast-enhanced, regarding spleen and liver, µCT data. All scans along with organ segmentation are freely accessible at the online repository Figshare. We encourage researchers to reuse the provided data to evaluate and improve methods and algorithms for accurate automated organ segmentation which may reduce manual segmentation effort, increase reproducibility, and even reduce the number of required laboratory animals by reducing a source of variability and having access to a reliable reference group.