Abstract 4694: Evaluation of tumor-associated antigen expression with the MACSimaTM high-content imaging platform

Abstract

Here we report the use of the MACSima™ imaging platform to perform high-content imaging for the pre-clinical validation of tumor target expression on tumor and healthy human tissues indicative for potential on-target/off-tumor toxicity in vivo. Major advances have been achieved in cancer therapy in the past decade. In particular, targeted-immunotherapy has progressed and clinical benefits for patients have been achieved. However, on-target/off-tumor toxicity is a potential threat which has been shown to be more pronounced in solid than in liquid tumors. These findings highlight the need for better pre-clinical assays to improve the safety profile of immunotherapies. On-target/off-tumor toxicity is mainly based on the expression of tumor-associated antigens (TAA) in healthy tissues under physiological conditions. Currently, most prediction methods for on-target/off-tumor expression are based on bulk mRNA expression data of healthy tissue. These prediction models, however, have limitations, mainly poor predictable relation between RNA and protein level. Moreover, it is frequently unclear which cell types are affected by on-target/off-tumor effects. To overcome these limitations we employ multi-parameter imaging to analyze the expression of TAAs directly at the protein level. Additionally, we gain spatial information about tissue and cellular distribution of TAAs. Notably, our novel high-content imaging technology potentially allows for the analysis of hundreds of markers in a single experiment, paving the way for high-dimensional characterization of cells within complex solid tissues. We performed high-content imaging with the MACSima™ platform to validate the expression of known TAAs across tumor and healthy tissue samples. Subsequently, we employed unbiased cluster analysis revealing correlation patterns within the datasets to identify cell types at risk. In detail, we analyzed several high-grade serous ovarian carcinoma and pancreatic ductal adenocarcinoma for the expression of known TAAs, described tumor markers, and tissue lineage markers. Additionally, we evaluated the expression of these TAAs across several healthy human tissues. Next we performed pixel- and object-based data analysis for unbiased cluster analysis. Thereby we identified cell clusters that express TAAs in ovarian and pancreatic cancers, as well as in healthy tissues. We found that primarily epithelial cells express the analyzed TAAs in different tissues and that TAA expression shows inter- and intra-tumor heterogeneity. Taken together, we established a novel workflow for multi-parameter characterization of tissues employing the MACSima™ imaging platform. Our work enables efficient identification of potential tissues for on-target/off-tumor toxicity, paving the way for improved pre-clinical evaluation of TAAs as new targets. Citation Format: Christoph Herbel, Vera Dittmer, Manuel Martinez-Osuna, Laura Nadine Kuester, Daniel Schaefer, Jan Drewes, Jutta Kollet, Werner Mueller, Michael Mallmann, Peter Mallmann, Philipp Stroebel, Olaf Hardt, Dominik Eckardt, Andreas Bosio. Evaluation of tumor-associated antigen expression with the MACSimaTM high-content imaging platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4694.

Immune contexture analysis in immuno‐oncology: applications and challenges of multiplex fluorescent immunohistochemistry

“…However, this process can be very labour intensive because of the need to stain and image each biomarker sequentially, 21,26 resulting in prolonged turnaround time and potential changes of the tissue morphology and antigenicity because of repetitive exposure to the dye bleaching and/or antibody stripping conditions 21 . Emerging antibody‐based imaging techniques, 27,28 such as imaging mass cytometry (IMC), 29 multiplexed ion beam imaging (MIBI), 30 Nanostring GeoMx ® , 31,32 CODEX ® ™, 33 InSituPlex ® , 34,35 and MACSima™ 36,37 can further produce omics‐like data through quantification of up to 40 markers. However, these technologies require longer measurement time, limiting the number of region of interests and size of the tissue that can be imaged (Table 5).…”

“…Some of these platforms also provide fully integrated image acquisition and multiplexed data analytics that may overcome current obstacles of integration and interoperability. For example, Nanostring's GeoMx ® Digital Spatial Profiling (DSP), 31,32 Akoya Biosciences CODEX ® , 33 Miltenybiotec's MACSima™, 36,37 and IONpath's MIBIscope™ 30 are some of the emerging platforms that offer end‐to‐end solutions from highly multiplexed staining and image acquisition to a fully integrated high‐plex data analytics. Advances in fully integrated multiplexed methodologies and tissue‐based image analysis solutions that can integrate with clinical digital pathology workflow are critical for delivering better diagnostic and treatment decision to cancer patients.…”

Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments

“…The latest innovations in imaging technologies allow for single cell resolution of specific proteins, facilitating in-depth study of the spatial arrangement of cell types within the TME. A wide variety of technologies are available for this purpose, each with different benefits and trade-offs [1][2][3][4][5][6][7]. For a review of the available technologies see [8].…”