New tools in high-dimensional spatial biology are leading to rapid advances in cancer research, biomarkers, and therapeutic targets. The MACSima spatial biology platform is a fully automated, ultrahigh-content imaging system that allows users to take a deep dive into the composition, cellular relationships, and interactions of normal and diseased tissue – providing much-needed spatial context for up to hundreds of proteomic markers on single or multiple tissues – all while leaving the tissue intact.
A broad range of specific and reliable antibodies is required for a comprehensive view of cellular subsets and biomarkers. This can be achieved with selected combinations of validated recombinant and hybridoma-derived antibodies, or with an unbiased approach using standardized REAscreenTM MAX Plates containing up to 205 dried-down antibodies.
Unlike other approaches that require challenging conjugation processes or untested antibodies, the MACSima uses cyclic staining of readily available fluorochrome conjugates from an extensive reagent portfolio while maintaining the flexibility to incorporate other antibodies qualified for immunofluorescence.
As the field of spatial biology continues to surge, data analysis software (such as MACS® iQ View) specifically designed to analyze large multidimensional data stacks will be critical to understanding the complexity of tissues and tumor microenvironments. Automation and an end-to-end solution gives the MACSima Imaging Platform the power to overcome historical multiplexing challenges such as manual workflows, a lack of readily available validated antibodies, and the need for robust data analysis software. Now, the platform is demonstrating utility across a wide range of cancer and immunotherapy applications.
Predicting immunotherapy response in lung cancer
In a recent paper, Hinterleitner et al. discovered that platelets expressing PD- L1 (pPD-L1) interact with lung cancer cells and that the pPD-L1 expression level can predict immunotherapy responses in non-small cell lung cancer (NSCLC) (1). Using the MACSima Imaging Platform, the researchers confirmed that NSCLC samples with high pPD-L1 levels show lower numbers of T cells in the tumor microenvironment and fewer infiltrating T cells.
Discovery of CAR target candidates in pancreatic carcinoma
A new publication has revealed target candidates for CAR T cell- based immunotherapy of pancreatic adenocarcinoma (2). The research team, led by Miltenyi Biotec, used a smart combination of data mining, flow cytometry, and ultrahigh-content analysis with the MACSima Imaging Platform to bypass a major roadblock to cellular immunotherapy – the lack of suitable tumor-specific antigens.
New potential target pair for ovarian carcinoma cell therapy
Kinkhabwalaetal.usedMACSima Imaging Cyclic Staining Technology to analyze human glioblastoma, ovarian, and pancreatic carcinoma, and 16 healthy tissues (3). The researchers showed that EPCAM and THY1 are only co-expressed on ovarian cancer cells and not on healthy tissue, identifying a new potential target pair for CAR T cell-based therapy.
Validation with CAR T cells demonstrated efficient killing of double-positive cells only, suggesting reduced toxicity of CAR T cells.
Spatial proteomic mapping of the liver
By combining multiple spatial transcriptomic and proteomic approaches, Guilliams et al. located and characterized all cells within the murine and human livers on a cellular level (4).
A more complete characterization of the cellular makeup of liver tissue with ultrahigh- content analysis using the MACSima Imaging Platform would enable deeper insights into the effects of disease on the cellular composition and interactions in the liver.
For research use only.
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References
- C Hinterleitner et al., “Platelet PD-L1 reflects collective intratumoral PD-L1 expression and predicts immunotherapy response in non-small cell lung cancer,” Nat Commun, 12, 7005 (2021). PMID: 34853305.
- D Schäfer et al., “Identification of CD318, TSPAN8 and CD66c as target candidates for CAR T cell based immunotherapy of pancreatic adenocarcinoma,” Nat Commun, 12, 1453 (2021). PMID: 33674603.
- A Kinkhabwala et al., “MACSima imaging cyclic staining (MICS) technology reveals combinatorial target pairs for CAR T cell treatment of solid tumors,” Sci Rep, 12, 1911 (2022). PMID: 35115587.
- M Guilliams et al., “Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches,” Cell, 185, 379 (2022). PMID: 35021063.
