Abstract 5643: High-spatial-resolution multi-omics analysis of cancer tissues

Recent technological breakthroughs in single cell sequencing have revealed that malignant cells and nonmalignant cells are both highly dynamic and in the case of tumor cells, that the intratumoral heterogeneity is quite remarkable. However, several questions remain, especially in a spatial context,...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Ill.), 2023-04, Vol.83 (7_Supplement), p.5643-5643
Hauptverfasser: Neil, Emily, Park, Dongju, Lloyd, Erica, Dibuono, Michael, Hosono, Seiyu, Muller, Reto, Lafayette, Hanna, Smith, Hsinyi, Pinard, Robert
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Sprache:eng
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Zusammenfassung:Recent technological breakthroughs in single cell sequencing have revealed that malignant cells and nonmalignant cells are both highly dynamic and in the case of tumor cells, that the intratumoral heterogeneity is quite remarkable. However, several questions remain, especially in a spatial context, and a rapidly growing need has been observed for imaging-based approaches with single-cell resolution to visualize and characterize the tumor microenvironment. In the current study, we used Miltenyi Biotec newly developed spatial gene expression technology and automated imaging platform, to acquire spatial microscopy data for multiple biological analytes and multiple cancer tissues. The approach is based on fluorescence microscopy and the MICS technology principle of cyclic staining (MACSima™ Imaging Cyclic Staining) along with validated fluorochrome-conjugated antibodies and specifically amplified oligonucleotide probes combined with a proprietary signal removal system. FFPE tissue blocks were analyzed and each gene, which display a unique emission spectrum during a single cycle, was decoded. Due to the non-destructive nature of the workflow, H&E staining, immunofluorescence and RNA data can be collected together into a single image and on a single section. Using our antibody and targeted RNA immune-oncology panel coupled with our smart segmentation and flexible gating software suite, we have generated a topographical map of the expression profile level for several cancer tissues i.e.: tonsil, pancreas, kidney and ovary. This technology allows for the analysis of hundreds of protein markers and RNA transcripts on a single tissue, the characterization of the spatial architecture and the expression topography of tumor tissue sections. A better understanding of tissue microenvironment and implementation of spatial biology approaches will help advance the identification of more suitable biomarkers and for cancer therapy. Citation Format: Emily Neil, Dongju Park, Erica Lloyd, Michael Dibuono, Seiyu Hosono, Reto Muller, Hanna Lafayette, Hsinyi Smith, Robert Pinard. High-spatial-resolution multi-omics analysis of cancer tissues. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5643.
ISSN:1538-7445
1538-7445
DOI:10.1158/1538-7445.AM2023-5643