Abstract 74: Single-cell 3D spatial omics for tumor hypoxia

Abstract Tumor hypoxia arises from the abnormal vasculature in tumors which limit the oxygen supply to the rapidly growing cancer cells. To acclimate to this deprived microenvironment, cancer cells upregulate hypoxia-inducible factor 1-alpha (HIF-1) signaling pathway priming themselves towards more aggressive and heterogeneous phenotypes. Hence, tumor hypoxia becomes a major obstacle for effective cancer treatment. Deciphering hypoxia-driven tumor heterogeneity within the tumors is essential to understanding cancer biology and developing novel therapeutic strategies. A stronger focus should be directed towards the effect of hypoxia types and levels rather than just the absence or presence of hypoxia since hypoxia is heterogeneous in the three-dimensional (3D) tumor microenvironment (TME). There are acute and chronic types of tumor hypoxia, and the hypoxia levels are also variable, forming unpredictable and irregular 3D hypoxic areas. Although traditional techniques (i.e., single-cell RNA sequencing (scRNA-seq), immunohistochemistry (IHC), and immunofluorescence (IF)) and innovative spatial transcriptomics have been developed and applied for investigating tumor cell heterogeneity. Underlying issue of missing spatial information, limited numbers of the biomarker detection, underrepresentation of 3D tumor structure, or limited analyzed area onto the array chip size exist respectively in these methods. The objective of this project is to develop a 3D spatial genomics approach with single-cell resolution, named sc3DSG, as an advanced spatial transcriptomic method to study hypoxia-driven cancer cell heterogeneity in 3D. Given that, I developed a 3D cellular fluorescence barcoding method by microscopic photobleaching in tumor macro-sections. The barcodes would maintain a fluorescent footprint of cells in different hypoxic areas upon tissue dissociation. Cells encoded with varied barcodes could be differentiated on flow cytometry and further sorted into separate groups for scRNA-seq. With the optimization with RNA preservation reagent in the workflow, sc3DSG achieves high-quality and high-yield RNA transcript for unbiased transcriptomic analysis. In summary, sc3DSG is an advanced spatial transcriptomic method including a sequential workflow of photobleaching barcoding, tissue dissociation, fluorescence-activated cell sorting (FACS), and scRNA-seq. Sc3DSG enables the study of tissue molecular features without losing spatial information and is a better fit for the study of complex 3D structure like vessels or tumor hypoxia. This approach will unravel hypoxia-driven bimolecular and cellular features by considering the degrees and types of tumor hypoxia. Citation Format: Yi-Chien Wu, Steve Seung-Young Lee. Single-cell 3D spatial omics for tumor hypoxia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 74.