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APAC User Group Meeting 2022: A Spatial Biology Approach for the Frontier of Multiplex Imaging and Spatial Phenotyping

Original Air Date: November 2, 2022

The theme for the APAC User Group 2022 event is a Spatial Biology Approach for the Frontier of Multiplex Imaging and Spatial Phenotyping. Pioneer researchers from Asia Pacific region will share their views regarding the frontiers of spatial biology.

Exploring the Diverse Capabilities and True Spatial Multiomics Enabled by PhenoCycler-Fusion

9:05 AM Singapore/China | 10:05 AM Japan/Korea | 12:05 PM Melbourne, Australia

Spatial Phenotyping is built upon whole-side imaging at single-cell resolution to visualize and quantitate biomarker expression and reveal how cells interact and organize across an entire tissue landscape. We will discuss deep spatial phenotyping with 103 protein markers in Immunology and cancer research, translational research and discover the novel insights generated by multiomics workflow enabled by PhenoCycler-Fusion.





Oliver Braubach, Ph.D.

Director of Applications, Akoya Biosciences

Decoding immunotherapy response using deep tissue profiling

11:00 AM Singapore/China | 12:00 PM Japan/Korea | 2:00 PM Melbourne, Australia

Immunotherapies have led to durable benefit in a number of solid malignancies including lung, head and neck and skin cancers. Identifying patients likely to achieve benefit remains an unmet clinical need. The tumour microenvironment (TME) is now recognized as a driving factor dictating response to immunotherapies. Here, we present comprehensive, cell-by-cell, tumour contexture profiling to delineate tissue signatures associated with response to therapy.




Arutha Kulasinghe

Arutha Kulasinghe, PhD

NHMRC Research Fellow, Clinical-oMx Lab Head, The University of Queensland, Australia

Enabling multiplex Imaging and Spatial Phenotyping through new spatial signature panels using novel protein chemistry on PhenoImager

11:30 AM Singapore/China | 12:30 PM Japan/Korea | 2:30 PM Melbourne, Australia

The new PhenoImager Fusion system brings the latest advances in multiplex imaging enabling whole-slide, multispectral imaging (MSI) at single-cell resolution at unprecedented speed (6 biomarkers per slide in under 20 minutes). Together with our high-throughput PhenoImager HT, these instruments are the fastest quantitative digital pathology imaging platforms enabling rapid and accurate spatial phenotyping at scale. You’ll also get a sneak peek at new spatial signature panels powered by a novel, universal chemistry that allows you to move seamlessly from high-plex spatial phenotyping assays for discovery on the PhenoCycler-Fusion to validate the resulting biomarkers on the Fusion, as a standalone system, at a capacity of 100+ samples per week.





Agnes Haggerty, PhD

Senior biomarker specialist, Akoya Biosciences

Applications of Spatial Transcriptome Analysis to elucidate the cancer heterogeneity

9:30 AM Singapore/China | 10:30 AM Japan/Korea | 12:30 PM Melbourne, Australia

During the initial formation and malignant transformation of cancers, cancer cells and their residing microenvironments play mutually-influencing complex roles. Here we conducted the spatial transcriptome sequencing (ST-seq) analysis, in combination with the barcode-mediated multiple immunohistochemistry (CODEX, now called Phenocycler) analysis. For the analysis of advanced cancers, we employed a total of eleven lung adenocarcinoma specimens, which were harvested from eight Japanese patients. We found that interactions with fibroblast cells and the immune cells play particularly pivotal roles to shape the invasion patterns of cancer cells in the backgrounds of varying genomic-mutation and pathological subtypes. We have also started to characterize when this interplay is firstly initiated. For this purpose, we are analyzing very early cancers, some of which are categorized as earlier than Stage 0 according to the WHO classification. There, key events of the cancer development is also being revealed by the data integration of ST-seq and CODEX.




Yutaka Suzuki

Yutaka Suzuki, PhD

Professor, Department of Computational Biology and Medical Sciences, the University of Tokyo, Japan